CN104714189A - Method for predicting cycle life of battery pack for electric car - Google Patents
Method for predicting cycle life of battery pack for electric car Download PDFInfo
- Publication number
- CN104714189A CN104714189A CN201510155755.3A CN201510155755A CN104714189A CN 104714189 A CN104714189 A CN 104714189A CN 201510155755 A CN201510155755 A CN 201510155755A CN 104714189 A CN104714189 A CN 104714189A
- Authority
- CN
- China
- Prior art keywords
- test
- battery
- capacity
- cycle life
- voltage
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 19
- 238000012360 testing method Methods 0.000 claims abstract description 55
- 125000004122 cyclic group Chemical group 0.000 claims description 6
- 238000011156 evaluation Methods 0.000 claims description 3
- 229940116007 ferrous phosphate Drugs 0.000 claims description 3
- 229910000155 iron(II) phosphate Inorganic materials 0.000 claims description 3
- SDEKDNPYZOERBP-UHFFFAOYSA-H iron(ii) phosphate Chemical group [Fe+2].[Fe+2].[Fe+2].[O-]P([O-])([O-])=O.[O-]P([O-])([O-])=O SDEKDNPYZOERBP-UHFFFAOYSA-H 0.000 claims description 3
- 229910052744 lithium Inorganic materials 0.000 claims description 3
- 229910001416 lithium ion Inorganic materials 0.000 abstract description 9
- HBBGRARXTFLTSG-UHFFFAOYSA-N Lithium ion Chemical compound [Li+] HBBGRARXTFLTSG-UHFFFAOYSA-N 0.000 abstract description 5
- 238000012545 processing Methods 0.000 abstract description 2
- 239000000178 monomer Substances 0.000 description 5
- 230000035882 stress Effects 0.000 description 5
- 239000011449 brick Substances 0.000 description 4
- 230000032683 aging Effects 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 238000011217 control strategy Methods 0.000 description 2
- 230000003679 aging effect Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000009792 diffusion process Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
- 238000012956 testing procedure Methods 0.000 description 1
Landscapes
- Secondary Cells (AREA)
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
Abstract
The invention relates to a method for predicting the cycle life of a battery pack for an electric car. The method comprises the following steps: step I, carrying out standard capacity test on the battery pack at normal temperature, and recording a real standard capacity of the battery pack; step II, carrying out dynamic stress working condition circulating test on the battery pack, returning to the step I after multiple times of working condition circulating test is ended, recording the test times of the standard capacity, ending the circulating test at the temperature if the real capacity of the standard capacity test for continuous 4 to 6 times is less than 80 percent of the rated capacity, wherein the test times of the standard capacity indicate the cycle life of the battery pack; step III, repeating the step I and the step II, and testing the cycle life of the battery pack under multiple temperature points. According to the method, the battery pack cycle life data at the grouped time is collected, a fitted equation is obtained by virtue of data processing, and the cycle life of a lithium ion battery at present can be predicted.
Description
Technical field
The invention belongs to electric vehicle battery system technical field, be specifically related to a kind of Forecasting Methodology of battery for electric automobile group cycle life.
Background technology
Along with socioeconomic growing, energy demand improves further, the cry of new energy technology is more and more higher, lithium ion battery because of its have that voltage is high, energy density is large, good cycle, self discharge are little and the outstanding advantages such as memory-less effect, are widely used in electric automobile field as drive energy.
Primary Study is carried out to battery life both at home and abroad, achieved interim achievement.Such as: based on the refined cell model of difference equation; Based on the analytic model of diffusion theory, can to any given load accurately predicting lithium-ions battery life-span.The current research to battery service life model is also in the elementary step, does not have systematic theory support, does not also produce the universal battery life model having and be generally worth.
Compare patent CN201410186038.2, introduction be the life prediction of monomer lithium ion battery, using with reality is all power brick difference to some extent in groups.In above disclosed patent, all that life prediction is carried out to cell, because batteries of electric automobile group has hundreds of or thousands of monomers to form, the aging effects factor of electric battery depends on the monomer that the performance of component units is the poorest, so simple cell life prediction can not on the battery pack.
Summary of the invention
In order to overcome the deficiencies in the prior art, the invention provides a kind of Forecasting Methodology of battery for electric automobile group cycle life, based on the test data of the Li-ion batteries piles of practical application, provide Life Prediction Model, can life-span of Accurate Prediction electric battery, greatly save the test period under the different test condition of car load or battery producer and expense, and the Li-ion batteries piles of same type all can according to this Forecasting Methodology.Employing high temperature circulation is tested, and accelerates the aging of battery, fast and effeciently can assess the cycle life performance of power brick, have very large using value.
