CN110927589B - Method for monitoring short circuit abnormality in battery on line - Google Patents
Method for monitoring short circuit abnormality in battery on line Download PDFInfo
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- CN110927589B CN110927589B CN201911251824.5A CN201911251824A CN110927589B CN 110927589 B CN110927589 B CN 110927589B CN 201911251824 A CN201911251824 A CN 201911251824A CN 110927589 B CN110927589 B CN 110927589B
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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]
- G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
- G01R31/3835—Arrangements for monitoring battery or accumulator variables, e.g. SoC involving only voltage measurements
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/10—Energy storage using batteries
Abstract
The invention provides a method for monitoring short circuit abnormality in a battery on line, which comprises the following steps: 1) Charging a lithium battery for the first time, and acquiring voltage data of two ends of the lithium battery in real time; 2) Monitoring and analyzing the initial static voltage, judging whether the initial static voltage is less than or equal to a constant A value, and stopping charging the lithium battery if the initial static voltage is less than or equal to the constant A value; 3) And monitoring and analyzing the dynamic voltage, counting and analyzing the dynamic voltage value and the interval voltage increment when different electric quantities are charged, identifying and feeding back abnormal voltage behaviors, and stopping charging the lithium battery if abnormality is found. The invention monitors and analyzes the static voltage and the dynamic voltage behavior of the battery on line aiming at the first charging process of the battery, further identifies and feeds back the position of the battery with the hidden trouble of internal short circuit abnormality, and rapidly stops the charging of the corresponding battery, thereby avoiding the occurrence of the safety accident of the thermal runaway ignition of the battery and providing effective guarantee for the safe production.
Description
Technical Field
The invention belongs to the technical field of short circuit detection in batteries, and particularly relates to a method for monitoring short circuit abnormality in a battery on line.
Background
The lithium ion soft package battery has the advantages of good safety performance, light weight, high capacity, large energy density, small internal resistance, flexible design and the like. With the explosive development of new energy automobiles and the demand and policy drive of the new energy automobiles on the energy density of the power battery, the soft-package power battery is rapidly developed and applied to the field of the new energy automobiles by virtue of the advantages of high energy density and high safety, and the market share of the soft-package power battery is continuously increased.
Lithium ion soft packet of power battery, when the activation is charged for the first time in production process, because defects such as the inside diaphragm of battery is discounted, damaged or diaphragm puncture, hole will lead to the inside partial discharge of battery to emit a large amount of heats, when heat release is too fast too much, will lead to further exothermic reactions such as SEI film decomposition and active material side reaction, lead to the thermal runaway incident that catches fire, cause the damage to charging and discharging equipment, cause the factory building damage even, bigger loss of property such as personal safety. Therefore, the abnormal battery with the internal short circuit is identified in time, the charging process is effectively controlled, and the method has great significance for production safety guarantee.
The current lithium ion battery charging equipment is generally provided with protection parameters of the upper limit of the charging voltage and the upper limit of the charging capacity of the battery when software is compiled, so that the problem of overcharge of the battery is avoided; the protection setting function of the voltage drop of the battery in the charging process is also added, and the protection setting function is used for identifying the rapid voltage drop condition caused by the internal short circuit of the battery.
Because the degree of the short circuit in the battery is greatly different, the leakage current of the direct contact or indirect contact electronic conduction of the positive and negative pole pieces is different, and the current conventional protection parameters can not be effectively identified and controlled, so that the hidden danger of battery charging thermal runaway ignition exists in a plurality of battery production factories in the first charging process.
