CN105334465B - A kind of health state of lithium ion battery evaluation method - Google Patents
A kind of health state of lithium ion battery evaluation method Download PDFInfo
- Publication number
- CN105334465B CN105334465B CN201510584670.7A CN201510584670A CN105334465B CN 105334465 B CN105334465 B CN 105334465B CN 201510584670 A CN201510584670 A CN 201510584670A CN 105334465 B CN105334465 B CN 105334465B
- Authority
- CN
- China
- Prior art keywords
- battery
- internal resistance
- health state
- value
- estimation
- 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.)
- Active
Links
Abstract
The present invention protects a kind of health state of lithium ion battery estimation on line method, uses the Recursive Least-square based on battery equivalent circuit model, and on-line identification characterizes the important parameter of cell health state and battery operation state: battery ohmic internal resistance.There is close contact with battery pack temperature, current ratio, battery charge state in view of battery ohmic internal resistance simultaneously, the method for introducing prefixed time interval screening internal resistance, and establish the relationship between the mean value internal resistance of screening and health status SOH, accurately reflect battery current health state with battery inner resistance, further promotes the safe handling of lithium ion battery.
Description
Technical field
The present invention relates to the technical field of lithium ion of new-energy automobile, more specifically to a kind of lithium-ion electric
Pond health status estimation on line method.
Background technique
Electric car has the advantages that low noise, almost zero-emission, comprehensive energy utilization etc. are prominent, is current solution energy
The important channel of the problems such as source, environmental protection, undoubtedly becomes the developing direction in auto industry future.As lithium ion battery is in new energy
Extensive use on automobile, cell health state (State of Health, SOH) is more and more by industry and science
The concern on boundary.
The internal resistance of battery is mostly important one of the characterisitic parameter of battery, it is characterization cell health state and battery fortune
The important parameter of row state is the outstanding feature that measurement electronics and ion transmit complexity in electrode.Accurate detection battery
Internal resistance is also the objective requirement of battery management and practical application.However, for the nonlinearity system as the battery, electricity
Pond internal resistance can not directly obtain, and cannot achieve on-line measurement.Meanwhile the internal resistance of cell and battery pack temperature, current ratio, battery
State-of-charge (State of Charge, SOC) has close connection, measures cell health state SOH with internal resistance, the two
Relationship is simultaneously non-linear, increases the difficulty for establishing relationship between the internal resistance of cell and health status.
Summary of the invention
In view of this, the present invention proposes a kind of health state of lithium ion battery estimation on line method, establish the internal resistance of cell with
The corresponding relationship of health status accurately reflects battery current health state by internal resistance of cell characteristic, further promote lithium from
The safe handling of sub- battery.
In order to solve the above technical problems, The technical solution adopted by the invention is as follows:
A kind of health state of lithium ion battery estimation on line method, comprising the following steps:
(1) characteristic ginseng value of on-line identification battery；
(2) internal resistance of cell is screened online with prefixed time interval；
(3) filtering internal resistance is solved；Mean value is taken to screening internal resistance, gliding smoothing filtering is carried out to mean value internal resistance, it finally will filter
Wave internal resistance carries out cell health state estimation；
Cell health state=100%- (current internal resistance value-service life initial internal resistance value)/(end-of-life internal resistance value-longevity
Order initial internal resistance value) * 100%.
The characteristic ginseng value of the on-line identification battery specifically: on-line identification algorithm, which uses, is based on battery equivalent circuit mould
The characteristic parameter of the Recursive Least-square of type, battery equivalent circuit model has: Voc open-circuit voltage, R0 ohmic internal resistance,
Rp polarization resistance, Cp polarization capacity；The Recursive Least-square of the battery model is established, algorithm can recognize battery characteristics
Parameter identification value.The present invention establishes the relationship of ohmic internal resistance and cell health state, i.e., what following internal resistances of cell considered is
Ohmic internal resistance value.
It is described that the internal resistance of cell is screened online with specified time interval specifically: the prefixed time interval of use makes with battery
Reduced with the increase of time.Fixed current multiplying power section [I1,I2], battery charge state section [SOC1,SOC2] and battery pack
Temperature range [T1,T2], wherein [T1,T2]、[I1,I2]、[SOC1,SOC2] it is algorithm preset value.Only current flow multiplying power, lotus
When electricity condition, battery pack temperature are in respectively in above-mentioned 3 fixed intervals, the internal resistance value of identification is subjected to screening in case subsequent estimate
Cell health state is calculated to use.
