CN107728072A - A kind of method for quick predicting of cycle life of lithium ion battery - Google Patents
A kind of method for quick predicting of cycle life of lithium ion battery Download PDFInfo
- Publication number
- CN107728072A CN107728072A CN201710936497.1A CN201710936497A CN107728072A CN 107728072 A CN107728072 A CN 107728072A CN 201710936497 A CN201710936497 A CN 201710936497A CN 107728072 A CN107728072 A CN 107728072A
- Authority
- CN
- China
- Prior art keywords
- battery
- cycle
- cycle life
- volume change
- lithium ion
- 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
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/385—Arrangements for measuring battery or accumulator variables
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Secondary Cells (AREA)
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
Abstract
The present invention discloses a kind of method for quick predicting of cycle life of lithium ion battery, comprises the following steps:The charge-discharge performance that battery to be evaluated is carried out to different cycle-indexes is tested, and records voltage in the charging process of different cycle-indexes, capacity and the relation curve of time;Calculating under different cycle-indexes voltage in battery charging process according to these curves increases to from 3.95V the changes delta C of this section inner capacities of 4.15V;Calculating is fitted according to volume change Δ C and cycle-index test data, the cycle life of battery is predicted.The present invention is compared with the cycle life method of testing of routine, it is simple and easy, substantially reduce the test period of cycle life, and compared with pure theory is calculated and empirical model is predicted, with more universality, it is more preferable with actual test result uniformity, research and development of products speed is accelerated, there is larger application in fields such as new energy.
Description
Technical field
The present invention relates to cycle life of lithium ion battery technical field of measurement and test, specifically a kind of cycle life of lithium ion battery
Method for quick predicting.
Background technology
Lithium ion battery is because its is environment-friendly, pollution is small, have extended cycle life, does not have the advantages that memory effect, extensive use
In mobile digital product, or even it is used for as energy-storage system among electric automobile.Service life is to weigh the weight of battery performance
Index is wanted, with the high speed development of battery technology, the battery cycle life in electric automobile field has reached 2000 times even
More than 2500 times.At present during the research and development, inspection and type selecting of lithium ion battery widely used life testing method be
Loop test is carried out under certain operating mode, it is well known that the major defect of these circulation test algorithms is that time-consuming, and this is not only caused very
Big equipment and energy resource consumption, it is slow to also result in research and development of products progress.Therefore if obtaining battery life correlation in a short time
Information will greatly shorten development time of Related product, and have in the field such as lithium ion battery exploitation and type selecting it is very big should
With value.
Researchers are largely studied in the rapid testing technology field of cycle life of lithium ion battery, have obtained one
A little accelerated test schemes, for example test etc. from quick charge and discharge operating mode and in high temperature environments, generally still need to thousands of small
Shi Caike completes test, however it remains the phenomenon of the wasting of resources.Therefore the cycle of shortening life assessment has become urgently to be resolved hurrily
The problem of.
The content of the invention
It is an object of the invention to provide a kind of method for quick predicting of cycle life of lithium ion battery, by battery
Charge-discharge test, the cycles left life-span of battery can be predicted, and required time is not grown, and need not expensive accurate survey
Try equipment and complicated theoretical calculation, by short-term loop test can fast prediction battery cycle life, greatly reduce
Time and the wasting of resources caused by conventionally test.
The purpose of the present invention can be achieved through the following technical solutions:
A kind of method for quick predicting of cycle life of lithium ion battery, comprises the following steps:
Step 1, the charge-discharge performance test by the different cycle-indexes of battery progress to be evaluated, record different cycle-indexes
Charging process in voltage, capacity and the relation curve of time;
Step 2, calculate under different cycle-indexes according to these curves that voltage increases to from 3.95V in battery charging process
Volume change Δ C in this section of 4.15V;
Step 3, calculating is fitted according to volume change Δ C and cycle-index test data, the circulation longevity to battery
Life is predicted:
1) it is fitted to obtain linear functional relation formula according to volume change Δ C and corresponding capability retention:Y=
0.002x-0.3349;Wherein, x represents that volume change Δ C (mAh), y represent capability retention;
2) it is fitted to obtain linear functional relation formula according to circulating battery number and corresponding volume change Δ C:y
=-0.1x+667.55, wherein, x represents circulating battery number, and y represents volume change Δ C;
3) corresponding circulating battery number when battery capacity conservation rate is 80% is calculated.
