CN114879066A - Battery pack consistency evaluation method and system - Google Patents
Battery pack consistency evaluation method and system Download PDFInfo
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- CN114879066A CN114879066A CN202210606608.3A CN202210606608A CN114879066A CN 114879066 A CN114879066 A CN 114879066A CN 202210606608 A CN202210606608 A CN 202210606608A CN 114879066 A CN114879066 A CN 114879066A
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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]
- G01R31/385—Arrangements for measuring battery or accumulator variables
- G01R31/387—Determining ampere-hour charge capacity or SoC
- G01R31/388—Determining ampere-hour charge capacity or SoC involving voltage measurements
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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
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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]
- G01R31/396—Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
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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
Abstract
The invention provides a method and a system for evaluating consistency of a battery pack, wherein the method comprises the following steps: collecting and obtaining a test sample, and respectively establishing an SOC-module minimum voltage value curve in the charging and discharging process; comparing an SOC-module minimum voltage value curve in the charging and discharging process, respectively converting the maximum and minimum voltages of the module in the charging and discharging stage to obtain corresponding SOC values, establishing a regression equation and a charging and discharging process SOC-delta SOC curve according to the calculated delta SOC, selecting not less than 2 groups of test samples, and respectively establishing a charging and discharging process standard SOC-delta SOC confidence interval according to the test samples; s3, acquiring data to be tested of the outgoing battery pack, comparing the data to be tested with a charge-discharge process standard SOC-delta SOC confidence interval to obtain a preset confidence interval excess proportion, judging the data to be tested, and judging the excess proportion data and the dispersion data of the battery pack according to the preset confidence interval excess proportion and the preset confidence interval excess proportion, so as to obtain a consistency estimation result of the outgoing battery pack. The technical problems that the whole testing process is not evaluated and the estimation precision is not high in the prior art are solved.
Description
Technical Field
The invention relates to the technical field of batteries, in particular to a battery pack consistency evaluation method and system.
Background
The lithium ion battery is used as a core component of the electric automobile, and the performance of the battery pack directly determines the performance of the electric automobile. Since the battery pack is formed by grouping a plurality of modules in series, the consistency of the modules directly determines the performance of the whole battery pack.
At present, the consistency of the battery pack is mainly judged by judging the pressure difference, and the consistency is judged by judging the dynamic pressure difference and the static pressure difference of charge cut-off and discharge cut-off in an electrical performance test. Prior invention patent application publication No. CN110031771A, a method for describing battery uniformity, comprises the following steps: s1, performing curve processing on the real-time charging curves of all the single batteries in the target lithium ion battery, extracting the characteristic values of all the single batteries, and recording the charging capacities of points corresponding to the characteristic values; s2, calculating SOC distribution values of all single batteries in the battery pack by taking the charging capacity of the characteristic value corresponding point obtained in the step S1 as an algorithm model input parameter; and S3, taking the SOC distribution values of all the single batteries in the battery pack obtained in the S2 as battery consistency description input parameters, and describing the battery consistency. The technical solution disclosed in the prior art document is different from the technical solution of the present application, the prior art document does not fully disclose the technical features of the present application, and the prior art document is used for describing the consistency of the battery, while the present application is used for evaluating the consistency of the battery pack, and the prior art document is different from the technical problems solved by the present application, and the technical effects of the present application cannot be achieved. The method, the device, the equipment and the medium for evaluating the consistency of the voltage of the battery module in the prior invention patent application document with the publication number of CN114094218A acquire at least one attribute parameter of the battery module to be tested in at least two time periods; each time segment comprises at least one time; respectively inputting each attribute parameter in different time periods into a pre-trained regression forest model to obtain at least one moment voltage corresponding to each time period; and respectively generating a state sequence corresponding to each time period according to the voltage at each moment, and evaluating the consistency of the voltage of the battery module to be tested according to the state sequences. The content of the specification of the patent indicates that the prior application document adopts a pre-trained regression forest model to process voltage data, and obtains a battery parameter state sequence through confidence interval prediction, and the specific implementation technical scheme is different from that of the application, and the adopted calculation logic is also greatly different from that of the application, so that the technical effect of the application cannot be achieved.
