WO2023139684A1 - 電池残価マネジメントシステム、および電池残価マネジメント方法 - Google Patents
電池残価マネジメントシステム、および電池残価マネジメント方法 Download PDFInfo
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- 238000007726 management method Methods 0.000 title claims description 110
- 238000000034 method Methods 0.000 claims abstract description 16
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- 238000012423 maintenance Methods 0.000 description 24
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- HBBGRARXTFLTSG-UHFFFAOYSA-N Lithium ion Chemical compound [Li+] HBBGRARXTFLTSG-UHFFFAOYSA-N 0.000 description 1
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- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/392—Determining battery ageing or deterioration, e.g. state of health
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- the present disclosure relates to a battery residual value management system and a battery residual value management method.
- Secondary batteries for example, lithium-ion batteries
- secondary batteries and stationary storage batteries are also used in factories. Since such a secondary battery deteriorates as it is used, it is necessary to evaluate the performance of the secondary battery (presence or absence of performance deterioration and life) during or after use.
- a method for evaluating the residual value of these secondary batteries has also been considered.
- Patent Document 1 discloses a graph in which one axis is the residual value of a secondary battery and the other axis is information on the elapsed time from the manufacturing time of the secondary battery.
- the SOH State Of Health: an index indicating the state of health or deterioration of the battery
- Evaluating the residual value of the secondary battery based on a graph including a boundary display of the groups divided into a plurality of groups indicating the type of application in which the can be used is disclosed.
- Patent Document 1 cannot accurately evaluate the residual value of the secondary battery because the residual value evaluation of the secondary battery is based only on the SOH. This is because even if the SOH value is high, the secondary battery may be in a deteriorated state due to another factor. For example, secondary batteries always have the risk of sudden abnormalities even if the SOH value is sound. Consumers (secondary battery users) end up using second-hand secondary batteries while bearing such risks. For this reason, the degree of deterioration, which is an index that indicates the degree of risk of occurrence of a sudden abnormality, is important for residual value evaluation.
- the present disclosure proposes a technique for more accurately evaluating the residual value of a secondary battery.
- the present disclosure is a battery residual value management system for managing the residual value of a battery, which is defined by one or more thresholds set for each index in a multidimensional vector space composed of at least three indices for evaluating the residual value of the battery, and stores information in the multidimensional vector space having a plurality of regions for determining the rank by residual value of the battery; at least one storage device; and at least one processor that determines the remaining value ranking of the battery subject to residual value assessment by determining where the battery subject to residual value assessment belongs in a plurality of regions in a multi-dimensional vector space.
- FIG. 1 is a diagram showing a schematic configuration example of an entire battery residual value management system 100 according to this embodiment
- FIG. FIG. 4 is a diagram showing an example of three-dimensional evaluation regions (divisions) according to this embodiment
- FIG. 10 is a diagram showing a relationship (example) between a rank by residual value and a range of each index (SOH, IR, and degree of abnormal deterioration);
- FIG. 10 is a diagram showing each measurement index value of the type (model name) of each diagnostic target battery (diagnostic battery) and ranks (examples) by remaining value, which are the corresponding evaluation results;
- 1 is a diagram showing a schematic configuration example 1 of a battery residual value assessment system 101 according to this embodiment;
- FIG. 2 is a diagram showing a schematic configuration example 2 of a battery residual value assessment system 101 using a cloud server
- FIG. 10 is a diagram showing a schematic configuration example 3 of a battery residual value assessment system 101 in an on-premise form
- FIG. 10 is a diagram showing a configuration example 4 of the battery residual value assessment system 101 in the form of edge computing
- FIG. 4 is a diagram for explaining an outline of a residual value matching function
- FIG. It is a figure which shows the example of a residual value matching result.
- 1 is a diagram showing a schematic configuration example of a battery residual value assessment system 101 including a residual value matching device according to the present embodiment
- FIG. FIG. 4 is a diagram (before calibration) for explaining an outline of a battery residual value assessment calibration function according to the embodiment
- FIG. 4 is a diagram (after calibration) for explaining an overview of a battery residual value assessment calibration function according to the embodiment;
- 1 is a diagram showing a schematic configuration example of a battery residual value assessment system 101 including a battery residual value assessment and calibration device according to the present embodiment;
- FIG. 4 is a diagram for explaining an outline of a battery residual value correction function according to the present embodiment, and is a diagram showing thresholds (examples) before correction;
- FIG. 4 is a diagram for explaining an outline of a battery residual value correction function according to the present embodiment, and is a diagram showing thresholds (examples) after correction.
- 1 is a diagram showing a schematic configuration example of a battery residual value assessment system 101 including a battery residual value correction device according to the present embodiment;
- FIG. 1 is a diagram showing an overall schematic configuration example 1 of a battery residual value management system 100 including a battery residual value corresponding supply chain system 102 according to the present embodiment
- FIG. 10 is a diagram showing an example of a generated demand plan by residual value (short-, medium-, and long-term reservation information)
- FIG. 2 is a diagram showing an overall schematic configuration example 2 of a battery residual value management system 100 including a battery residual value corresponding supply chain system 102 according to the present embodiment.
- FIG. 10 is a diagram showing an example of a generated procurement plan by residual value (short-, medium-, and long-term reservation information);
- FIG. 3 is a diagram showing an overall schematic configuration example 3 of a battery residual value management system 100 including a battery residual value corresponding supply chain system 102 according to the present embodiment.
- FIG. 10 is a diagram showing a configuration example of a battery supply-demand suitability determination result for each residual value;
- FIG. 10 is a diagram showing an overall schematic configuration example 4 of a battery residual value management system 100 including a battery residual value corresponding supply chain system 102 according to the present embodiment;
- FIG. 10 is a diagram showing a display example of surplus and shortage quantities predicted in the future from the results of future supply prediction and demand prediction. It is a figure explaining the concept of a surplus/missing item prediction.
- FIG. 10 is a diagram showing a configuration example of a battery supply-demand suitability determination result for each residual value
- FIG. 10 is a diagram showing an overall schematic configuration example 4 of a battery residual value management system 100 including a battery residual value corresponding supply chain system 102 according to the present embodiment
- FIG. 10 is a diagram showing a display example
- FIG. 10 is a diagram showing an overall schematic configuration example 5 of a battery residual value management system 100 including a battery residual value corresponding supply chain system 102 according to the present embodiment;
- FIG. 10 is a diagram showing adjustment results of battery provision based on future prediction data;
- 1 is a diagram showing an overall schematic configuration example 1 of a battery residual value management system 100 including a battery residual value corresponding maintenance management system 103 according to the present embodiment;
- FIG. 10 is a diagram showing security service content (upper table) corresponding to the degree of abnormal deterioration of a battery and the security service provision result (lower table) determined for each battery;
- 2 is a diagram showing an overall schematic configuration example 2 of a battery residual value management system 100 including a battery residual value corresponding maintenance management system 103 according to the present embodiment.
- FIG. 10 is a diagram showing the content of deterioration monitoring service (upper table) corresponding to the degree of abnormal deterioration of batteries and the result of provision of security service determined for each battery (lower table);
- FIG. 3 is a diagram showing an overall schematic configuration example 3 of a battery residual value management system 100 including a battery residual value corresponding maintenance management system 103 according to the present embodiment;
- FIG. 10 is a diagram showing how the threshold calibrated by the remaining battery value assessment/calibration function is reflected in the determination of the contents of the guarantee service and the contents of the deterioration monitoring service;
- FIG. 10 is a diagram showing a schematic configuration example of a battery residual value management system 100 according to a modification;
- FIG. 1 is a diagram showing a schematic configuration example of the entire battery residual value management system 100 according to this embodiment.
- the battery residual value management system 100 includes, for example, in the cloud, a battery residual value assessment system 101 that evaluates (assesses) the residual value of secondary batteries (hereinafter sometimes simply referred to as "batteries"), a battery residual value support supply chain system 102 that manages the supply of secondary batteries whose residual value has been evaluated, and a battery residual value support maintenance management system 103 that manages insurance/guarantee services and monitoring services for secondary batteries to be supplied. It is connected to the group 20, the battery demander's computer group 30, and the service provider's computer group 40, respectively.
- a battery residual value assessment system 101 that evaluates (assesses) the residual value of secondary batteries (hereinafter sometimes simply referred to as "batteries")
- a battery residual value support supply chain system 102 that manages the supply of secondary batteries whose residual value has been evaluated
- a battery residual value support maintenance management system 103 that manages insurance/guarantee services and monitoring services for secondary batteries to be supplied. It is connected to the group 20, the battery demander's computer group 30, and
- the battery residual value management system 100 it is not necessary to include all of the battery residual value assessment system 101 , the battery residual value corresponding supply chain system 102 , and the battery residual value corresponding maintenance management system 103 .
- the battery residual value management system 100 is established. That is, for example, a battery residual value management system 100 composed of only the battery residual value assessment system 101, the battery residual value assessment system 101 + the battery residual value correspondence supply chain system 102, and the battery residual value assessment system 101 + the battery residual value correspondence supply chain system 102 + the battery residual value correspondence maintenance management system 103 can be considered.
- a battery supplier's computer group 20 is connected to a battery residual value assessment system 101 and a battery residual value corresponding supply chain system 102 .
- the computer group 30 of the battery demand business is connected to the supply chain system 102 for remaining battery value, and the computer group 40 of the service business is connected to the maintenance management system 103 for remaining battery value.
- the battery residual value assessment system 101, the battery residual value corresponding supply chain system 102, and the battery residual value corresponding maintenance management system 103 may be realized by one server computer.
- these internal systems 101 to 103 may be configured to be connected to computers of at least one type of business operator (for example, a battery supplier) without a network (on-premise), or these internal systems 101 to 103 may be arranged (distributed arrangement may be possible) near the battery business operator (for example, a battery recycling business) and only the calculation results may be stored in the cloud (edge computing).
- the battery residual value assessment system 101 can assess the residual value of the battery by processing secondary battery data that is accessed from the computer group 20 of the battery supplier and uploaded to the cloud (one example).
- the battery residual value correspondence supply chain system 102 acquires data from the battery supplier's computer group 20 and the battery demander's computer group 30 to optimize battery supply and demand.
- the battery residual value corresponding maintenance management system 103 provides data used by insurance/guarantee service providers and monitoring service providers to maintain and monitor batteries.
- FIGS. 2A to 2C are diagrams showing examples of battery residual value evaluation elements according to the present embodiment.
- SOH State Of Health: capacity
- two further indices for example IR (Internal Resistance) and the degree of abnormal deterioration, are introduced, and the residual value of the secondary battery is assessed (evaluated) by combining these.
- FIG. 2A is a diagram showing an example of three-dimensional evaluation regions (divisions) according to this embodiment.
- three factors indices
- SOH 0.1%
- IR evaluation of internal resistance value or by rate of increase
- degree of abnormal deterioration defective to good.
- Residual value evaluation is performed using a plurality of spatial regions defined by the range of each index value in a three-dimensional space centered on these three indexes (residual value ranking is determined).
