CN105527582A - Method for pre-judging fault battery in power battery pack - Google Patents
Method for pre-judging fault battery in power battery pack Download PDFInfo
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- CN105527582A CN105527582A CN201610076005.1A CN201610076005A CN105527582A CN 105527582 A CN105527582 A CN 105527582A CN 201610076005 A CN201610076005 A CN 201610076005A CN 105527582 A CN105527582 A CN 105527582A
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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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Abstract
The invention provides a method for pre-judging a fault battery in a power battery pack. The method includes the steps of: dividing fault pre-judging intervals, recording abnormal data, pre-judging the abnormal battery, restarting abnormal data recording, and circularly performing detection. The method for pre-judging the fault battery in the power battery pack can effectively pre-judge the single battery which may break down by performing real-time monitoring and statistic analysis on the charging and discharging states of the single battery in the power battery pack, timely finds out the single battery with the fault hidden trouble, and improves the usage security of the battery pack in the whole service life period of the battery pack. The method for pre-judging the fault battery in the power battery pack can be directly implemented by a BMS system connected to the battery pack without extra hardware cost.
Description
Technical field
The present invention relates to field of batteries, be specifically related to a kind of pre-judging method of power battery pack fail battery.
Background technology
Along with the extensive popularization of electric automobile, the concern of battery security is got more and more, in the actual use procedure of electric battery, in most cases have influence on whole electric battery because battery performance is poor, and when waiting until that fault quoted by the battery of poor performance in electric battery, may appear in driving conditions and reach charge cutoff fast in unexpected broken height piezoelectricity situation or charging process, such as electric automobile is when running at high speed, because the cell of a poor performance is because persistent current electric discharge, voltage drop is fast especially, car load or BMS system may carry out corresponding fault protection, cutoff high relay, electric automobile is run out of steam, serious potential safety hazard is caused to the personal security on car.Meanwhile, during electric battery charging, because the monomer battery voltage of a poor performance rises fast especially, thus charge cutoff condition may be reached in advance and complete charge, now other batteries underfill, so whole electric battery be impacted, reduce the performance of electric battery.Domestic and international at present electric automobile power battery group is safeguarded it is carry out maintain and replace process again after discovery fault substantially, not yet have relatively effective method of in advance battery of fault or poor performance being carried out to anticipation.
Summary of the invention
For the problems referred to above, the invention provides a kind of pre-judging method of power battery pack fail battery, comprising:
A. fault anticipation interval division, divides multiple continuous print fault anticipation according to the SOH value attenuation degree of electric battery interval, and the change of the SOH value of Real-Time Monitoring electric battery;
B. abnormal data record, in each fault anticipation interval, adds up the charging and discharging number of times of each cell, and monitors each cell and whether have exception when charging and discharging, and records position and the number information of abnormal cell;
C. abnormal battery anticipation, add up the charging and discharging number of times sum of each cell and be recorded the number of times of abnormal data, and calculate each cell when reaching next fault anticipation and being interval and be recorded the number of times of abnormal data and the ratio of charging and discharging number of times, as probability of malfunction, and the Position Number information of M the highest for a probability of malfunction cell is quoted, driver needs to repair or replace, and wherein M is natural number;
Preferably, in step, 6 fault anticipations are set according to electric battery SOH value successively by 5% decay interval.
Further, in step, respectively according to SOH value > 95%, 95% >=SOH value > 90%, 90% >=SOH value > 85%, 85% >=SOH value > 80%, 80% >=SOH value > 75%, 75% >=SOH value > 70%, is divided into 6 fault anticipations interval, scraps during SOH value≤70%.
Preferably, in stepb, in stepb, when each electric battery charging reaches constant-voltage phase, record the Position Number information of the highest N number of cell of now voltage, when each battery power discharge reaches voltage decline flex point fast, record the Position Number information of the minimum N number of cell of now voltage, wherein N is natural number.
Further, N be 4 or 5 or 6, M be 4 or 5 or 6.
Preferably, step D is carried out after step C completes, abnormal data record is restarted in described step D, M the cell the highest to probability of malfunction carries out fault detect, and really have the cell of potential faults to repair or replace to detection, by maintenance or the statistics of cell after changing, the number of times comprising charging and discharging number of times sum and be recorded abnormal data empties, and re-starts abnormal data record.
Preferably, circulation carries out step B.C.D, until the battery capacity dough softening of electric battery reaches Rejection standard.
Preferably, in step D, when re-starting abnormal data record, the statistic record of all cells re-starts after being all cleared.
As the preferred scheme of another kind, in step D, when re-starting abnormal data record, except the cell repaired or replaced, the statistics of other all cell, the number of times comprising charging and discharging number of times sum and be recorded abnormal data all retains and continues statistics on its basis.
