CN108646183B - Battery fault diagnosis method in battery pack - Google Patents
Battery fault diagnosis method in battery pack Download PDFInfo
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- CN108646183B CN108646183B CN201810278942.4A CN201810278942A CN108646183B CN 108646183 B CN108646183 B CN 108646183B CN 201810278942 A CN201810278942 A CN 201810278942A CN 108646183 B CN108646183 B CN 108646183B
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Abstract
The invention discloses a battery fault diagnosis method in a battery pack, which is characterized in that after battery pack integral diagnosis and fault module positioning are carried out through charging tail end voltage, fault types are further diagnosed through the voltage after standing. The invention can realize reliable diagnosis of the faults of the power battery pack, reduce misjudgment of the faults of the battery pack, avoid unnecessary repeated maintenance of the battery pack and save the maintenance cost.
Description
Technical Field
The invention relates to the technical field of power batteries for vehicles, in particular to a battery fault diagnosis method in a battery pack.
Background
When the electric automobile runs, the use mode of the battery is that a battery pack formed by connecting single batteries in a series-parallel connection mode meets the requirement of power in the running process of the automobile. The battery pack containing a large number of series and parallel battery monomers is influenced by a plurality of uncontrollable factors in the manufacturing process or the use process, so that the difference among the battery monomers can be caused, the power performance of the battery pack is further reduced, the capacity, the energy, the pressure difference, the endurance mileage and the service life of the battery pack are seriously influenced, and the experience of a user in the use process is further influenced.
When the battery pack is charged, the voltage of a single battery is abnormal, so that the charging is finished when the charging cut-off condition is reached in advance, and other batteries are not fully charged, so that the whole battery pack is influenced, and the performance of the battery pack is reduced. Therefore, power battery pack failure is currently determined based on the cell differential pressure of the battery pack. And reporting a low voltage fault or a high voltage fault by the battery management system BMS only according to the inconsistency of the collected voltages. However, the fault judgment method has the defects that the cause of the fault is not reflected, and the subsequent balancing work cannot be effectively guided.
Disclosure of Invention
Based on the technical problems in the background art, the invention provides a battery fault diagnosis method in a battery pack.
The invention provides a battery fault diagnosis method in a battery pack, which comprises the following steps:
s1, recording remote monitoring data after the whole vehicle provided with the battery pack is charged for multiple times and is discharged under working conditions; the remote monitoring data comprises the monomer voltage, the charging current and the discharging current of each module in the running process of the whole vehicle;
s2, charging the battery pack, obtaining voltage values V11, V12 to V1n of each series module at the charging end of the battery pack, wherein n is the number of the series modules, screening a highest voltage value Vmax and a lowest voltage value Vmin, and calculating a voltage average value V1 of each series module;
s3, obtaining a differential pressure value delta V, wherein the delta V is Vmax-Vmin;
s4, judging whether the differential pressure value delta V is larger than a preset first voltage threshold value U1; if not, judging that the battery pack is normal;
s5, if yes, the battery pack is judged to be in fault, the highest voltage value Vmax and the lowest voltage value Vmin in the battery pack are respectively compared with the voltage average value V1, and a fault module is located;
s6, after the battery pack is placed statically for a preset first time value, obtaining the static voltage values V21, V22 to V2n of each series module in the battery pack, and obtaining the static voltage average value V2 of each series module;
s7, comparing the standing voltage value V2m of the fault module with the standing voltage average value V2, wherein m is more than or equal to 1 and less than or equal to n;
and S8, combining the comparison results of the step S5 and the step S7 to judge the fault type.
Preferably, step S5 specifically includes the following steps:
s51, presetting a second voltage threshold U2;
s52, judging whether the difference value between the maximum voltage value Vmax and the voltage average value V1 is larger than a second voltage threshold value U2; if yes, judging the fault of the series module corresponding to the maximum voltage value Vmax;
s53, if not, judging whether the difference value between the voltage average value V1 and the lowest voltage value Vmin is larger than a second voltage threshold value U2; if yes, judging the fault of the series module corresponding to the lowest voltage value Vmin.