- the state of deterioration of the secondary battery is defined within a three-dimensional spatial region formed by multiplying the region defined on the two-index (two-dimensional) map of SOH and IR with the degree of abnormal deterioration of the third index (battery residual value assessment device).
- One or more thresholds are set for each index, and the secondary batteries are ranked according to the deterioration state of the battery for each index.
- a three-dimensional space (three-dimensional vector space) consisting of three indices is introduced and a region is defined therein, but three dimensions is an example.
- the number of indices may be three or more, and a threshold may be set for each index to define a region in a multidimensional vector space, and ranks by residual value may be determined according to the state of deterioration of each secondary battery.
- FIG. 2B is a diagram showing the relationship (example) between the rank by residual value and the range of each index (SOH, IR, and degree of abnormal deterioration).
- SOH the threshold value of the SOH value of the secondary battery is set, and the region is determined. For example, when the SOH value is, for example, 70% or more and less than 100%, it is in the SOH first region (rank I), when it is 50% or more and less than 70%, it is in the SOH second region (rank II), and when it is 30% or more and less than 50%, it is in the SOH third region (rank III).
- an SOH of 70% which is generally guaranteed for electric vehicles, is set as the first threshold
- an SOH of 50% which can be operated as an electric vehicle in a practically limited operating space area (for example, limited to a factory or a factory site)
- the third threshold may be 30% SOH, which is generally considered to have low charging efficiency and low reuse and utilization effect even for stationary use.
- the IR threshold is set by the internal resistance increase rate from the design value (initial value) of the secondary battery, and the region is determined. This is because the resistance value designed for each secondary battery is different. For example, if the rate of increase in internal resistance value is less than 10% with respect to the initial value, IR first region (rank I), if the rate of increase in internal resistance value is 10% or more and less than 20%, IR second region (rank II), If the rate of increase in internal resistance value is 20% or more and less than 30%, it can be IR third region (rank III), and so on.
- a DC interruption method can be used for specific diagnosis (estimation) of SOH and IR.
- IR is estimated using the voltage variation ⁇ Va in the first period ta
- SoH is estimated using the voltage variation ⁇ Vb in the second period tb.
- the relationship table used in the DC blocking method describes the internal resistance parameters that define the function f IR representing the relationship between IR and ⁇ Va.
- the internal resistance parameters include c_IR_I, which varies with battery output current, and c_IR_T, which varies with battery temperature.
- IR can be accurately estimated even when the function f IR fluctuates depending on the temperature of the battery and the output current of the battery.
- the state-of-degradation parameter that defines the function f SOH defines the function f SOH .
- the relationship table describes the internal resistance parameter and the deterioration state parameter for each of the rest period after charging and the rest period after discharging. Accordingly, IR and SOH can be accurately estimated even when the functions (ie, battery characteristics) differ between the rest period after charging and the rest period after discharging. Specifically, IR and SOH are calculated (estimated) according to the following formulas (1) and (2).
- Ri fRi ( ⁇ Va, c_Ri_T_1, c_Ri_T_2, ..., c_Ri_I_1, c_Ri_I_2, ...) ...
- SOH fSOH( ⁇ Vb, c_SOH_T_1, c_SOH_T_2, ..., c_SOH_I_1, c_SOH_I_2, 7) ...
- a threshold is set according to the number of abnormalities detected in the secondary battery, and the area is determined.
- the degree of abnormal deterioration it is conceivable to discriminate the degree of abnormal deterioration based on the abnormal slope or abnormal variation of the recovery voltage in the minute change time by the direct current interruption method.
- the discrimination of the degree of abnormal deterioration due to the abnormal slope of the recovery voltage in the minute change time by the DC interruption method calculates the ratio of the voltage difference ⁇ Va in the first period to the voltage difference ⁇ Vb in the second period, and if the ratio is equal to or greater than the threshold value ⁇ Va_lim, it is estimated that there is a problem with the battery.
- the relationship between ⁇ Va_lim and ⁇ Vb can be defined for each value of ⁇ t.
- the function representing the relationship between ⁇ Vb and ⁇ Va_lim may change depending on at least one of battery temperature T, battery discharge current I, and battery discharge end voltage V.
- FIG. In that case, function parameters are defined in advance for each value of T, each value of I, and each value of V, and ⁇ Va_lim can be calculated using the function parameters corresponding to these actually measured values. Therefore, the function f representing the relationship between ⁇ Vb and ⁇ Va_lim in this case is defined as the following equation (3).
- ⁇ Va_lim f ( ⁇ Vb, c_Rn_T_1, c_Rn_T_2, ..., c_Rn_I_1, c_Rn_I_2, ..., c_Rn_V_1, c_Rn_V_2, 7) (3)
- function f Since Va_lim is a function of ⁇ Vb, function f has ⁇ Vb as an argument.
- the function f further includes one or more parameters c_Rn_T that change according to the temperature T.
- one or more parameters c_Rn_I that change according to the current I and c_Rn_V that change according to the voltage V are included.
- the voltage variation (standard deviation ⁇ ) in the third period is equal to or greater than the threshold ⁇ _lim, it is estimated that there is a problem with the battery.
- the threshold ⁇ _lim it is possible to estimate whether or not the battery is in a normal state without preparing equipment used for impedance measurement, for example, in the same manner as the discrimination of the degree of abnormal deterioration based on the abnormal slope.
- the first threshold when one of the above abnormalities is detected is detected
- the second threshold when two are detected and the third threshold when the degree of abnormal deterioration greatly deviates from the threshold.
- the abnormality deterioration level is A (rank I)
- the abnormality deterioration level is B (rank II)
- the abnormality deterioration level is C (rank III)
- These threshold settings are examples, and threshold values may be set based on different ideas.
- Ranking is performed according to the state of deterioration of the battery using the three indices defined above. Assuming that there are K types of threshold settings for SOH, L types of threshold settings for IR, and M types of threshold settings for the degree of abnormal deterioration, K ⁇ L ⁇ M regions are set in the three-dimensional space of FIG. Different residual value ranks may be assigned to all of the K ⁇ L ⁇ M regions, or the same residual value rank may be assigned to a plurality of regions.
- FIG. 2C is a diagram showing each measurement index value of the type (model name) of each diagnostic target battery (diagnostic battery) and the rank by residual value (example) corresponding to the evaluation result.
- the battery residual value assessment system 101 stores ranks by residual value (for example, a table) corresponding to combinations of ranks (K ⁇ L ⁇ M combinations) of the three indicators in a storage unit (storage device) described later, and can be configured to acquire (determine) ranks by residual value corresponding to combinations of ranks of the SOH, IR, and degree of abnormal deterioration of the secondary battery to be diagnosed (evaluated).
- FIG. 2C shows ranks by residual value of each secondary battery thus obtained.
- the secondary battery determination (assessment) result can be composed of, for example, a battery ID that uniquely identifies and identifies the secondary battery, a battery model that indicates the type of secondary battery, the SOH value, IR value, and degree of abnormal deterioration of the secondary battery obtained by measurement, and information on the determined rank by residual value.
- the IR value and the degree of abnormal deterioration are introduced as indicators, and the residual value is evaluated in a three-dimensional space. For example, even if the SOH value is high, the degree of abnormal deterioration may be poor. In such a case, the secondary battery provider can inform the purchaser in advance of the possibility of sudden abnormalities.
- FIG. 3A is a diagram showing a schematic configuration example 1 of the battery residual value assessment system 101 according to the present embodiment.
- the battery residual value assessment system 101 includes a battery residual value assessment device 303 that acquires a measurement result from a charge/discharge device (or tester) 302, which is a dedicated device for measuring a battery (secondary battery) 301, via a network (e.g., the Internet) and evaluates (assesses) the residual value of the battery 301, and a memory 304 that temporarily stores the evaluation result to display it on a display screen and/or to transmit the evaluation result information to the user.
- a charge/discharge device or tester
- a memory 304 that temporarily stores the evaluation result to display it on a display screen and/or to transmit the evaluation result information to the user.
- the charging/discharging device 302 includes a detection unit 3021 that measures the voltage value V, current value I, and temperature T of the battery 301, and a communication unit (communication device) 3022 that transmits the measured data to the battery residual value assessment device 303 via the network and receives evaluation results from the battery residual value assessment device 303.
- a processor CPU that controls operations of the detection unit 3021 and the communication unit 3022 may be provided.
- the battery residual value assessment device 303 can be configured by a computer, and includes a detection unit 3031 , a calculation unit (processor) 3032 and a storage unit 3033 .
- the detection unit 3031 can be configured by, for example, a communication device, and receives data transmitted from the charging/discharging device 302 .
- the calculation unit 3032 calculates the SOH value, the IR value, and the degree of abnormal deterioration based on the information on the voltage value V, current value I, and temperature T of the battery 301, and determines the residual value rank (FIGS. 2A and B) based on the combination thereof.
- the calculation unit 3032 stores the calculated SOH value, IR value, degree of abnormal deterioration, and information on the determined rank by residual value in the storage unit 3033 and also in the memory 304 .
- the memory 304 may be provided inside the remaining battery value assessment device 303 .
- FIG. 3B is a diagram showing schematic configuration example 2 of the remaining battery value assessment system 101 using a cloud server, similar to FIG. 3A.
- the configuration of FIG. 3B differs from the configuration of FIG. 3A in that instead of using the charging/discharging device 302, the user uses a computer (example) 305 that measures the voltage value V, current value I, and temperature T of the battery 301 with a charging/discharging device (not shown) that does not have a communication function. It is not always necessary for the user to actually measure the battery 301, and information on the voltage value V, current value I, and temperature T measured in advance for the target battery 301 may be obtained from another data server (not shown) and transmitted to the remaining battery value assessment device 303 using the computer 305.
- FIG. 3C is a diagram showing configuration example 3 of the on-premise battery residual value assessment system 101 .
- the remaining battery value assessment system 101 in the on-premise form has the same components and functions as the system in the cloud server form, except for the communication unit 3034 .
- battery residual value assessment device 303 is configured to be directly connected to charge/discharge device 302 without going through a network.
- a communication unit (which can be realized by a communication device) 3034 transmits and stores calculation results (SOH value, IR value, and degree of abnormal deterioration) and evaluation results (ranks by residual value) to the memory 304 via a communication line. If battery residual value assessing device 303 and memory 304 are not connected via a communication line, communication unit 3034 is not necessary, and calculation results and evaluation results are directly stored in memory 304 from calculation unit 3032 .
- FIG. 3D is a diagram showing configuration example 4 of the battery residual value assessment system 101 in the form of edge computing.
- a battery residual value assessment system 101 in the form of edge computing includes a battery 301, a memory 304 in the cloud, and a battery residual value assessment device 303 directly connected to the battery 301 and connected to the memory 304 in the cloud via a network.
- the battery remaining value assessment device 303 is a device that receives power from the directly connected battery 301, and may be integrated with a charging/discharging device, a tester, or the like.
- Battery residual value assessment device 303 includes detection unit 3031 , calculation unit 3032 , storage unit 3033 , and communication unit 3034 . Detector 3031 obtains voltage V, current I, and temperature T of battery 301 .
- the functions of the calculation unit 3032 and the storage unit 3033 are as described above.
