CN115092012A - Equivalent state-of-charge estimation method considering multiple working modes of hybrid power supply system - Google Patents
Equivalent state-of-charge estimation method considering multiple working modes of hybrid power supply system Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
- B60L58/10—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries
- B60L58/12—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries responding to state of charge [SoC]
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L3/00—Electric devices on electrically-propelled vehicles for safety purposes; Monitoring operating variables, e.g. speed, deceleration or energy consumption
- B60L3/12—Recording operating variables ; Monitoring of operating variables
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L50/00—Electric propulsion with power supplied within the vehicle
- B60L50/40—Electric propulsion with power supplied within the vehicle using propulsion power supplied by capacitors
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L50/00—Electric propulsion with power supplied within the vehicle
- B60L50/50—Electric propulsion with power supplied within the vehicle using propulsion power supplied by batteries or fuel cells
- B60L50/60—Electric propulsion with power supplied within the vehicle using propulsion power supplied by batteries or fuel cells using power supplied by batteries
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L2260/00—Operating Modes
- B60L2260/40—Control modes
- B60L2260/50—Control modes by future state prediction
- B60L2260/52—Control modes by future state prediction drive range estimation, e.g. of estimation of available travel distance
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- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
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- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/70—Energy storage systems for electromobility, e.g. batteries
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Abstract
The invention provides an equivalent state of charge estimation method considering multiple working modes of a composite power supply system for a vehicle, which is specifically completed by a method based on a comprehensive weight factor. The method comprises the following steps: s1, acquiring the maximum discharge capacity of a battery pack and a super capacitor and the output power of the battery pack and the super capacitor; s2, determining the working mode state of the vehicle according to the output power of the battery pack and the output power of the super capacitor; s3, calculating the state of charge (SOC) of the battery pack bat And state of charge SOC of super capacitor uc At equivalent state of charge ESOC weight factor λ bat And λ uc Taking values in the working mode state; s4, calculating an equivalent state of charge (ESOC), wherein: ESOC＝λ bat SOC bat +λ uc SOC uc . The method has the advantages of simple flow and uncomplicated algorithm, is convenient to embed into the vehicle composite power supply management system, realizes equivalent state of charge estimation of the vehicle composite power supply system in different working modes, and can provide data support for accurate prediction of the driving distance of the electric vehicle, thereby having a plurality of beneficial effects which are not possessed by the prior art.
Description
Technical Field
The invention relates to the technical field of management of a vehicle composite power supply system, in particular to an equivalent state of charge estimation method considering multiple working modes of a composite power supply system.
Background
The composite power supply system composed of the lithium ion battery and the super capacitor can meet the dual requirements of the electric automobile on high specific energy and high specific power, and becomes one of the important development directions of the automobile industry. In the prior art, a State of Charge (SOC) estimation method for a single energy storage system, especially for a power battery/super capacitor, is relatively mature. However, the technology for performing equivalent state of charge ESOC estimation by regarding the hybrid power supply system as a whole is still deficient. The ESOC is also an important parameter, and the value can provide data support for the accurate prediction of the driving distance of the electric automobile, and meanwhile, the driver can reasonably arrange the travel according to the value. If the ESOC estimation is inaccurate, the vehicle can be anchored on the road due to insufficient energy supply, and even a traffic accident can be caused.
Meanwhile, in the face of complex automobile operation conditions, each energy storage element in the composite power supply system needs to be in an on or off state according to different optimization targets, and the composite power supply system is in different working modes, so that the advantages of a battery and a super capacitor are fully exerted, and the power requirement of the system is met. However, the flexible operation mode of the hybrid power system makes it difficult for the existing state of charge estimation technology for the battery/super capacitor to reflect the remaining energy and power output capability of the hybrid power system as a whole in the current operation mode.