Technical scheme of the present invention is: a kind of Forecasting Methodology of battery for electric automobile group cycle life, comprises the steps: step one: carry out normal capacity test to electric battery at normal temperatures, the actual standard capacity of record electric battery; Step 2: the test of dynamic stress Operation mode cycle is carried out to electric battery, after every 40-60 Operation mode cycle test terminates, return step one and carry out a normal capacity test, record standard volume test number of times K, if the actual capacity of 4-6 standard volume test continuously is all less than 80% of rated capacity C, then terminate to the loop test at temperature, normal capacity testing time K represents the battery cyclic life-span; Step 3: repeating step one to two, test the battery cyclic life-span under multiple temperature spot respectively, by being captured in the number of times K of testing standard capacity under condition of different temperatures, making T
-1/ 10
-3-lnK curve, is extrapolated the cycle life of power battery pack at other temperature by fit equation.The concrete steps of described step one are: the first step, 1/3C steady current are discharged to battery power discharge cut-off voltage, leave standstill on request; Second step, 0.2C constant current charge are to cut-off voltage, then constant-voltage charge to electric current is 0.05C cut-off, leaves standstill on request; 3rd step, 1/3C steady current are discharged to cut-off voltage, leave standstill on request; Wherein, C is the rated capacity of electric battery.Described electric battery is ferrous phosphate lithium battery group, and the rated capacity of electric battery is 60Ah, and rated voltage is 330V.In described step 2 dynamic stress Operation mode cycle test have by condition: depth of discharge is 80%DOD, and the discharge cut-off voltage of electric battery is 295V, and charge cutoff voltage is 367V.In described step 2, a normal capacity test is carried out in every 50 dynamic stress Operation mode cycles test, and when the actual capacity of continuous 5 standard volume tests is all less than 80% of rated capacity C, loop test terminates.In described step 3, test temperature 10 DEG C, the cycle life of electric battery at 15 DEG C, 25 DEG C, 35 DEG C, 45 DEG C, fit equation is: lnKi=-7.453+3940/Ti (308K≤Ti < 333K), lnKi=12.25-1947/T (273K≤Ti < 308K), wherein: Ki is the battery cyclic life-span, Ti is the absolute temperature of working temperature.Also comprise step: utilize fit equation to estimate cycle life at 5 DEG C, 55 DEG C and actual test, and compare the validity determining evaluation method.
The present invention has following good effect: by acquisition time power brick cycle life data in groups, pass through data processing, obtain fit equation, can to current actual right Li-ion batteries piles Cycle life prediction, employing high temperature circulation is tested, accelerate the aging of battery, fast and effeciently can assess the cycle life performance of electric battery.
Accompanying drawing explanation
Fig. 1 is specific embodiment of the invention electric battery ambulatory stress test Operation mode cycle figure;
Fig. 2 is specific embodiment of the invention T
-1/ 10
-3-lnK linear relationship chart.
Embodiment
Contrast accompanying drawing below, by the description to embodiment, the specific embodiment of the present invention is as the effect of the mutual alignment between the shape of involved each component, structure, each several part and annexation, each several part and principle of work, manufacturing process and operation using method etc., be described in further detail, have more complete, accurate and deep understanding to help those skilled in the art to inventive concept of the present invention, technical scheme.
The invention provides a kind of electric automobile power battery group Cycle life prediction method, comprise the following steps:
Step one: the Li-ion batteries piles of a rated voltage (> 300V), (25 ± 2 DEG C) carry out normal capacity test at normal temperatures:
The first step, 1/3C steady current are discharged to battery power discharge cut-off voltage, leave standstill on request;
Second step, 0.2C constant current charge are to cut-off voltage, then constant-voltage charge to electric current is 0.05C cut-off, leaves standstill on request;
3rd step, 1/3C steady current are discharged to cut-off voltage, leave standstill on request;
Wherein, C is the rated capacity of electric battery, the 3rd step release charge value be when time normal capacity, be designated as Ck (k is expressed as standard cycle number of times, k=0,1,2 ...).Electric battery is ferrous phosphate lithium battery group, and be made up of some cell connection in series-parallel, the rated capacity of electric battery is preferably 60Ah, and rated voltage is preferably 330V.