In conclusion, the prior art is lack of the technical problems of evaluating the whole test process and low estimation precision.
Disclosure of Invention
The invention aims to solve the technical problems that the whole test process is not evaluated and the estimation precision is not high in the prior art.
The invention adopts the following technical scheme to solve the technical problems: the battery pack consistency evaluation method comprises the following steps:
s1, collecting and obtaining test data to serve as test samples, and respectively establishing SOC-module minimum voltage value curves in the charging and discharging processes according to the test samples;
s2, contrasting the SOC-module minimum voltage value curve in the charging and discharging process, respectively converting the module maximum voltage and the module minimum voltage in the charging and discharging stage to obtain corresponding SOC values, establishing a regression equation, a charging process SOC-delta SOC curve and a discharging process SOC-delta SOC curve according to the calculated delta SOC, selecting not less than 2 groups of test samples, and respectively establishing a charging process standard SOC-delta SOC confidence interval and a discharging process standard SOC-delta SOC confidence interval according to the selected test samples;
s3, acquiring data to be tested of a factory battery pack, comparing the data to be tested according to the charging process standard SOC-delta SOC confidence interval and the discharging process standard SOC-delta SOC confidence interval to obtain an exceeding proportion of a preset confidence interval, and judging the exceeding proportion data and the dispersion data of the factory battery pack according to the data to be tested to obtain a consistency estimation result of the factory battery pack.
According to the invention, a delta SOC is obtained through calculation to establish a regression equation and a charge-discharge process SOC-delta SOC curve, at least 2 groups of test samples are selected to respectively establish a charge-discharge process standard SOC-delta SOC confidence interval, the to-be-tested data of a factory battery is compared with the standard SOC-delta SOC confidence interval, if the to-be-tested data exceeds or exceeds a certain proportion, the to-be-tested data does not meet the requirement, the to-be-tested data is judged to be abnormal, and the larger the exceeding proportion is, the larger the dispersion degree is, and the worse the consistency of the battery pack is reflected. The evaluation method provided by the invention can effectively monitor and judge the consistency of the battery pack in the factory test charging and discharging processes, and can carry out targeted reason analysis according to the time position of the occurrence of the abnormity.
In a more specific technical solution, the step S2 includes:
s21, comparing the SOC-module minimum voltage value curve, respectively converting the module maximum voltage and the module minimum voltage of the corresponding SOC in the charging process and the discharging process into corresponding SOC values;
s22, processing the SOC of the maximum voltage of the module and the SOC of the minimum voltage of the module by preset logic to obtain the difference value delta SOC between the maximum voltage value SOC of the module and the minimum SOC of the module;
s23, calculating the delta SOC corresponding to the different obtained SOCs according to preset logic to establish a regression equation, the SOC-delta SOC curve in the charging process and the SOC-delta SOC curve in the discharging process;
and S24, selecting not less than 2 groups of test samples, and respectively establishing standard SOC-delta SOC confidence intervals in the charging and discharging process by using preset statistical logic.
According to the invention, a regression equation is established according to delta SOC corresponding to different SOC obtained by calculation to obtain an SOC-delta SOC curve in the charging process and an SOC-delta SOC curve in the discharging process, and a plurality of groups of sample test data are selected according to the method to respectively establish standard SOC-delta SOC confidence intervals in the charging process and the discharging process by utilizing a statistical method, so that the technical problems of incomplete test and low accuracy caused by the fact that the consistency is judged only by specific parameters such as battery pressure difference, charge and discharge cut-off and the like in the conventional battery pack consistency testing mode in the prior art are solved, and the accuracy of battery pack consistency evaluation is improved.