Disclosure of Invention
In view of the above, the invention provides an equivalent state of charge estimation method considering multiple working modes of a hybrid power supply system, which has the advantages of simple process and uncomplicated algorithm, is conveniently embedded into an automotive hybrid power supply management system, realizes equivalent state of charge estimation of the hybrid power supply system in different working modes, and can provide data support for accurate prediction of the driving distance of an electric automobile, thereby having many beneficial effects which are not provided in the prior art, and being suitable for a hybrid power supply vehicle consisting of a battery pack and a super capacitor. The method comprises the following steps:
s1, acquiring the maximum discharge capacity of a battery pack and a super capacitor and the output power of the battery pack and the super capacitor;
s2, determining the working mode state of the vehicle according to the output power of the battery pack and the output power of the super capacitor;
s3, calculating the state of charge (SOC) of the battery pack bat And state of charge SOC of the super capacitor uc At equivalent state of charge ESOC weight factor λ bat And λ uc Taking values in the working mode state;
s4, calculating an equivalent state of charge (ESOC), wherein:
ESOC＝λ bat SOC bat +λ uc SOC uc 。
further, the step S2 specifically includes:
s21, defining a symbolic function m 1 、m 2 、m 3 And m 4 The method specifically comprises the following steps:
wherein, P ave And P batmax Respectively representing the average output power and the maximum output power of the battery pack; p bat And P uc Respectively representing the output power of the battery pack and the output power of the super capacitor pack;
s22, judging the current working mode state of the composite power supply system according to the sign function, specifically:
if m is 1 ＝1、m 2 ＝0、m 3 M is less than or equal to 0 4 If the number is less than 0, the working mode is 1;
if 0 < m 1 ＜1、0＜m 2 ＜1、m 3 0 and m 4 If the value is less than 0, the working mode is 2;
if 0 < m 1 ＜1、0＜m 2 ＜1、m 3 > 0 and m 4 If the value is 0, the working mode is 3;
if m is 1 ≤0、m 2 ≤0、m 3 < 0 and m 4 If the current value is less than 0, the working mode is in a 4 working mode;
otherwise, it is in the operation mode 5.
Further, step S3 specifically includes:
if the working state of the vehicle hybrid power supply system is in the mode 1, the following steps:
in the formula of lambda bat1 And λ uc1 Respectively represents the SOC when the hybrid power system is in the working mode 1 bat And super SOC uc The size of the weight of (c);
if the working state of the vehicle hybrid power supply system is in the mode 2, the following steps are carried out:
in the formula, λ bat2 And λ uc2 Respectively represents the SOC when the hybrid power system is in the working mode 2 bat And SOC uc The size of the weight of (c); c C The ratio of the maximum available capacity of the battery pack to the maximum available total capacity of the hybrid power system is obtained; i represents a vehicle driving condition, and i-1 represents a driving condition 1; n is i Is a capacity change probability function under the driving condition i.
If the working state of the vehicle composite power supply system is in the mode 3, the calculation method is the same as that in the mode 2;
if the working state of the vehicle hybrid power supply system is in the mode 4, the following steps:
in the formula, λ bat4 And λ uc4 Respectively represents the SOC when the composite power supply system is in the working mode 4 bat And SOC uc The size of the weight of (c); c bat And C uc Respectively representing the maximum available capacity of the battery pack and the super capacitor pack;
if the operating state of the hybrid power supply system of the vehicle is in the mode 5, the calculation method is the same as that in the mode 4.
Further, when the working state of the vehicle hybrid power supply system is in the mode 2, the ratio C of the maximum available capacity of the battery pack to the maximum available total capacity of the hybrid power supply system C And a capacity change probability function n under the driving condition i i The calculation method comprises the following steps:
t 2 ＝t 21 +t 22 +...+t 2i ,i＝1,2,3,4,....
wherein, C bat And C uc Respectively representing the maximum available capacity of the battery pack and the super capacitor pack; t is t 2i 、C a2i And C b2i Respectively representing the duration of the composite power supply system in the mode 2, the capacity change rate of the battery pack and the capacity change rate of the super capacitor pack under the driving working condition i; t is t 2 The total length of time that all operating conditions are in mode 2.
Drawings
The invention is further described below with reference to the following figures and examples:
FIG. 1 is a flow chart of an equivalent state of charge estimation method that considers multiple operating modes of a hybrid power system;
FIG. 2 is an equivalent circuit model of the built hybrid power system for a vehicle;
fig. 3 shows a specific operation mode and a transition path of an operation state of the hybrid power supply system for a vehicle;
fig. 4 is a simulation verification effect diagram of the equivalent state of charge ESOC index of the composite power supply system in different working modes when the vehicle is in the comprehensive driving working condition.