Preferably, in step S8, if the faulty module is a series module corresponding to the highest voltage value Vmax, and the module resting voltage value V2m is smaller than the resting voltage average value V2, it is determined that the module is damaged;
preferably, in step S8, if the faulty module is a series module corresponding to the highest voltage value Vmax, and the module resting voltage value V2m is greater than the resting voltage average value V2, it is determined that the module SOC state is higher;
preferably, in step S8, if the faulty module is the series module corresponding to the lowest voltage value Vmin and the module resting voltage value V2m is greater than the resting voltage average value V2, it is determined that the module is damaged;
preferably, in step S8, if the faulty module is the series module corresponding to the lowest voltage value Vmin and the module resting voltage value V2m is smaller than the resting voltage average value V2, it is determined that the module SOC state is lower.
Preferably, the first voltage threshold U1 and the second voltage threshold U2 are set according to the battery pack charging current.
According to the battery fault diagnosis method in the battery pack, after the battery pack is integrally diagnosed and the fault module is positioned through the charging tail end voltage, the fault type is further diagnosed through the voltage after standing. The invention can realize reliable diagnosis of the faults of the power battery pack, reduce misjudgment of the faults of the battery pack, avoid unnecessary repeated maintenance of the battery pack and save the maintenance cost.
According to the invention, the battery pack is integrally diagnosed through the maximum voltage value Vmax and the minimum voltage value Vmin of the battery pack series module, so that the battery pack diagnosis efficiency is improved, and a fault battery pack is screened for accurate diagnosis. In addition, the invention is beneficial to ensuring that the fault detection of the battery pack accords with the practical application environment through the operation of the whole vehicle, and is beneficial to providing reference basis for parameter setting in the fault detection through remote monitoring data.
Drawings
Fig. 1 is a flowchart of a method for diagnosing a battery fault in a battery pack according to the present invention;
FIG. 2 is a schematic diagram of the voltage distribution of a series module at the end of charge and at rest in a battery pack;
FIG. 3 is a schematic diagram of the voltage distribution of another series module at the end of charge and at rest in a battery pack;
fig. 4 is a schematic diagram of the voltage distribution of yet another series module in a battery pack at the end of charging and at rest.
Detailed Description
Referring to fig. 1, a method for diagnosing a battery fault in a battery pack according to the present invention includes the following steps.
And S1, recording remote monitoring data after the whole vehicle with the battery pack is charged for many times and is discharged under working conditions. The remote monitoring data comprises the monomer voltage, the charging current and the discharging current of each module in the running process of the whole vehicle.
In the step, the whole vehicle runs, so that the fault detection of the battery pack is favorably ensured to be in accordance with the practical application environment, and the reference basis is favorably provided for parameter setting in the fault detection through remote monitoring data.
And S2, charging the battery pack, acquiring voltage values V11, V12 to V1n of each series module at the charging end of the battery pack, wherein n is the number of the series modules, screening the highest voltage value Vmax and the lowest voltage value Vmin, and calculating the voltage average value V1 of each series module.
Specifically, in this step, the maximum voltage value Vmax and the minimum voltage value Vmin are the maximum value and the minimum value of the voltage values V11, V12 to V1n, respectively, and V1 is (V11+ V12+ … … V1 n)/n.
And S3, acquiring the differential pressure value delta V, wherein the delta V is Vmax-Vmin.
S4, judging whether the differential pressure value delta V is larger than a preset first voltage threshold value U1; otherwise, the battery pack is judged to be normal. The first voltage threshold U1 is set according to the battery pack charging current.
And S5, if yes, judging that the battery pack is in fault, and comparing the highest voltage value Vmax and the lowest voltage value Vmin in the battery pack with the voltage average value V1 respectively to locate a fault module.
In this way, in the present embodiment, the battery pack is integrally diagnosed through the maximum voltage value Vmax and the minimum voltage value Vmin of the battery pack series module, which is beneficial to improving the battery pack diagnosis efficiency and screening a faulty battery pack for accurate diagnosis.