- the communication unit 3034 can transmit the deterioration state calculated by the calculation unit 3032 to the outside of the remaining battery value assessment device 303 (memory 394 provided in the cloud system).
- the remaining battery value assessment system 101 may be realized by incorporating an algorithm for assessing the remaining battery value into measuring equipment such as the charging/discharging device 302, tester, and oscilloscope.
- the residual value matching device has a residual value matching function that matches the residual value-assessed battery defined in the three-dimensional spatial region of FIG.
- An outline of the residual value matching function (FIG. 4), a residual value matching result (FIG. 5), and a configuration example of the battery residual value assessment system 101 including the residual value matching device (FIG. 6) will be sequentially described below.
- FIG. 4 is a diagram for explaining an overview of the residual value matching function.
- the residual value matching function is a function of matching a battery (secondary battery) whose deterioration state has been diagnosed by three indexes defined (calculated) by the battery residual value assessment device 303 and a battery that meets the specification range required by each business operator.
- the state of deterioration of batteries that is permitted and required by each business operator differs greatly.
- a battery is required that maintains a high SOH (e.g., 70% or more), IR is close to the design value (e.g., an increase in internal resistance within 30% of the design value), and has a good degree of abnormal deterioration (e.g., A) (see specification range 402 of operator A).
- Operator B which assumes operation within a limited space area, such as an electric forklift that runs in a factory
- SOH is permitted to a lesser range than electric vehicles (e.g., 50% or higher), and the degree of abnormal deterioration may also be permitted to a range that includes defective areas (e.g., D or higher) (see Operator B's specification range 403).
- IR is allowed to increase significantly from the design value (e.g., an increase within 100% of the design value), but the degree of abnormal deterioration may be moderate (e.g., B or C) (see specification range 404 of operator C).
- the above range of specifications requested by customers is an example, and the range is not limited to this.
- the secondary batteries ranked in the area of the degradation diagnosis result 401 in FIG. 4 do not match the specification range 402 of the operator A, but match the specification ranges 403 and 404 of the operators B and C, and operators B and C can be selected as supply destination candidates.
- FIG. 5 is a diagram showing an example of a residual value matching result.
- the residual value matching result is configured by adding the demand business candidate 501 for the target battery derived by the residual value matching to the residual value diagnosis result shown in FIG. 1C. From FIG. 5 , for example, the battery with battery ID A0001 conforms to the specification ranges of operators B and C, the battery with battery ID A0002 conforms only to operator C's specification range, and the battery with battery ID A0003 conforms to the specification ranges of operators A, B, and C, so these operators are selected as demand operator (supply destination) candidates. In this manner, the residual value matching function makes it possible to present potential customer companies that can be provided for each battery diagnosed as having a deteriorated state.
- FIG. 6 is a diagram showing a schematic configuration example of the battery residual value assessment system 101 including the residual value matching device according to the present embodiment.
- FIG. 6 shows the remaining battery value assessment device 303 and remaining value matching device 602 as cloud servers, but they may be implemented in the above-described on-premise form or edge computing form.
- the battery residual value assessment system 101 includes, in addition to the battery residual value assessment device 303 and memory 304 described above, a residual value matching device 602 provided in the cloud and connected to at least one operator computer 601 via a network.
- the operator's computer 601 includes an input unit (can be composed of a keyboard, mouse, etc.) 6011 for inputting customer-required specifications for the operator's battery (secondary battery), and a communication unit (communication device) 6012 for transmitting customer-required specification information to the residual value matching device 602 via a network.
- an input unit can be composed of a keyboard, mouse, etc.
- a communication unit communication device
- the residual value matching device 602 includes a detection unit (which can be configured by a communication device) 6021 for receiving customer requested specification information transmitted from the business computer 601, an arithmetic unit (which can be configured by a processor) 6022, and a purchase residual value demand value storage unit (which can be configured by a storage device) 6023.
- the calculation unit 6022 acquires the deterioration state information (SOH value, IR value, degree of abnormal deterioration, and rank by residual value) of each battery generated by the battery residual value assessment device 303, compares this information with the customer requested specification information, determines secondary batteries that meet the customer requested specifications, and extracts demand business candidate for each battery. Further, the calculation unit 6022 stores the received customer required specification information and the generated residual value matching result (see FIG. 5) in the required purchase residual value storage unit 6023, and also stores the deterioration state information and the residual value matching result in the memory 304.
- SOH value, IR value, degree of abnormal deterioration, and rank by residual value the deteriorati
- the battery residual value assessment device 303 and the residual value matching device 602 may be configured integrally as one device (for example, they can be implemented on one server computer).
- Battery residual value assessment/calibration device provides a function of calibrating residual value assessment thresholds for batteries that have undergone residual value assessment defined in the three-dimensional spatial region of FIG.
- An outline of the battery residual value assessment and calibration function (FIG. 7) and a configuration example of the battery residual value assessment system 101 including the battery residual value assessment and calibration device (FIG. 8) will be sequentially described below.
- FIGS. 7A and 7B are diagrams for explaining an overview of the battery remaining value assessment and calibration function according to the present embodiment.
- the battery residual value assessment system 101 performs ranking (ranking according to residual value) according to the deterioration state of the battery using the three indices of SOH, IR, and degree of abnormal deterioration.
- a threshold value set for each index (for example, when the abnormal deterioration degree ranges from C to A, A is the highest abnormal deterioration degree) is set according to design specifications, specifications requested by each business operator, and the like.
- the battery residual value assessment/calibration device 802 provides a function of calibrating each threshold value using a deterioration trend analysis value in the actual operating state in the market in order to correct such a difference.
- the current threshold for example, the initially set provisional threshold: the threshold indicated by the dotted line in FIG. 7A
- the change points 1 to 3 are not taken into consideration, so the degree of abnormal deterioration of the battery and the frequency of occurrence of battery abnormalities and defects in the market cannot be correctly evaluated.
- the threshold value is calibrated according to the sudden change points 1 to 3 of the frequency of occurrence of anomalies, and the new threshold value (the threshold value indicated by the solid line in FIG. 7B) is used for subsequent battery residual value assessment, so that the battery residual value evaluation can be properly performed.
- the new threshold for example, the size of each area for rank assignment (the above K ⁇ L ⁇ M areas) set relatively evenly in FIG. 2A is biased (see the change from FIG. 7A to FIG. 7B). For example, in FIG.
- the index is the degree of abnormal deterioration
- the areas determined to be abnormal deterioration degree A (good) and abnormal deterioration degree C (bad) are large, and the area determined to be abnormal deterioration degree B (intermediate) can be set finely (for example, the area determined to be B is set as B1 (upper middle) and B2 (lower middle)).
- FIG. 8 is a diagram showing a schematic configuration example of the battery residual value assessment system 101 including the battery residual value assessment/calibration device 802 according to the present embodiment.
- FIG. 8 shows the remaining battery value assessment device 303 and the remaining battery value assessment and calibration device 802 as cloud servers, but they may be realized in the above-described on-premise form or edge computing form.
- the battery residual value assessment system 101 includes, in addition to the aforementioned battery residual value assessment device 303 and memory 304, a battery residual value assessment calibration device 802 provided in the cloud and connected to at least one operator computer 801 via a network.
- a business computer e.g., one of the computer groups 30 of a battery demand business
- 801 includes an input unit (can be composed of a keyboard, a mouse, etc.) 8011 for inputting a deterioration trend analysis value (for example, information obtained from a battery deterioration database for each business type and battery actual operation state) in the actual operation state of the battery (secondary battery) of the business operator in the market, and a communication unit (communication device) 8012 for transmitting the deterioration trend analysis value to the battery residual value assessment calibration device 802 via the network.
- a deterioration trend analysis value for example, information obtained from a battery deterioration database for each business type and battery actual operation state
- a communication unit for transmitting the deterioration trend analysis value to the battery residual value assessment calibration device 802 via the network.
- the battery residual value assessment and calibration device 802 includes a detection unit (which can be configured by a communication device) 8021 for receiving the deterioration trend analysis value transmitted from the business computer 801, an arithmetic unit (which can be configured by a processor) 8022, and a deterioration trend analysis value storage unit (which can be configured by a storage device) 8023.
- the calculation unit 8022 collates the deterioration trend analysis value in the actual operating state in the market with the current assessment threshold (for example, the provisional threshold) to calibrate the threshold.
- the calculation unit 8022 acquires the deterioration state information (SOH value, IR value, degree of abnormal deterioration, and rank by residual value) of each battery generated by the battery residual value assessment device 303, and newly ranks the secondary battery to be evaluated (the battery 301 that has been diagnosed by the battery residual value assessment device 303) based on the new threshold value (calibrated threshold value) (re-evaluation). Since the deterioration tendency analysis value is accumulated in the deterioration tendency analysis value storage unit 8023 over time, the abnormal deterioration degree threshold can be calibrated periodically.
- the deterioration trend analysis value of the battery in the actual operating state is obtained based on the relationship between the degree of abnormality deterioration and the frequency of abnormality occurrence, but it may be based on the relationship between the SOH or IR and the frequency of abnormality occurrence.
- the remaining battery value assessment device 303 and the remaining battery value assessment and calibration device 802 may be integrally configured as one device (for example, they can be mounted on one server computer).
- the battery residual value correcting device provides a function of correcting the initially set threshold value and/or the threshold value calibrated by the battery residual value assessment calibration function, and also taking into consideration the market price of used batteries in the market (market price reflecting battery residual value correcting device).
- FIG. 9 is a diagram for explaining an outline of the battery residual value correction function according to the present embodiment.
- FIG. 9A is a diagram showing a threshold (example) before correction
- FIG. 9B is a diagram showing a threshold (example) after correction.
- the three indexes of SOH, IR, and degree of abnormal deterioration are used to rank the batteries according to their deterioration state.
- the threshold value (basic value) set for each index is set according to design specifications, specifications requested by customers of each business operator, and the like. However, there may be a difference between the setting of the threshold and the used battery market price in the market. Therefore, by providing a battery residual value correction function that reflects the market price, each threshold is corrected according to the used battery market price in the market, and the deviation from the market is corrected.
- the threshold value is corrected by dividing and subdividing the range where the slope of the market price change is large as shown in FIG. 9B.
- the threshold value is corrected based on the relationship between the SOH and the market price here, the threshold value may be corrected based on the relationship between the IR or the degree of abnormal deterioration and the market price.
- FIG. 10 is a diagram showing a schematic configuration example of the battery residual value assessment system 101 including the battery residual value correction device according to the present embodiment.
- FIG. 10 shows the remaining battery value assessment device 303 and the remaining battery value correction device 1002 as cloud servers, they may be realized in the above-described on-premise form or edge computing form.
- the battery residual value assessment system 101 includes, in addition to the aforementioned battery residual value assessment device 303 and memory 304, a battery residual value correction device 1002 provided in the cloud and connected to at least one operator computer 1001 via a network.
