CN115877238A - Battery capacity detection method and device, readable storage medium and electronic equipment - Google Patents
Battery capacity detection method and device, readable storage medium and electronic equipment 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
- B60L3/00—Electric devices on electrically-propelled vehicles for safety purposes; Monitoring operating variables, e.g. speed, deceleration or energy consumption
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- G—PHYSICS
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- 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
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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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- 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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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
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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
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- 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 disclosure relates to a method and a device for detecting battery capacity, a readable storage medium and an electronic device, relating to the field of power batteries, wherein the method comprises the following steps: the method comprises the steps of firstly obtaining battery charging process characteristic values corresponding to a plurality of charging records meeting battery capacity detection requirements, secondly determining battery system capacities corresponding to the plurality of charging records through the battery charging process characteristic values, determining abnormal capacity thresholds of a battery system according to the battery system capacities corresponding to the plurality of charging records, and finally identifying the battery system capacity state of a target vehicle according to the abnormal capacity thresholds. Through the implementation mode, the battery system capacity of the power battery can be obtained through a plurality of charging records in the big data, and the abnormal capacity threshold value of the battery system is determined according to the obtained battery system capacity by combining a statistical method, so that the abnormal capacity state of the battery system of the target vehicle can be identified, and the accuracy of detecting the battery system capacity can be improved.
Description
Technical Field
The disclosure relates to the technical field of power batteries, in particular to a battery capacity detection method and device, a readable storage medium and electronic equipment.
Background
The battery capacity of a power battery system of the electric automobile inevitably ages in the using process, and the endurance mileage of the electric automobile is directly influenced. The optimal maintenance and replacement time can be determined according to the abnormal state of the power battery, so that the service life of the power battery is effectively prolonged, and the endurance mileage of the electric automobile is increased, therefore, the detection of the capacity state of the power battery system is necessary in the using process.
In the prior art, a detection method such as attenuation of a partial discharge depth charging capacity instead of a rated capacity is generally adopted, so that the obtained capacity error of a battery system is large, and whether the capacity of the battery system is abnormal or not cannot be accurately detected.
Disclosure of Invention
The present disclosure is directed to a method and an apparatus for detecting battery capacity, a readable storage medium, and an electronic device, to solve the above-mentioned related problems.
In order to achieve the above object, a first aspect of the embodiments of the present disclosure provides a method for detecting battery capacity, including:
acquiring battery charging process characteristic values corresponding to a plurality of charging records meeting the battery capacity detection requirement;
determining the system capacity of the battery corresponding to the plurality of charging records according to the characteristic value of the battery charging process;
determining an abnormal capacity threshold of the battery system according to the battery system capacity corresponding to the plurality of charging records;
and identifying the battery system capacity state of the target vehicle according to the abnormal capacity threshold value.
Optionally, the obtaining characteristic values of the battery charging process corresponding to a plurality of charging records that meet the requirement of detecting the battery capacity includes:
acquiring charging records of battery systems of a plurality of vehicles in a charging process;
forming a first data matrix based on charging records of the battery systems of the plurality of vehicles in the charging process;
screening the first data matrix to form a second data matrix, wherein the second data matrix comprises a plurality of screened charging records;
and acquiring the characteristic value of the battery charging process through the second data matrix.
Optionally, the obtaining the characteristic value of the battery charging process through the second data matrix includes:
acquiring the charging quantity of the battery charging process corresponding to each charging record in the second data matrix;
acquiring a charging terminal voltage curve in each charging record in the second data matrix, and normalizing the charging terminal voltage curve to form a relation curve of voltage and a chargeable capacity;
according to the relation curve, acquiring the minimum inpaintable capacity and the maximum inpaintable capacity respectively corresponding to the maximum voltage and the minimum voltage of each charging record in the second data matrix when the battery charging is finished;
and acquiring a corrected charge state corresponding to the minimum voltage at the beginning of battery charging corresponding to each charging record in the second data matrix.
Optionally, the determining, according to the characteristic value of the battery charging process, the battery system capacity corresponding to the plurality of charging records includes:
for each charging record in the plurality of charging records, determining system discharge energy corresponding to the minimum voltage condition through the charged electric quantity, the minimum rechargeable capacity and the corrected state of charge;
and determining the battery system capacity corresponding to the charging record through the system discharging energy, the charging capacity and the maximum chargeable capacity.
Optionally, the determining an abnormal capacity threshold of the battery system according to the battery system capacities corresponding to the plurality of charging records includes:
obtaining a scatter diagram of mileage and battery system capacity according to the battery system capacity corresponding to the plurality of charging records;
and processing the battery system capacities of the plurality of vehicles corresponding to the plurality of charging records in a window sliding mode according to a preset distance step length on the basis of the scatter diagram to obtain an abnormal capacity threshold value corresponding to window sliding.