Further scheme, in step 1, the cycle-index is 200~500 times, stops the battery after loop test and is in
Discharge condition.
Further scheme, in the charge-discharge performance test in step 1, charging process is that constant current 1C charges to 4.2V, turns perseverance
Pressure charging 0.05C cut-offs;Constant-current discharge electric current is 1C.
Further scheme, charging voltage section corresponding to the volume change Δ C in step 2 is 3.95V to 4.15V.
Beneficial effects of the present invention:
1st, the present invention does not change original method of testing, it is only necessary to especially pick out by being circulated in short term to battery
Volume change in a certain section of voltage range, establishes model, so as to finally establish it is a kind of by short-term test realize to lithium from
The method of the sub- long-term Cycle life prediction of battery.
2nd, the inventive method can be applied in lithium ion battery R&D process study in Cycle life prediction in, so as to for
Corresponding battery exploitation provides Fast Evaluation means, shortens the Performance Evaluation time caused by time-consuming because of regular circulation test and grows
The problem of.
3rd, the inventive method is by carrying out short-term loop test to battery to be evaluated, you can according to cycle-index, circulation
Relation between tri- numerical value of capability retention and Δ C is fitted calculating, so as to predict the battery in this test condition
Cycle life, this substantially reduces test period compared with regular circulation is tested, and also therefore avoids by long-term test is produced
Raw energy consumption and the wasting of resources;In addition, Forecasting Methodology of the present invention is the data fitting carried out on the basis of short-term measured data, with
Pure theory calculates and empirical model is compared and has more universality, therefore prediction accuracy is higher.
4th, the inventive method is only to carry out certain processing in original loop test data to can be achieved to follow battery for a long time
The prediction in ring life-span, therefore there is universal applicability.
Brief description of the drawings
Fig. 1 is Δ C and capability retention fit correlation figure in the different number charge and discharge cycles tests of the present invention;
Fig. 2 is Δ C and cycle-index fit correlation figure in the different number charge and discharge cycles tests of the present invention.
Embodiment
The present invention is described in further detail with specific embodiment below in conjunction with the accompanying drawings.
Embodiment
A kind of method for quick predicting of cycle life of lithium ion battery, specifically includes following steps:
Step 1:The charge-discharge performance that battery to be evaluated is carried out to different cycle-indexes is tested, and records different circulations time
Voltage, capacity and the relation curve of time in several charging processes;
Step 2:Voltage is calculated under different cycle-indexes in battery charging process from 3.95V increases according to these curves
To the changes delta C of this section inner capacities of 4.15V;
Step 3:Calculating is fitted according to volume change Δ C and cycle-index test data, the circulation longevity to battery
Life is predicted;
As shown in Figure 1, 2, the method for the Fitting Calculation, specifically includes following steps:
(1) it is fitted to obtain linear functional relation formula according to volume change Δ C and corresponding capability retention:Y=
0.002x-0.3349;X represents that volume change Δ C (mAh), y represent capability retention;
(2) it is fitted to obtain linear functional relation formula according to circulating battery number and correspondingly volume change Δ C:y
=-0.1x+667.55, wherein, x represents circulating battery number, and y represents volume change Δ C;
(3) corresponding circulating battery number when battery capacity conservation rate is 80% is calculated.
The present embodiment is by taking battery core model 2.95Ah ternary battery core batteries as an example, initial discharge capacity 2.94Ah;Charging
Volume change Δ C of the voltage range between 3.95-4.15V is 647.3mAh;Loop test condition is with 1C multiplying powers at 25 DEG C
Carrying out cycle charge-discharge experiment, charge and discharge mode is constant-current constant-voltage charging-shelve-constant-current discharge, charge cutoff voltage 4.2V,
Discharge cut-off voltage is 3.0V, and it is 30min to shelve dormancy time, and the test equipment used is the new prestige charge-discharge tests of 5V/10A
Cabinet.Choose 10 with batch battery circulate respectively 10 times, 20 times, 30 times, 40 times, 50 times, 100 times, 200 times, 300 times, 400
It is secondary, 500 times, correspondingly capability retention is recorded, in the charging process for then calculating different cycle-index battery cores respectively
ΔC.In order to which more intuitively the variation relation between explanation cycle-index, capability retention, Δ C, this example test data are summarized as follows
Table 1.