- the operator's computer 1001 includes an input unit (can be composed of a keyboard, a mouse, etc.) 10011 for inputting used battery market prices (for example, information obtained from a database that stores used battery market prices corresponding to battery types) of batteries (secondary batteries) of the relevant operator, and a communication unit (communication device) 10012 for transmitting used battery market price information of the target battery to the battery residual value correction device 1002 via a network.
- an input unit can be composed of a keyboard, a mouse, etc.
- used battery market prices for example, information obtained from a database that stores used battery market prices corresponding to battery types
- batteries secondary batteries
- the battery residual value correction device 1002 includes a detection unit (which can be configured by a communication device) 10021 for receiving information on the market price value of the target battery transmitted from the operator computer 1001, an arithmetic unit (which can be configured by a processor) 10022, and a market price storage unit (which can be configured by a storage device) 10023.
- the calculation unit 10022 compares the received market price of the used battery with the current assessment threshold (for example, the provisional threshold), and corrects the threshold.
- the calculation unit 10022 acquires the deterioration state information (SOH value, IR value, degree of abnormal deterioration, and rank by residual value) of each battery generated by the battery residual value assessment device 303, and newly ranks the secondary battery to be evaluated (the battery 301 that has been diagnosed by the battery residual value assessment device 303) based on the new threshold value (corrected threshold value) (re-evaluation). Since the market price of used batteries is accumulated in the market price storage unit 10023 over time, the threshold value can be corrected periodically.
- SOH value, IR value, degree of abnormal deterioration, and rank by residual value the secondary battery to be evaluated (the battery 301 that has been diagnosed by the battery residual value assessment device 303) based on the new threshold value (corrected threshold value) (re-evaluation). Since the market price of used batteries is accumulated in the market price storage unit 10023 over time, the threshold value can be corrected periodically.
- the remaining battery value assessment device 303 and the remaining battery value assessment and calibration device 802 may be integrally configured as one device (for example, they can be mounted on one server computer).
- the battery residual value management system 100 is configured as a battery residual value corresponding supply chain system 102 by adding a residual value demand plan calculation device 1100 that provides a residual value reservation function (short-medium-long term) to the purchase residual value request value storage unit 6023 in the residual value matching device 602.
- 11A is composed only of the residual value-based demand plan calculation device 1100, but in addition to the residual value-based demand plan calculation device 1100, as will be described later, a residual value-based procurement plan calculation device 1200 (see FIG.
- FIG. 12A shows the battery residual value management system 100 including the battery residual value corresponding supply chain system 102 as a cloud server, but it may be realized in the above-described on-premise form or edge computing form.
- the demand planning calculation device by residual value 1100 acquires the residual value data (battery type, SOH, IR, degree of abnormal deterioration, quantity, delivery date, etc.) of the battery requested by the demand side (computer group 30 of the battery demand business operator), refers to the data accumulated in the required purchase residual value storage unit 6023, organizes information on the reservation status of the candidate demand business operator, and displays it on the screen of the display device (not shown) as necessary. At this time, it is also possible to display the reservation status by classifying it into short, medium and long term.
- the residual value data battery type, SOH, IR, degree of abnormal deterioration, quantity, delivery date, etc.
- FIG. 11B is a diagram showing an example of a generated demand plan by residual value (short-, medium-, and long-term reservation information).
- the demand plan calculation device 1100 by residual value totals reservation data (desired battery residual value data: battery type, SOH, IR, degree of abnormality, quantity, delivery date, etc.) transmitted from the demand side (computer group 30 of the battery demand business operator), and classifies them into short-term reservation (for example, delivery within one month), medium-term reservation (for example, delivery within one year), and long-term reservation (for example, delivery within five years), as shown in FIG. 11B.
- short-term reservation for example, delivery within one month
- medium-term reservation for example, delivery within one year
- long-term reservation for example, delivery within five years
- the desired delivery date is sorted into short-term reservations, medium-term reservations, and long-term reservations, and in each, the data of the battery type, SOH, IR, degree of abnormal deterioration, and quantity desired by each demand business are summarized in a predetermined format.
- the battery residual value management system 100 is configured as a battery residual value corresponding supply chain system 102 by adding a procurement plan calculation device 1200 for each residual value that provides a battery procurement function for each residual value (short, medium and long term) to the required purchase residual value storage unit 6023 in the residual value matching device 602.
- the supply chain system 102 corresponding to residual value of batteries in FIG. 12A is composed only of procurement plan calculation device 1200 by residual value, but in addition to procurement plan calculation device 1200 by residual value, demand plan calculation device 1100 by residual value (see FIG.
- FIG. 12A shows the battery residual value management system 100 including the battery residual value corresponding supply chain system 102 as a cloud server, but it may be realized in the above-described on-premise form or edge computing form.
- the procurement plan calculation device 1200 for each residual value acquires the procurement plan data of each business (residual value data of batteries that can be provided: battery type, SOH, IR, degree of abnormal deterioration, quantity, delivery date (procurement time), etc.) from the supply side (computer group 20 of the battery supplier), refers to the data accumulated in the required purchase residual value storage unit 6023, organizes the data of the supplier in association with the battery procurement plan data, and displays it on the screen of the display device (not shown) as necessary. do. At this time, it is also possible to display the battery procurement plan by classifying it into short, medium and long term.
- FIG. 12B is a diagram showing an example of a generated procurement plan by residual value (short-, medium-, and long-term reservation information).
- the procurement plan calculation device 1200 by residual value aggregates procurement plan data (residual value data of batteries scheduled to be procured (provided): battery type, SOH, IR, degree of abnormal deterioration, quantity, delivery date (procurement time), etc.) transmitted from the supply side (computer group 20 of the battery supplier), and as shown in FIG.
- the scheduled procurement time is sorted into short-term procurement, medium-term procurement, and long-term procurement, and in each of them, the battery type, SOH, IR, degree of abnormal deterioration, quantity, and delivery date (procurement time) scheduled by each supplier are summarized in a predetermined format.
- FIG. 13A shows the battery residual value management system 100 including the battery residual value supply chain system 102 as a cloud server, it may be realized in the above-described on-premise form or edge computing form.
- the battery supply and demand suitability determination device 1300 for each residual value compares the demand plan data for each residual value (FIG. 11B) from the demand plan calculation device 1100 for each residual value (FIG. 11B) and the procurement plan data for each residual value (FIG. 12B) from the procurement plan calculation device for each residual value 1200 with the deterioration state data of each battery calculated by the battery residual value assessment device 303, and determines the battery supply and demand suitability decision result for each residual value ( 13B), and a storage unit 1302 for storing the determination result of battery supply and demand suitability for each residual value. Further, the calculation unit 1301 also stores the determination result of battery supply-demand suitability by remaining value in the memory 304 for screen display or for provision to the supply side and the demand side. This makes it possible to present short-, medium-, and long-term supply and demand plans.
- FIG. 13B is a diagram showing a configuration example of the battery supply-demand suitability determination result by residual value.
- the demand plan data by residual value 1313 (the same data as in FIG. 11B) and the procurement plan data by residual value 1312 (the same data as in FIG. 12B) are compared for each delivery date (short, medium, and long term), and the battery that the demand side desires (reservation: demand plan) is assigned to the battery that the supply side can supply (procurement plan).
- demand plan the surplus/missing item quantity is 0 or + (plus)
- the surplus/missing item quantity is ⁇ (minus)
- the battery residual value management system 100 includes, as a battery residual value corresponding supply chain system 102, a residual value-based demand plan calculation device 1100 that provides the above-described residual value-based reservation function (short, medium, and long term), a residual value-based procurement plan calculation device 1200 that provides the above-described residual value-based procurement function (short, medium, and long term), a residual value-based battery supply and demand suitability determination device 1300 that provides the above-described battery supply and demand suitability determination function, and a residual value-based medium-to-long term plan recommendation device 1400. is added in the cloud.
- FIG. 14A shows the battery residual value management system 100 including the battery residual value corresponding supply chain system 102 as a cloud server, it may be realized in the above-described on-premise form or edge computing form.
- the medium- to long-term plan recommendation device 1400 for battery procurement by residual value is provided with a calculation unit (processor) 1401 that learns deviation values of surplus or shortage from the data accumulated by the battery supply and demand suitability determination device 1300 by residual value, and derives future supply forecast and demand forecast by applying, for example, random forest to this deviation value, and a storage unit 1402 that stores future supply forecast and demand forecast data. Further, the calculation unit 1401 temporarily stores the future supply forecast and demand forecast data in the memory 304 to display them on the display screen of a display device (not shown) as needed.
- the calculation unit 1401 calculates the future predicted surplus and shortage quantity from the results of future supply prediction and demand prediction, and displays them on the display screen (see FIG. 14B). In addition, the calculation unit 1401 predicts the thresholds of the three indicators (SoH, IR, and degree of abnormal deterioration) that represent the deterioration state of the battery that can change from now to the future from the deterioration trend analysis value in the actual operation state in the past market and the used battery market price, minimizes the difference between supply and demand, and recommends optimal operation.
- the three indicators SoH, IR, and degree of abnormal deterioration
- FIG. 14C is a diagram explaining the concept of surplus/outage prediction.
- a supply forecast 1411 and a demand forecast 1412 are obtained as a result of executing the medium- to long-term plan recommendation function for battery procurement by residual value.
- the calculation unit 1401 compares both for each predetermined period (e.g., monthly) and for each residual value rank (e.g., I to IV), determines whether there is a surplus or a shortage (whether there is a deviation in the supply and demand forecast), and generates surplus/missing forecast data 1413.
- the monthly surplus/outage forecast 1413 is shown as a bar graph, but the weekly and yearly surplus/outage forecasts can also be generated and output.
- the calculation unit 1401 generates medium- to long-term plan recommendation information 1414 regarding various batteries (various batteries specified by information from the battery type to the residual value rank).
- the medium to long term plan recommendation information 1411 can be provided to the demand side and the supply side.
- the supply side can make future procurement plans for various batteries
- the demand side can make reservation plans for various batteries.
- Battery procurement plan cooperation function A function for linking the battery procurement vendor that matches the medium- to long-term procurement plan by the medium- to long-term plan recommendation function for battery procurement by residual value and the necessary procurement amount information for each residual value recommended by the medium-to-long term plan recommendation function for battery procurement by residual value.
- the battery residual value management system 100 includes, as a battery residual value corresponding supply chain system 102, a residual value-based demand plan calculation device 1100 that provides the above-described residual value-based reservation function (short, medium, and long term), a residual value-based procurement plan calculation device 1200 that provides the above-described residual value-based procurement function (short, medium, and long term), a residual value-based battery supply and demand suitability determination device 1300 that provides the above-described battery supply and demand suitability determination function, and a residual value-based medium-to-long term plan recommendation device 140. 0, and a battery procurement plan cooperation system 1500 in the cloud.
- FIG. 15A shows the battery residual value management system 100 including the battery residual value supply chain system 102 as a cloud server, it may be realized in the above-described on-premise form or edge computing form.
- the battery procurement plan cooperation system 1500 acquires the future forecast data generated by the medium- to long-term plan recommendation device 1400 for battery procurement by residual value in the calculation unit 1501, summarizes information such as medium- to long-term battery demand and supply forecast quantity, delivery date, etc. for each business operator, displays it on a display device (not shown), and stores the information in the memory 304 for presentation to each business operator.