In a more specific technical solution, in step S22, the module maximum voltage value SOC and the module minimum SOC difference Δ SOC are calculated by using the following logic:
ΔSOC＝SOC vmax -SOC Vmin
wherein SOC is Vmax Is the maximum voltage value SOC, SOC of the module Vmin Is the module minimum.
In a more specific technical solution, the step S2 includes:
s241, randomly selecting not less than 2 test samples to calculate a test curve;
s242, calculating the difference value delta SOC between the maximum voltage value SOC of the module and the minimum SOC of the module corresponding to the test curve under different SOCs, and generating a delta SOC normal distribution diagram;
s243, processing the delta SOC normal distribution diagram to obtain a sample mean value and a standard deviation;
and S244, calculating the confidence interval according to the mean value and the standard deviation to obtain a standard confidence interval from 0% to 100% under S0C.
In a more specific technical solution, in the step 2 and the step 3, a capacity value in a charging stage and a capacity value in a discharging stage are obtained and processed to obtain the SOC value.
In a more specific technical scheme, the SOC value corresponds to a minimum voltage value of the battery pack internal module one to one.
In a more specific technical solution, in the step S21, the SOC value of the charging stage is calculated by using the following logic:
wherein, SOC C Is SOC in the charging phase, C C For the capacity of the currently charged battery pack,
the total capacity charged by the battery pack from the start of charging to the end of charging.
In a more specific technical solution, in the step S21, the SOC value in the discharging stage is calculated by using the following logic:
wherein, SOC D Is SOC in the discharge stage, C D The capacity that the current battery pack has discharged,
is the total capacity discharged from the battery pack from the beginning of discharge to the end of discharge.
According to the invention, the difference value of the maximum voltage value SOC of the module and the minimum SOC of the module is adopted, and the SOC value in the charging stage and the SOC value in the discharging stage are calculated by a specific algorithm, so that the technical problems of low accuracy caused by the fact that the consistency of a battery pack is evaluated only by using parameters such as battery voltage and the like and the corresponding differential pressure of the SOC in different stages is inconsistent in the prior art are solved.
In a more specific technical solution, the step S3 includes:
s31, respectively establishing SOC-module minimum voltage value curves in the charging and discharging processes according to the data to be tested;
s32, comparing the SOC-module minimum voltage value curve, and respectively converting the module maximum voltage and the module minimum voltage of the factory battery pack in the charging and discharging stages into corresponding SOC values;
s33, subtracting the SOC of the minimum module voltage from the SOC value of the maximum module voltage of the battery pack leaving the factory to obtain delta SOC;
s34, calculating to obtain delta SOC of the factory battery pack corresponding to different SOC values, establishing a regression equation, and obtaining an SOC-delta SOC curve of the factory battery pack in the charging process and an SOC-delta SOC curve of the factory battery pack in the discharging process;
s35, fitting the SOC-delta SOC curve of the charging process, the SOC-delta SOC curve of the discharging process and the SOC-delta SOC confidence interval of the charging process and the discharging process of the to-be-tested data, and if the SOC-delta SOC confidence interval exceeds a proportional discrete threshold value in a preset mode, estimating the consistency of the ex-factory battery pack.
The method selects the electrical performance test data to be detected, wherein the data to be recorded comprise a module maximum voltage value Vmax, a module minimum voltage value Vmin, charging capacity and discharging capacity, the acquired battery pack data to be detected comprises data in a charging process and a discharging process, the technical scheme that only data of two time points of a charging cut-off and a discharging cut-off are taken for consistency evaluation in the traditional technology is replaced, and evaluation of the whole test process is achieved.