In addition consider that four seasons environment temperature, battery pack are influenced using factors such as the rising of rear temperature, battery pack heat managements, if any
Necessity, battery pack temperature range may be selected two groups or three groups, enhance SOH algorithm adaptability.
It can be seen from the above technical scheme that characteristic ginseng value of the method for the present invention by on-line identification battery, and with
Specified time interval screens the internal resistance of cell online, solves filtering internal resistance, final to establish filtering internal resistance and health status relationship, passes through
Internal resistance of cell characteristic accurately reflects battery current health state, further promotes the safe handling of lithium ion battery.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, the prior art will be retouched below
Attached drawing needed in stating is briefly described.
Fig. 1 is the battery equivalent circuit diagram that the present invention applies；
Fig. 2 is the flow chart of health state of lithium ion battery estimation on line method disclosed by the embodiments of the present invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiment is only a part of the embodiments of the present invention, instead of all the embodiments.Base
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts it is all its
His embodiment, shall fall within the protection scope of the present invention.
Health state of lithium ion battery estimation on line method disclosed by the embodiments of the present invention establishes the internal resistance of cell and healthy shape
The corresponding relationship of state accurately reflects battery current health state by internal resistance of cell characteristic, further promotes lithium ion battery
Safe handling.
As shown in Fig. 2, health state of lithium ion battery estimation on line method the following steps are included:
The characteristic ginseng value of S1, on-line identification battery；
Specifically, on-line identification algorithm uses the Recursive Least-square based on battery equivalent circuit model, electricity
Pool model is as shown in Figure 1, battery model characteristic parameter: Voc is open-circuit voltage, R0 is ohmic internal resistance, and Rp is polarization resistance, and Cp is
Polarization capacity；The Recursive Least-square of the battery model is established, algorithm can recognize battery characteristics parameter identification value.
S2, prefixed time interval screen the internal resistance of cell online；
Specifically, the prefixed time interval used reduces with the increase of service time of battery, as shown in table 1.It is fixed
Current ratio section [I1,I2], battery charge state section [SOC1,SOC2] and battery pack temperature range [T1,T2], wherein [T1,
T2]、[I1,I2]、[SOC1,SOC2] it is algorithm preset value.Only current flow multiplying power, state-of-charge, battery pack temperature are located respectively
When in above-mentioned 3 fixed intervals, only current flow multiplying power ∈ [I1,I2], state-of-charge ∈ [SOC1,SOC2], battery pack temperature
Spend ∈ [T1,T2], the internal resistance value of identification could be screened.
Further, it is also contemplated that four seasons environment temperature, battery pack use the factors such as the rising of rear temperature, battery pack heat management
It influences, two groups or three groups is selected to battery pack temperature range, SOH algorithm adaptability can be enhanced in this way.
S3, filtering internal resistance is solved；
Specifically, the internal resistance of cell value to screening takes mean value, as Rave, to RaveCarry out gliding smoothing filtering, estimation electricity
Pond health status.Gliding smoothing filtering is as follows:
Rave1、Rave2、Rave3Take mean value as Rave1', Rave1' again with Rave2、Rave3Taking mean value is Rave2', Rave2' again with
Rave3、Rave4Taking mean value is Rave3' and so on.
Filtering internal resistance is finally subjected to cell health state estimation.
S4, filtering internal resistance and health status relationship, estimation on line cell health state are established；
Specifically, cell health state=100%- (current internal resistance value-service life initial internal resistance value)/(in end-of-life
Resistance value-service life initial internal resistance value) * 100%.
Selected parameter specifically: life performance is carried out to battery and is known the real situation, service life initial internal resistance value and longevity are obtained by test
Life terminates internal resistance value.
In the above-described embodiments, the present invention uses the Recursive Least-square based on battery equivalent circuit model,
The important parameter of on-line identification characterization cell health state and battery operation state: battery ohmic internal resistance.Battery is considered simultaneously
Ohmic internal resistance and battery pack temperature, current ratio, battery charge state have it is close contact, introduce specified time interval screening
The method of internal resistance, and the relationship between the mean value internal resistance of screening and health status SOH is established, it is accurately anti-with battery inner resistance
Battery current health state is reflected, the safe handling of lithium ion battery is further promoted.
Each embodiment in this specification is described in a progressive manner, the highlights of each of the examples are with other
The difference of embodiment, the same or similar parts in each embodiment may refer to each other.
The foregoing description of the disclosed embodiments enables those skilled in the art to implement or use the present invention.
Various modifications to these embodiments will be readily apparent to those skilled in the art, as defined herein
General Principle can be realized in other embodiments without departing from the spirit or scope of the present invention.Therefore, of the invention
It is not intended to be limited to the embodiments shown herein, and is to fit to and the principles and novel features disclosed herein phase one
The widest scope of cause.