Detailed Description
The invention provides an equivalent state of charge estimation method considering multiple working modes of a composite power supply system, which is suitable for a composite power supply vehicle consisting of a battery pack and a super capacitor, and comprises the following steps:
s1, acquiring the maximum discharge capacity of a battery pack and a super capacitor and the output power of the battery pack and the super capacitor;
s2, determining the working mode state of the vehicle according to the output power of the battery pack and the output power of the super capacitor;
s3, calculating the state of charge (SOC) of the battery pack bat And state of charge SOC of super capacitor uc At equivalent state of charge ESOC weight factor λ bat And λ uc Taking values in the working mode state;
s4, calculating an equivalent state of charge (ESOC), wherein:
ESOC＝λ bat SOC bat +λ uc SOC uc 。
in this embodiment, an equivalent circuit model of the hybrid power supply system for the vehicle is established, and as shown in fig. 2, the equivalent circuit is composed of a voltage source U oc An ohmic internal resistance R 0 And a parallel polarization resistor R b And a polarization capacitor C b The series connection is formed in sequence, and the concrete form is as follows:
in the formula i 0 Representing charge and discharge current; u shape oc 、U b And U t Respectively representing an open circuit voltage, a polarization voltage and an output voltage;
in this embodiment, a transmission model of a vehicle is established, which is embodied in the following form:
in the formula, P req Representing the required power of the vehicle; v. of a Indicates the running speed of the vehicle in unitsKm/h; alpha represents the gradient of the road surface on which the vehicle runs; eta, m, f, C ar A and delta respectively represent the transmission system efficiency, full load mass, rolling resistance coefficient, air resistance coefficient, windward area and rotating mass correction coefficient of the vehicle; g represents the acceleration of gravity.
In this embodiment, the step S2 specifically includes:
s21, defining a symbolic function m 1 、m 2 、m 3 And m 4 The method specifically comprises the following steps:
wherein, P ave And P batmax Respectively representing the average output power and the maximum output power of the battery pack; p bat And P uc Respectively representing the output power of the battery pack and the output power of the super capacitor pack;
s22, judging the current working mode state of the composite power supply system according to the sign function, specifically:
if m is 1 ＝1、m 2 ＝0、m 3 M is less than or equal to 0 4 If the number is less than 0, the working mode is 1;
if 0 < m 1 ＜1、0＜m 2 ＜1、m 3 0 and m 4 If the value is less than 0, the working mode is 2;
if 0 < m 1 ＜1、0＜m 2 ＜1、m 3 > 0 and m 4 If 0, the working mode is 3;
if m is 1 ≤0、m 2 ≤0、m 3 < 0 and m 4 If the value is less than 0, the working mode is 4;
otherwise, it is in the operation mode 5.
In this embodiment, the specific working mode and the operation state transition path thereof are as shown in fig. 3, where the mode 1 refers to: 0 < P req ≤P ave At this time P req Smaller, battery packs can independently and continuously meet the power and energy requirements of the drive motor, i.e., P bat ＝P req 、P uc ＝0；
The mode 2 refers to: 0 < P ave ＜P req ≤P batmax ，P req Is divided into two parts, wherein the battery pack continuously outputs P ave The super capacitor group outputs the rest power, i.e. P bat ＝P ave 、P uc ＝P req -P bat ；
The mode 3 refers to: 0 < P batmax ＜P req Output of battery pack P batmax The excess part is borne by the super capacitor bank, i.e. P bat ＝P batmax 、P uc ＝P req -P bat ；
The mode 4 refers to: p is req Less than 0; in this case, the regenerative electric energy generated by braking the vehicle is preferentially absorbed by the super capacitor bank until the SOC is reached uc When the peak charging power reaches the upper limit value, the battery pack recovers the residual energy according to the peak charging power;
the mode 5 refers to: p req 0; in this mode, the vehicle is in a standby state, at which time neither the battery pack nor the supercapacitor pack outputs/recovers any power or energy to the drive motor, i.e., P bat ＝0、P uc ＝0；
In this embodiment, the step S3 specifically includes:
if the working state of the vehicle hybrid power supply system is in the mode 1, the following steps:
in the formula, λ bat1 And λ uc1 Respectively represents the SOC when the hybrid power system is in the working mode 1 bat And super SOC uc The size of the weight of (c);
if the working state of the vehicle hybrid power supply system is in the mode 2, the following steps are carried out:
in the formula, λ bat2 And λ uc2 Respectively represents the SOC when the hybrid power system is in the working mode 2 bat And SOC uc The size of the weight of (c); c C The ratio of the maximum available capacity of the battery pack to the maximum available total capacity of the hybrid power system is obtained; i represents the driving condition of the vehicle, and i is 1, which represents the driving condition 1; n is i Is a capacity change probability function under the driving condition i.