Optionally, the processing, based on the scatter diagram, the battery system capacities of multiple vehicles corresponding to the multiple charging records in a window sliding manner according to a preset distance step to obtain an abnormal capacity threshold corresponding to the window sliding includes:
based on the scatter diagram, performing window sliding on the battery system capacity of the plurality of vehicles corresponding to the plurality of charging records by taking a first distance as a window sliding step length to obtain a battery system capacity median corresponding to each window sliding;
filtering abnormal data in the battery system capacity of each vehicle in the plurality of vehicles based on the median of the battery system capacity to obtain the filtered battery system capacity of each vehicle;
summarizing the filtered battery system capacity of each vehicle to obtain the filtered battery system capacity of the plurality of vehicles;
and performing window sliding on the filtered battery system capacities of the plurality of vehicles by taking the second distance as a window sliding step length, and determining the corresponding upper limit threshold value and the lower limit threshold value of the battery system capacity by using a four-bit distance method for the battery system capacity corresponding to each window sliding. Optionally, the identifying the battery system capacity state of the target vehicle according to the abnormal capacity threshold includes:
acquiring a battery charging process characteristic value of the target vehicle;
determining the battery system capacity of the target vehicle according to the battery charging process characteristic value of the target vehicle;
and identifying the battery system capacity state of the target vehicle according to the battery system capacity of the target vehicle and the abnormal capacity threshold, wherein the battery system capacity state comprises abnormal battery system capacity or normal battery system capacity.
Optionally, the forming a first data matrix based on the charging records of the battery systems of the plurality of vehicles during the charging process includes:
cleaning the battery data;
acquiring charging records of the battery systems of the plurality of vehicles in the charging process;
and screening the charging records meeting preset conditions from the charging records of the battery systems of the plurality of vehicles in the charging process to form the first data matrix.
According to a second aspect of the embodiments of the present disclosure, there is provided a device for detecting battery capacity, including:
the acquisition module is used for acquiring battery charging process characteristic values corresponding to a plurality of charging records meeting the battery capacity detection requirement;
the determining module is used for determining the battery system capacity corresponding to the plurality of charging records through the characteristic value of the battery charging process;
the determining module is further configured to determine an abnormal capacity threshold of the battery system according to the battery system capacities corresponding to the plurality of charging records;
and the identification module is used for identifying the battery system capacity state of the target vehicle according to the abnormal capacity threshold value.
According to a third aspect of embodiments of the present disclosure, there is provided a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method of any one of the above-mentioned first aspects.
According to a fourth aspect of the embodiments of the present disclosure, there is provided an electronic apparatus including:
a memory having a computer program stored thereon;
a processor for executing the computer program in the memory to implement the steps of the method of any one of the above first aspects.
In the technical scheme, the battery charging process characteristic values corresponding to a plurality of charging records meeting the battery capacity detection requirement are firstly obtained, the battery system capacity corresponding to the plurality of charging records is secondly determined according to the battery charging process characteristic values, the abnormal capacity threshold value of the battery system is determined according to the battery system capacity corresponding to the plurality of charging records, and finally the battery system capacity state of the target vehicle is identified according to the abnormal capacity threshold value. Through the implementation mode, the battery system capacity of the power battery can be obtained through a plurality of charging records in the big data, and the abnormal capacity threshold value of the battery system is determined according to the obtained battery system capacity by combining a statistical method, so that the abnormal state of the battery system capacity of the target vehicle can be identified, and the accuracy of detecting the battery system capacity can be improved.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure, but do not constitute a limitation of the disclosure. In the drawings:
FIG. 1 is a flow chart illustrating a method of battery capacity detection according to an exemplary embodiment;
FIG. 2 is a flow chart illustrating a method of battery capacity detection according to an exemplary embodiment;
FIG. 3 is a flow chart illustrating a method of battery capacity detection according to an exemplary embodiment;
FIG. 4 is a flow chart illustrating a method of battery capacity detection in accordance with an exemplary embodiment;
FIG. 5 is a flow chart illustrating a method of battery capacity detection in accordance with an exemplary embodiment;
FIG. 6 is a flow chart illustrating a method of battery capacity detection in accordance with an exemplary embodiment;
FIG. 7 is a flow chart illustrating a method of battery capacity detection in accordance with an exemplary embodiment;
FIG. 8 is a scatter plot shown in accordance with an exemplary embodiment;
FIG. 9 is a flow chart illustrating a method of battery capacity detection in accordance with an exemplary embodiment;
FIG. 10 is a block diagram illustrating a battery capacity detection arrangement according to an exemplary embodiment;
FIG. 11 is a block diagram illustrating an electronic device in accordance with an exemplary embodiment;
FIG. 12 is a block diagram of an electronic device shown in accordance with an example embodiment.
Detailed Description
The following detailed description of the embodiments of the disclosure refers to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the present disclosure, are given by way of illustration and explanation only, not limitation.
Fig. 1 is a flow chart illustrating a method of detecting battery capacity according to an exemplary embodiment, which includes the following steps, as shown in fig. 1.
In step S11, battery charging process characteristic values corresponding to a plurality of charging records satisfying the battery capacity detection requirement are acquired.