Preferably, setting in BMS system is adopted to divide fault anticipation interval, and the change of the SOH value of Real-Time Monitoring electric battery, and carry out abnormal data record and abnormal battery anticipation by BMS system, and quote to driver, after repairing or replacing abnormal battery, manually empty the record in BMS system, then BMS system proceeds the abnormal data record in next anticipation interval.
The present invention is by carrying out Real-Time Monitoring to the charging and discharging state of cell in power battery pack and carrying out statistical study, the cell that can effectively may break down carries out anticipation, the cell of potential faults can be found out in time, the security that it uses is improved within the whole cycle in serviceable life of electric battery, and directly can utilize the BMS System Implementation be connected with electric battery, there is no extra hardware cost.
Embodiment
Below in conjunction with embodiment, the invention will be further described.
Voltage is the main form of expression of cell performance, monomer battery voltage charge, electric discharge time rise too fast or fall too fast, being all non-normal phenomenon, is all the performance of battery performance difference.Too fast or fall too fast risen when charging, electric discharge have appearred in certain cell simultaneously and the highest at charging terminal voltage, electric discharge terminal voltage is minimum, and just can judge this cell performance degradation or battery junction abnormal (such as loosening) when repeatedly occurring.
Therefore, respectively according to SOH value > 95% in the BMS system be connected with power battery pack, 95% >=SOH value > 90%, 90% >=SOH value > 85%, 85% >=SOH value > 80%, 80% >=SOH value > 75%, 75% >=SOH value > 70%, set 6 continuous print fault anticipations interval, maintain accordingly at the interval end of each fault anticipation, and the change of the SOH value of Real-Time Monitoring electric battery.
Setting BMS system adds up the charging and discharging number of times of each cell in each fault anticipation interval, and when the charging of each electric battery reaches constant-voltage phase (usual ferric phosphate lithium cell 3.65V, ternary material battery 4.15V), record the Position Number information of 5 the highest cells of now voltage, when each battery power discharge reaches voltage decline flex point fast, (selection of flex point can according to different battery factory settings, also can according to different battery discharge multiplying powers, discharge curve under different temperatures and choose), record the Position Number information of 5 minimum cells of now voltage, when the battery capacity attenuation degree of electric battery reaches next fault anticipation interval, BMS system statistics all cell charging and dischargings number of times and be recorded the number of times of abnormal data, and calculate each cell and be recorded the number of times of abnormal data and the ratio of charging and discharging number of times, as probability of malfunction, and the Position Number information of the highest for probability of malfunction 5 cells is quoted, driver needs to repair or replace, after really having the cell of potential faults to repair or replace to detection, Non-follow control BMS system is by the statistics of the cell after maintenance or replacing, the number of times comprising charging and discharging number of times sum and be recorded abnormal data empties, and automatically re-start abnormal data record by BMS system, except the cell repaired or replaced, the statistics of other all cell, the number of times comprising charging and discharging number of times sum and be recorded abnormal data all retains and continues statistics on its basis.
Along with the SOH value of electric battery decays gradually, said process is carried out in circulation, until scrap during SOH value≤70% of electric battery.
The present invention can judge the fail battery of the follow-up existence of batteries of electric automobile group in advance in electric automobile use procedure, change fail battery in advance, maintain battery with two side terminals like this, thus extend the life-span of whole electric battery, vehicle can be avoided equally in use to occur suddenly because the mishap of battery failures.
Below for preferred embodiment, the present invention is described, just the above, be only and make those skilled in the art be easy to understand content of the present invention, be not used for limiting interest field of the present invention.
Claims (10)
1. a power battery pack fail battery pre-judging method, comprising:
A. fault anticipation interval division, divides multiple continuous print fault anticipation according to the SOH value attenuation degree of electric battery interval, and the change of the SOH value of Real-Time Monitoring electric battery;
B. abnormal data record, in each fault anticipation interval, adds up the charging and discharging number of times of each cell, and monitors each cell and whether have exception when charging and discharging, and records position and the number information of abnormal cell;
C. abnormal battery anticipation, add up the charging and discharging number of times sum of each cell and be recorded the number of times of abnormal data, and calculate each cell when reaching next fault anticipation and being interval and be recorded the number of times of abnormal data and the ratio of charging and discharging number of times, as probability of malfunction, and the Position Number information of M the highest for a probability of malfunction cell is quoted, driver needs to repair or replace, and wherein M is natural number.
2. according to power battery pack fail battery pre-judging method described in claim 1, it is characterized in that: in step, set 6 fault anticipations according to electric battery SOH value successively by 5% decay interval.