In a more specific aspect, a system for evaluating battery pack consistency includes:
the minimum voltage value curve establishing module is used for acquiring and obtaining test data to serve as test samples, and establishing SOC-module minimum voltage value curves in the charging and discharging processes respectively according to the test samples;
a confidence interval module, which is used for contrasting the SOC-module minimum voltage value curve in the charging and discharging process, respectively converting the module maximum voltage and the module minimum voltage in the charging and discharging stage to obtain corresponding SOC values, establishing a regression equation, a charging process SOC-delta SOC curve and a discharging process SOC-delta SOC curve according to the calculated delta SOC, selecting not less than 2 groups of test samples, and respectively establishing a charging process standard SOC-delta SOC confidence interval and a discharging process standard SOC-delta SOC confidence interval, wherein the confidence interval module is connected with the minimum voltage value curve establishing module;
the consistency estimation module is used for acquiring data to be tested of an ex-factory battery pack, comparing the data to be tested according to the charging process standard SOC-delta SOC confidence interval and the discharging process standard SOC-delta SOC confidence interval to obtain an exceeding proportion of a preset confidence interval, judging the exceeding proportion data and the dispersion data of the ex-factory battery pack according to the data to be tested to obtain a consistency estimation result of the ex-factory battery pack, and the consistency estimation module is connected with the confidence interval module.
Compared with the prior art, the invention has the following advantages: according to the invention, a delta SOC is obtained through calculation to establish a regression equation and a charge-discharge process SOC-delta SOC curve, at least 2 groups of test samples are selected to respectively establish a charge-discharge process standard SOC-delta SOC confidence interval, the to-be-tested data of a factory battery is compared with the standard SOC-delta SOC confidence interval, if the to-be-tested data exceeds or exceeds a certain proportion, the to-be-tested data does not meet the requirement, the to-be-tested data is judged to be abnormal, and the larger the exceeding proportion is, the larger the dispersion degree is, and the worse the consistency of the battery pack is reflected. The evaluation method provided by the invention can effectively monitor and judge the consistency of the battery pack in the factory test charging and discharging processes, and can carry out targeted reason analysis according to the time position of the occurrence of the abnormity.
According to the invention, a regression equation is established according to delta SOC corresponding to different SOC obtained by calculation to obtain an SOC-delta SOC curve in the charging process and an SOC-delta SOC curve in the discharging process, and a plurality of groups of sample test data are selected according to the method to respectively establish standard SOC-delta SOC confidence intervals in the charging process and the discharging process by utilizing a statistical method, so that the technical problems of incomplete test and low accuracy caused by the fact that the consistency is judged only by specific parameters such as battery pressure difference, charge and discharge cut-off and the like in the conventional battery pack consistency testing mode in the prior art are solved, and the accuracy of battery pack consistency evaluation is improved.
According to the invention, the difference value of the maximum voltage value SOC of the module and the minimum SOC of the module is adopted, and the SOC value in the charging stage and the SOC value in the discharging stage are calculated by a specific algorithm, so that the technical problems of low accuracy caused by the fact that the consistency of a battery pack is evaluated only by using parameters such as battery voltage and the like and the corresponding differential pressure of the SOC in different stages is inconsistent in the prior art are solved.
The method selects the electrical performance test data to be detected, wherein the data to be recorded comprise a module maximum voltage value Vmax, a module minimum voltage value Vmin, charging capacity and discharging capacity, the acquired battery pack data to be detected comprises data in a charging process and a discharging process, the technical scheme that only data of two time points of a charging cut-off and a discharging cut-off are taken for consistency evaluation in the traditional technology is replaced, and evaluation of the whole test process is achieved. The invention solves the technical problems that the prior art is lack of assessment on the whole test process and has low estimation precision.