It can be understood that the battery capacity of the power battery used by the new energy automobile is continuously reduced in the using process, so that the detection of the battery capacity is necessary. The plurality of charging records satisfying the battery capacity detection requirement may include a plurality of charging records obtained by counting a plurality of vehicle charging processes, for example, a data record of each charging process of each vehicle, and the charging process characteristic value may include data of a standing time before charging, a voltage at a charging start and a charging end, an SOC (State of Charge) at the charging start and the charging end, and the like.
In step S12, the battery system capacity corresponding to the plurality of charging records is determined by the battery charging process characteristic value.
Wherein each charge record of the plurality of charge records has a corresponding battery system capacity.
In step S13, an abnormal capacity threshold of the battery system is determined according to the battery system capacities corresponding to the plurality of charging records.
Wherein the abnormal capacity threshold of the battery system includes an upper threshold and a lower threshold.
In step S14, the battery system capacity state of the target vehicle is identified based on the abnormal capacity threshold.
It can be understood that when the battery system capacity of the target vehicle exceeds the upper threshold, it may be caused by a problem in the detection process or mismatching between the detected vehicle and the battery; when the battery system capacity of the target vehicle is lower than the lower threshold, it may be that the battery is severely degraded and the power battery needs to be repaired or replaced. Therefore, in the case where the battery system capacity is higher than the upper threshold or lower than the lower threshold, it is possible to determine that the battery system capacity state of the target vehicle is a battery system capacity abnormality.
Fig. 2 is a flowchart illustrating a method for detecting battery capacity according to an exemplary embodiment, where as shown in fig. 2, obtaining battery charging process characteristic values corresponding to a plurality of charging records satisfying a battery capacity detection requirement in step S11 may include the following steps:
step S111 acquires charging records of the battery systems of the plurality of vehicles during charging.
It can be understood that different vehicles have multiple charging processes during use, so that charging records of the battery systems of multiple vehicles during the charging process can be obtained from the vehicle information database.
In step S112, a first data matrix is formed based on the charging records of the battery systems of the plurality of vehicles during the charging process.
For example, the charging record of each charging process of each vehicle may include time, voltage, current, temperature, SOC, mileage, state of charge, and the like, and therefore, the charging records of each charging process of all vehicles may be extracted to form the first data matrix A1, so that the first data matrix A1 may include the time, voltage, current, temperature, SOC, mileage, state of charge, and the like, of a plurality of charging processes of a plurality of vehicles.
Further, fig. 3 is a flowchart illustrating a method for detecting battery capacity according to an exemplary embodiment, and as shown in fig. 3, the step S112 forms a first data matrix based on charging records of the battery systems of the plurality of vehicles during charging, which may include the following steps:
in step S1121, the battery data is cleaned.
For example, in the original charging record of each charging process of the power battery of each vehicle, there may be abnormal data with null value or exceeding threshold value, and when acquiring the charging record, the abnormal data needs to be cleaned first, and the data needing to be cleaned may include:
for time, current, temperature and mileage, the null row in these data is deleted;
deleting rows exceeding a threshold value from the data for the voltage and the SOC, wherein the threshold value for the voltage may be set to 0.5 to 4.5v and the threshold value for the SOC may be set to 0 to 100;
the charging status, the row with abnormal status flag bit is deleted, for example, the status flag bit may be numbers 1, 2, 3, 4, where 1 represents the charging status, 4 represents the charging completion status, 2 represents the driving status, and 3 represents other abnormal statuses, and when the charging status in the charging record is shown as 2 or 3, it represents that the status flag bit is abnormal, and the row needs to be deleted. The abnormal condition of the status flag bit can be set according to the actual condition, and the disclosure is not limited.
For example, the charging record after data washing may be as shown in table 1.
TABLE 1
Here, when the SOC of two recording points decreases and the time interval is 600s, it can be considered that the last charging is finished and the next charging is started. Illustratively, as shown in Table 1, where the time interval between two records is (7200-3600) > 600 and the SOC is reduced from 90 to 40, the two records can be considered as the record of the 1 st end of charge and the 2 nd start of charge, respectively.
In step S1122, charging records of the battery systems of the plurality of vehicles during charging are acquired.
It is understood that table 1 above is a charging record of a plurality of charging processes of each vehicle, and the charging records of the battery systems of a plurality of vehicles during the charging process are obtained by summarizing the charging records of each vehicle.
Step S1123, selecting charging records meeting preset conditions from the charging records of the battery systems of the plurality of vehicles during charging, and forming the first data matrix.
Illustratively, from these records, the mileage, the pre-charge rest time, and the initial charge V are selected for each vehicle min 、V max 、T min 、T max And SOC, end of charge V min 、V max 、T min 、T max And SOC, and charging capacityData of the quantity, which data form a record for each vehicle. Here, when the absolute value of the current is less than C/20 (C represents a charge/discharge capacity ratio) or 3A, the state can be considered as a static state. The charge capacity can be obtained by ampere-hour integration. The records for each of the plurality of vehicles form a first data matrix A1. The first data matrix A1 may contain characteristic data as shown in table 2.
TABLE 2
Step S113, performing a screening process on the first data matrix to form a second data matrix, where the second data matrix includes a plurality of screened charging records.