Disclosure of Invention
In view of the above, the present invention is directed to a method for monitoring internal short circuit abnormality on line, in which a battery with hidden danger of internal short circuit abnormality is analyzed and identified on line by monitoring a voltage state and a voltage variation curve of the battery on line in a first charging process.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
a method for online monitoring of short circuit anomalies within a battery, the method comprising:
1) Charging a lithium battery for the first time, and acquiring voltage data of two ends of the lithium battery in real time;
2) Monitoring and analyzing the initial static voltage, judging whether the initial static voltage is less than or equal to a constant A value, and stopping charging the lithium battery if the initial static voltage is less than or equal to the constant A value;
3) And monitoring and analyzing the dynamic voltage, counting and analyzing the dynamic voltage value and the interval voltage increment when different electric quantities are charged, identifying and feeding back abnormal voltage behaviors, and stopping charging the lithium battery if abnormality is found.
Further, the constant a = the median- (4 δ to 6 δ) of the distribution of the initial static voltages of the modules, δ being the median of the standard deviation of the initial static voltage distribution of 100 modules of the model, and is set through background analysis. The decision criterion constant a for each module floats with the median of the initial quiescent voltage distribution for that module. Wherein, a module refers to an independent unit which is charged and discharged simultaneously in the equipment, and the number of batteries is generally between 36 and 96 pcs. .
Further, the dynamic voltage value and the interval voltage increment when different electric quantities are charged are counted and analyzed, and whether the dynamic voltage meets the following conditions is specifically judged:
V2＞B，V3＞C，C1＞△V1＞C2，V4＞D，D1＞△V2＞D2，V5＞E，E1＞△V3＞E2；
the dynamic voltage is recorded as V2 when the first percentage SOC is charged, the dynamic voltage is recorded as V3 when the second percentage SOC is charged, interval voltage increment V3-V2 is recorded as delta V1, the dynamic voltage is recorded as V4 when the third percentage SOC is charged, interval voltage increment V4-V3 is recorded as delta V2, the dynamic voltage is recorded as V5 when the fourth percentage SOC is charged, and interval voltage increment V5-V4 is recorded as delta V3;
B. c, D and E are constants and are respectively the lower limit of 5 +/-1 delta of the overall data distribution of all dynamic voltages V2, V3, V4 and V5 of the module, namely the module data median value- (4 delta-6 delta), delta is the median value of the standard deviation of the dynamic voltage distribution of the charging state corresponding to 100 modules of the model, and the standard deviation is analyzed and set through a background. The decision criterion constant for each module is floating with the median of the dynamic voltage distribution for that module. C1, C2, D1, D2, E1 and E2 are constants and respectively represent the upper limit of 5 +/-1 delta and the lower limit of 5 +/-1 delta of the overall voltage increment delta V1, delta V2 and delta V3 distribution of all intervals of the module, namely the median value of the module data is +/- (4 delta-6 delta), delta is the median value of the standard deviation of the voltage increment distribution of the interval corresponding to 100 modules of the model, and the median value is analyzed and set through a background. The decision criterion constant for each module is floating with the median of the dynamic voltage distribution for that module. (ii) a
B. And C, D, E, C1, C2, D1, D2, E1 and E2 are constants, correspond to the corresponding modules, and the constants among different modules are calculated and updated in real time.
Further, in the charging process, when the voltage is reduced or the amplitude of the current rise in the constant-voltage charging process exceeds a certain percentage, the battery charging is stopped.
Compared with the prior art, the invention has the following advantages:
(1) The invention aims at the first charging process of the battery, particularly at the initial charging stage (within 10 percent of SOC), monitors and analyzes the static voltage and the dynamic voltage behavior on line, wherein the dynamic voltage behavior comprises a dynamic voltage value and an interval dynamic voltage increment, and further identifies and feeds back the position of the battery with the potential hazard of internal short circuit abnormality, and rapidly controls the charging stop of the corresponding battery, thereby avoiding the occurrence of the safety accident of thermal runaway ignition of the battery and providing effective guarantee for safe production.
(2) When static voltage and dynamic voltage behaviors are monitored and analyzed, modularized overall data distribution analysis is adopted, 5 +/-1 delta is used as an upper limit control standard and a lower limit control standard to identify and feed back abnormal behaviors of the battery voltage, rejection standards among different modules are calculated and updated in real time, slight floating change is achieved within a certain range, and a consistency control idea is fully embodied.