In this embodiment, the specific manner of locating the fault module is as follows:
s51, presetting a second voltage threshold U2. The second voltage threshold U2 is set according to the battery pack charging current.
S52, judging whether the difference value between the maximum voltage value Vmax and the voltage average value V1 is larger than a second voltage threshold value U2; if yes, judging the fault of the series module corresponding to the maximum voltage value Vmax.
And S53, if not, judging whether the difference value between the voltage average value V1 and the lowest voltage value Vmin is larger than a second voltage threshold value U2. If yes, judging the fault of the series module corresponding to the lowest voltage value Vmin.
In this way, in the present embodiment, a fault is directly detected from the serial module corresponding to the highest voltage value Vmax and the lowest voltage value Vmin, which is beneficial to improving the fault locating efficiency and avoiding the redundant work of detecting each serial module one by one.
S6, after the battery pack is placed statically for a preset first time value, obtaining the static voltage values V21, V22 to V2n of each series module in the battery pack, and obtaining the static voltage average value V2 of each series module.
S7, comparing the standing voltage value V2m of the fault module with the standing voltage average value V2, wherein m is more than or equal to 1 and less than or equal to n.
And S8, combining the comparison results of the step S5 and the step S7 to judge the fault type.
In step S8 of the present embodiment, the fault type is determined according to a preset fault determination model, specifically: if the fault module is a series module corresponding to the maximum voltage value Vmax and the standing voltage value V2m of the module is smaller than the standing voltage average value V2, judging that the module is damaged and needing to be replaced;
if the fault module is a series module corresponding to the maximum voltage value Vmax and the standing voltage value V2m of the module is greater than the standing voltage average value V2, judging that the SOC state of the module is higher and performing module balancing;
if the fault module is a series module corresponding to the lowest voltage value Vmin and the standing voltage value V2m of the module is greater than the standing voltage average value V2, judging that the module is damaged and needing to be replaced;
and if the fault module is a series module corresponding to the lowest voltage value Vmin and the standing voltage value V2m of the module is smaller than the standing voltage average value V2, judging that the SOC state of the module is low and performing module balancing.
In this way, in the present embodiment, after the entire battery pack is diagnosed and the fault module is located by the charge end voltage, the type of the fault is further diagnosed by the voltage after the rest. The method and the device can realize reliable diagnosis of the faults of the power battery pack, reduce misjudgment of the faults of the battery pack, avoid unnecessary repeated maintenance of the battery pack and save maintenance cost.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (7)
1. A method of diagnosing a battery failure in a battery pack, comprising the steps of:
s1, recording remote monitoring data after the whole vehicle provided with the battery pack is charged for multiple times and is discharged under working conditions; the remote monitoring data comprises the monomer voltage, the charging current and the discharging current of each module in the running process of the whole vehicle;
s2, charging the battery pack, obtaining voltage values V11, V12 to V1n of each series module at the charging end of the battery pack, wherein n is the number of the series modules, screening a highest voltage value Vmax and a lowest voltage value Vmin, and calculating a voltage average value V1 of each series module;
s3, obtaining a differential pressure value delta V, wherein the delta V is Vmax-Vmin;
s4, judging whether the differential pressure value delta V is larger than a preset first voltage threshold value U1; if not, judging that the battery pack is normal;
s5, if yes, the battery pack is judged to be in fault, the highest voltage value Vmax and the lowest voltage value Vmin in the battery pack are respectively compared with the voltage average value V1, and a fault module is located;
s6, after the battery pack is placed statically for a preset first time value, obtaining the static voltage values V21, V22 to V2n of each series module in the battery pack, and obtaining the static voltage average value V2 of each series module;
s7, comparing the standing voltage value V2m of the fault module with the standing voltage average value V2, wherein m is more than or equal to 1 and less than or equal to n;
and S8, combining the comparison results of the step S5 and the step S7 to judge the fault type.