- information display on the battery residual value correspondence supply chain system 102 side and information presentation (display) on the computer group 20 side of the battery supplier can be linked.
- the battery procurement plan cooperation system 1500 presents (proposes) to each battery supplier the timing of occurrence of demand for the target battery and the provision of batteries of different remaining value ranks that are in short supply from the demand and supply forecast. Specifically, it is proposed to provide a battery of residual value rank II closer to residual value rank III (battery of residual value rank II close to the boundary (threshold value) between residual value ranks II and III) as residual value rank III. It can also be used to adjust production and procurement quantities. To explain with reference to FIG.
- FIG. 16A shows the battery residual value management system 100 including the battery residual value maintenance management system 103 as a cloud server, it may be realized in the above-described on-premise form or edge computing form. Also, in FIG. 16A, the matching system 1600 for guarantee service provision is connected to the residual value matching device 602, but the residual value matching device 602 is not an essential component, and may be directly connected to the residual battery value assessment device 303.
- the computing unit (processor) 1601 determines the content of the security service and the security cost based on the degree of abnormal deterioration of the battery (grades A, B, C, D, .
- the information stored in the memory 304 is used when presenting the content of the decision to the demand business operator or the like.
- FIG. 16B is a diagram showing the content of security service corresponding to the degree of abnormal deterioration of the battery (upper table) and the result of providing security service determined for each battery (lower table). As shown in FIG. 16B (upper table), it is possible to set different insurance service contents and insurance costs according to the grade of the degree of abnormal deterioration. In FIG. 16B, the contents of insurance are different depending on the grade of the degree of abnormal deterioration, but the contents of insurance may be the same and only the insurance costs may be different.
- FIG. 16B upper table
- when purchasing a battery with an abnormal deterioration grade of B it is possible to provide insurance service contents such as replacement/overhead costs and property damage.
- the abnormal deterioration grade changes according to the diagnosis result that is performed together with the renewal of the warranty service, it is recommended to change the contents of the warranty service according to the grade.
- the battery residual value management system 100 is configured by adding a deterioration monitoring service provision type matching system 1700 to the cloud as a battery residual value corresponding maintenance management system 103 .
- FIG. 17A shows the battery residual value management system 100 including the battery residual value maintenance management system 103 as a cloud server, it may be realized in the above-described on-premise form or edge computing form.
- the deterioration monitoring service provision type matching system 1700 is connected to the residual value matching device 602, but the residual value matching device 602 is not an essential component, and may be directly connected to the residual battery value assessment device 303.
- the deterioration monitoring service provision type matching system 1700 provides a deterioration monitoring service according to each grade according to the grade of the degree of abnormality deterioration of the battery.
- the arithmetic unit (processor) 1701 refers to the deterioration monitoring service information (FIG. 17B) corresponding to the grade of the degree of abnormal deterioration stored in the storage unit 1702, determines the content of the deterioration monitoring service and the monitoring frequency based on the degree of abnormal deterioration (grades A, B, C, D, .
- the information stored in the memory 304 is used when presenting the content of the decision to the demand business operator or the like.
- the monitoring function includes, for example, the calculation unit 1701 compares the past diagnosis results of the target battery stored in the storage unit 1702 with the newly obtained diagnosis results through regular monitoring and constant monitoring, and calculates the fluctuation of the abnormal deterioration level. .
- diagnosis is performed at the same time when the battery is charged or during regular maintenance.
- FIG. 17B is a diagram showing the deterioration monitoring service content (upper table) corresponding to the degree of abnormal deterioration of the battery and the guarantee service provision result (lower table) determined for each battery. As shown in FIG. 17B (upper table), it is possible to set different deterioration monitoring service contents and monitoring frequencies according to the grade of the degree of abnormal deterioration.
- FIG. 18A is a diagram showing an overall schematic configuration example 3 of the battery residual value management system 100 including the battery residual value corresponding maintenance management system 103 according to this embodiment.
- the battery residual value management system 100 is configured by adding a security service providing matching system 1600 and a deterioration monitoring service providing matching system 1700 to the cloud as a maintenance management system 103 corresponding to the battery residual value.
- FIG. 18A shows the battery residual value management system 100 including the battery residual value corresponding maintenance management system 103 as a cloud server, it may be realized in the above-described on-premise form or edge computing form.
- the battery residual value corresponding maintenance management system 103 shown in FIG. 18A provides a function (battery operation maintenance management function) for allocating the matching result determined by the residual value matching device 602 based on the residual value evaluation (assessment) result of the battery residual value using the threshold calibrated by the battery residual value assessment and calibration device 802 in consideration of the battery deterioration tendency analysis.
- a function battery operation maintenance management function
- the degree of abnormal deterioration is graded in accordance with the operating status of the target battery based on thresholds set according to battery characteristics and design values.
- thresholds set according to battery characteristics and design values.
- the security (insurance) service content and monitoring service content presented/provided for each battery are optimized.
- the battery threshold value is continuously updated to improve the determination accuracy.
- the content of the updated threshold data can be reflected in the fee structure/price of the insurance/monitoring service.
- Determination of the content of the security service, the security cost, and the content of the deterioration monitoring service and the frequency of monitoring are performed by referring to the content of the security service corresponding to the degree of abnormal deterioration of the battery (upper table of FIG. 16B) and the content of the deterioration monitoring service corresponding to the degree of abnormal deterioration of the battery (upper table of FIG. 17B).
- the threshold for determining the grade of the degree of abnormal deterioration fluctuates due to the remaining battery value assessment and calibration as described above, which is reflected in the determination of the content of the guarantee service and the content of the deterioration monitoring service.
- 18B is a diagram showing how the threshold calibrated by the remaining battery value assessment calibration function is reflected in the determination of the contents of the security service and the contents of the deterioration monitoring service.
- the grades of the degree of abnormal deterioration are equally classified, and the contents of the security service and the contents of the deterioration monitoring service are determined based on this.
- the threshold value for determining the grade of the degree of abnormal deterioration is changed by the battery residual value assessment/calibration function as indicated by reference number 1802
- the determination ranges of the content of the guarantee service and the content of the deterioration monitoring service change accordingly, as indicated by reference number 1803.
- FIG. 19 is a diagram showing a schematic configuration example of the battery residual value management system 100 according to a modification.
- a group of computers 60 of a battery recycler is installed between the remaining battery value assessment system 101, the supply chain system 102 for battery residual value, and the group of computers 20 of the battery supplier.
- the system is configured so that the battery data supplied from the battery supplier to the battery recycler can be uploaded by the battery recycler to the battery residual value assessment system 101 and/or the battery residual value corresponding supply chain system 102.
- the battery residual value correspondence supply chain system 102 can acquire data from the computer group 60 of the battery recycling business and the computer group 30 of the battery demand business, and optimize the supply and demand of batteries.
- the battery residual value management system 100 may have at least one of the functions described above. However, the functions established by cooperation need to be configured as a set. For example, the residual value-based reservation function of the residual value-based demand plan computing device 1100 and the residual value-based battery procurement function of the residual value-based procurement plan computing device 1200 require the residual value matching function of the residual value matching device 602 to be executed as a prerequisite. On the other hand, the remaining battery value assessment and calibration function of the remaining battery value assessment and calibration device 802 is established as the remaining battery value management system 100 if the remaining battery value assessment device 303 exists as a premise, and the remaining value matching device 602 is not an essential component.
- the battery residual value management system 100 stores at least one piece of multidimensional vector space information (see FIG. 2A) defined by one or more thresholds set for each index (e.g., SOH, IR (internal resistance-related information: e.g., internal resistance increase rate), abnormal deterioration degree) set in a multidimensional vector space (three-dimensional space or more) composed of at least three indices for evaluating the residual value of a battery (secondary battery), and having a plurality of regions for determining the rank of the battery by residual value (see FIG. 2A). held in the device.
- index e.g., SOH, IR (internal resistance-related information: e.g., internal resistance increase rate), abnormal deterioration degree
- the system 100 acquires information of the multidimensional vector space from the storage device, and determines the residual value rank of the battery to be assessed by determining where the battery to be assessed belongs in a plurality of areas of the multidimensional vector space based on at least three indexes of the battery to be assessed (obtained by calculation from measured values input from the outside (charging and discharging devices and computers connected via a network)). By doing so, it is possible to more accurately determine the rank by residual value of the battery.
- the battery residual value management system 100 uses a residual value matching device 602 to extract batteries that match a desired specification range (a desired SOH value or range, a desired IR value or range, and a desired abnormal deterioration grade) input from the outside (for example, the computers 31, 32, 33, . By doing so, it becomes possible to present possible customer business operators (demand business operators) candidates for each battery diagnosed as having a deteriorated state.
- a desired specification range a desired SOH value or range, a desired IR value or range, and a desired abnormal deterioration grade
- the battery residual value management system 100 uses the battery residual value assessment and calibration device 802 to acquire deterioration information in the actual battery operation state from the outside (for example, a battery deterioration database by business type and battery actual operation state), form deterioration trend information in the battery actual operation state from the deterioration information (see FIG. 7A: for example, a graph having a plurality of change points), and calibrate one or more thresholds (for example, the threshold for determining the grade of the abnormal deterioration degree) in the index (for example, the degree of abnormal deterioration) based on the deterioration trend information.
- a process is executed to determine (correct) the remaining value rank of the battery to be subjected to remaining value assessment using the calibrated threshold value.
- the threshold value of the index can be calibrated according to the actual operating state, and the above multidimensional vector space can be more accurately divided into a plurality of regions by reflecting this, so that the residual value of the battery can be evaluated more accurately.
- the battery residual value management system 100 acquires market price information corresponding to the value of the battery index (e.g., SOH) value from an external source (e.g., a market price database that manages the market price of second-hand batteries) by means of the battery residual value correction device 1002 that reflects the market price, executes processing for correcting one or more thresholds in the index based on the market price information, and determines (corrects) the residual value rank of the battery subject to residual value assessment using the corrected threshold.
- the threshold value of the index can be calibrated according to the market price, and the above multidimensional vector space can be more accurately divided into a plurality of areas by reflecting this, so that the residual value of the battery can be evaluated more accurately.
- the battery residual value management system 100 acquires battery reservation information including residual value data, quantity, and delivery date of a desired battery from the outside (computer group 30 of the battery demand business operator) by the residual value-based demand plan calculation device 1100, summarizes the battery reservation information based on the battery type, and outputs it as demand plan information. Also, the battery reservation information may be classified into short-term reservation, medium-term reservation, and long-term reservation according to the timing of the delivery date, and may be output as demand plan information collectively for each classification. By doing so, it becomes possible to manage which battery is required at what time and in what quantity.
- the battery residual value management system 100 acquires battery procurement information including residual value data, quantity, and delivery date of batteries that can be supplied by the supplier from the outside (battery supplier's computer group 20) using the residual value procurement plan calculation device 1200, summarizes the battery procurement information based on the battery type, and outputs it as procurement plan information. Also, the battery procurement information may be classified into short-term procurement, medium-term procurement, and long-term procurement according to the timing of delivery on the supply side, and may be output as procurement plan information collectively for each classification. By doing so, it becomes possible to manage which battery can be supplied at what time and in what quantity.