Drawings
Fig. 1 is a schematic basic flow chart of a method for consistency of a battery pack according to embodiment 1 of the present invention;
fig. 2 is a schematic diagram of a flow of establishing a confidence interval of an electric quantity state in embodiment 2 of the present invention;
FIG. 3 is a schematic diagram of the comparison process between the detection data and the confidence interval in example 2 of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
As shown in fig. 1, a method of battery pack compliance includes the steps of:
in this embodiment, the specific steps of establishing the SOC-SOC confidence interval include:
s1, establishing an SOC-module minimum voltage value curve according to the sample data;
s2, converting the maximum module voltage and the minimum module voltage into corresponding SOC values respectively;
s3, calculating a difference value delta SOC between the maximum voltage value SOC of the module and the minimum SOC of the module;
s4, establishing an SOC-delta SOC curve of the electric quantity state in the charging and discharging process;
in this embodiment, the specific steps of comparing the monitoring data with the confidence interval include:
s1', establishing a SOC-module minimum voltage value curve according to the data to be tested;
s2', converting the module maximum voltage and the module minimum voltage into corresponding SOC values;
s3', calculating the difference value delta SOC between the maximum module voltage value SOC and the minimum module SOC of the battery to be tested and delivered from the factory;
s4', establishing a SOC-delta SOC curve of the charge and discharge process of the data to be tested;
and S5, establishing a standard SOC-delta SOC confidence interval according to the multiple groups of data.
Example 2
The invention provides a method for battery pack consistency, which comprises the steps of establishing an SOC-delta SOC confidence interval and comparing detection data with the confidence interval.
As shown in fig. 2, establishing the SOC- Δ SOC confidence interval includes the steps of:
step S101: selecting the historical detection data of the electrical property test as sample data, wherein the data to be recorded comprises a module maximum voltage value Vmax, a module minimum voltage value Vmin, a charging capacity and a discharging capacity. Calculating the SOC value of each time point in the charging stage and the discharging stage by adopting the following method:
wherein SOCC is SOC of the charging stage, CC is the capacity of the current charged battery pack,
the total capacity charged by the battery pack from the start of charging to the end of charging.
Wherein, SOCD is SOC at the discharging stage, CD is the discharged capacity of the current battery pack,
is the total capacity discharged from the battery pack from the beginning of discharge to the end of discharge.
And taking the charging SOC and the discharging SOC as an X axis, taking the module minimum voltage value Vmin as a Y axis, and drawing an SOC-Vmin curve.
Step S102: respectively converting the module maximum voltage and the module minimum voltage at each time point in the charging process and the discharging process into corresponding SOC values by contrasting the SOC-Vmin curve;
step S103: and subtracting the SOC of the minimum voltage of the module from the SOC of the maximum voltage of the module to obtain delta SOC, wherein the calculation mode is as follows:
ΔSOC＝SOC Vmax -SOC Vmin
wherein, the delta SOC is a difference value between the maximum voltage value SOC of the module and the minimum SOC of the module, the SOCVmax is the maximum voltage value SOC of the module, and the SOCVmin is the minimum voltage value SOC of the module.
Step S104: establishing a regression equation according to the delta SOC corresponding to the different SOC obtained by calculation, and fitting to obtain an SOC-delta SOC curve in the charging process and an SOC-delta SOC curve in the discharging process;
step S105: selecting a plurality of groups of sample test data (the larger the sample amount is, the better the sample amount is, the suggested N is more than or equal to 30), fitting by using the method to obtain a plurality of groups of SOC-delta SOC curves in the charging process and the discharging process, calculating corresponding delta SOC in the charging process and the discharging process under different SOC, making a delta SOC normal distribution diagram to obtain a sample mean value and a standard deviation, selecting 95% or 90% of confidence coefficient, setting a confidence interval, and obtaining a delta SOC standard confidence interval under 0% to 100% S0C;
as shown in fig. 3, the comparison of the test data with the confidence interval comprises the following steps:
step S201: and selecting the electrical property test data to be detected, wherein the data to be recorded comprises a module maximum voltage value Vmax, a module minimum voltage value Vmin, a charging capacity and a discharging capacity. Calculating the SOC value of each time point in the charging stage and the discharging stage by adopting the following method:
wherein SOCC is SOC of the charging stage, CC is the capacity of the current charged battery pack,
from the beginning of charging to the charging junctionTotal capacity charged by the bundle battery pack.
