CN113759252B - Online evaluation method for cell cluster inconsistency of energy storage power station based on direct-current internal resistance ir pressure drop - Google Patents
Online evaluation method for cell cluster inconsistency of energy storage power station based on direct-current internal resistance ir pressure drop Download PDFInfo
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- CN113759252B CN113759252B CN202111175261.3A CN202111175261A CN113759252B CN 113759252 B CN113759252 B CN 113759252B CN 202111175261 A CN202111175261 A CN 202111175261A CN 113759252 B CN113759252 B CN 113759252B
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- 238000004146 energy storage Methods 0.000 title claims abstract description 21
- 238000011156 evaluation Methods 0.000 title description 7
- 239000000178 monomer Substances 0.000 claims abstract description 23
- 238000012512 characterization method Methods 0.000 claims abstract description 18
- 230000008859 change Effects 0.000 claims abstract description 13
- 238000000034 method Methods 0.000 claims abstract description 12
- 238000012216 screening Methods 0.000 claims abstract description 5
- 230000003247 decreasing effect Effects 0.000 claims abstract description 4
- 230000032683 aging Effects 0.000 claims description 7
- 238000012544 monitoring process Methods 0.000 claims description 4
- 230000009471 action Effects 0.000 claims description 2
- HBBGRARXTFLTSG-UHFFFAOYSA-N Lithium ion Chemical compound [Li+] HBBGRARXTFLTSG-UHFFFAOYSA-N 0.000 description 7
- 229910001416 lithium ion Inorganic materials 0.000 description 7
- 238000007600 charging Methods 0.000 description 4
- 238000007599 discharging Methods 0.000 description 3
- 238000005070 sampling Methods 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010277 constant-current charging Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000009795 derivation Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000012983 electrochemical energy storage Methods 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- 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]
- G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- 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]
- G01R31/378—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC] specially adapted for the type of battery or accumulator
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- 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]
- G01R31/389—Measuring internal impedance, internal conductance or related variables
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- 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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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/10—Energy storage using batteries
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Abstract
The invention discloses an energy storage power station battery cluster inconsistency online assessment method based on direct current internal resistance ir voltage drop, which comprises the following steps: screening a battery PACK box based on two parameter indexes of available capacity and direct current internal resistance, and selecting a characterization monomer; the voltage drop amplitude delta U dc、Δudc of the battery cluster and the characterization monomer ir is obtained in real time, the change rate f '(delta U dc,n·Δudc) is obtained based on the linear fitting relation f (delta U dc,n·Δudc), n is the number of battery PACK boxes, and if f' (delta U dc,n·Δudc) shows a decreasing trend along with the circulation, the non-uniformity of the battery cluster is reflected to be aggravated. The method is low in implementation cost, easy to apply practically and capable of effectively evaluating the inconsistency of the battery clusters on line.
Description
Technical Field
The invention relates to the field of electrochemical energy storage, in particular to the field of detection of the health state of a lithium ion battery cluster for electric power energy storage.
Background
Along with the continuous construction of a novel power system, renewable energy gradually replaces fossil energy, an energy storage link plays a key role more and more, and the lithium ion battery energy storage plays an important role in the domestic energy storage project, so that safe and stable operation of the lithium ion battery energy storage system is important and difficult to develop in the future of the novel power system. And Battery management system (Battery MANAGEMENT SYSTEM, BMS) is limited in computational power due to the hardware level. Therefore, the actual application problem needs to be considered while the operation state evaluation means of the energy storage battery is continuously updated.
Nowadays, lithium ion battery energy storage power stations adopt a battery module unit box (called a battery PACK box for short) as a basic unit to construct a battery cluster. However, due to certain differences between the initial performance parameters of the battery PACK box and the external working environment, monitoring of inconsistency problems during operation is extremely important. If each single battery SOH in the box body is detected in real time, the operability is not high. Therefore, a floating rule of a corresponding relation between a battery cluster parameter and a battery PACK box parameter caused by the inconsistency of battery aging in the constant-current charging and discharging process is explored, and the inconsistency of the battery cluster is evaluated on line based on a related result, so that the method has important significance for safe and stable operation of an energy storage power station and retirement of the battery PACK box.
Disclosure of Invention
In order to ensure the safe running state of the battery clusters of the energy storage power station, reduce the possibility of unbalanced accidents and promote the realizability of echelon utilization of the energy storage batteries, the invention provides the on-line evaluation method for the inconsistency of the battery clusters based on the direct-current internal resistance ir pressure drop, and the parameters of an energy storage Battery Management System (BMS) are effectively utilized to improve the safety of the energy storage power station. Meanwhile, the method hardly produces disturbance on the evaluated object, and is easy to be practically applied.