Table 1
Circulating battery number, capability retention, the data of electrolyte retention during 10-50 times according to listed by table 1 circulation,
Can be to these short-term data digital simulations and predicting long-term cycle life.First, using volume change Δ C as X-axis, capacity is kept
Rate is that Y-axis does linear relationship chart, and fits linear relation y=0.002x-0.3349 with software, as shown in figure 1, closing accordingly
Be formula can calculate battery capacity conservation rate for 80% when volume change Δ C=567.45mAh;Secondly, with circulating battery
Number is X-axis, and volume change Δ C is Y-axis, does linear relationship chart, and fit linear relation y=-0.1x+ with software
667.55, as shown in Fig. 2 the electrolyte that previous step is calculated, which possesses rate score 567.45mAh, substitutes into this relation, can calculate
It is 1000 times to obtain corresponding cycle life when battery capacity conservation rate is 80%, as can be seen from Table 1 should in actual test
Cycle-index is 1057 times when batch battery capacity decays to 80%, and relative error is about 5.4%, it is seen that the inventive method is to lithium
Ion battery Cycle life prediction result is more accurate.
The above-mentioned description to embodiment is understood that for ease of those skilled in the art and using this hair
It is bright.Person skilled in the art obviously can easily make various modifications to case study on implementation, and described herein one
As principle be applied in other embodiment without by performing creative labour.Therefore, the invention is not restricted to implementation case here
Example, for those skilled in the art according to the announcement of the present invention, not departing from improvement that scope made and modification all should be
Within protection scope of the present invention.
Claims (4)
1. a kind of method for quick predicting of cycle life of lithium ion battery, it is characterised in that comprise the following steps:
Step 1, the charge-discharge performance test by the different cycle-indexes of battery progress to be evaluated, record filling for different cycle-indexes
Voltage, capacity and the relation curve of time in electric process;
Step 2, calculate under different cycle-indexes according to these curves that voltage increases to from 3.95V in battery charging process
Volume change Δ C in this section of 4.15V;
Step 3, calculating is fitted according to volume change Δ C and cycle-index test data, the cycle life of battery is entered
Row prediction:
1)It is fitted to obtain linear functional relation formula according to volume change Δ C and corresponding capability retention:Y=
0.002x-0.3349;Wherein, x represents volume change Δ C(mAh), y expression capability retentions;
2)It is fitted to obtain linear functional relation formula according to circulating battery number and corresponding volume change Δ C:Y=-
0.1x+667.55, wherein, x represents circulating battery number, and y represents volume change Δ C;
3)Calculate corresponding circulating battery number when battery capacity conservation rate is 80%.
2. the method for quick predicting of cycle life of lithium ion battery according to claim 1, it is characterised in that in step 1,
The cycle-index is 200~500 times, stops the battery after loop test and is in discharge condition.
3. the method for quick predicting of cycle life of lithium ion battery according to claim 1, it is characterised in that in step 1
Charge-discharge performance test in, charging process be constant current 1C charge to 4.2V, turn constant-voltage charge 0.05C cut-off;Constant-current discharge electricity
Flow for 1C.