Step 2: respectively under different temperature environments, carry out dynamic stress working condition measurement (DST) to above-mentioned electric battery, testing procedure and operating mode are as table 1 and table 2:
Table 1:
Table 2:
DST operating mode has 20 steps, carries out loop test, be provided with cut-off condition by Variable power discharge and recharge: BMS (battery management system) monomer voltage, temperature protection, and electric battery stagnation pressure is protected, and depth of discharge is 80%DOD, till arriving first protection point.Described monomer discharge cut-off voltage is preferably 2.0V, and charge cutoff voltage is preferably 3.65V; Temperature < 60 DEG C; The discharge cut-off voltage of electric battery is preferably 295V, and charge cutoff voltage is preferably 367V.
Step 3: after every 50 DST Operation mode cycles, carry out normal capacity test, so circulate.If the discharge capacity of continuous 5 standard loop tests is all less than 80% of rated capacity, then loop test terminates, record standard volume test number of times, i.e. cycle life.
Step 4: test 10 DEG C respectively, 15 DEG C, 20 DEG C, 25 DEG C, 35 DEG C, the cycle life of electric battery under 45 DEG C of environment temperatures.Loop-around data is processed, in table 3:
Under table 3 different temperatures, cycle life
| T,℃ | Cycle index, K | T —1(k)/10 -3 | lnK |
| 10 | 210 | 3.534 | 5.347 |
| 15 | 250 | 3.472 | 5.521 |
| 25 | 300 | 3.356 | 5.704 |
| 35 | 240 | 3.247 | 5.481 |
| 45 | 130 | 3.145 | 4.867 |
According to formula lnKi=a+b/Ti, make the linear relationship chart of lnK and 1/T, see Fig. 2, wherein a, b are coefficient.According to the operating characteristic of lithium ion battery, when low temperature or high temperature, charge-discharge performance impact is comparatively large, and life time decay accelerates.Therefore to the cycle life of the electric battery of 35 DEG C and above temperature, sectional linear fitting is carried out.Fit equation is as follows:
lnKi＝-7.453+3940/Ti (308K≤Ti＜333K)
lnKi＝12.25-1947/Ti (273K≤Ti＜308K)
Wherein: Ki is cycle life (number of times) under different temperatures, and Ti is the absolute temperature of working temperature.
Fit equation is utilized to estimate cycle life at 5 DEG C, 55 DEG C and actual test, and to compare the validity determining evaluation method, in table 4:
| T,℃ | Estimation cycle index, K | Actual cycle number of times, K | Error % |
| 5 | 189 | 186 | 1.61％ |
| 55 | 95 | 93 | 2.15％ |
Table 4 estimates that cycle index and actual cycle number of times contrast
The cycle life calculated by above equation and actual test value very close, predict the outcome good, demonstrate the accuracy of Life Calculating Methods.Therefore to the estimation of power brick cycle life under different temperatures and can compare, also provide Data support for BMS (battery management system) control strategy simultaneously.Tested by power battery pack high-temperature cycle life, accelerate the aging of battery, fast and effeciently can assess the cycle life performance of electric battery.
Cycle life data provided by the invention, from the electric battery of practical application, can be directly used in and instruct BMS control strategy, have very great practical significance.
Above content is in conjunction with concrete embodiment further description made for the present invention, can not assert that specific embodiment of the invention is confined to these explanations.For general technical staff of the technical field of the invention, without departing from the inventive concept of the premise, some simple deductions can also be made or replace, all should be considered as belonging to protection scope of the present invention.
Claims (7)
1. a Forecasting Methodology for battery for electric automobile group cycle life, is characterized in that, comprises the steps:
Step one: at normal temperatures normal capacity test is carried out to electric battery, the actual standard capacity of record electric battery;
Step 2: the test of dynamic stress Operation mode cycle is carried out to electric battery, after every 40-60 Operation mode cycle test terminates, return step one and carry out a normal capacity test, record standard volume test number of times K, if the actual capacity of 4-6 standard volume test continuously is all less than 80% of rated capacity C, loop test then at this temperature terminates, and normal capacity testing time K represents the battery cyclic life-span;
Step 3: repeating step one to two, test the battery cyclic life-span under multiple temperature spot respectively, by being captured in the number of times K of testing standard capacity under condition of different temperatures, making T
-1/ 10
-3-lnK curve, is extrapolated the cycle life of power battery pack at other temperature by fit equation.