3. according to power battery pack fail battery pre-judging method described in claim 2, it is characterized in that: in step, respectively according to SOH value > 95%, 95% >=SOH value > 90%, 90% >=SOH value > 85%, 85% >=SOH value > 80%, 80% >=SOH value > 75%, 75% >=SOH value > 70%, is divided into 6 fault anticipations interval, scraps during SOH value≤70%.
4. according to the arbitrary described power battery pack fail battery pre-judging method of claim 1,2,3, it is characterized in that: in stepb, when each electric battery charging reaches constant-voltage phase, record the Position Number information of the highest N number of cell of now voltage, when each battery power discharge reaches voltage decline flex point fast, record the Position Number information of the minimum N number of cell of now voltage, wherein N is natural number.
5., according to power battery pack fail battery pre-judging method described in claim 4, it is characterized in that: N be 4 or 5 or 6, M be 4 or 5 or 6.
6. according to a kind of power battery pack fail battery pre-judging method described in claim 4, it is characterized in that: after step C completes, carry out step D, abnormal data record is restarted in described step D, M the cell the highest to probability of malfunction carries out fault detect, and really have the cell of potential faults to repair or replace to detection, by the statistics of the cell after maintenance or replacing, the number of times comprising charging and discharging number of times sum and be recorded abnormal data empties, and re-starts abnormal data record.
7. according to a kind of power battery pack fail battery pre-judging method described in claim 6, it is characterized in that: circulation carries out step B.C.D, until the battery capacity dough softening of electric battery reaches Rejection standard.
8. according to power battery pack fail battery pre-judging method described in claim 6, it is characterized in that: in step D, when re-starting abnormal data record, the statistic record of all cells re-starts after being all cleared.
9. according to power battery pack fail battery pre-judging method described in claim 6, it is characterized in that: in step D, when re-starting abnormal data record, except the cell repaired or replaced, the statistics of other all cell, the number of times comprising charging and discharging number of times sum and be recorded abnormal data all retains and continues statistics on its basis.
10. according to the arbitrary described power battery pack fail battery pre-judging method of claim 6,7,8,9, it is characterized in that: adopt BMS default to divide fault anticipation interval, and the change of the SOH value of Real-Time Monitoring electric battery, and carry out abnormal data record and abnormal battery anticipation by BMS system, and quote to driver, after repairing or replacing abnormal battery, manually empty the record in BMS system, then BMS system proceeds the abnormal data record in next anticipation interval.
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| CN108196189A (en) * | 2017-11-14 | 2018-06-22 | 歌尔科技有限公司 | A kind of method and apparatus for detecting double cell product battery exception |
| CN109031138A (en) * | 2018-06-29 | 2018-12-18 | 上海科列新能源技术有限公司 | A kind of safety evaluation method and device of power battery |
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| WO2021134829A1 (en) * | 2019-12-31 | 2021-07-08 | 深圳市普兰德储能技术有限公司 | Battery testing system |
| CN113721157A (en) * | 2021-08-31 | 2021-11-30 | 星恒电源股份有限公司 | Method, device, terminal and storage medium for prolonging service life of battery pack |
| CN115963408A (en) * | 2022-12-19 | 2023-04-14 | 北京双登慧峰聚能科技有限公司 | Fault early warning system and method for single battery of energy storage power station |
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| CN110678763A (en) * | 2017-09-29 | 2020-01-10 | 株式会社Lg化学 | Contactor failure rate prediction system and method |
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| CN109100654A (en) * | 2018-06-26 | 2018-12-28 | 宇龙计算机通信科技(深圳)有限公司 | A kind of battery loss based reminding method and mobile terminal |
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| US11209493B2 (en) | 2019-06-11 | 2021-12-28 | Volvo Car Corporation | Detecting latent faults within a cell of an energy storage system |
| US11635471B2 (en) | 2019-06-11 | 2023-04-25 | Volvo Car Corporation | Detecting latent faults within a cell of an energy storage system |
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| WO2021134829A1 (en) * | 2019-12-31 | 2021-07-08 | 深圳市普兰德储能技术有限公司 | Battery testing system |
| CN113721157A (en) * | 2021-08-31 | 2021-11-30 | 星恒电源股份有限公司 | Method, device, terminal and storage medium for prolonging service life of battery pack |
| CN115963408A (en) * | 2022-12-19 | 2023-04-14 | 北京双登慧峰聚能科技有限公司 | Fault early warning system and method for single battery of energy storage power station |
| CN115963408B (en) * | 2022-12-19 | 2024-04-16 | 北京双登慧峰聚能科技有限公司 | Energy storage power station single battery fault early warning system and method |
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