Wherein, SOCD is SOC at the discharging stage, CD is the discharged capacity of the current battery pack,
is the total capacity discharged from the battery pack from the beginning of discharge to the end of discharge.
And taking the charging SOC and the discharging SOC as an X axis, taking the module minimum voltage value Vmin as a Y axis, and drawing an SOC-Vmin curve.
Step S202: respectively converting the module maximum voltage and the module minimum voltage at each time point in the charging process and the discharging process into corresponding SOC values by contrasting the SOC-Vmin curve;
step S203: and subtracting the SOC of the minimum voltage of the module from the SOC of the maximum voltage of the module to obtain delta SOC, wherein the calculation mode is as follows:
ΔSOC＝SOC Vmax -SOC Vmin
wherein, the delta SOC is a difference value between the maximum voltage value SOC of the module and the minimum SOC of the module, the SOCVmax is the maximum voltage value SOC of the module, and the SOCVmin is the minimum voltage value SOC of the module.
Step S204: establishing a regression equation according to delta SOC corresponding to different calculated SOC, and fitting to obtain a charging process SOC-delta SOC curve and a discharging process SOC-delta SOC curve of the data to be detected;
step S205: and comparing the SOC-delta SOC curve of the charging process and the SOC-delta SOC standard confidence interval of the discharging process with the SOC-delta SOC curve of the charging process and the discharging process, if the SOC-delta SOC curve exceeds or exceeds a certain proportion, judging that the requirement is not met, judging that the consistency of the battery pack is abnormal, wherein the larger the exceeding proportion is, the larger the dispersion is, and the worse the consistency of the battery pack is reflected.
In summary, the invention first obtains Δ SOC by calculation to establish a regression equation and a charge-discharge process SOC- Δ SOC curve, selects at least 2 groups of test samples, establishes a charge-discharge process standard SOC- Δ SOC confidence interval respectively, compares the data to be tested of the outgoing battery with the standard SOC- Δ SOC confidence interval, determines that the data do not meet the requirements if the data exceed or exceed a certain proportion, and determines that the data are abnormal, wherein the larger the proportion exceeds, the larger the dispersion is, and the worse the consistency of the battery pack is. The evaluation method provided by the invention can effectively monitor and judge the consistency of the battery pack in the factory test charging and discharging processes, and can carry out targeted reason analysis according to the time position of the occurrence of the abnormity.
According to the invention, a regression equation is established according to delta SOC corresponding to different SOC obtained by calculation to obtain an SOC-delta SOC curve in the charging process and an SOC-delta SOC curve in the discharging process, and a plurality of groups of sample test data are selected according to the method to respectively establish standard SOC-delta SOC confidence intervals in the charging process and the discharging process by utilizing a statistical method, so that the technical problems of incomplete test and low accuracy caused by the fact that the consistency is judged only by specific parameters such as battery pressure difference, charge and discharge cut-off and the like in the conventional battery pack consistency testing mode in the prior art are solved, and the accuracy of battery pack consistency evaluation is improved.
According to the invention, the difference value of the maximum voltage value SOC of the module and the minimum SOC of the module is adopted, and the SOC value in the charging stage and the SOC value in the discharging stage are calculated by a specific algorithm, so that the technical problems of low accuracy caused by the fact that the consistency of a battery pack is evaluated only by using parameters such as battery voltage and the like and the corresponding differential pressure of the SOC in different stages is inconsistent in the prior art are solved.
The method selects the electrical performance test data to be detected, wherein the data to be recorded comprise a module maximum voltage value Vmax, a module minimum voltage value Vmin, charging capacity and discharging capacity, the acquired battery pack data to be detected comprises data in a charging process and a discharging process, the technical scheme that only data of two time points of a charging cut-off and a discharging cut-off are taken for consistency evaluation in the traditional technology is replaced, and evaluation of the whole test process is achieved. The invention solves the technical problems that the prior art is lack of assessment on the whole test process and has low estimation precision.