(3) According to the invention, when the voltage is reduced in the charging process and the current is increased in the constant-voltage charging process, the charging process of the corresponding battery is automatically stopped when the amplitude exceeds 0.5%, the continuous charging is forbidden, and the final rejection is carried out.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate an embodiment of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
FIG. 1 is a graph of voltage-SOC curves monitored on-line during the first charging process (SOC: 0% -30% interval, voltage: 0-4V interval) according to an embodiment of the present invention;
FIG. 2 is a graph of voltage-SOC curves monitored online during the first charging process according to the embodiment of the present invention (SOC: 0% -6% interval, voltage: 1-3.5V interval).
Detailed Description
It should be noted that the embodiments and features of the embodiments of the present invention may be combined with each other without conflict.
In the examples of the present invention, mention is made of:
the internal short circuit means that the positive and negative pole pieces in the battery are in direct contact or conductive foreign matter is in indirect conduction contact, and the electrons are conducted between the positive and negative poles.
And activation refers to a process of first charging and activating the battery, reacting a chemical system in the battery, generating an SEI film on the surface of a pole piece, and converting electric energy into chemical energy in the battery for the first time.
SOC, also known as state of charge, refers to the ratio of the charge capacity of the battery to the charge capacity of the battery.
A module: the device is an independent unit which is charged and discharged simultaneously in the device, and the number of batteries is generally 36-96 pcs.
The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings.
The method for monitoring the short circuit abnormality in the battery on line provided by the embodiment of the invention is used for monitoring and analyzing the static voltage and dynamic voltage behavior of the battery on line aiming at the first charging process of the battery, further feeding back the position of the battery with the hidden danger of the internal short circuit abnormality and performing rapid charging stop control, and the method is shown in fig. 1 and 2 as an on-line monitoring voltage behavior curve in the first charging process of the invention.
Generally, the behavior of static voltage and dynamic voltage is abnormal as follows:
(1) Initial static voltage monitoring analysis.
The initial quiescent voltage (denoted as V1) needs to satisfy: v1 is more than A, wherein A is a constant and is generally within the range of 0.15 +/-0.05V, and the specific value is mainly influenced by a positive and negative electrode system of the battery and the formula of the electrolyte.
Preferably, the lower limit of 5 ± 1 δ of the initial static voltage V1 distribution of the corresponding system model is set, that is, a = the median- (4 δ to 6 δ) of the initial static voltage V1 distribution, δ is the median of the standard deviation of the initial static voltage distribution of 100 modules of the model to which the battery belongs, and is set through background analysis. The decision criterion constant a for each module floats with the median of the initial quiescent voltage distribution for that module. Wherein, a module is an independent unit which is charged and discharged in the equipment at the same time, and the number of batteries is generally between 36 and 96 pcs.
And when the static initial voltage V1 is not more than A, the equipment automatically stops the charging process of the corresponding battery, prohibits charging and carries out final rejection.
(2) And monitoring and analyzing dynamic voltage in the charging process.
Generally, a step-type current increment charging mode is adopted when the battery is charged for the first time, and the initial current step is in the range of 0.05C-0.1C.
And monitoring and analyzing the dynamic voltage behavior, wherein the dynamic voltage value and the interval voltage increment when different electric quantities are charged need to be counted and analyzed, and the abnormal voltage behavior is identified and fed back.
In the initial charging stage, the voltage is between 1.0V and 3.0V, the metal foreign matters in the battery are subjected to oxidation reaction in the potential interval, or the internal diaphragm is broken, so that local electron exchange is carried out, the voltage increment is reduced, and therefore the potential battery can be identified by the initial charging voltage behavior.