If the working state of the vehicle composite power supply system is in mode 3, P is in the moment req The battery pack and the super capacitor pack share the same role, so the calculation method is the same as that of the mode 2;
if the working state of the vehicle hybrid power supply system is in the mode 4, the following steps:
in the formula, λ bat4 And λ uc4 Respectively represents the SOC when the composite power supply system is in the working mode 4 bat And SOC uc The size of the weight of (c); c bat And C uc Respectively representing the maximum available capacity of the battery pack and the super capacitor pack;
if the working state of the vehicle hybrid power supply system is in the mode 5, the vehicle is in the standby state at this time, and the calculation method is the same as that of the mode 4.
In this embodiment, when the operating state of the hybrid power supply system of the vehicle is in mode 2, the ratio C of the maximum available capacity of the battery pack to the maximum available total capacity of the hybrid power supply system C And a capacity change probability function n under the driving condition i i The calculation method comprises the following steps:
t 2 ＝t 21 +t 22 +...+t 2i ,i＝1,2,3,4,....
wherein, C bat And C uc Respectively representing the maximum available capacity of the battery pack and the super capacitor pack; t is t 2i 、C a2i And C b2i Respectively representing the duration of the composite power supply system in the mode 2, the capacity change rate of the battery pack and the capacity change rate of the super capacitor pack under the driving working condition i; t is t 2 The total length of time that all operating conditions are in mode 2.
In this embodiment, the duration t of the hybrid power supply system in the mode 2 of the vehicle under different driving conditions 2i And rate of change of capacity C of the battery pack a2i And rate of change of capacity C of the supercapacitor pack b2i Is obtained through simulation software; in this embodiment, 3 different typical vehicle driving conditions are selected: UDDS (urban operating mode), WVUSUB (suburban operating mode), HWFET (high speed operating mode).
In this embodiment, in step S4, SOC bat And SOC uc The estimation method adopts an ampere-hour integral method, and the calculation formula is as follows:
in the formula, SOC 0 The initial nuclear power state of the battery pack/super capacitor pack is set; c n The maximum available capacity of the battery/supercapacitor pack; i.e. i t The current value of the battery pack/super capacitor pack at the current moment is obtained.
In the embodiment, when the vehicle is in the comprehensive driving working condition, the simulation operation data of the composite power supply system in different working modes is shown in fig. 4; general variation trend of equivalent state of charge (ESOC) and state of charge (SOC) of battery pack bat Are identical and when only the battery pack outputs power, the vehicle hybrid power supply system is in operating mode 1, equivalent state of charge ESOC and battery pack state of charge SOC bat The curve is in a descending trend, and the state of charge SOC of the super capacitor uc No change occurs; the required power is composed of battery pack and super powerWhen the capacitor banks are provided together, the complex power supply system is in a mode 2 or mode 3 state, and the state of charge SOC of the battery pack is at the moment bat SOC of super capacitor uc The equivalent state of charge ESOC curve shows a descending trend; when the required power is negative, the composite power supply system is in a mode 4, the super capacitor bank recovers braking energy, and the state of charge SOC of the super capacitor is uc The curve rises rapidly and the equivalent state of charge ESOC increases slowly because the operating principle of the supercapacitor pack is that the auxiliary battery pack fulfills the power demand of the load. Therefore, the equivalent state of charge ESOC index obtained by the method provided by the invention can reflect the change of the actual available capacity of the hybrid power system when the hybrid power system is switched into different working modes, can predict the driving distance of the electric vehicle, and has great significance for the stable operation of the hybrid power system.
Finally, the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all of them should be covered in the claims of the present invention.