2. The method for diagnosing a battery failure in a battery pack according to claim 1, wherein the step S5 specifically includes the steps of:
s51, presetting a second voltage threshold U2;
s52, judging whether the difference value between the maximum voltage value Vmax and the voltage average value V1 is larger than a second voltage threshold value U2; if yes, judging the fault of the series module corresponding to the maximum voltage value Vmax;
s53, if not, judging whether the difference value between the voltage average value V1 and the lowest voltage value Vmin is larger than a second voltage threshold value U2; if yes, judging the fault of the series module corresponding to the lowest voltage value Vmin.
3. The method for diagnosing a battery failure in a battery pack according to claim 2, wherein in the step S8, if the failed module is a series module corresponding to the highest voltage value Vmax, and the module rest voltage value V2m is less than the rest voltage average value V2, it is determined that the module is damaged.
4. The method for diagnosing the battery malfunction in the battery pack according to claim 2, wherein in the step S8, if the faulty module is a series module corresponding to the highest voltage value Vmax, and the module rest voltage value V2m is greater than the rest voltage average value V2, it is determined that the module SOC state is high.
5. The method for diagnosing a battery failure in a battery pack according to claim 2, wherein in the step S8, if the failed module is a series module corresponding to the lowest voltage value Vmin and the module rest voltage value V2m is greater than the rest voltage average value V2, it is determined that the module is damaged.
6. The method of diagnosing a battery failure in a battery pack according to claim 2, wherein in the step S8, if the failed module is a series module corresponding to the lowest voltage value Vmin and the module rest voltage value V2m is smaller than the rest voltage average value V2, it is determined that the module SOC state is low.
7. The in-battery-pack battery-failure diagnosis method according to any one of claims 1 to 6, wherein the first voltage threshold U1 and the second voltage threshold U2 are set in accordance with a battery pack charging current.
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| KR20210031336A (en) | 2019-09-11 | 2021-03-19 | 주식회사 엘지화학 | Apparatus and method for diagnosing battery |
| KR20210039705A (en) * | 2019-10-02 | 2021-04-12 | 주식회사 엘지화학 | Method and system for detecting connection failure in parallel connection cell |
| CN111562503B (en) * | 2020-04-07 | 2022-05-03 | 天津力神电池股份有限公司 | Method for analyzing and processing failure of lithium ion battery charging and discharging equipment |
| CN111579998B (en) * | 2020-04-14 | 2022-05-06 | 浙江零跑科技股份有限公司 | Battery SOC calibration method and device and storage medium |
| CN111580000B (en) * | 2020-04-14 | 2022-05-17 | 浙江零跑科技股份有限公司 | Battery SOC calibration method |
| CN114114057B (en) * | 2021-10-28 | 2023-11-07 | 合肥国轩高科动力能源有限公司 | New energy electric automobile battery monomer anomaly prediction method |
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| CN101930057B (en) * | 2010-06-13 | 2013-04-10 | 深圳市睿德电子实业有限公司 | Method and system for detecting faults of power batteries |
| CN102565711A (en) * | 2011-12-02 | 2012-07-11 | 毛广甫 | Method for testing voltage condition of battery pack |
| CN104614675A (en) * | 2014-12-31 | 2015-05-13 | 普天新能源车辆技术有限公司 | Power battery group consistency detection method and device |
| CN105846483B (en) * | 2015-01-14 | 2018-07-17 | 北京普莱德新能源电池科技有限公司 | A kind of unbalanced fault verification of battery pack and equalization methods |
| CN104916875B (en) * | 2015-04-21 | 2017-07-18 | 合肥国轩高科动力能源有限公司 | A kind of power battery pack fault diagnosis and method for maintaining |
| CN105548908B (en) * | 2016-01-25 | 2019-03-26 | 北京华特时代电动汽车技术有限公司 | A kind of internal resistance consistency detecting method of power battery pack |
| CN107612071B (en) * | 2017-09-24 | 2021-04-09 | 合肥国轩高科动力能源有限公司 | Battery failure judgment and processing method for battery pack |
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