Preferably, the dynamic voltage at soc (noted as V2) is charged 0.1%, the dynamic voltage at soc (noted as V3) and the first interval voltage increase (noted as Δ V1= V3-V2) is charged 1%, the dynamic voltage at soc (noted as V4) and the second interval voltage increase (noted as Δ V2= V4-V3) are charged 2%.
The dynamic voltage needs to satisfy the following conditions: v2 > B, V3 > C, C1 >. DELTA.V 1 > C2, V4 > D, D1 >. DELTA.V 2 > D2, V5 > E, E1 >. DELTA.V 3 > E2.
B, C, D and E are constants, are respectively the lower limit of 5 +/-1 delta (namely, the module data median value- (4 delta-6 delta) of the overall data distribution of all dynamic V2, V3, V4 and V5 modules (36-96 pcs), delta is the median value of the standard deviation of the dynamic voltage distribution of 100 modules of the model to which the battery belongs, and are analyzed and set in the background, the judgment standard of each module is floated along with the module dynamic voltage distribution median value, C1, C2, D1, D2, E1 and E2 are constants, are respectively the upper limit of 5 +/-1 delta and the lower limit of 5 +/-1 delta (namely, the module data median value +/-4 delta-6 delta) of the overall data distribution of all intervals delta V1, delta V2 and delta V3 of the module (36-96 pcs), delta is the median value of the standard deviation of the voltage increment distribution of 100 module intervals of the model, and are analyzed and set in the background, and the judgment standard of each module is floated along with the dynamic voltage and the median increment distribution of the module.
B. C, D, E, C1, C2, D1, D2, E1, E2 are constants, correspond to corresponding module, the constant calculates and updates in real time among different modules, and slightly float and change in a certain range, carry on the concordance and reject.
And when the voltage behavior exceeds the specification range in the charging process, the equipment automatically stops the charging process of the corresponding battery, prohibits continuous charging and carries out final rejection.
According to the difference of different systems, the dynamic voltage monitoring analysis position can be properly adjusted within the SOC range of 10% in the initial charging stage, thereby realizing the identification and control of the abnormal battery through the voltage behavior.
Meanwhile, when the voltage is reduced in the charging process and the current is increased in the constant-voltage charging process, the charging process of the corresponding battery is automatically stopped when the amplitude exceeds 0.5%, the continuous charging is forbidden, and the final rejection is carried out.
In the first charging process, the method analyzes and identifies the internal short circuit abnormal hidden trouble battery on line by monitoring the voltage state and the voltage change curve of the battery on line, and rapidly finishes the corresponding battery charging stopping operation, thereby avoiding the occurrence of the thermal runaway ignition safety accident of the battery and providing effective guarantee for the safety production.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (3)
1. A method for online monitoring of short circuit anomalies in a battery, the method comprising:
1) Charging a lithium battery for the first time, and acquiring voltage data of two ends of the lithium battery in real time;
2) Monitoring and analyzing the initial static voltage, judging whether the initial static voltage is less than or equal to a constant A value, and stopping charging the lithium battery if the initial static voltage is less than or equal to the constant A value;
3) Monitoring and analyzing the dynamic voltage, counting and analyzing dynamic voltage values and interval voltage increments when different electric quantities are charged, identifying feedback abnormal voltage behaviors, and stopping charging the lithium battery if abnormality is found;
counting and analyzing dynamic voltage values and interval voltage increments when different electric quantities are charged, and specifically judging whether the dynamic voltage meets the following conditions:
V2＞B，V3＞C，C1＞△V1＞C2，V4＞D，D1＞△V2＞D2，V5＞E，E1＞△V3＞E2；
the dynamic voltage is recorded as V2 when the first percentage SOC is charged, the dynamic voltage is recorded as V3 when the second percentage SOC is charged, interval voltage increment V3-V2 is recorded as delta V1, the dynamic voltage is recorded as V4 when the third percentage SOC is charged, interval voltage increment V4-V3 is recorded as delta V2, the dynamic voltage is recorded as V5 when the fourth percentage SOC is charged, and interval voltage increment V5-V4 is recorded as delta V3;