4. the method for quick predicting of cycle life of lithium ion battery according to claim 1, it is characterised in that in step 2
Volume change Δ C corresponding to charging voltage section be 3.95V to 4.15V.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201710936497.1A CN107728072A (en) | 2017-10-10 | 2017-10-10 | A kind of method for quick predicting of cycle life of lithium ion battery |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201710936497.1A CN107728072A (en) | 2017-10-10 | 2017-10-10 | A kind of method for quick predicting of cycle life of lithium ion battery |
Publications (1)
Publication Number | Publication Date |
---|---|
CN107728072A true CN107728072A (en) | 2018-02-23 |
Family
ID=61210066
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201710936497.1A Pending CN107728072A (en) | 2017-10-10 | 2017-10-10 | A kind of method for quick predicting of cycle life of lithium ion battery |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN107728072A (en) |
Cited By (29)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108445414A (en) * | 2018-04-26 | 2018-08-24 | 合肥国轩高科动力能源有限公司 | A kind of method for rapidly testing of ternary cycle life of lithium ion battery |
CN109116259A (en) * | 2018-10-22 | 2019-01-01 | 中兴高能技术有限责任公司 | Cycle life of lithium ion battery prediction technique, equipment, system and storage medium |
CN109188303A (en) * | 2018-08-13 | 2019-01-11 | 莱茵技术监护(深圳)有限公司 | Fast charge system detection method, equipment and storage medium |
CN109633475A (en) * | 2018-11-30 | 2019-04-16 | 天合光能股份有限公司 | A kind of LiFePO4 energy-type cells life prediction method |
CN109856559A (en) * | 2019-02-28 | 2019-06-07 | 武汉理工大学 | A kind of prediction technique of lithium battery cycle life |
CN110687470A (en) * | 2019-10-03 | 2020-01-14 | 天合光能股份有限公司 | Method and system for on-line prediction of service life of lithium battery in energy storage system |
CN110806544A (en) * | 2018-07-18 | 2020-02-18 | 北汽福田汽车股份有限公司 | Method and device for predicting remaining life of battery |
CN111077457A (en) * | 2019-12-26 | 2020-04-28 | 国网河南省电力公司电力科学研究院 | Method and device for evaluating accelerated attenuation of lithium iron phosphate battery by gradient utilization |
CN111208160A (en) * | 2020-02-20 | 2020-05-29 | 东莞维科电池有限公司 | Method for evaluating cycle performance of ternary material |
CN111448469A (en) * | 2018-03-07 | 2020-07-24 | 株式会社Lg化学 | Apparatus and method for predicting state of health of battery |
CN111707954A (en) * | 2020-06-18 | 2020-09-25 | 中汽研汽车检验中心(天津)有限公司 | Lithium iron phosphate power battery life prediction method |
CN111856298A (en) * | 2020-07-23 | 2020-10-30 | 上海空间电源研究所 | On-orbit residual capacity prediction method for lithium ion storage battery for spacecraft |
CN111896880A (en) * | 2020-09-01 | 2020-11-06 | 湖州快驴科技有限公司 | Method for detecting service life of lithium ion battery for electric vehicle |
CN112034367A (en) * | 2020-11-06 | 2020-12-04 | 瑞浦能源有限公司 | Lithium ion battery capacity prediction method and system |
CN112114260A (en) * | 2020-08-04 | 2020-12-22 | 中汽研汽车检验中心(天津)有限公司 | Method for testing and evaluating overcharge stability of lithium ion battery monomer |
CN112198444A (en) * | 2020-10-10 | 2021-01-08 | 联动天翼新能源有限公司 | Method for predicting cycle life of lithium ion battery based on expansion degree of pole piece |
CN112946505A (en) * | 2019-12-11 | 2021-06-11 | 珠海冠宇电池股份有限公司 | Method for rapidly testing cycle life of lithium ion battery |
CN112946502A (en) * | 2019-12-11 | 2021-06-11 | 珠海冠宇电池股份有限公司 | Method for rapidly testing cycle life of lithium ion battery |
CN112946500A (en) * | 2019-12-11 | 2021-06-11 | 珠海冠宇电池股份有限公司 | Method for rapidly testing cycle life of lithium ion battery |
CN113406506A (en) * | 2021-05-12 | 2021-09-17 | 天能电池集团股份有限公司 | Method for predicting service life of lead storage battery |