2. Forecasting Methodology according to claim 1, is characterized in that, the concrete steps of described step one are:
The first step, 1/3C steady current are discharged to battery power discharge cut-off voltage, leave standstill on request;
Second step, 0.2C constant current charge are to cut-off voltage, then constant-voltage charge to electric current is 0.05C cut-off, leaves standstill on request;
3rd step, 1/3C steady current are discharged to cut-off voltage, leave standstill on request;
Wherein, C is the rated capacity of electric battery.
3. Forecasting Methodology according to claim 2, is characterized in that, described electric battery is ferrous phosphate lithium battery group, and the rated capacity of electric battery is 60Ah, and rated voltage is 330V.
4. Forecasting Methodology according to claim 2, is characterized in that, in described step 2, the cut-off condition of dynamic stress Operation mode cycle test has: depth of discharge is 80%DOD, and the discharge cut-off voltage of electric battery is 295V, and charge cutoff voltage is 367V.
5. Forecasting Methodology according to claim 1, it is characterized in that, in described step 2, a normal capacity test is carried out in every 50 dynamic stress Operation mode cycles test, when the actual capacity of continuous 5 standard volume tests is all less than 80% of rated capacity C, loop test terminates.
6. Forecasting Methodology according to claim 1, it is characterized in that, in described step 3, test temperature 10 DEG C, the cycle life of electric battery at 15 DEG C, 25 DEG C, 35 DEG C, 45 DEG C, fit equation is: lnKi=-7.453+3940/Ti (308K≤Ti < 333K)
lnKi＝12.25-1947/Ti (273K≤Ti＜308K)
Wherein: Ki is the battery cyclic life-span, Ti is the absolute temperature of working temperature.
7. Forecasting Methodology according to claim 6, is characterized in that, also comprises step: utilize fit equation to estimate cycle life at 5 DEG C, 55 DEG C and actual test, compare the validity determining evaluation method.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510155755.3A CN104714189A (en) | 2015-04-02 | 2015-04-02 | Method for predicting cycle life of battery pack for electric car |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510155755.3A CN104714189A (en) | 2015-04-02 | 2015-04-02 | Method for predicting cycle life of battery pack for electric car |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN104714189A true CN104714189A (en) | 2015-06-17 |
Family
ID=53413680
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510155755.3A Pending CN104714189A (en) | 2015-04-02 | 2015-04-02 | Method for predicting cycle life of battery pack for electric car |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104714189A (en) |
Cited By (27)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104991195A (en) * | 2015-06-25 | 2015-10-21 | 中国电子科技集团公司第十八研究所 | High-temperature accelerated storage test method for zinc-silver battery |
| CN105425156A (en) * | 2015-11-06 | 2016-03-23 | 安徽江淮汽车股份有限公司 | Cycle life testing method for power battery |
| CN105842630A (en) * | 2016-05-05 | 2016-08-10 | 超威电源有限公司 | Urban condition life detection formulating method for lead-acid battery used for electric vehicle |
| CN106093794A (en) * | 2016-08-01 | 2016-11-09 | 深圳市电科电源股份有限公司 | The high temperature service life accelerated test method of ferric phosphate lithium cell |
| CN106199445A (en) * | 2016-07-14 | 2016-12-07 | 安徽轰达电源有限公司 | Quickly charging battery cycle life detection method |
| CN106526486A (en) * | 2016-08-30 | 2017-03-22 | 郑州轻工业学院 | Construction method for lithium battery health life model |
| CN106950507A (en) * | 2017-05-12 | 2017-07-14 | 国家电网公司 | A kind of intelligent clock battery high reliability lifetime estimation method |
| CN107544033A (en) * | 2016-09-05 | 2018-01-05 | 北京航空航天大学 | Digital-analog fusion prediction method for remaining service life of lithium ion battery |