The above examples are only intended to illustrate the technical solution of the present invention, and not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for battery pack consistency assessment, the method comprising:
s1, collecting and obtaining test data to serve as test samples, and respectively establishing SOC-module minimum voltage value curves in the charging and discharging processes according to the test samples;
s2, contrasting the SOC-module minimum voltage value curve in the charging and discharging process, respectively converting the module maximum voltage and the module minimum voltage in the charging and discharging stage to obtain corresponding SOC values, establishing a regression equation, a charging process SOC-delta SOC curve and a discharging process SOC-delta SOC curve according to the calculated delta SOC, selecting not less than 2 groups of test samples, and respectively establishing a charging process standard SOC-delta SOC confidence interval and a discharging process standard SOC-delta SOC confidence interval according to the selected test samples;
s3, acquiring data to be tested of a factory battery pack, comparing the data to be tested according to the charging process standard SOC-delta SOC confidence interval and the discharging process standard SOC-delta SOC confidence interval to obtain an exceeding proportion of a preset confidence interval, and judging the exceeding proportion data and the dispersion data of the factory battery pack according to the data to be tested to obtain a consistency estimation result of the factory battery pack.
2. The method for evaluating the consistency of a battery pack according to claim 1, wherein the step S2 includes:
s21, comparing the SOC-module minimum voltage value curve, respectively converting the module maximum voltage and the module minimum voltage of the corresponding SOC in the charging process and the discharging process into corresponding SOC values;
s22, processing the SOC of the maximum voltage of the module and the SOC of the minimum voltage of the module by preset logic to obtain a difference value delta SOC between the maximum voltage value SOC of the module and the minimum SOC of the module;
s23, calculating the delta SOC corresponding to the different obtained SOCs according to preset logic to establish a regression equation, the SOC-delta SOC curve in the charging process and the SOC-delta SOC curve in the discharging process;
and S24, selecting not less than 2 groups of test samples, and respectively establishing standard SOC-delta SOC confidence intervals in the charging and discharging process by using preset statistical logic.
3. The method for detecting consistency of battery packs according to claim 2, wherein the method comprises the following steps: in step S22, the difference Δ SOC between the module maximum voltage value SOC and the module minimum SOC is calculated by the following logic:
ΔSOC＝SOC Vmax -SOC Vmin
wherein SOC is Vmax Is the maximum voltage value SOC, SOC of the module Vmin Is the module minimum.
4. The method for detecting consistency of battery packs according to claim 2, wherein the method comprises the following steps: the step S2 includes:
s241, randomly selecting not less than 2 test samples to calculate a test curve;
s242, calculating the difference value delta SOC between the maximum voltage value SOC of the module and the minimum SOC of the module corresponding to the test curve under different SOCs, and generating a delta SOC normal distribution diagram;
s243, processing the delta SOC normal distribution diagram to obtain a sample mean value and a standard deviation;
and S244, calculating the confidence interval according to the mean value and the standard deviation to obtain a standard confidence interval from 0% to 100% under S0C.
5. The method for detecting consistency of battery packs according to claim 1, wherein the method comprises the following steps: in the step 2 and the step 3, the capacity value in the charging stage and the capacity value in the discharging stage are obtained and processed to obtain the SOC value.
6. The method for detecting consistency of battery packs according to claim 5, wherein the method comprises the following steps: the SOC values correspond to the minimum voltage values of the modules in the battery pack one by one.
7. The method for detecting consistency of battery packs according to claim 5, wherein the method comprises the following steps: in step S21, the SOC value of the charging stage is calculated by using the following logic:
wherein, SOC C Is SOC in the charging phase, C C For the capacity of the currently charged battery pack,
the total capacity charged by the battery pack from the start of charging to the end of charging.