Further, after the first data matrix A1 is obtained, the data in A1 is screened, and the screening condition may include one or more of the following conditions:
the standing time before charging is more than 30 minutes;
initial charging V min A plateau voltage less than the SOC-OCV curve, a charge initiation SOC less than 20;
end of charge V min And if the voltage is larger than the platform area voltage of the charging curve, the SOC at the end of charging is larger than 90.
And screening the A1 according to the conditions, and deleting the records which do not meet the conditions to obtain a second data matrix A2.
Step S114, obtaining the characteristic value of the battery charging process through the second data matrix.
For example, the battery charging process characteristic value required for determining the capacity of the battery system may include: capacity of charged amount cha Minimum voltage V at the end of charging min And a maximum voltage V max Corresponding minimum subsidizable capacity min And maximum subsidizable capacity max Initial charging V min System discharge energy capacity in state res These eigenvalues can be obtained from the data in the second data matrix A2.
Further, fig. 4 is a flowchart illustrating a method for detecting battery capacity according to an exemplary embodiment, and as shown in fig. 4, the step S114 of obtaining the characteristic value of the battery charging process through the second data matrix may include the following steps:
step S1141, acquiring a charging amount of the battery charging process corresponding to each charging record in the second data matrix.
It is understood that the second data matrix A2 is obtained by screening the first data matrix A1, and the charging capacity of the battery charging process is obtained by ampere-hour integration in A1 cha Therefore, the charging capacity of the battery charging process corresponding to each charging record can be directly obtained from the second data matrix A2 cha 。
Step S1142, obtaining a charging terminal voltage curve in each charging record in the second data matrix, and normalizing the charging terminal voltage curve to form a relationship curve between voltage and rechargeable capacity.
For example, after obtaining the second data matrix A2, first filter A2 for T before charging min And (3) extracting a charging terminal voltage curve in the original operation data corresponding to the charging record with the SOC of 100 after the charging is finished and the temperature of more than 20 ℃, and forming a relation curve between the voltage V and the chargeable electric quantity, wherein the charging terminal is data with the SOC of more than 90. And dividing the mileage into different gears, taking every 1000km as one gear, such as 0-1000 km, 1000-2000 km, 2000-3000 km and the like, and storing the voltage curve of the charging terminal into different gears according to the mileage to form a charging terminal curve database corresponding to the mileage. And then, normalizing the charging terminal curve in each mileage unit, and outputting a relation curve of voltage V and the chargeable electric quantity by each gear.
Step S1143, according to the relationship curve, obtaining a minimum chargeable capacity and a maximum chargeable capacity respectively corresponding to the maximum voltage and the minimum voltage at the end of battery charging corresponding to each charging record in the second data matrix.
Further, the minimum voltage V at the end of charging in the second data matrix A2 is set min And maxVoltage V max Substituting the obtained normalized curve into the terminal charging curve to obtain the minimum voltage V at the end of charging min And a maximum voltage V max Corresponding minimum reservable Capacity min And maximum subsidizable capacity max 。
In step S1144, a corrected state of charge corresponding to the minimum voltage at the beginning of battery charging corresponding to each charging record in the second data matrix is obtained.
Illustratively, the minimum voltage V at the start of charging in the second data matrix A2 is set min Substituting the obtained voltage into an SOC-OCV curve to obtain a minimum voltage V at the beginning of charging min Corresponding corrected SOC.
Fig. 5 is a flowchart illustrating a method for detecting battery capacity according to an exemplary embodiment, where as shown in fig. 5, the step S12 of determining the battery system capacity corresponding to the plurality of charging records through the characteristic value of the battery charging process may include the following steps:
step S121, for each of the plurality of charging records, determining a system discharge energy corresponding to the minimum voltage condition through the charging amount, the minimum rechargeable capacity, and the corrected state of charge.
Illustratively, the charge initiation V min System discharge energy capacity in state res This can be obtained by the following formula:
and step S122, determining the battery system capacity corresponding to the charging record through the system discharging energy, the charging capacity and the maximum chargeable capacity.
Illustratively, battery system capacity = capacity cha +capacity max +capacity res 。
In the technical scheme, the battery system capacity corresponding to the plurality of charging records is determined through the characteristic value of the battery charging process.
Fig. 6 is a flowchart illustrating a method for detecting battery capacity according to an exemplary embodiment, where, as shown in fig. 6, the step S13 of determining the abnormal capacity threshold of the battery system according to the battery system capacities corresponding to the plurality of charging records may include the following steps:
step S131, obtaining a scatter diagram of the mileage and the battery system capacity according to the battery system capacity corresponding to the plurality of charging records.
For example, after the battery system capacity is obtained by the above method, the battery system capacities corresponding to the plurality of charging records are collected, and a scatter diagram of the mileage and the battery system capacity is obtained.
Step S132, based on the scatter diagram, processing the battery system capacities of the vehicles corresponding to the plurality of charging records in a window sliding manner according to a preset distance step, so as to obtain an abnormal capacity threshold corresponding to the window sliding.