- the battery residual value management system 100 is provided with a demand plan calculation device 1100 by residual value and a procurement plan calculation device 1200 by residual value, and a battery supply and demand suitability judgment device 1300 by residual value.
- the demand plan information and the procurement plan information are collated in the battery supply and demand suitability determination device 1300 by residual value to determine the balance between demand and supply of each battery (the quantity of surplus and missing items and availability of supply).
- the battery residual value management system 100 includes a residual value-based demand plan calculation device 1100, a residual value-based procurement plan calculation device 1200, and a residual value-based battery supply and demand suitability determination device 1300, as well as a medium- to long-term plan recommendation device 1400 for battery procurement by residual value. Generate prediction information including the prediction information, and output the prediction information.
- the battery residual value management system 100 uses the battery procurement plan cooperation system 1500 to generate recommended information regarding battery supply based on the forecast information, and transmits the recommended information to the computer on the supply side and/or the demand side. By providing such forecast information (recommended information) to both the demand side and the supply side, it is possible to minimize the difference (divergence) between supply and demand and to operate the battery market optimally.
- the battery residual value management system 100 determines and outputs the content of the battery security service according to the grade of the degree of abnormal deterioration of the battery by the security service provision type matching system 1600 . As a result, it becomes possible to provide a security service according to the grade of the degree of abnormal deterioration of the battery. Further, the battery residual value management system 100 determines and outputs the content of the battery deterioration monitoring service according to the grade of the degree of abnormal deterioration of the battery by the deterioration monitoring service provision type matching system 1700 . This makes it possible to provide a deterioration monitoring service according to the grade of the degree of abnormal deterioration of the battery. Note that the content of the battery security service and the content of the battery deterioration monitoring service may be determined according to the grade of the degree of abnormal deterioration determined by the calibrated threshold. This makes it possible to provide services more accurately.
- control lines and information lines are those considered necessary for explanation, and not all control lines and information lines are necessarily shown on the product. All configurations may be interconnected.
- battery residual value management system 101 battery residual value assessment system 102 battery residual value response supply chain system 103 battery residual value response maintenance management system 20 battery supplier computer group 30 battery demand business computer group 40 service provider computer group 51, 52, 53 network 303 battery residual value assessment device 602 residual value matching device 802 battery residual value assessment and calibration device 1002 market price reflection type Battery residual value correction device 1100 Demand plan calculation device by residual value 1200 Procurement plan calculation device by residual value 1300 Suitability determination device for battery supply and demand by residual value 1400 Medium- to long-term plan recommendation device for battery procurement by residual value 1500 Battery procurement plan cooperation system 1600 Security service provision type matching system 1700 Deterioration monitoring service provision type matching system
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Abstract
Description
本開示は、このような状況に鑑み、より正確に二次電池の残価を評価する技術を提案する。
本明細書の記述は典型的な例示に過ぎず、本開示の請求の範囲又は適用例をいかなる意味においても限定するものではない。
図1は、本実施形態による電池残価マネジメントシステム100全体の概略構成例を示す図である。
(i)二次電池の残価評価要素
図2Aから図2Cは、本実施形態による電池残価評価要素の例を示す図である。本実施形態による電池残価査定システム101では、SOH(Sate Of Health:容量)のほかに、さらに2つの指標、例えば、IR(Internal Resistance:内部抵抗)と異常劣化度を導入し、これらの組み合わせにより二次電池の残価を査定(評価)するようにしている。
図2Aは、本実施形態による3次元評価領域(区分)の例を示す図である。図2Aに示されるように、本実施形態では、SOH(0から100%)、IR(内部抵抗値で評価、あるいは増加率で評価)、および異常劣化度(不良から良好)の3つの要因(指標)を導入し、これら3つの指標を軸とした3次元空間において各指標値の範囲で規定される複数の空間領域によって残価評価を行う(残価別ランクを決定する)。つまり、二次電池の劣化状態を、SOHおよびIRの2指標(2次元)マップ上で定義される領域と、3指標目の異常劣化度の掛け合わせによって構成される3次元空間領域内で定義する(電池残価査定装置)。それぞれの指標には1つ以上の閾値を設定し、二次電池を指標毎に電池の劣化状態に応じてランク分けするようにしている。
図2Bは、残価別ランクと各指標(SOH、IR、および異常劣化度)の範囲との関係(例)を示す図である。まず、SOHについては、二次電池のSOH値の閾値を設定し、領域を決定する。例えば、SOH値が例えば70%以上100%未満の場合にはSOH第1領域(ランクI)に、50%以上70%未満の場合にはSOH第2領域(ランクII)、30%以上50%未満の場合にはSOH第3領域(ランクIII)、・・・とすることができる。ここでは、一般的に電気自動車で保障されているSOH70%を第1閾値とし、実用上限定的な運用空間領域(例えば、工場内や工場現場内に限定するなど)であれば電気自動車として運用することが可能なSOH50%を第2閾値とすることができる。また、一般的に充電効率が低く、定置型利用としても再利用活用効果が低いとされるSOH30%を第3閾値とすることができる。
SOH=fSOH(ΔVb,c_SOH_T_1,c_SOH_T_2,・・・,c_SOH_I_1,c_SOH_I_2,・・・) ・・・ (2)
図2Cは、各診断対象の電池(診断電池)の種類(モデル名)の各測定指標値とそれに対応する評価結果である残価別ランク(例)を示す図である。
(ii-1)基本構成例:クラウドサーバを用いて実現する構成例
図3Aは、本実施形態による電池残価査定システム101の概略構成例1を示す図である。電池残価査定システム101は、電池(二次電池)301を測定する専用装置である充放電装置(テスタでもよい)302からネットワーク(例えば、インタネット)を介して測定結果を取得し電池301の残価を評価(査定)する、電池残価査定装置303と、評価結果を表示画面上に表示するため、および/またはユーザに評価結果の情報を送信するために一時的に格納するメモリ304と、を備える。
図3Cは、オンプレミス形態による電池残価査定システム101の構成例3を示す図である。オンプレミス形態による電池残価査定システム101は、通信部3034以外クラウドサーバ形態によるシステムと同一構成要素および機能を有している。また、電池残価査定装置303は、充放電装置302とネットワークを介さずに直接接続されるように構成される。通信部(通信デバイスで実現可能)3034は、通信線を介して、演算結果(SOH値、IR値、および異常劣化度)および評価結果(残価別ランク)をメモリ304に送信し格納する。電池残価査定装置303とメモリ304とが通信線を介して接続されていない場合には通信部3034を設ける必要はなく、演算部3032から直接メモリ304に演算結果および評価結果が格納される。
残価マッチング装置は、図2Aの3次元空間内領域で定義される残価査定済み電池を、需要事業者の購入残価要件(購入残価要求値記憶部)に見合うようにする残価マッチング機能を有している。以下、残価マッチング機能の概要(図4)、残価マッチング結果(図5)、および残価マッチング装置を含む電池残価査定システム101の構成例(図6)について順次説明する。
図4は、残価マッチング機能の概要について説明するための図である。残価マッチング機能は、電池残価査定装置303によって定義(算出)された3つの指標によって劣化状態が診断された電池(二次電池)と各事業者が要求する仕様範囲に合致する電池とをマッチングする機能である。