| WO2018054166A1 (en) * | 2016-09-21 | 2018-03-29 | 蔚来汽车有限公司 | Environment temperature-based battery cycle life test method |
| CN108732499A (en) * | 2017-04-13 | 2018-11-02 | 中国电力科学研究院 | A kind of method and system of detection cycle life of lithium ion battery |
| CN109904533A (en) * | 2017-12-11 | 2019-06-18 | 奥动新能源汽车科技有限公司 | The battery life analysis system and method for battery for electric automobile packet |
| CN109991557A (en) * | 2018-11-30 | 2019-07-09 | 常州车之翼动力科技有限公司 | Dynamic lithium battery cycle life detection method |
| CN110068409A (en) * | 2019-04-11 | 2019-07-30 | 蜂巢能源科技有限公司 | Lithium battery stress prediction method and apparatus |
| CN110244234A (en) * | 2019-07-24 | 2019-09-17 | 中国科学院电工研究所 | A kind of battery accelerating lifetime testing method |
| CN110416647A (en) * | 2019-06-28 | 2019-11-05 | 国网天津市电力公司电力科学研究院 | It is a kind of to enter network detecting method suitable for distribution terminal lead-acid accumulator |
| CN110470991A (en) * | 2019-08-23 | 2019-11-19 | 江西优特汽车技术有限公司 | A kind of power battery cycle life evaluating method |
| CN110658463A (en) * | 2019-10-31 | 2020-01-07 | 上海派能能源科技股份有限公司 | Method for predicting cycle life of lithium ion battery |
| CN111044927A (en) * | 2019-12-25 | 2020-04-21 | 中国第一汽车股份有限公司 | Power battery service life evaluation method and system |
| CN111366863A (en) * | 2020-03-13 | 2020-07-03 | 上海应用技术大学 | Lithium ion battery service life acceleration pre-judging method based on low-temperature circulation |
| CN112098113A (en) * | 2020-08-28 | 2020-12-18 | 奇瑞新能源汽车股份有限公司 | Method for testing protection capability of each system of electric automobile in high-temperature environment |
| CN112305439A (en) * | 2019-07-31 | 2021-02-02 | 比亚迪股份有限公司 | Battery life testing method and device and readable storage medium |
| CN112462275A (en) * | 2019-09-09 | 2021-03-09 | 河南森源重工有限公司 | Battery pack cycle life testing method |
| CN112599876A (en) * | 2020-12-22 | 2021-04-02 | 江苏双登富朗特新能源有限公司 | Regulation and control method for prolonging service life of lithium ion battery pack |
| CN113109728A (en) * | 2021-04-16 | 2021-07-13 | 惠州亿纬锂能股份有限公司 | Method and device for testing shallow DOD (disk on disk) cycle life |
| CN113761716A (en) * | 2021-08-12 | 2021-12-07 | 惠州市豪鹏科技有限公司 | Lithium ion battery cycle life prediction method and application thereof |
| CN117434453A (en) * | 2023-12-21 | 2024-01-23 | 南昌大学 | Method for detecting service life abnormality of lithium ion battery |
| CN112462275B (en) * | 2019-09-09 | 2024-05-31 | 河南森源重工有限公司 | Method for testing cycle life of battery pack |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH09257890A (en) * | 1996-03-21 | 1997-10-03 | Nissan Motor Co Ltd | Method for detecting total capacity of secondary cell for electric vehicle, remaining capacity meter using the method and remaining life meter |
| JP4215171B2 (en) * | 2001-08-13 | 2009-01-28 | 日立マクセル株式会社 | Battery capacity detection method |
| CN102736035A (en) * | 2012-07-03 | 2012-10-17 | 奇瑞汽车股份有限公司 | Power battery durability test method and system |
| CN103528911A (en) * | 2013-09-29 | 2014-01-22 | 奇瑞汽车股份有限公司 | Experimental method for testing liquid absorption rate of isolating membrane of lithium ion secondary battery |
-
2015
- 2015-04-02 CN CN201510155755.3A patent/CN104714189A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH09257890A (en) * | 1996-03-21 | 1997-10-03 | Nissan Motor Co Ltd | Method for detecting total capacity of secondary cell for electric vehicle, remaining capacity meter using the method and remaining life meter |
| JP4215171B2 (en) * | 2001-08-13 | 2009-01-28 | 日立マクセル株式会社 | Battery capacity detection method |
| CN102736035A (en) * | 2012-07-03 | 2012-10-17 | 奇瑞汽车股份有限公司 | Power battery durability test method and system |
| CN103528911A (en) * | 2013-09-29 | 2014-01-22 | 奇瑞汽车股份有限公司 | Experimental method for testing liquid absorption rate of isolating membrane of lithium ion secondary battery |
Non-Patent Citations (1)
| Title |
|---|
| 时玮: "动力锂离子电池组寿命影响因素及测试方法研究", 《中国博士学位论文全文数据库工程科技Ⅱ辑》 * |