Claims (3)
1. a kind of health state of lithium ion battery estimation on line method, comprising the following steps:
(1) characteristic ginseng value of on-line identification battery；
(2) internal resistance of cell is screened online with prefixed time interval；
(3) filtering internal resistance is solved；Mean value is taken to screening internal resistance, gliding smoothing filtering is carried out to mean value internal resistance, it finally will be in filtering
Resistance carries out cell health state estimation；
Cell health state=100%- (current internal resistance value-service life initial internal resistance value)/(end-of-life internal resistance value-is at the beginning of the service life
Beginning internal resistance value) * 100%；
(4) filtering internal resistance and health status relationship, estimation on line cell health state are established；
It is described that the internal resistance of cell is screened online with prefixed time interval specifically: when the prefixed time interval of use is used with battery
Between increase and reduce, fixed current multiplying power section [I1,I2], battery charge state section [SOC1,SOC2] and battery pack temperature
Section [T1,T2], wherein [T1,T2]、[I1,I2]、[SOC1,SOC2] it is algorithm preset value, only current flow multiplying power, charged shape
When state, battery pack temperature are in respectively in above-mentioned 3 fixed intervals, the internal resistance value of identification is subjected to screening in case subsequent estimation electricity
Pond health status uses.
2. health state of lithium ion battery estimation on line method according to claim 1, which is characterized in that described to distinguish online
Know the characteristic ginseng value of battery specifically: use battery equivalent circuit model, the recursive least-squares for establishing the battery model are distinguished
Know algorithm, battery characteristics parameter identification value is recognized by algorithm.
3. health state of lithium ion battery estimation on line method according to claim 2, which is characterized in that the battery pack
Temperature range selects two groups or three groups.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510584670.7A CN105334465B (en) | 2015-09-15 | 2015-09-15 | A kind of health state of lithium ion battery evaluation method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510584670.7A CN105334465B (en) | 2015-09-15 | 2015-09-15 | A kind of health state of lithium ion battery evaluation method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105334465A CN105334465A (en) | 2016-02-17 |
| CN105334465B true CN105334465B (en) | 2019-03-26 |
Family
ID=55285108
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510584670.7A Active CN105334465B (en) | 2015-09-15 | 2015-09-15 | A kind of health state of lithium ion battery evaluation method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105334465B (en) |
Families Citing this family (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106291380B (en) * | 2016-08-16 | 2019-09-17 | 苏州协鑫集成科技工业应用研究院有限公司 | The appraisal procedure and device of cell degradation |
| CN106896325B (en) * | 2017-01-24 | 2020-08-14 | 广东恒沃动力科技有限公司 | Battery parameter online identification method and system |
| CN107589382A (en) * | 2017-10-25 | 2018-01-16 | 宁夏黑金昊源绿能科技有限公司 | A kind of detection means of battery surplus and health status |
| CN108805217B (en) * | 2018-06-20 | 2020-10-23 | 山东大学 | Lithium ion battery health state estimation method and system based on support vector machine |
| CN109490765A (en) * | 2018-09-21 | 2019-03-19 | 上海电科电器科技有限公司 | Device for switching contact residual Life Calculation method and detection device, contactor |
| KR102629463B1 (en) * | 2019-03-12 | 2024-01-25 | 삼성에스디아이 주식회사 | Method of estimating state of health (SOH) of battery |
| CN112748350A (en) * | 2019-10-29 | 2021-05-04 | 南京德朔实业有限公司 | Battery pack fault judgment method, fault detection system and battery pack |
| CN111751731B (en) * | 2020-07-19 | 2022-09-27 | 东北石油大学 | Method and device for determining battery activity, electronic equipment and storage medium |
| CN111965555B (en) * | 2020-09-18 | 2022-05-03 | 重庆长安新能源汽车科技有限公司 | Parallel connection group screening method for single batteries |
| CN112986834B (en) * | 2021-02-26 | 2023-08-15 | 深蓝汽车科技有限公司 | Battery safety monitoring method and system based on voltage sequencing |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102253343A (en) * | 2011-04-21 | 2011-11-23 | 北京世纪瑞尔技术股份有限公司 | Method for estimating state of health and state of charge of storage battery |
| CN102930173A (en) * | 2012-11-16 | 2013-02-13 | 重庆长安汽车股份有限公司 | SOC(state of charge) online estimation method for lithium ion battery |