CN113495212A (en) * | 2020-03-18 | 2021-10-12 | 北京好风光储能技术有限公司 | Method for estimating maintenance regeneration times and cycle life of maintainable regenerative battery |
CN113655397A (en) * | 2020-05-12 | 2021-11-16 | 北京京东乾石科技有限公司 | Method, device and storage medium for determining full charge and discharge frequency of battery |
CN113702852A (en) * | 2021-09-13 | 2021-11-26 | 合肥国轩高科动力能源有限公司 | Calculation method for direct current internal resistance of lithium ion batteries in same batch |
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 |
CN113884932A (en) * | 2021-10-28 | 2022-01-04 | 广东电网有限责任公司 | Method and device for evaluating service life of battery |
CN114047452A (en) * | 2022-01-13 | 2022-02-15 | 浙江玥视科技有限公司 | Method and device for determining cycle life of battery |
CN114217238A (en) * | 2021-11-24 | 2022-03-22 | 浙江南都电源动力股份有限公司 | Method for predicting cycle life of lithium ion battery |
CN115219902A (en) * | 2022-07-06 | 2022-10-21 | 山东大学 | Method and system for rapidly testing service life of power battery |
CN116754981A (en) * | 2023-08-16 | 2023-09-15 | 宁德新能源科技有限公司 | Battery capacity prediction method and device, electronic equipment and storage medium |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20130166233A1 (en) * | 2011-12-23 | 2013-06-27 | Seung Bum Suh | Device for estimating a lifetime of a secondary battery and method thereof |
CN103344917A (en) * | 2013-06-13 | 2013-10-09 | 北京交通大学 | Lithium battery cycle life quick testing method |
CN103698712A (en) * | 2013-12-20 | 2014-04-02 | 天津力神电池股份有限公司 | Method for predicating cycle life of lithium ion battery |
CN104793144A (en) * | 2015-03-31 | 2015-07-22 | 中国人民解放军92537部队 | Rapid detection method for battery life |
CN105068009A (en) * | 2015-07-14 | 2015-11-18 | 盐城工学院 | Battery cycle life prediction method |
CN106324524A (en) * | 2016-10-11 | 2017-01-11 | 合肥国轩高科动力能源有限公司 | Rapid prediction method of cycle life of lithium-ion battery |
-
2017
- 2017-10-10 CN CN201710936497.1A patent/CN107728072A/en active Pending
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20130166233A1 (en) * | 2011-12-23 | 2013-06-27 | Seung Bum Suh | Device for estimating a lifetime of a secondary battery and method thereof |
CN103344917A (en) * | 2013-06-13 | 2013-10-09 | 北京交通大学 | Lithium battery cycle life quick testing method |
CN103698712A (en) * | 2013-12-20 | 2014-04-02 | 天津力神电池股份有限公司 | Method for predicating cycle life of lithium ion battery |
CN104793144A (en) * | 2015-03-31 | 2015-07-22 | 中国人民解放军92537部队 | Rapid detection method for battery life |
CN105068009A (en) * | 2015-07-14 | 2015-11-18 | 盐城工学院 | Battery cycle life prediction method |
CN106324524A (en) * | 2016-10-11 | 2017-01-11 | 合肥国轩高科动力能源有限公司 | Rapid prediction method of cycle life of lithium-ion battery |
Non-Patent Citations (2)
Title |
---|
孟祥峰等: "动力电池循环寿命预测方法研究", 《电源技术》 * |
谭江等: "湿法球磨制备LiCo1/3Mn1/3Ni1/3O2 材料及表征", 《电源技术》 * |
Cited By (44)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111448469A (en) * | 2018-03-07 | 2020-07-24 | 株式会社Lg化学 | Apparatus and method for predicting state of health of battery |
US11307263B2 (en) | 2018-03-07 | 2022-04-19 | Lg Energy Solution, Ltd. | Device and method for predicting state-of-health of battery |
CN111448469B (en) * | 2018-03-07 | 2022-07-08 | 株式会社Lg新能源 | Apparatus and method for predicting state of health of battery |
CN108445414B (en) * | 2018-04-26 | 2020-12-04 | 合肥国轩高科动力能源有限公司 | Method for rapidly testing cycle life of ternary lithium ion battery |
CN108445414A (en) * | 2018-04-26 | 2018-08-24 | 合肥国轩高科动力能源有限公司 | A kind of method for rapidly testing of ternary cycle life of lithium ion battery |
CN110806544A (en) * | 2018-07-18 | 2020-02-18 | 北汽福田汽车股份有限公司 | Method and device for predicting remaining life of battery |
CN109188303A (en) * | 2018-08-13 | 2019-01-11 | 莱茵技术监护(深圳)有限公司 | Fast charge system detection method, equipment and storage medium |