In an example, based on the acquired mileage and the scatter diagram of the battery system capacity, the battery system capacity is processed in a window sliding mode, an abnormal fluctuation value occurring in the cleaning detection process is obtained, and then the abnormal capacity threshold of the battery system is obtained by combining a statistical method.
Further, fig. 7 is a flowchart illustrating a method for detecting battery capacity according to an exemplary embodiment, and as shown in fig. 7, the step S132, based on the scatter diagram, may include the following steps of processing the battery system capacities of the vehicles corresponding to the plurality of charging records in a window sliding manner according to a preset distance step to obtain an abnormal capacity threshold corresponding to the window sliding:
and step S1321, based on the scatter diagram, performing window sliding on the battery system capacities of the vehicles corresponding to the charging records by taking the first distance as a window sliding step length to obtain the median of the battery system capacities corresponding to each window sliding.
It is understood that the scatter diagram is a summary of the battery system capacities corresponding to the plurality of charging records, wherein the battery system capacity of each vehicle is included, and for the scatter diagram of the mileage and the battery system capacity of each vehicle, window sliding is firstly performed by taking the first distance as a window sliding step length to obtain the median of the battery system capacity corresponding to each window sliding.
For example, for a scatter plot of mileage and battery system capacity for each vehicle, window sliding may be performed to take a median, which may be a window length of 1000km, a window sliding step of 500 km.
In step S1322, the abnormal data in the battery system capacity of each of the plurality of vehicles is filtered based on the median of the battery system capacities, and the filtered battery system capacity of each of the vehicles is obtained.
For example, after the window slides, a median of battery capacity corresponding to different mileage of each vehicle is obtained, and based on the median, abnormal data in the battery system capacity of each vehicle is filtered, so that the filtered battery system capacity corresponding to different mileage of each vehicle is obtained.
In step S1323, the filtered battery system capacity of each vehicle is summarized to obtain the filtered battery system capacities of the plurality of vehicles.
It can be understood that, by summarizing the battery system capacities corresponding to different mileage of each vehicle, the battery system capacities corresponding to different mileage of a plurality of vehicles after filtering can be obtained.
And step S1324, performing window sliding on the filtered battery system capacities of the plurality of vehicles by taking the second distance as a window sliding step length, and determining a corresponding battery system capacity upper limit threshold and a corresponding battery system capacity lower limit threshold by using a quartile distance method for the battery system capacity corresponding to each window sliding.
Further, in one embodiment, in performing the above-described calculation of the upper and lower battery system capacity thresholds by window sliding, the battery state of health may be calculated by SOH (stateof health, battery state of health,
to characterize battery system capacity, FIG. 8 is a scatter plot showing mileage (in km) on the horizontal axis and SOH on the vertical axis for an exemplary embodiment, as shown in FIG. 8And performing window sliding on the battery system capacities corresponding to the filtered different mileage of the plurality of vehicles by taking the second distance as a window sliding step length, wherein the window length can be 5000km, and the window sliding step length can be 1km.
In the window activity process, firstly, 75-bit thre75 and 25-bit thre25 of each window are obtained, and then the thre75 and thre25 are used to calculate the upper threshold and the lower threshold of the battery system capacity of each window, and the calculation method may be:
upper threshold thre _ up' = thre75+ c (thre 75-thre 25)
Lower threshold value thre _ down' = min { thre25-c (thre 75-thre 25), SOH min -0.5}
The unit of the upper threshold value thre _ up 'and the lower threshold value thre _ down' is SOH, the SOH median can represent the battery capacity median, and the upper threshold value thre _ up ', the lower threshold value thre _ down', and the SOH median can be converted into the upper threshold value, the lower threshold value, the battery capacity median, SOH and the like by the SOH calculation method according to the requirement min End of life battery capacity retention, typically 0.8, required for warranty; c is a hyper-parameter, generally 1 to 3, and can be optimized according to the result.
After the thre _ up 'and thre _ down' of each window are obtained through calculation by the method, the window sliding is performed on the summarized data of all windows by taking the second distance as the window sliding step length again to obtain the final upper limit threshold thre _ up and lower limit threshold thre _ down of the battery system capacity, and then the upper limit threshold and lower limit threshold of the battery capacity corresponding to different mileage are obtained.
Fig. 9 is a flowchart illustrating a method for detecting battery capacity according to an exemplary embodiment, and as shown in fig. 9, the step S14 for identifying the battery system capacity state of the target vehicle according to the abnormal capacity threshold may include the following steps:
in step S141, a battery charging process characteristic value of the target vehicle is acquired.
And step S142, determining the battery system capacity of the target vehicle according to the battery charging process characteristic value of the target vehicle.
And step S143, identifying the battery system capacity state of the target vehicle according to the battery system capacity of the target vehicle and the abnormal capacity threshold, wherein the battery system capacity state comprises abnormal battery system capacity or normal battery system capacity.
For example, the method for determining the capacity of the battery system of the target vehicle and the method for identifying the capacity state of the battery system are the same as the above-mentioned method for detecting the battery capacity, and are not described herein again.