Cited By (37)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104991195A (en) * | 2015-06-25 | 2015-10-21 | 中国电子科技集团公司第十八研究所 | High-temperature accelerated storage test method for zinc-silver battery |
| CN105425156A (en) * | 2015-11-06 | 2016-03-23 | 安徽江淮汽车股份有限公司 | Cycle life testing method for power battery |
| CN105425156B (en) * | 2015-11-06 | 2018-07-10 | 安徽江淮汽车集团股份有限公司 | A kind of power battery cycle life test method |
| CN105842630A (en) * | 2016-05-05 | 2016-08-10 | 超威电源有限公司 | Urban condition life detection formulating method for lead-acid battery used for electric vehicle |
| CN105842630B (en) * | 2016-05-05 | 2018-09-07 | 超威电源有限公司 | A kind of electronic automobile-used lead-acid battery city operating mode life tests formulating method |
| CN106199445B (en) * | 2016-07-14 | 2019-03-26 | 安徽轰达电源有限公司 | Quickly charging battery cycle life detection method |
| CN106199445A (en) * | 2016-07-14 | 2016-12-07 | 安徽轰达电源有限公司 | Quickly charging battery cycle life detection method |
| CN106093794A (en) * | 2016-08-01 | 2016-11-09 | 深圳市电科电源股份有限公司 | The high temperature service life accelerated test method of ferric phosphate lithium cell |
| CN106093794B (en) * | 2016-08-01 | 2018-10-12 | 深圳市电科电源股份有限公司 | The high temperature service life accelerated test method of ferric phosphate lithium cell |
| CN106526486A (en) * | 2016-08-30 | 2017-03-22 | 郑州轻工业学院 | Construction method for lithium battery health life model |
| CN107544033A (en) * | 2016-09-05 | 2018-01-05 | 北京航空航天大学 | Digital-analog fusion prediction method for remaining service life of lithium ion battery |
| CN107544033B (en) * | 2016-09-05 | 2020-01-10 | 北京航空航天大学 | Digital-analog fusion prediction method for remaining service life of lithium ion battery |
| WO2018054166A1 (en) * | 2016-09-21 | 2018-03-29 | 蔚来汽车有限公司 | Environment temperature-based battery cycle life test method |
| CN108732499A (en) * | 2017-04-13 | 2018-11-02 | 中国电力科学研究院 | A kind of method and system of detection cycle life of lithium ion battery |
| CN108732499B (en) * | 2017-04-13 | 2021-08-27 | 中国电力科学研究院 | Method and system for detecting cycle life of lithium ion battery |
| CN106950507A (en) * | 2017-05-12 | 2017-07-14 | 国家电网公司 | A kind of intelligent clock battery high reliability lifetime estimation method |
| CN109904533A (en) * | 2017-12-11 | 2019-06-18 | 奥动新能源汽车科技有限公司 | The battery life analysis system and method for battery for electric automobile packet |
| CN109991557A (en) * | 2018-11-30 | 2019-07-09 | 常州车之翼动力科技有限公司 | Dynamic lithium battery cycle life detection method |
| CN110068409A (en) * | 2019-04-11 | 2019-07-30 | 蜂巢能源科技有限公司 | Lithium battery stress prediction method and apparatus |
| CN110416647A (en) * | 2019-06-28 | 2019-11-05 | 国网天津市电力公司电力科学研究院 | It is a kind of to enter network detecting method suitable for distribution terminal lead-acid accumulator |
| CN110244234A (en) * | 2019-07-24 | 2019-09-17 | 中国科学院电工研究所 | A kind of battery accelerating lifetime testing method |
| CN112305439B (en) * | 2019-07-31 | 2022-01-07 | 比亚迪股份有限公司 | Battery life testing method and device and readable storage medium |
| CN112305439A (en) * | 2019-07-31 | 2021-02-02 | 比亚迪股份有限公司 | Battery life testing method and device and readable storage medium |
| CN110470991A (en) * | 2019-08-23 | 2019-11-19 | 江西优特汽车技术有限公司 | A kind of power battery cycle life evaluating method |
| CN112462275A (en) * | 2019-09-09 | 2021-03-09 | 河南森源重工有限公司 | Battery pack cycle life testing method |
| CN112462275B (en) * | 2019-09-09 | 2024-05-31 | 河南森源重工有限公司 | Method for testing cycle life of battery pack |
| CN110658463A (en) * | 2019-10-31 | 2020-01-07 | 上海派能能源科技股份有限公司 | Method for predicting cycle life of lithium ion battery |
| CN111044927A (en) * | 2019-12-25 | 2020-04-21 | 中国第一汽车股份有限公司 | Power battery service life evaluation method and system |
| CN111366863A (en) * | 2020-03-13 | 2020-07-03 | 上海应用技术大学 | Lithium ion battery service life acceleration pre-judging method based on low-temperature circulation |