図5は、残価マッチング結果例を示す図である。残価マッチング結果は、図1Cに示される残価診断結果に、残価マッチングにより導き出された対象電池の需要事業者候補501が追加されて構成される。図5からは、例えば、電池IDがA0001の電池は、事業者BおよびCの仕様範囲に適合し、電池IDがA0002の電池は、事業者Cの仕様範囲のみに適合し、電池IDがA0003の電池は、事業者A、BおよびCの仕様範囲に適合するため、これらの事業者が需要事業者(提供先)候補として選択される。このように、残価マッチング機能により、劣化状態が診断された各電池に対しては、提供可能な顧客事業者候補を提示することが可能となる。
図6は、本実施形態による残価マッチング装置を含む電池残価査定システム101の概略構成例を示す図である。図6には、クラウドサーバとして、電池残価査定装置303および残価マッチング装置602が示されているが、前述のオンプレミス形態やエッジコンピューティング形態で実現してもよい。
電池残価査定校正装置は、図2Aの3次元の空間内領域で定義される残価査定済み電池について、市場での実稼働状態における劣化傾向分析値(事業形態別および電池実稼働状態別の電池劣化データベース)を加味して残価査定の閾値を校正する機能を提供する。以下、電池残価査定校正機能の概要(図7)、および電池残価査定校正装置を含む電池残価査定システム101の構成例(図8)について順次説明する。
図7Aおよび図7Bは、本実施形態による電池残価査定校正機能の概要を説明するための図である。図2を参照して説明したように、電池残価査定システム101においては、SOH、IR、および異常劣化度の3つの指標により電池の劣化状態に応じて、ランク分け(残価別ランク分け)を行っている。各指標に対して設定される閾値(例えば、異常劣化度がCからAの場合には、異常劣化度としてAが最高ランクになる)は、設計仕様や各事業者の顧客要求仕様などにより設定される。しかし、その閾値の設定と市場で生じる電池の異常や不具合の発生頻度には相違が生じる場合がある。そこで、電池残価査定校正装置802は、このような相違を修正するため、各閾値を市場での実稼働状態における劣化傾向分析値により校正する機能を提供する。
図8は、本実施形態による電池残価査定校正装置802を含む電池残価査定システム101の概略構成例を示す図である。図8には、クラウドサーバとして、電池残価査定装置303および電池残価査定校正装置802が示されているが、前述のオンプレミス形態やエッジコンピューティング形態で実現してもよい。
本実施形態による電池残価補正装置は、初期設定された閾値、および/または電池残価査定校正機能によって校正された閾値を、さらに、市場での中古電池市況価格をも加味して閾値を補正する機能を提供する(市況価格反映型の電池残価補正装置)。
図9は、本実施形態による電池残価補正機能の概要を説明するための図である。図9Aは補正前の閾値(例)を示す図であり、図9Bは補正後の閾値(例)を示す図である。
図10は、本実施形態による電池残価補正装置を含む電池残価査定システム101の概略構成例を示す図である。図10には、クラウドサーバとして、電池残価査定装置303および電池残価補正装置1002が示されているが、前述のオンプレミス形態やエッジコンピューティング形態で実現してもよい。
(i)残価別予約機能:電池需要事業者の予約データを時期(短期・中期・長期など)に応じて振り分けて表示する機能
図11Aは、本実施形態による電池残価対応サプライチェーンシステム102を含む電池残価マネジメントシステム100の全体概略構成例1を示す図である。当該電池残価マネジメントシステム100は、電池残価対応サプライチェーンシステム102として、残価マッチング装置602における購入残価要求値記憶部6023に残価別予約機能(短中長期)を提供する残価別需要計画演算装置1100を付加することにより構成される。なお、図11Aにおける電池残価対応サプライチェーンシステム102は、残価別需要計画演算装置1100のみが構成要素となっているが、残価別需要計画演算装置1100以外にも、後述のように、残価別調達計画演算装置1200(図12A参照)、残価別電池需給の適合判断装置1300(図13A参照)、残価別電池調達の中長期計画推奨装置1400(図14A参照)、および電池調達計画連携システム1500(図15A参照)の少なくとも何れかを含むように構成してもよい。また、図11Aには、クラウドサーバとして、電池残価対応サプライチェーンシステム102を含む電池残価マネジメントシステム100が示されているが、前述のオンプレミス形態やエッジコンピューティング形態で実現してもよい。
図12Aは、本実施形態による電池残価対応サプライチェーンシステム102を含む電池残価マネジメントシステム100の全体概略構成例2を示す図である。当該電池残価マネジメントシステム100は、電池残価対応サプライチェーンシステム102として、残価マッチング装置602における購入残価要求値記憶部6023に残価別電池調達機能(短中長期)を提供する残価別調達計画演算装置1200を付加することにより構成される。なお、図12Aにおける電池残価対応サプライチェーンシステム102は、残価別調達計画演算装置1200のみが構成要素となっているが、残価別調達計画演算装置1200以外にも、後述のように、残価別需要計画演算装置1100(図11A参照)、残価別電池需給の適合判断装置1300(図13A参照)、残価別電池調達の中長期計画推奨装置1400(図14A参照)、および電池調達計画連携システム1500(図15A参照)の少なくとも何れかを含むように構成してもよい。また、図12Aには、クラウドサーバとして、電池残価対応サプライチェーンシステム102を含む電池残価マネジメントシステム100が示されているが、前述のオンプレミス形態やエッジコンピューティング形態で実現してもよい。
図13Aは、本実施形態による電池残価対応サプライチェーンシステム102を含む電池残価マネジメントシステム100の全体概略構成例3を示す図である。当該電池残価マネジメントシステム100は、電池残価対応サプライチェーンシステム102として、上記残価別予約機能(短中長期)を提供する残価別需要計画演算装置1100、上記残価別調達機能(短中長期)を提供する残価別調達計画演算装置1200、および残価別電池需給適合判断機能を提供する残価別電池需給の適合判断装置1300をクラウド内に付加することにより構成される。なお、図13Aには、クラウドサーバとして、電池残価対応サプライチェーンシステム102を含む電池残価マネジメントシステム100が示されているが、前述のオンプレミス形態やエッジコンピューティング形態で実現してもよい。
図14Aは、本実施形態による電池残価対応サプライチェーンシステム102を含む電池残価マネジメントシステム100の全体概略構成例4を示す図である。当該電池残価マネジメントシステム100は、電池残価対応サプライチェーンシステム102として、上述の残価別予約機能(短中長期)を提供する残価別需要計画演算装置1100、上述の残価別調達機能(短中長期)を提供する残価別調達計画演算装置1200、上述の残価別電池需給適合判断機能を提供する残価別電池需給の適合判断装置1300、および残価別電池調達の中長期計画推奨装置1400をクラウド内に付加することにより構成される。なお、図14Aには、クラウドサーバとして、電池残価対応サプライチェーンシステム102を含む電池残価マネジメントシステム100が示されているが、前述のオンプレミス形態やエッジコンピューティング形態で実現してもよい。
図15Aは、本実施形態による電池残価対応サプライチェーンシステム102を含む電池残価マネジメントシステム100の全体概略構成例5を示す図である。当該電池残価マネジメントシステム100は、電池残価対応サプライチェーンシステム102として、上述の残価別予約機能(短中長期)を提供する残価別需要計画演算装置1100、上述の残価別調達機能(短中長期)を提供する残価別調達計画演算装置1200、上述の残価別電池需給適合判断機能を提供する残価別電池需給の適合判断装置1300、上述の残価別電池調達の中長期計画推奨装置1400、および電池調達計画連携システム1500をクラウド内に付加することにより構成される。なお、図15Aには、クラウドサーバとして、電池残価対応サプライチェーンシステム102を含む電池残価マネジメントシステム100が示されているが、前述のオンプレミス形態やエッジコンピューティング形態で実現してもよい。
(i)保障サービス付与型マッチング機能:残価マッチング装置602による残価マッチング結果において、特に3指標目の異常劣化度に基づくグレードに連動して保障サービスを付与する機能
図16Aは、本実施形態による電池残価対応保守管理システム103を含む電池残価マネジメントシステム100の全体概略構成例1を示す図である。当該電池残価マネジメントシステム100は、電池残価対応保守管理システム103として、保障サービス付与型マッチングシステム1600をクラウド内に付加することにより構成される。なお、図16Aには、クラウドサーバとして、電池残価対応保守管理システム103を含む電池残価マネジメントシステム100が示されているが、前述のオンプレミス形態やエッジコンピューティング形態で実現してもよい。また、図16Aでは、保障サービス付与型マッチングシステム1600は、残価マッチング装置602に接続されているが、残価マッチング装置602は必須の構成要素ではなく、直接電池残価査定装置303に接続されるようにしてもよい。
図17Aは、本実施形態による電池残価対応保守管理システム103を含む電池残価マネジメントシステム100の全体概略構成例2を示す図である。当該電池残価マネジメントシステム100は、電池残価対応保守管理システム103として、劣化監視サービス付与型マッチングシステム1700をクラウド内に付加することにより構成される。なお、図17Aには、クラウドサーバとして、電池残価対応保守管理システム103を含む電池残価マネジメントシステム100が示されているが、前述のオンプレミス形態やエッジコンピューティング形態で実現してもよい。図17Aでは、劣化監視サービス付与型マッチングシステム1700は、残価マッチング装置602に接続されているが、残価マッチング装置602は必須の構成要素ではなく、電池残価査定装置303に直接接続されるようにしてもよい。
図18Aは、本実施形態による電池残価対応保守管理システム103を含む電池残価マネジメントシステム100の全体概略構成例3を示す図である。当該電池残価マネジメントシステム100は、電池残価対応保守管理システム103として、保障サービス付与型マッチングシステム1600と劣化監視サービス付与型マッチングシステム1700をクラウド内に付加することにより構成される。なお、図18Aには、クラウドサーバとして、電池残価対応保守管理システム103を含む電池残価マネジメントシステム100が示されているが、前述のオンプレミス形態やエッジコンピューティング形態で実現してもよい。
(i)電池残価マネジメントシステム100の変形例
図19は、変形例による電池残価マネジメントシステム100の概略構成例を示す図である。当該変形例においては、電池残価査定システム101と電池残価対応サプライチェーンシステム102と電池供給事業者のコンピュータ群20との間に、電池再生事業者のコンピュータ群60を設置する。これにより、電池供給事業者からのデータだけではなく、電池再生事業者からのデータをも活用することができる。例えば、電池供給事業者から電池再生事業者に供給された電池のデータを電池再生事業者が電池残価査定システム101および/または電池残価対応サプライチェーンシステム102にアップロードすることができるようにシステムが構成される。これにより、電池の残価を査定し、電池の二次利用に活用することができる。また、電池残価対応サプライチェーンシステム102は、電池再生事業者のコンピュータ群60および電池需要事業者のコンピュータ群30からデータを取得し、電池の需給を最適化することができる。
(i)本実施形態によれば、電池残価マネジメントシステム100は、電池(二次電池)の残価を評価するための少なくとも3つの指標で構成される多次元ベクトル空間(3次元空間以上)において、各指標(例えば、SOH、IR(内部抵抗関連情報:例えば、内部抵抗増加率)、異常劣化度)に設定された1以上の閾値で定義され、電池の残価別ランクを決定するための複数の領域を有する多次元ベクトル空間の情報(図2A参照)を少なくとも1つの記憶デバイスに保持している。当該システム100は、記憶デバイスから多次元ベクトル空間の情報を取得し、残価査定対象の電池の少なくとも3つの指標(外部(ネットワークを介して接続された充放電装置やコンピュータ)から入力された測定値から演算によって得られる)に基づいて、当該残価査定対象の電池が多次元ベクトル空間の複数の領域のどこに属するか判定することにより、残価査定対象の電池の残価別ランクを決定する。このようにすることにより、より正確に電池の残価別ランクを決定することができる。
101 電池残価査定システム
102 電池残価対応サプライチェーンシステム
103 電池残価対応保守管理システム
20 電池供給事業者のコンピュータ群
30 電池需要事業者のコンピュータ群
40 サービス事業者のコンピュータ群
51、52、53 ネットワーク
303 電池残価査定装置
602 残価マッチング装置
802 電池残価査定校正装置
1002 市況価格反映型の電池残価補正装置
1100 残価別需要計画演算装置
1200 残価別調達計画演算装置
1300 残価別電池需給の適合判断装置
1400 残価別電池調達の中長期計画推奨装置
1500 電池調達計画連携システム
1600 保障サービス付与型マッチングシステム
1700 劣化監視サービス付与型マッチングシステム
Claims (32)
- 電池の残価を管理する電池残価マネジメントシステムであって、
前記電池の残価を評価するための少なくとも3つの指標で構成される多次元ベクトル空間において、各指標に設定された1以上の閾値で定義された領域であって、前記電池の残価別ランクを決定するための複数の領域を有する多次元ベクトル空間の情報を格納する、少なくとも1つの記憶デバイスと、
前記記憶デバイスから前記多次元ベクトル空間の情報を取得し、残価査定対象の電池の前記少なくとも3つの指標に基づいて、当該残価査定対象の電池が前記多次元ベクトル空間の前記複数の領域のどこに属するか判定することにより、前記残価査定対象の電池の残価別ランクを決定する、少なくとも1つのプロセッサと、
を備える、電池残価マネジメントシステム。 - 請求項1において、