It is understood that, based on the battery system capacity of the target vehicle and the abnormal capacity threshold, the battery system capacity state of the target vehicle is identified, and when the battery system capacity of the target vehicle exceeds the upper threshold, it may be a cause of a problem in the detection process or a mismatch between the detected vehicle and the battery; when the battery system capacity of the target vehicle is lower than the lower threshold, it may be that the battery is severely degraded and the power battery needs to be repaired or replaced. Therefore, in the case where the battery system capacity is higher than the upper threshold or lower than the lower threshold, it may be determined that the battery system capacity state of the target vehicle is a battery system capacity abnormality; if the battery system capacity is between the upper limit threshold and the lower limit threshold, the battery system capacity state of the target vehicle can be determined as the normal battery system capacity.
In the technical scheme, firstly, battery charging process characteristic values corresponding to a plurality of charging records meeting the battery capacity detection requirement are obtained, secondly, the battery system capacity corresponding to the plurality of charging records is determined according to the battery charging process characteristic values, an abnormal capacity threshold value of the battery system is determined according to the battery system capacity corresponding to the plurality of charging records, and finally, the battery system capacity state of the target vehicle is identified according to the abnormal capacity threshold value. Through the implementation mode, the battery system capacity of the power battery can be obtained through a plurality of charging records in the big data, and the abnormal capacity threshold value of the battery system is determined according to the obtained battery system capacity by combining a statistical method, so that the abnormal capacity state of the battery system of the target vehicle can be identified, and the accuracy of detecting the battery system capacity can be improved.
Fig. 10 is a block diagram illustrating a battery capacity detection apparatus 200 according to an exemplary embodiment, and referring to fig. 10, the apparatus 200 includes an acquisition module 210, a determination module 220, and an identification module 230.
The obtaining module 210 is configured to obtain characteristic values of a battery charging process corresponding to a plurality of charging records that meet a battery capacity detection requirement;
the determining module 220 is configured to determine the battery system capacity corresponding to the plurality of charging records according to the battery charging process characteristic value;
the determining module 220 is further configured to determine an abnormal capacity threshold of the battery system according to the battery system capacities corresponding to the plurality of charging records;
the identifying module 230 is configured to identify a battery system capacity state of the target vehicle according to the abnormal capacity threshold.
Optionally, the obtaining module 210 may include:
the first acquisition submodule is used for acquiring charging records of battery systems of a plurality of vehicles in a charging process;
generating a submodule for forming a first data matrix based on charging records of the battery systems of the plurality of vehicles in the charging process;
the generation submodule is used for screening the first data matrix to form a second data matrix, and the second data matrix comprises a plurality of screened charging records;
the first obtaining submodule is used for obtaining the characteristic value of the battery charging process through the second data matrix.
Optionally, the first obtaining sub-module is configured to:
acquiring the charging quantity of the battery charging process corresponding to each charging record in the second data matrix;
acquiring minimum and maximum inpaintable capacities corresponding to the maximum and minimum voltages of the second data matrix at the end of charging the battery corresponding to each charging record;
and acquiring a corrected charge state corresponding to the minimum voltage at the beginning of battery charging corresponding to each charging record in the second data matrix.
Optionally, the determining module 220 is configured to:
for each charging record in the plurality of charging records, determining system discharge energy corresponding to the minimum voltage condition through the charged electric quantity, the minimum chargeable capacity and the corrected state of charge;
and determining the battery system capacity corresponding to the charging record through the system discharging energy, the charging capacity and the maximum chargeable capacity.
Optionally, the determining module 220 may include a second obtaining sub-module and a processing sub-module:
the second obtaining submodule is used for obtaining a scatter diagram of the mileage and the battery system capacity according to the battery system capacity corresponding to the plurality of charging records;
the processing submodule is used for processing the battery system capacities of the vehicles corresponding to the charging records in a window sliding mode according to the preset distance step length on the basis of the scatter diagram, and obtaining the abnormal capacity threshold corresponding to the window sliding.
Optionally, the processing submodule is configured to:
based on the scatter diagram, performing window sliding on the battery system capacity of each vehicle in the plurality of vehicles corresponding to the plurality of charging records by taking the first distance as a window sliding step length to obtain a battery system capacity median corresponding to each window sliding;
filtering abnormal data in the battery system capacity of each vehicle in the plurality of vehicles based on the median of the battery system capacity to obtain the filtered battery system capacity of each vehicle;
summarizing the filtered battery system capacity of each vehicle to obtain the filtered battery system capacity of a plurality of vehicles;
and performing window sliding on the filtered battery system capacities of the plurality of vehicles by taking the second distance as a window sliding step length, and determining the corresponding upper limit threshold value and the lower limit threshold value of the battery system capacity by using a four-bit distance method for the battery system capacity corresponding to each window sliding.
Optionally, the identification module 230 may include a determination sub-module and an identification sub-module:
the acquisition submodule is used for acquiring a characteristic value of a battery charging process of the target vehicle;
the determining submodule is used for determining the battery system capacity of the target vehicle according to the battery charging process characteristic value of the target vehicle;
the identification submodule is used for identifying the battery system capacity state of the target vehicle according to the battery system capacity of the target vehicle and the abnormal capacity threshold, wherein the battery system capacity state comprises abnormal battery system capacity or normal battery system capacity.