Claims (4)
1. An equivalent state-of-charge estimation method considering multiple working modes of a hybrid power system is suitable for a hybrid power vehicle consisting of a battery pack and a super capacitor, and is characterized in that: the method comprises the following steps:
s1, acquiring the maximum discharge capacity of a battery pack and a super capacitor and the output power of the battery pack and the super capacitor;
s2, determining the working mode state of the vehicle according to the output power of the battery pack and the output power of the super capacitor;
s3, calculating the state of charge (SOC) of the battery pack bat And state of charge SOC of super capacitor uc At equivalent state of charge ESOC weight factor λ bat And λ uc Taking values in the working mode state;
s4, calculating an equivalent state of charge (ESOC), wherein:
ESOC＝λ bat SOC bat +λ uc SOC uc 。
2. the method of claim 1, wherein the method comprises: the step S2 specifically includes:
s21, defining a symbolic function m 1 、m 2 、m 3 And m 4 The method specifically comprises the following steps:
wherein, P ave And P batmax Respectively representing the average output power and the maximum output power of the battery pack; p bat And P uc Respectively representing the output power of the battery pack and the output power of the super capacitor pack;
s22, judging the current working mode state of the composite power supply system according to the sign function, specifically:
if m is 1 ＝1、m 2 ＝0、m 3 M is less than or equal to 0 4 If the number is less than 0, the working mode is 1;
if 0 < m 1 ＜1、0＜m 2 ＜1、m 3 0 and m 4 If the value is less than 0, the working mode is 2;
if 0 < m 1 ＜1、0＜m 2 ＜1、m 3 > 0 and m 4 If 0, the working mode is 3;
if m is 1 ≤0、m 2 ≤0、m 3 < 0 and m 4 If the value is less than 0, the working mode is 4;
otherwise, it is in the operation mode 5.
3. The method of claim 1, wherein the method comprises: the step S3 specifically includes:
if the working state of the vehicle hybrid power supply system is in the mode 1, the following steps:
in the formula, λ bat1 And λ uc1 Respectively represents the SOC when the hybrid power system is in the working mode 1 bat And super SOC uc The size of the weight of (c);
if the working state of the vehicle hybrid power supply system is in the mode 2, the following steps are carried out:
in the formula, λ bat2 And λ uc2 Respectively represents the SOC when the hybrid power system is in the working mode 2 bat And SOC uc The size of the weight of (c); c C The ratio of the maximum available capacity of the battery pack to the maximum available total capacity of the hybrid power system is obtained; i represents a vehicle driving condition, and i-1 represents a driving condition 1; n is i Is a capacity change probability function under the driving condition i.
If the working state of the vehicle composite power supply system is in the mode 3, the calculation method is the same as that in the mode 2;
if the working state of the vehicle hybrid power supply system is in the mode 4, the following steps:
in the formula, λ bat4 And λ uc4 Respectively represents the SOC when the hybrid power system is in the working mode 4 bat And SOC uc The size of the weight of (c); c bat And C uc Respectively representing the maximum available capacity of the battery pack and the super capacitor pack;
if the operating state of the hybrid power supply system of the vehicle is in the mode 5, the calculation method is the same as that in the mode 4.
4. The method of claim 3, wherein the method comprises: when the working state of the vehicle composite power supply system is in the mode 2, the ratio C of the maximum available capacity of the battery pack to the maximum available total capacity of the composite power supply system C And a capacity change probability function n under the driving condition i i The calculating method comprises the following steps:
t 2 ＝t 21 +t 22 +...+t 2i ,i＝1,2,3,4,....
wherein, C bat And C uc Respectively representing the maximum available capacity of the battery pack and the super capacitor pack; t is t 2i 、C a2i And C b2i Respectively representing the duration of the composite power supply system in the mode 2, the capacity change rate of the battery pack and the capacity change rate of the super capacitor pack under the driving working condition i; t is t 2 The total duration that all operating conditions last in mode 2.