CN109116259A (en) * | 2018-10-22 | 2019-01-01 | 中兴高能技术有限责任公司 | Cycle life of lithium ion battery prediction technique, equipment, system and storage medium |
CN109116259B (en) * | 2018-10-22 | 2020-07-07 | 中兴高能技术有限责任公司 | Lithium ion battery cycle life prediction method, device, system and storage medium |
CN109633475A (en) * | 2018-11-30 | 2019-04-16 | 天合光能股份有限公司 | A kind of LiFePO4 energy-type cells life prediction method |
CN109856559B (en) * | 2019-02-28 | 2021-10-22 | 武汉理工大学 | Lithium battery cycle life prediction method |
CN109856559A (en) * | 2019-02-28 | 2019-06-07 | 武汉理工大学 | A kind of prediction technique of lithium battery cycle life |
CN110687470A (en) * | 2019-10-03 | 2020-01-14 | 天合光能股份有限公司 | Method and system for on-line prediction of service life of lithium battery in energy storage system |
CN112946500B (en) * | 2019-12-11 | 2023-09-15 | 珠海冠宇电池股份有限公司 | Method for rapidly testing cycle life of lithium ion battery |
CN112946505B (en) * | 2019-12-11 | 2023-03-14 | 珠海冠宇电池股份有限公司 | Method for rapidly testing cycle life of lithium ion battery |
CN112946502B (en) * | 2019-12-11 | 2023-03-14 | 珠海冠宇电池股份有限公司 | Method for rapidly testing cycle life of lithium ion battery |
CN112946505A (en) * | 2019-12-11 | 2021-06-11 | 珠海冠宇电池股份有限公司 | Method for rapidly testing cycle life of lithium ion battery |
CN112946502A (en) * | 2019-12-11 | 2021-06-11 | 珠海冠宇电池股份有限公司 | Method for rapidly testing cycle life of lithium ion battery |
CN112946500A (en) * | 2019-12-11 | 2021-06-11 | 珠海冠宇电池股份有限公司 | Method for rapidly testing cycle life of lithium ion battery |
CN111077457A (en) * | 2019-12-26 | 2020-04-28 | 国网河南省电力公司电力科学研究院 | Method and device for evaluating accelerated attenuation of lithium iron phosphate battery by gradient utilization |
CN111208160A (en) * | 2020-02-20 | 2020-05-29 | 东莞维科电池有限公司 | Method for evaluating cycle performance of ternary material |
CN113495212A (en) * | 2020-03-18 | 2021-10-12 | 北京好风光储能技术有限公司 | Method for estimating maintenance regeneration times and cycle life of maintainable regenerative battery |
CN113655397A (en) * | 2020-05-12 | 2021-11-16 | 北京京东乾石科技有限公司 | Method, device and storage medium for determining full charge and discharge frequency of battery |
CN111707954A (en) * | 2020-06-18 | 2020-09-25 | 中汽研汽车检验中心(天津)有限公司 | Lithium iron phosphate power battery life prediction method |
CN111856298A (en) * | 2020-07-23 | 2020-10-30 | 上海空间电源研究所 | On-orbit residual capacity prediction method for lithium ion storage battery for spacecraft |
CN112114260A (en) * | 2020-08-04 | 2020-12-22 | 中汽研汽车检验中心(天津)有限公司 | Method for testing and evaluating overcharge stability of lithium ion battery monomer |
CN111896880A (en) * | 2020-09-01 | 2020-11-06 | 湖州快驴科技有限公司 | Method for detecting service life of lithium ion battery for electric vehicle |
CN112198444B (en) * | 2020-10-10 | 2022-07-26 | 联动天翼新能源有限公司 | Method for predicting cycle life of lithium ion battery based on expansion degree of pole piece |
CN112198444A (en) * | 2020-10-10 | 2021-01-08 | 联动天翼新能源有限公司 | Method for predicting cycle life of lithium ion battery based on expansion degree of pole piece |
CN112034367B (en) * | 2020-11-06 | 2021-01-15 | 瑞浦能源有限公司 | Lithium ion battery capacity prediction method and system |
CN112034367A (en) * | 2020-11-06 | 2020-12-04 | 瑞浦能源有限公司 | Lithium ion battery capacity prediction method and system |
CN113406506A (en) * | 2021-05-12 | 2021-09-17 | 天能电池集团股份有限公司 | Method for predicting service life of lead storage battery |
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 |
CN113702852B (en) * | 2021-09-13 | 2023-10-10 | 合肥国轩高科动力能源有限公司 | Calculation method of direct current internal resistance of lithium ion batteries in same batch |
CN113702852A (en) * | 2021-09-13 | 2021-11-26 | 合肥国轩高科动力能源有限公司 | Calculation method for direct current internal resistance of lithium ion batteries in same batch |
CN113884932B (en) * | 2021-10-28 | 2024-04-09 | 广东电网有限责任公司 | Method and device for evaluating service life of battery |