Optionally, the generating sub-module is configured to:
cleaning the battery data;
acquiring charging records of the battery systems of the plurality of vehicles in the charging process;
and screening the charging records meeting preset conditions from the charging records of the battery systems of the plurality of vehicles in the charging process to form the first data matrix.
With regard to the apparatus in the above embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be described in detail here.
Fig. 11 is a block diagram illustrating an electronic device 700 in accordance with an example embodiment. As shown in fig. 11, the electronic device 700 may include: a processor 701 and a memory 702. The electronic device 700 may also include one or more of a multimedia component 703, an input/output interface 704, and a communication component 705.
The processor 701 is configured to control the overall operation of the electronic device 700, so as to complete all or part of the steps in the above-mentioned method for detecting the battery capacity. The memory 702 is used to store various types of data to support operation at the electronic device 700, such as instructions for any application or method operating on the electronic device 700 and application-related data, such as contact data, transmitted and received messages, pictures, audio, video, and the like. The Memory 702 may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random Access Memory (SRAM), electrically Erasable Programmable Read-Only Memory (EEPROM), erasable Programmable Read-Only Memory (EPROM), programmable Read-Only Memory (PROM), read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk, or optical disk. The multimedia components 703 may include screen and audio components. Wherein the screen may be, for example, a touch screen and the audio component is used for outputting and/or inputting audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may further be stored in the memory 702 or transmitted through the communication component 705. The audio assembly also includes at least one speaker for outputting audio signals. The input/output interface 704 provides an interface between the processor 701 and other interface modules, such as a keyboard, mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 705 is used for wired or wireless communication between the electronic device 700 and other devices. Wireless Communication, such as Wi-Fi, bluetooth, near Field Communication (NFC), 2G, 3G, 4G, NB-IOT, eMTC, or other 5G, etc., or one or a combination thereof, which is not limited herein. The corresponding communication component 705 may thus include: wi-Fi module, bluetooth module, NFC module, etc.
In an exemplary embodiment, the electronic Device 700 may be implemented by one or more Application Specific Integrated Circuits (ASICs), digital Signal Processors (DSPs), digital Signal Processing Devices (DSPDs), programmable Logic Devices (PLDs), field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components, for performing the above-mentioned battery capacity detection method.
In another exemplary embodiment, there is also provided a computer readable storage medium including program instructions, which when executed by a processor, implement the steps of the above-described battery capacity detection method. For example, the computer readable storage medium may be the memory 702 comprising program instructions executable by the processor 701 of the electronic device 700 to perform the above-described battery capacity detection method.
Fig. 12 is a block diagram illustrating an electronic device 1900 in accordance with an example embodiment. For example, electronic device 1900 may be provided as a server. Referring to fig. 12, an electronic device 1900 includes a processor 1922, which may be one or more in number, and a memory 1932 for storing computer programs executable by the processor 1922. The computer program stored in memory 1932 may include one or more modules that each correspond to a set of instructions. Further, the processor 1922 may be configured to execute the computer program to perform the above-described battery capacity detection method.
Additionally, electronic device 1900 may also include a power component 1926 and a communication component 1950, the power component 1926 may be configured to perform power management of the electronic device 1900, and the communication component 1950 may be configured to enable communication, e.g., wired or wireless communication, of the electronic device 1900. In addition, the electronic device 1900 may also include an input/output interface 1958. The electronic device 1900 may operate based on an operating system stored in the memory 1932.
In another exemplary embodiment, there is also provided a computer readable storage medium including program instructions, which when executed by a processor, implement the steps of the above-described battery capacity detection method. For example, the non-transitory computer readable storage medium may be the memory 1932 including program instructions described above that are executable by the processor 1922 of the electronic device 1900 to perform the method of battery capacity detection described above.
In another exemplary embodiment, a computer program product is also provided, which comprises a computer program executable by a programmable apparatus, the computer program having code portions for performing the above-mentioned battery capacity detection method when executed by the programmable apparatus.
The preferred embodiments of the present disclosure are described in detail with reference to the accompanying drawings, however, the present disclosure is not limited to the specific details of the above embodiments, and various simple modifications may be made to the technical solution of the present disclosure within the technical idea of the present disclosure, and these simple modifications all belong to the protection scope of the present disclosure.
It should be noted that, in the foregoing embodiments, various features described in the above embodiments may be combined in any suitable manner, and in order to avoid unnecessary repetition, various combinations that are possible in the present disclosure are not described again.
In addition, any combination of various embodiments of the present disclosure may be made, and the same should be considered as the disclosure of the present disclosure, as long as it does not depart from the spirit of the present disclosure.
Claims (10)
1. A method for detecting battery capacity, the method comprising:
acquiring battery charging process characteristic values corresponding to a plurality of charging records meeting the battery capacity detection requirement;
determining the system capacity of the battery corresponding to the plurality of charging records according to the characteristic value of the battery charging process;
determining an abnormal capacity threshold of the battery system according to the battery system capacity corresponding to the plurality of charging records;
and identifying the battery system capacity state of the target vehicle according to the abnormal capacity threshold value.