前記多次元ベクトル空間は、電池のSOH、電池の内部抵抗関連情報、および電池の異常劣化度を含む指標で構成される、電池残価マネジメントシステム。 - 請求項1において、
前記プロセッサは、外部から入力された所望の仕様範囲に合致する電池を、前記残価別ランクが決定済の複数の電池から抽出し、抽出した情報を出力する、電池残価マネジメントシステム。 - 請求項1において、
前記プロセッサは、前記電池の実稼働状態における劣化情報を外部から取得し、当該劣化情報から前記電池の実稼働状態における劣化傾向情報を構成し、当該劣化傾向情報に基づいて前記指標における前記1以上の閾値を校正する処理を実行し、当該校正された閾値を用いて前記残価査定対象の電池の残価別ランクを決定する、電池残価マネジメントシステム。 - 請求項1において、
前記プロセッサは、前記電池の前記指標の値に対応する市況価格情報を外部から取得し、当該市況価格情報に基づいて前記指標における前記1以上の閾値を補正する処理を実行し、当該補正された閾値を用いて前記残価査定対象の電池の残価別ランクを決定する、電池残価マネジメントシステム。 - 請求項3において、
前記プロセッサは、外部から需要側の所望の電池の残価データ、数量、および納期を含む電池予約情報を取得し、当該電池予約情報を電池の種別に基づいてまとめ、需要計画情報として出力する、電池残価マネジメントシステム。 - 請求項6において、
前記プロセッサは、前記電池予約情報を前記納期のタイミングに応じて短期予約、中期予約、および長期予約に分類し、当該分類ごとにまとめて前記需要計画情報として出力する、電池残価マネジメントシステム。 - 請求項3において、
前記プロセッサは、外部から供給側が供給可能な電池の残価データ、数量、および納期を含む電池調達情報を取得し、当該電池調達情報を電池の種別に基づいてまとめ、調達計画情報として出力する、電池残価マネジメントシステム。 - 請求項8において、
前記プロセッサは、前記電池調達情報を前記供給側の納期のタイミングに応じて短期調達、中期調達、および長期調達に分類し、当該分類ごとにまとめて前記調達計画情報として出力する、電池残価マネジメントシステム。 - 請求項6において、
前記プロセッサは、外部から供給側が供給可能な電池の残価データ、数量、および納期を含む電池調達情報を取得し、当該電池調達情報を電池の種別に基づいてまとめ、調達計画情報として出力する、電池残価マネジメントシステム。 - 請求項10において、
前記プロセッサは、前記需要計画情報と前記調達計画情報とを照合し、各電池の需要と供給のバランスを判定する、電池残価マネジメントシステム。 - 請求項11において、
前記プロセッサは、各電池の需要と供給のバランスを示す情報に対して機械学習を実行することにより、将来の供給予測と需要予測を含む予測情報を生成し、当該予測情報を出力する、電池残価マネジメントシステム。 - 請求項12において、
前記プロセッサは、前記予測情報に基づいて、電池供給に関する推奨情報を生成し、前記供給側のコンピュータに前記推奨情報を送信するように構成される、電池残価マネジメントシステム。 - 請求項2において、
前記プロセッサは、前記電池の異常劣化度のグレードに応じて、前記電池の保障サービス内容を決定し、出力する、電池残価マネジメントシステム。 - 請求項2において、
前記プロセッサは、前記電池の異常劣化度のグレードに応じて、前記電池の劣化監視サービス内容を決定し、出力する、電池残価マネジメントシステム。 - 請求項4において、
前記指標は、異常劣化度であり、
前記プロセッサは、前記校正された閾値によって判定された前記異常劣化度のグレードに応じて、前記電池の保障サービス内容および前記電池の劣化監視サービス内容を決定し、出力する、電池残価マネジメントシステム。 - 電池の残価を管理する電池残価マネジメント方法であって、
少なくとも1つのプロセッサが、前記電池の残価を評価するための少なくとも3つの指標で構成される多次元ベクトル空間において、各指標に設定された1以上の閾値で定義される領域であって、前記電池の残価別ランクを決定するための複数の領域を有する多次元ベクトル空間の情報を格納する少なくとも1つの記憶デバイスから前記多次元ベクトル空間の情報を取得することと、
前記プロセッサが、残価査定対象の電池の前記少なくとも3つの指標に基づいて、当該残価査定対象の電池が前記多次元ベクトル空間の前記複数の領域のどこに属するか判定することにより、前記残価査定対象の電池の残価別ランクを決定することと、
を含む、電池残価マネジメント方法。 - 請求項17において、
前記多次元ベクトル空間は、電池のSOH、電池の内部抵抗関連情報、および電池の異常劣化度を含む指標で構成される、電池残価マネジメント方法。 - 請求項17において、さらに、
前記プロセッサが、外部から入力された所望の仕様範囲に合致する電池を、前記残価別ランクが決定済の複数の電池から抽出し、抽出した情報を出力することを含む、電池残価マネジメント方法。 - 請求項17において、さらに、
前記プロセッサが、前記電池の実稼働状態における劣化情報を外部から取得することと、
前記プロセッサが、前記劣化情報から前記電池の実稼働状態における劣化傾向情報を構成することと、
前記プロセッサが、前記劣化傾向情報に基づいて前記指標における前記1以上の閾値を校正する処理を実行することと、を含み、
前記プロセッサは、前記校正された閾値を用いて前記残価査定対象の電池の残価別ランクを決定する、電池残価マネジメント方法。 - 請求項17において、さらに、
前記プロセッサが、前記電池の前記指標の値に対応する市況価格情報を外部から取得することと、
前記プロセッサが、前記市況価格情報に基づいて前記指標における前記1以上の閾値を補正する処理を実行することと、を含み、
前記プロセッサは、前記補正された閾値を用いて前記残価査定対象の電池の残価別ランクを決定する、電池残価マネジメント方法。 - 請求項19において、さらに、
前記プロセッサが、外部から需要側の所望の電池の残価データ、数量、および納期を含む電池予約情報を取得することと、
前記プロセッサが、前記電池予約情報を電池の種別に基づいてまとめ、需要計画情報として出力することと、
を含む、電池残価マネジメント方法。 - 請求項22において、
前記プロセッサは、前記電池予約情報を前記納期のタイミングに応じて短期予約、中期予約、および長期予約に分類し、当該分類ごとにまとめて前記需要計画情報として出力する、電池残価マネジメント方法。 - 請求項19において、さらに、
前記プロセッサが、外部から供給側が供給可能な電池の残価データ、数量、および納期を含む電池調達情報を取得することと、
前記プロセッサが、前記電池調達情報を電池の種別に基づいてまとめ、調達計画情報として出力することと、
を含む、電池残価マネジメント方法。 - 請求項24において、さらに、
前記プロセッサが、前記電池調達情報を前記供給側の納期のタイミングに応じて短期調達、中期調達、および長期調達に分類し、当該分類ごとにまとめて前記調達計画情報として出力する、電池残価マネジメント方法。 - 請求項22において、さらに、
前記プロセッサが、外部から供給側が供給可能な電池の残価データ、数量、および納期を含む電池調達情報を取得することと、
前記プロセッサが、前記電池調達情報を電池の種別に基づいてまとめ、調達計画情報として出力することと、
を含む、電池残価マネジメント方法。 - 請求項26において、さらに、
前記プロセッサが、前記需要計画情報と前記調達計画情報とを照合し、各電池の需要と供給のバランスを判定することを含む、電池残価マネジメント方法。 - 請求項27において、さらに、
前記プロセッサが、各電池の需要と供給のバランスを示す情報に対して機械学習を実行することにより、将来の供給予測と需要予測を含む予測情報を生成することと、
前記プロセッサが、前記予測情報を出力することと、
を含む、電池残価マネジメント方法。 - 請求項28において、さらに、
前記プロセッサが、前記予測情報に基づいて、電池供給に関する推奨情報を生成することと、
前記プロセッサが、前記供給側のコンピュータに前記推奨情報を送信することと、
を含む、電池残価マネジメント方法。 - 請求項18において、さらに、
前記プロセッサが、前記電池の異常劣化度のグレードに応じて、前記電池の保障サービス内容を決定し、出力することを含む、電池残価マネジメント方法。 - 請求項18において、さらに、
前記プロセッサが、前記電池の異常劣化度のグレードに応じて、前記電池の劣化監視サービス内容を決定し、出力することを含む、電池残価マネジメント方法。 - 請求項20において、さらに、
前記指標は、異常劣化度であり、
前記プロセッサが、前記校正された閾値によって判定された前記異常劣化度のグレードに応じて、前記電池の保障サービス内容および前記電池の劣化監視サービス内容を決定し、出力することを含む、電池残価マネジメント方法。
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Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2011044346A (ja) * | 2009-08-21 | 2011-03-03 | Toyota Motor Corp | 二次電池の制御装置、二次電池の制御方法および制御マップの作成方法 |
JP2014190763A (ja) * | 2013-03-26 | 2014-10-06 | Toshiba Corp | 電池寿命推定方法及び電池寿命推定装置 |
JP2015225723A (ja) * | 2014-05-26 | 2015-12-14 | トヨタ自動車株式会社 | 余寿命推定方法 |
JP2017009540A (ja) * | 2015-06-25 | 2017-01-12 | トヨタ自動車株式会社 | 二次電池の内部抵抗推定方法および出力制御方法 |
JP2017034781A (ja) * | 2015-07-30 | 2017-02-09 | 国立大学法人電気通信大学 | 蓄電池管理システム、蓄電池情報サーバ、充放電制御装置及び蓄電池 |
JP2018147827A (ja) * | 2017-03-08 | 2018-09-20 | 株式会社東芝 | 充放電制御装置、使用条件作成装置、プログラム、及び蓄電システム |
JP2021136182A (ja) * | 2020-02-28 | 2021-09-13 | 株式会社デンソー | 情報算出システム |
WO2021193005A1 (ja) * | 2020-03-27 | 2021-09-30 | 本田技研工業株式会社 | 管理システム、管理方法、サーバ装置、プログラム、バッテリ情報提供システム、およびバッテリ情報提供方法 |
WO2021235522A1 (ja) * | 2020-05-22 | 2021-11-25 | 株式会社携帯市場 | 情報処理装置、情報処理方法、及びプログラム |
Family Cites Families (5)
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---|---|---|---|---|
US20170286882A1 (en) * | 2016-04-01 | 2017-10-05 | Demand Energy Networks, Inc. | Control systems and methods for economical optimization of an electrical system |
US10539621B2 (en) * | 2017-08-02 | 2020-01-21 | Total Solar International | Method and apparatus for identifying a battery model |
JP6722955B1 (ja) * | 2019-04-02 | 2020-07-15 | 東洋システム株式会社 | バッテリー残存価値表示装置 |
JP7457943B2 (ja) * | 2020-03-27 | 2024-03-29 | パナソニックIpマネジメント株式会社 | 充放電システム、充放電装置 |
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Patent Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2011044346A (ja) * | 2009-08-21 | 2011-03-03 | Toyota Motor Corp | 二次電池の制御装置、二次電池の制御方法および制御マップの作成方法 |
JP2014190763A (ja) * | 2013-03-26 | 2014-10-06 | Toshiba Corp | 電池寿命推定方法及び電池寿命推定装置 |
JP2015225723A (ja) * | 2014-05-26 | 2015-12-14 | トヨタ自動車株式会社 | 余寿命推定方法 |
JP2017009540A (ja) * | 2015-06-25 | 2017-01-12 | トヨタ自動車株式会社 | 二次電池の内部抵抗推定方法および出力制御方法 |
JP2017034781A (ja) * | 2015-07-30 | 2017-02-09 | 国立大学法人電気通信大学 | 蓄電池管理システム、蓄電池情報サーバ、充放電制御装置及び蓄電池 |
JP2018147827A (ja) * | 2017-03-08 | 2018-09-20 | 株式会社東芝 | 充放電制御装置、使用条件作成装置、プログラム、及び蓄電システム |
JP2021136182A (ja) * | 2020-02-28 | 2021-09-13 | 株式会社デンソー | 情報算出システム |
WO2021193005A1 (ja) * | 2020-03-27 | 2021-09-30 | 本田技研工業株式会社 | 管理システム、管理方法、サーバ装置、プログラム、バッテリ情報提供システム、およびバッテリ情報提供方法 |
WO2021235522A1 (ja) * | 2020-05-22 | 2021-11-25 | 株式会社携帯市場 | 情報処理装置、情報処理方法、及びプログラム |
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