| CN111366863B (en) * | 2020-03-13 | 2022-04-05 | 上海应用技术大学 | Lithium ion battery service life acceleration pre-judging method based on low-temperature circulation |
| CN112098113A (en) * | 2020-08-28 | 2020-12-18 | 奇瑞新能源汽车股份有限公司 | Method for testing protection capability of each system of electric automobile in high-temperature environment |
| CN112599876A (en) * | 2020-12-22 | 2021-04-02 | 江苏双登富朗特新能源有限公司 | Regulation and control method for prolonging service life of lithium ion battery pack |
| CN113109728A (en) * | 2021-04-16 | 2021-07-13 | 惠州亿纬锂能股份有限公司 | Method and device for testing shallow DOD (disk on disk) cycle life |
| CN113761716A (en) * | 2021-08-12 | 2021-12-07 | 惠州市豪鹏科技有限公司 | Lithium ion battery cycle life prediction method and application thereof |
| CN113761716B (en) * | 2021-08-12 | 2024-02-02 | 惠州市豪鹏科技有限公司 | Lithium ion battery cycle life prediction method and application thereof |
| CN117434453A (en) * | 2023-12-21 | 2024-01-23 | 南昌大学 | Method for detecting service life abnormality of lithium ion battery |
| CN117434453B (en) * | 2023-12-21 | 2024-02-20 | 南昌大学 | Method for detecting service life abnormality of lithium ion battery |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104714189A (en) | Method for predicting cycle life of battery pack for electric car | |
| CN106291372B (en) | A kind of new lithium-ion-power cell method for predicting residual useful life | |
| Jiaqiang et al. | Effects analysis on active equalization control of lithium-ion batteries based on intelligent estimation of the state-of-charge | |
| Xiong et al. | Modeling for lithium-ion battery used in electric vehicles | |
| CN105717456B (en) | The Forecasting Methodology of power battery life performance attenuation | |
| Meng et al. | A novel multiple correction approach for fast open circuit voltage prediction of lithium-ion battery | |
| CN109856559A (en) | A kind of prediction technique of lithium battery cycle life | |
| CN104051810B (en) | A kind of lithium-ion energy storage battery system SOC estimates rapid correction method | |
| CN103278777B (en) | A kind of lithium battery health condition estimation method based on dynamic bayesian network | |
| CN103698710A (en) | Prediction method for life cycle of battery | |
| CN102608535A (en) | Method for pre-measuring volume of lithium ion battery | |
| CN105738815A (en) | Method for detecting state of health of lithium ion battery online | |
| CN105223515A (en) | A kind of lithium-ion-power cell charge state estimation method | |
| CN105510847A (en) | Method for screening consistency of lithium ion batteries | |
| CN102508165A (en) | Method for evaluating self-discharge consistency of lithium iron phosphate battery | |
| CN111562501A (en) | Lithium ion battery SOC-OCV relation curve calibration method | |
| CN102520367A (en) | Method for evaluating life of space hydrogen-nickel storage batteries | |
| Feng et al. | A graphical model for evaluating the status of series‐connected lithium‐ion battery pack | |
| CN111366864B (en) | Battery SOH on-line estimation method based on fixed voltage rise interval | |
| CN111064253A (en) | Battery health degree rapid evaluation method based on average discrete Frechet distance | |
| CN106249158A (en) | Ferric phosphate lithium cell actual active volume detection method, system and electric automobile | |
| CN103353575A (en) | Test apparatus and test method for measuring correspondence between OCV (open circuit voltage) and SOC (state of charge) | |
| CN105738821B (en) | The accurate method for calculating battery coulombic efficiency under different temperatures | |
| CN115267555A (en) | Battery SOH (State of health) evaluation system of energy storage system based on battery multipoint temperature measurement | |
| CN105116338A (en) | Parallel type battery system modeling method based on SOC compensator |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20150617 |