2. The method of claim 1, wherein obtaining the battery charging process characteristic values corresponding to a plurality of charging records satisfying the battery capacity detection requirement comprises:
acquiring charging records of battery systems of a plurality of vehicles in a charging process;
forming a first data matrix based on charging records of the battery systems of the plurality of vehicles in the charging process;
screening the first data matrix to form a second data matrix, wherein the second data matrix comprises a plurality of screened charging records;
and acquiring the characteristic value of the battery charging process through the second data matrix.
3. The method of claim 2, wherein the obtaining the characteristic value of the battery charging process through the second data matrix comprises:
acquiring the charging quantity of the battery charging process corresponding to each charging record in the second data matrix;
acquiring a charging terminal voltage curve in each charging record in the second data matrix, and normalizing the charging terminal voltage curve to form a relation curve of voltage and the rechargeable capacity;
according to the relation curve, acquiring the minimum inpaintable capacity and the maximum inpaintable capacity respectively corresponding to the maximum voltage and the minimum voltage of each charging record in the second data matrix when the battery charging is finished;
and acquiring a corrected state of charge corresponding to the minimum voltage at the beginning of battery charging corresponding to each charging record in the second data matrix.
4. The method of claim 3, wherein determining the battery system capacity corresponding to the plurality of charging records according to the characteristic value of the battery charging process comprises:
for each charge record in the plurality of charge records, determining a system discharge energy corresponding to the minimum voltage condition through the charged electric quantity, the minimum chargeable capacity and the corrected state of charge;
and determining the battery system capacity corresponding to the charging record through the system discharging energy, the charging capacity and the maximum chargeable capacity.
5. The method of claim 1, wherein determining the abnormal capacity threshold of the battery system according to the battery system capacities corresponding to the plurality of charging records comprises:
acquiring a scatter diagram of mileage and battery system capacity according to the battery system capacity corresponding to the plurality of charging records;
and processing the battery system capacities of the plurality of vehicles corresponding to the plurality of charging records in a window sliding mode according to a preset distance step length on the basis of the scatter diagram to obtain an abnormal capacity threshold value corresponding to window sliding.
6. The method according to claim 5, wherein the processing the battery system capacities of the plurality of vehicles corresponding to the plurality of charging records in a window sliding manner according to a preset distance step based on the scatter diagram to obtain an abnormal capacity threshold corresponding to the window sliding includes:
based on the scatter diagram, performing window sliding on the battery system capacity of the plurality of vehicles corresponding to the plurality of charging records by taking a first distance as a window sliding step length to obtain a battery system capacity median corresponding to each window sliding;
filtering abnormal data in the battery system capacity of each vehicle in the plurality of vehicles based on the median of the battery system capacity to obtain the filtered battery system capacity of each vehicle;
summarizing the filtered battery system capacity of each vehicle to obtain the filtered battery system capacity of the plurality of vehicles;
and performing window sliding on the filtered battery system capacities of the plurality of vehicles by taking the second distance as a window sliding step length, and determining the corresponding upper limit threshold value and the lower limit threshold value of the battery system capacity by using a four-bit distance method for the battery system capacity corresponding to each window sliding.
7. The method of claim 1, wherein the identifying a battery system capacity state of a target vehicle according to the abnormal capacity threshold comprises:
acquiring a battery charging process characteristic value of the target vehicle;
determining the battery system capacity of the target vehicle according to the characteristic value of the battery charging process of the target vehicle;
and identifying the battery system capacity state of the target vehicle according to the battery system capacity of the target vehicle and the abnormal capacity threshold, wherein the battery system capacity state comprises abnormal battery system capacity or normal battery system capacity.
8. An apparatus for detecting battery capacity, the apparatus comprising:
the acquisition module is used for acquiring battery charging process characteristic values corresponding to a plurality of charging records meeting the battery capacity detection requirement;
the determining module is used for determining the battery system capacity corresponding to the plurality of charging records through the characteristic value of the battery charging process;
the determining module is further configured to determine an abnormal capacity threshold of the battery system according to the battery system capacities corresponding to the plurality of charging records;
and the identification module is used for identifying the battery system capacity state of the target vehicle according to the abnormal capacity threshold value.
9. A non-transitory computer-readable storage medium, on which a computer program is stored, which program, when executed by a processor, performs the steps of the method of any one of claims 1 to 7.
10. An electronic device, comprising:
a memory having a computer program stored thereon;
a processor for executing the computer program in the memory to implement the steps of the method of any one of claims 1-7.
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| CN202211559408.3A CN115877238B (en) | 2022-12-06 | 2022-12-06 | Method and device for detecting battery capacity, readable storage medium and electronic equipment |
| PCT/CN2022/137645 WO2024119449A1 (en) | 2022-12-06 | 2022-12-08 | Battery capacity inspection method and apparatus, and readable storage medium and electronic device |
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| WO2024119449A1 (en) | 2024-06-13 |
| CN115877238B (en) | 2023-11-07 |
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