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Citations (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006017544A (en) * | 2004-06-30 | 2006-01-19 | Fuji Heavy Ind Ltd | Remaining capacity computing device for electricity accumulating device |
| DE102011104320A1 (en) * | 2010-06-22 | 2011-12-22 | Gm Global Technology Operations Llc (N.D.Ges.D. Staates Delaware) | Adaptive Battery Parameter Extraction and SOC Estimation for a Lithium Ion Battery |
| US20120109556A1 (en) * | 2010-10-29 | 2012-05-03 | GM Global Technology Operations LLC | Band select state of charge weighted scaling method |
| CN102540081A (en) * | 2010-12-29 | 2012-07-04 | 上海汽车集团股份有限公司 | Method for determining charge state of vehicle-mounted storage battery |
| CN104071033A (en) * | 2013-12-07 | 2014-10-01 | 西南交通大学 | Method for matching and optimizing parameters of mixed power locomotive with fuel cell and super capacitor |
| US20150231986A1 (en) * | 2014-02-20 | 2015-08-20 | Ford Global Technologies, Llc | Battery Capacity Estimation Using State of Charge Initialization-On-The-Fly Concept |
| US20170259688A1 (en) * | 2016-03-09 | 2017-09-14 | Ford Global Technologies, Llc | Battery Capacity Estimation Based on Open-Loop And Closed-Loop Models |
| CN107402353A (en) * | 2017-06-30 | 2017-11-28 | 中国电力科学研究院 | A kind of state-of-charge to lithium ion battery is filtered the method and system of estimation |
| US20190036356A1 (en) * | 2017-07-31 | 2019-01-31 | Robert Bosch Gmbh | Method and System for Estimating Battery Open Cell Voltage, State of Charge, and State of Health During Operation of the Battery |
| CN110208703A (en) * | 2019-04-24 | 2019-09-06 | 南京航空航天大学 | The method that compound equivalent-circuit model based on temperature adjustmemt estimates state-of-charge |
| CN110303945A (en) * | 2019-07-15 | 2019-10-08 | 福州大学 | A kind of battery group electricity adaptive optimization balance control method |
| WO2020129478A1 (en) * | 2018-12-18 | 2020-06-25 | パナソニックＩｐマネジメント株式会社 | Battery state estimation device, battery state estimation method, and battery system |
| CN112345940A (en) * | 2020-10-27 | 2021-02-09 | 中北大学 | Vehicle composite power supply system fuzzy logic control method based on SOC estimation |
| AU2020103886A4 (en) * | 2020-12-04 | 2021-02-11 | Nanjing Forestry University | A Method for Estimating SOC of a Fractional-Order Kinetic Battery Considering Temperature and Hysteresis Effect |
| CN112421745A (en) * | 2020-10-27 | 2021-02-26 | 武汉大学 | Energy management method for composite power supply system of electric automobile |
| CN112434463A (en) * | 2020-10-27 | 2021-03-02 | 中北大学 | Energy management system for vehicle hybrid power supply |
| CN113495214A (en) * | 2021-05-25 | 2021-10-12 | 四川轻化工大学 | Super capacitor charge state estimation method based on temperature change model |
| CN114572053A (en) * | 2022-03-04 | 2022-06-03 | 中南大学 | Electric automobile energy management method and system based on working condition identification |
| US20220212545A1 (en) * | 2021-01-07 | 2022-07-07 | Ford Global Technologies, Llc | Electrified vehicle control using battery electrochemical equilibrium based state of charge and power capability estimates |
-
2022
- 2022-07-20 CN CN202210857107.2A patent/CN115092012B/en active Active
Patent Citations (20)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006017544A (en) * | 2004-06-30 | 2006-01-19 | Fuji Heavy Ind Ltd | Remaining capacity computing device for electricity accumulating device |
| DE102011104320A1 (en) * | 2010-06-22 | 2011-12-22 | Gm Global Technology Operations Llc (N.D.Ges.D. Staates Delaware) | Adaptive Battery Parameter Extraction and SOC Estimation for a Lithium Ion Battery |
| US20120109556A1 (en) * | 2010-10-29 | 2012-05-03 | GM Global Technology Operations LLC | Band select state of charge weighted scaling method |
| CN102540081A (en) * | 2010-12-29 | 2012-07-04 | 上海汽车集团股份有限公司 | Method for determining charge state of vehicle-mounted storage battery |