In a first aspect, the uncertainty difference in available capacity and internal resistance is a major source of battery pack inconsistency. Therefore, before the battery cluster is put into operation in groups, the battery PACK box is screened based on two parameter indexes of available capacity and direct current internal resistance, and the characterization monomers are selected, wherein the screening conditions are as follows:
The available capacity q and the direct current internal resistance r dc of the characterization monomer are closest to the average value of the available capacities of all battery PACK boxes in the battery cluster and the average value of the direct current internal resistances, and the characterization monomer is taken as a reference object to provide a reference for the inconsistency in the working process of the battery cluster.
In a second aspect, a method for evaluating the inconsistency of a battery cluster of an energy storage power station based on the voltage drop of a direct current internal resistance ir is provided, which comprises the following steps:
The charge and discharge current of the energy storage power station is kept unchanged, the voltage drop amplitude delta U dc、Δudc of the battery cluster and the characterization monomer due to the direct current internal resistance is obtained, real-time fitting is carried out, a linear change relation f (delta U dc,n·Δudc) is obtained, and n is the number of battery PACK boxes;
Deriving a rate of change f' (Δu dc,n·Δudc) based on a linear fit change relationship f (Δu dc,n·Δudc);
Under the condition that the sampling step length is unchanged, online recording is carried out on the change rate f '(delta U dc,n·Δudc), and if f' (delta U dc,n·Δudc) shows a decreasing trend, the situation that the inconsistency of the battery clusters is aggravated and the aging degree of the battery PACK box is uneven is reflected.
Further, in determining PACK case inconsistency in a battery cluster, further comprising:
And (3) disconnecting the direct-current side contactor of the converter and the BMS high-voltage box switch, detecting the direct-current internal resistance of each battery PACK box, and replacing the one with larger direct-current internal resistance, namely the one with deeper aging degree.
Advantageous effects
The invention provides an online evaluation method for the inconsistency of the lithium ion battery cluster for energy storage based on direct current internal resistance ir voltage drop, which has the advantages of lower implementation cost, no disturbance, easy practical application and capability of effectively evaluating the inconsistency of the battery cluster online.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a method for evaluating inconsistency of a battery cluster according to an embodiment of the present invention
Fig. 2 is a schematic diagram of screening a battery cluster characterization monomer according to an embodiment of the present invention
FIG. 3 is a graph depicting the ir drop of a cell according to an example of the invention
Fig. 4 is an example battery ir drop of the invention
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail below. It will be apparent that the described embodiments are only some, but not all, embodiments of the invention. All other embodiments, based on the examples herein, which are within the scope of the invention as defined by the claims, will be within the scope of the invention as defined by the claims.
The battery management system BMS can monitor the discharge voltage of the battery cluster and the characterization monomer on line in real time. With the increasing number of charge and discharge cycles and the difference of external conditions, the consistency of the charge and discharge cycles and the difference of external conditions is difficult to ensure, and the difference of voltage drop amplitude values of the battery cluster and the characterization monomer ir is amplified continuously. Therefore, ir pressure drop DeltaU dc、Δudc of the battery cluster and the characterization monomer caused by direct current internal resistance is obtained in real time, and the inconsistency of the battery cluster is reflected through the linear fitting relation of the pressure drop amplitude values of the battery cluster and the characterization monomer.
As shown in fig. 1, an embodiment of the present invention provides a flowchart of a method for evaluating inconsistency of a battery cluster of an energy storage power station, including:
S1: before the battery clusters are put into operation in groups, the battery PACK boxes are screened based on two parameter indexes of available capacity and direct current internal resistance, and a representation monomer is selected, namely the available capacity q and the direct current internal resistance r dc of the representation monomer are closest to the average value of the available capacities and the average value of the direct current internal resistances of all the battery PACK boxes in the battery clusters, and a screening schematic diagram is shown in figure 2.
S2: the charge and discharge current of the energy storage power station is kept unchanged, and the voltage drop amplitude delta U dc、Δudc of the battery cluster and the characterization monomer ir is obtained in real time.
S3: and performing real-time fitting to obtain a linear change relation f (delta U dc,n·Δudc), wherein n is the number of battery PACK boxes.
S4: and carrying out real-time derivation based on the linear fitting relation f (delta U dc,n·Δudc) to obtain the change rate f' (delta U dc,n·Δudc), and carrying out online recording on the change rate.