B. c, D and E are constants and are respectively the lower limit of 5 +/-1 delta of the overall data distribution of all dynamic voltages V2, V3, V4 and V5 of the module to which the battery belongs, namely the module data median value- (4 delta-6 delta), delta is the median value of the standard deviation of the dynamic voltage distribution of the charging states corresponding to a plurality of modules of which the battery belongs to, and is analyzed and set through a background, and the judgment standard of each module floats along with the dynamic voltage distribution median value of the module; c1, C2, D1, D2, E1 and E2 are constants and are respectively the upper limit of 5 +/-1 delta and the lower limit of 5 +/-1 delta of the overall data distribution of all interval voltage increments delta V1, delta V2 and delta V3 of the module, namely the module data median value +/-4 delta-6 delta, delta is the median value of standard deviation of voltage increment distribution of each interval corresponding to a plurality of modules of which the types of the battery belong to statistics, the judgment standard of each module floats along with the dynamic voltage increment distribution median value of the interval of the module, wherein one module is an independent unit which is charged and discharged in equipment at the same time;
B. and C, D, E, C1, C2, D1, D2, E1 and E2 are constants, correspond to the corresponding modules, and the constants among different modules are calculated and updated in real time.
2. The method for on-line monitoring of battery short circuit abnormality according to claim 1, wherein: the constant A = the median value- (4 δ -6 δ) of the distribution of the initial static voltages of the modules to which the battery belongs, δ is the median value of the standard deviations of the initial static voltage distributions of a plurality of modules of which the model of the battery belongs, and the judgment standard constant A of each module floats along with the median value of the initial static voltage distribution of the module, wherein one module refers to an independent unit which is charged and discharged in the equipment at the same time.
3. The method for on-line monitoring of battery short circuit abnormality according to claim 1, wherein: in the charging process, when the voltage is reduced or the current is increased by more than a certain percentage in the constant-voltage charging process, the battery is stopped to be charged.
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| CN112180266A (en) * | 2020-09-21 | 2021-01-05 | 上海理工大学 | Tracking early warning method for whole process of short circuit in battery |
| CN113093018A (en) * | 2021-03-09 | 2021-07-09 | 北京交通大学 | Lithium ion battery instantaneous internal short circuit detection device and method |
| CN113466702A (en) * | 2021-06-29 | 2021-10-01 | 广东省万谷能源技术有限公司 | Lithium ion battery early warning method and system |
| CN117349631A (en) * | 2023-12-04 | 2024-01-05 | 斯润天朗(合肥)科技有限公司 | Electric vehicle thermal runaway prejudging method, model training method, device and related equipment |
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| JPH1010212A (en) * | 1996-06-24 | 1998-01-16 | Sony Corp | Method for evaluating battery and device for evaluating battery |
| JP5225559B2 (en) * | 2006-06-06 | 2013-07-03 | パナソニック株式会社 | Battery pack abnormality determination method and battery pack |
| JP2009032506A (en) * | 2007-07-26 | 2009-02-12 | Panasonic Corp | Internal short-circuit detection method and device of non-aqueous electrolyte secondary battery |
| JP2009170397A (en) * | 2007-12-18 | 2009-07-30 | Mitsumi Electric Co Ltd | Battery pack and portable device using the same, internal short-circuit detection method for the same, and internal short-circuit detection program |
| JP5235959B2 (en) * | 2010-09-10 | 2013-07-10 | 日立ビークルエナジー株式会社 | Battery controller and voltage abnormality detection method |
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| CN103515643A (en) * | 2012-06-16 | 2014-01-15 | 哈尔滨智木科技有限公司 | Intelligent formation method and device of secondary battery |
| JP5744956B2 (en) * | 2013-04-12 | 2015-07-08 | プライムアースＥｖエナジー株式会社 | Battery status judgment device |
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