| CN104071033A (en) * | 2013-12-07 | 2014-10-01 | 西南交通大学 | Method for matching and optimizing parameters of mixed power locomotive with fuel cell and super capacitor |
| US20150231986A1 (en) * | 2014-02-20 | 2015-08-20 | Ford Global Technologies, Llc | Battery Capacity Estimation Using State of Charge Initialization-On-The-Fly Concept |
| US20170259688A1 (en) * | 2016-03-09 | 2017-09-14 | Ford Global Technologies, Llc | Battery Capacity Estimation Based on Open-Loop And Closed-Loop Models |
| CN107402353A (en) * | 2017-06-30 | 2017-11-28 | 中国电力科学研究院 | A kind of state-of-charge to lithium ion battery is filtered the method and system of estimation |
| US20190036356A1 (en) * | 2017-07-31 | 2019-01-31 | Robert Bosch Gmbh | Method and System for Estimating Battery Open Cell Voltage, State of Charge, and State of Health During Operation of the Battery |
| WO2020129478A1 (en) * | 2018-12-18 | 2020-06-25 | パナソニックＩｐマネジメント株式会社 | Battery state estimation device, battery state estimation method, and battery system |
| CN110208703A (en) * | 2019-04-24 | 2019-09-06 | 南京航空航天大学 | The method that compound equivalent-circuit model based on temperature adjustmemt estimates state-of-charge |
| CN110303945A (en) * | 2019-07-15 | 2019-10-08 | 福州大学 | A kind of battery group electricity adaptive optimization balance control method |
| CN112345940A (en) * | 2020-10-27 | 2021-02-09 | 中北大学 | Vehicle composite power supply system fuzzy logic control method based on SOC estimation |
| CN112421745A (en) * | 2020-10-27 | 2021-02-26 | 武汉大学 | Energy management method for composite power supply system of electric automobile |
| CN112434463A (en) * | 2020-10-27 | 2021-03-02 | 中北大学 | Energy management system for vehicle hybrid power supply |
| AU2020103886A4 (en) * | 2020-12-04 | 2021-02-11 | Nanjing Forestry University | A Method for Estimating SOC of a Fractional-Order Kinetic Battery Considering Temperature and Hysteresis Effect |
| US20220212545A1 (en) * | 2021-01-07 | 2022-07-07 | Ford Global Technologies, Llc | Electrified vehicle control using battery electrochemical equilibrium based state of charge and power capability estimates |
| CN114714974A (en) * | 2021-01-07 | 2022-07-08 | 福特全球技术公司 | Electric vehicle control using battery state of charge and power capacity estimation |
| CN113495214A (en) * | 2021-05-25 | 2021-10-12 | 四川轻化工大学 | Super capacitor charge state estimation method based on temperature change model |
| CN114572053A (en) * | 2022-03-04 | 2022-06-03 | 中南大学 | Electric automobile energy management method and system based on working condition identification |
Non-Patent Citations (6)
| Title |
|---|
| CHEN, L (CHEN, LIN) [1] ; WANG, ZZ (WANG, ZENGZHENG) ; LÜ, ZQ (LU, ZHIQIANG) ; LI, JZ (LI, JUNZI) ; JI, B (JI, BING) ; WEI, HY (: "A Novel State-of-Charge Estimation Method of Lithium-Ion Batteries Combining the Grey Model and Genetic Algorithms", 《IEEE TRANSACTIONS ON POWER ELECTRONICS 》, 1 October 2018 (2018-10-01), pages 8797 - 8807, XP011687270, DOI: 10.1109/TPEL.2017.2782721 * |
| P. B. BOBBA AND K. R. RAJAGOPAL: "Modeling and analysis of hybrid energy storage systems used in Electric vehicles", 《IEEE INTERNATIONAL CONFERENCE ON POWER ELECTRONICS, DRIVES AND ENERGY SYSTEMS》, 19 December 2012 (2012-12-19) * |
| 尹其林: "基于粒子群算法的电动汽车混合储能系统能量管理策略研究", 《中国硕士学位论文全文数据库 工程科技II辑》, 6 June 2016 (2016-06-06) * |
| 王春，李强: "基于无迹卡尔曼滤波的超级电容SOC估计", 《电源技术》, 20 December 2021 (2021-12-20) * |
| 蒋玮，薛帅，严学庆，杨陈，朱程伟，张磊: "考虑多工作模式的链式混合储能系统广义等效模型及荷电状态估计技术研究", 《中国电机工程学报》, no. 2019, 5 January 2019 (2019-01-05), pages 182 - 191 * |
| 鲍慧;于洋;: "基于安时积分法的电池SOC估算误差校正", 计算机仿真, no. 11, 15 November 2013 (2013-11-15) * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11707987B1 (en) * | 2022-12-06 | 2023-07-25 | Mercedes-Benz Group AG | Vehicle simulating method and system |
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