S41: under the condition that the sampling step length is unchanged, along with the progress of circulation, f' (delta U dc,n·Δudc) shows the trend of reducing, then reflects that the battery cluster inconsistency is aggravated, and the battery PACK case has the uneven condition of ageing degree, opens converter direct current side contactor and BMS high voltage box switch, carries out direct current internal resistance detection to each battery PACK case, changes the great one of direct current internal resistance.
S42: the sampling step length is kept unchanged, the change rate f' (delta U dc,n·Δudc) is kept stable along with the circulation, the consistency of the battery cluster is good, the protection action is not executed, and the real-time online monitoring of the voltage drop of the battery cluster and the characterization monomer ir is continuously carried out.
For a further understanding of the technical solution of the present invention, the present invention will be further described with reference to the following examples.
The experimental platform consists of a biochemical incubator, a high-performance battery monitoring system and a human-computer interaction interface, wherein the temperature of the incubator is maintained at 30 ℃, and the experimental object is a lithium ion button battery. Firstly, constant-current charge-discharge aging is carried out on a battery:
① Discharging to 1.1V at discharge current of 2mA, and standing for 1min;
② Charging to 2.1V at charging current of 2mA, and standing for 1min;
③ Repeating the step ①～② to circularly charge and discharge for 85 times;
④ The constant voltage was discharged to 1.7V.
After aging, the battery is connected with a new lithium ion button battery in series, constant current charge and discharge are carried out, the initial voltage of the battery and the new battery is similar, and the new battery is used as a representation monomer. Constant current charge and discharge were also performed:
① Discharging to 2.2V at discharge current of 2mA, standing for 1min;
② Charging to 4.2V at charging current of 2mA, and standing for 1min;
③ The charge and discharge are repeated 35 times by repeating the step ①～②.
Characterization of monomer ir pressure drop is shown in fig. 3; the series stack ir drop is shown in fig. 4.
As can be seen from the graph, the ir drop caused by the internal dc resistance, Δu dc is greater than Δu dc, and as the cycle progresses, the difference between the voltage drop amplitude of the battery pack and the voltage drop amplitude of the 2 times characterization monomer increases gradually, and the change rate f' (Δu dc,2·Δudc) of the linear fitting relation between the two shows a decreasing trend.
Through the analysis, the change rule of the voltage drop of the direct current internal resistance ir of the battery pack and the representation single battery is consistent with the theoretical analysis of the battery cluster inconsistency on-line evaluation method, and the beneficial effect of the evaluation method is proved from the side face.
While embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the invention, and that variations, modifications, alternatives and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the invention.
Claims (3)
1. The method for online evaluating the inconsistency of the battery clusters of the energy storage power station based on the direct-current internal resistance ir voltage drop is characterized by comprising the following steps:
step one: based on two parameter indexes of the available capacity q and the direct current internal resistance r dc, the battery PACK box is screened to select the characterization monomer, and the screening conditions are as follows:
The available capacity q and the direct current internal resistance r dc of the characterization monomer are closest to the average value of the available capacities and the direct current internal resistances of all battery PACK boxes in the battery cluster;
Step two: obtaining a battery cluster and representing the voltage drop amplitude of the direct-current internal resistance ir of a monomer in real time, and performing linear fitting to obtain a linear relation f (delta U dc,n·Δudc), wherein delta U dc is the voltage drop amplitude of the battery cluster caused by the direct-current internal resistance, delta U dc is the voltage drop amplitude of the monomer represented by the direct-current internal resistance, and n is the number of battery PACK boxes;
Step three: deriving the linear relationship to obtain the rate of change f' (Δu dc,n·Δudc); if f' (ΔU dc,n·Δudc) exhibits a decreasing trend, it is determined that the battery cluster inconsistency is exacerbated.
2. The method for online assessment of battery cluster inconsistency according to claim 1, further comprising, after determining that the inconsistency is exacerbated:
And (3) disconnecting the direct-current side contactor of the converter and the BMS high-voltage box switch, detecting the direct-current internal resistance of each battery PACK box, and replacing the one with larger direct-current internal resistance, namely the one with deeper aging degree.
3. The method for online assessment of battery cluster inconsistency according to claim 1, further comprising:
If the change rate f' (Δu dc,n·Δudc) remains stable, the consistency of the battery cluster is good, no protection action is executed, and the real-time online monitoring of the voltage drop Δu dc、Δudc of the battery cluster and the characterization monomer ir is continued.
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