CN113884932A (en) * | 2021-10-28 | 2022-01-04 | 广东电网有限责任公司 | Method and device for evaluating service life of battery |
CN114217238A (en) * | 2021-11-24 | 2022-03-22 | 浙江南都电源动力股份有限公司 | Method for predicting cycle life of lithium ion battery |
CN114047452A (en) * | 2022-01-13 | 2022-02-15 | 浙江玥视科技有限公司 | Method and device for determining cycle life of battery |
CN114047452B (en) * | 2022-01-13 | 2022-05-13 | 浙江玥视科技有限公司 | Method and device for determining cycle life of battery |
CN115219902A (en) * | 2022-07-06 | 2022-10-21 | 山东大学 | Method and system for rapidly testing service life of power battery |
CN116754981A (en) * | 2023-08-16 | 2023-09-15 | 宁德新能源科技有限公司 | Battery capacity prediction method and device, electronic equipment and storage medium |
CN116754981B (en) * | 2023-08-16 | 2024-01-19 | 宁德新能源科技有限公司 | Battery capacity prediction method and device, electronic equipment and storage medium |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN107728072A (en) | A kind of method for quick predicting of cycle life of lithium ion battery | |
Zheng et al. | A novel capacity estimation method for lithium-ion batteries using fusion estimation of charging curve sections and discrete Arrhenius aging model | |
CN109856559B (en) | Lithium battery cycle life prediction method | |
CN106291372B (en) | A kind of new lithium-ion-power cell method for predicting residual useful life | |
CN106324524B (en) | Method for rapidly predicting cycle life of lithium ion battery | |
CN110031770B (en) | Method for rapidly obtaining capacity of all single batteries in battery pack | |
CN110161425B (en) | Method for predicting remaining service life based on lithium battery degradation stage division | |
CN107271913B (en) | A method of it is predicted applied to power battery residual capacity | |
CN108919129A (en) | When a kind of under variable working condition power battery life-span prediction method | |
CN103698712B (en) | A kind of method of predicting cycle life of lithium ion battery | |
CN106055775B (en) | A kind of service life of secondary cell prediction technique that particle filter is combined with mechanism model | |
CN112198444B (en) | Method for predicting cycle life of lithium ion battery based on expansion degree of pole piece | |
CN109856542B (en) | Calibration method of lithium battery SOC-OCV curve cluster, SOC correction method and device | |
CN106772064A (en) | A kind of health state of lithium ion battery Forecasting Methodology and device | |
CN105866700B (en) | A kind of method that lithium ion battery quickly screens | |
CN105634063B (en) | A kind of active equalization method based on battery history data | |
CN103091639A (en) | Battery service life detecting method and detecting device | |
CN105353316B (en) | SOC variable quantities and charge capacity conversion factor measuring method during power battery charging | |
CN109782190A (en) | Method for estimating the remaining life of single battery or single batch of battery | |
CN109061478A (en) | A method of it is tested using EIS and carries out lithium ion battery service life qualitative forecasting | |
CN103424712A (en) | Method for measuring residual capacity of battery in online manner on basis of particle swarm optimization | |
Jiang et al. | An aging-aware soc estimation method for lithium-ion batteries using xgboost algorithm | |
CN108732499A (en) | A kind of method and system of detection cycle life of lithium ion battery | |
CN106707179A (en) | Method and device for predicting capacity of battery | |
CN110221210A (en) | A kind of cycle life of lithium ion battery method for quick predicting |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
RJ01 | Rejection of invention patent application after publication |
Application publication date: 20180223 |
|
RJ01 | Rejection of invention patent application after publication |