8. The method for detecting consistency of battery packs according to claim 5, wherein the method comprises the following steps: in step S21, the SOC value of the discharge stage is calculated by using the following logic:
wherein, SOC D Is SOC in the discharge stage, C D The capacity that the current battery pack has discharged,
is the total capacity discharged from the battery pack from the beginning of discharge to the end of discharge.
9. The method for detecting consistency of battery packs according to claim 5, wherein the method comprises the following steps: the step S3 includes:
s31, respectively establishing SOC-module minimum voltage value curves in the charging and discharging processes according to the data to be tested;
s32, comparing the SOC-module minimum voltage value curve, and respectively converting the module maximum voltage and the module minimum voltage of the factory battery pack in the charging and discharging stages into corresponding SOC values;
s33, subtracting the SOC of the minimum module voltage from the SOC value of the maximum module voltage of the battery pack leaving the factory to obtain delta SOC;
s34, calculating to obtain delta SOC of the factory battery pack corresponding to different SOC values, establishing a regression equation, and obtaining an SOC-delta SOC curve of the factory battery pack in the charging process and an SOC-delta SOC curve of the factory battery pack in the discharging process;
s35, fitting the SOC-delta SOC curve of the charging process, the SOC-delta SOC curve of the discharging process and the SOC-delta SOC confidence interval of the charging process and the discharging process of the to-be-tested data, and if the SOC-delta SOC confidence interval exceeds a proportional discrete threshold value in a preset mode, estimating the consistency of the ex-factory battery pack.
10. A battery pack consistency evaluation system, the system comprising:
the minimum voltage value curve establishing module is used for acquiring test data to serve as test samples and respectively establishing an SOC-module minimum voltage value curve in the charging and discharging process according to the test samples;
a confidence interval module, which is used for contrasting the SOC-module minimum voltage value curve in the charging and discharging process, respectively converting the module maximum voltage and the module minimum voltage in the charging and discharging stage to obtain corresponding SOC values, establishing a regression equation, a charging process SOC-delta SOC curve and a discharging process SOC-delta SOC curve according to the calculated delta SOC, selecting not less than 2 groups of test samples, and respectively establishing a charging process standard SOC-delta SOC confidence interval and a discharging process standard SOC-delta SOC confidence interval, wherein the confidence interval module is connected with the minimum voltage value curve establishing module;
the consistency estimation module is used for acquiring data to be tested of an ex-factory battery pack, comparing the data to be tested according to the charging process standard SOC-delta SOC confidence interval and the discharging process standard SOC-delta SOC confidence interval to obtain an exceeding proportion of a preset confidence interval, judging the exceeding proportion data and the dispersion data of the ex-factory battery pack according to the data to be tested to obtain a consistency estimation result of the ex-factory battery pack, and the consistency estimation module is connected with the confidence interval module.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116008820A (en) * | 2023-03-24 | 2023-04-25 | 中国汽车技术研究中心有限公司 | Method, device and medium for detecting inconsistency of vehicle battery cells |
| CN116691351A (en) * | 2023-08-03 | 2023-09-05 | 四川吉利学院 | Intelligent monitoring and management method, device and system for safety of new energy automobile battery |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116008820A (en) * | 2023-03-24 | 2023-04-25 | 中国汽车技术研究中心有限公司 | Method, device and medium for detecting inconsistency of vehicle battery cells |
| CN116008820B (en) * | 2023-03-24 | 2023-10-10 | 中国汽车技术研究中心有限公司 | Method, device and medium for detecting inconsistency of vehicle battery cells |
| CN116691351A (en) * | 2023-08-03 | 2023-09-05 | 四川吉利学院 | Intelligent monitoring and management method, device and system for safety of new energy automobile battery |
| CN116691351B (en) * | 2023-08-03 | 2023-10-17 | 四川吉利学院 | Intelligent monitoring and management method, device and system for safety of new energy automobile battery |
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