| CN103020445A (en) * | 2012-12-10 | 2013-04-03 | 西南交通大学 | SOC (State of Charge) and SOH (State of Health) prediction method of electric vehicle-mounted lithium iron phosphate battery |
| CN103399277A (en) * | 2013-07-29 | 2013-11-20 | 重庆长安汽车股份有限公司 | Power battery actual capacity estimation method |
| CN103558556A (en) * | 2013-10-31 | 2014-02-05 | 重庆长安汽车股份有限公司 | Power battery SOH estimation method |
| CN103698713A (en) * | 2013-12-30 | 2014-04-02 | 长城汽车股份有限公司 | Method for assessing SOH (state of health) of lithium ion battery |
| CN103744030A (en) * | 2014-01-12 | 2014-04-23 | 中国科学院电工研究所 | Device and method for estimating health status and state of charge of battery pack on line |
-
2015
- 2015-09-15 CN CN201510584670.7A patent/CN105334465B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102253343A (en) * | 2011-04-21 | 2011-11-23 | 北京世纪瑞尔技术股份有限公司 | Method for estimating state of health and state of charge of storage battery |
| CN102930173A (en) * | 2012-11-16 | 2013-02-13 | 重庆长安汽车股份有限公司 | SOC(state of charge) online estimation method for lithium ion battery |
| CN103020445A (en) * | 2012-12-10 | 2013-04-03 | 西南交通大学 | SOC (State of Charge) and SOH (State of Health) prediction method of electric vehicle-mounted lithium iron phosphate battery |
| CN103399277A (en) * | 2013-07-29 | 2013-11-20 | 重庆长安汽车股份有限公司 | Power battery actual capacity estimation method |
| CN103558556A (en) * | 2013-10-31 | 2014-02-05 | 重庆长安汽车股份有限公司 | Power battery SOH estimation method |
| CN103698713A (en) * | 2013-12-30 | 2014-04-02 | 长城汽车股份有限公司 | Method for assessing SOH (state of health) of lithium ion battery |
| CN103744030A (en) * | 2014-01-12 | 2014-04-23 | 中国科学院电工研究所 | Device and method for estimating health status and state of charge of battery pack on line |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105334465A (en) | 2016-02-17 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105334465B (en) | A kind of health state of lithium ion battery evaluation method | |
| CN107192914B (en) | Lithium-ion-power cell internal short-circuit detection method | |
| CN103869256B (en) | Method for estimating SOH of power lithium ion battery based on alternating current impedance test | |
| CN109143108B (en) | Lithium ion battery SOH estimation method based on electrochemical impedance spectroscopy | |
| Samadani et al. | Empirical modeling of lithium-ion batteries based on electrochemical impedance spectroscopy tests | |
| CN108919137B (en) | A kind of battery aging status estimation method considering different battery status | |
| Monem et al. | Lithium-ion batteries: Evaluation study of different charging methodologies based on aging process | |
| CN104569835B (en) | A kind of method of the state-of-charge for the electrokinetic cell for estimating electric automobile | |
| CN103399277B (en) | A kind of power battery actual capacity estimation method | |
| Ma et al. | Investigation of path dependence in commercial lithium-ion cells for pure electric bus applications: Aging mechanism identification | |
| US10569660B2 (en) | Systems and methods for battery state-of-health monitoring | |
| CN102930173B (en) | A kind of charge states of lithium ion battery estimation on line method | |
| CN106291378B (en) | A kind of measuring method of electric automobile power battery SOH | |
| CN110395141A (en) | Dynamic lithium battery SOC estimation method based on adaptive Kalman filter method | |
| CN105676138B (en) | A kind of method and system of the remaining capacity of prediction battery | |
| Chang et al. | An improvement of equivalent circuit model for state of health estimation of lithium-ion batteries based on mid-frequency and low-frequency electrochemical impedance spectroscopy | |
| CN107121643A (en) | Health state of lithium ion battery combined estimation method | |
| CN104833921B (en) | The computational methods and computing device of battery bag state-of-charge | |
| CN110795851A (en) | Lithium ion battery modeling method considering environmental temperature influence | |
| CN105044606B (en) | A kind of SOC methods of estimation based on parameter adaptive battery model | |
| CN104345275A (en) | Method for dynamically evaluating battery consistency | |
| CN112526352B (en) | SOH estimation method for retired lithium ion battery | |
| Divakar et al. | Battery management system and control strategy for hybrid and electric vehicle | |
| CN108828448A (en) | Battery charge state estimation on line method based on charging voltage curve fusion Kalman filtering | |
| CN108595729A (en) | A kind of power battery intelligence self-regulation heated current computational methods, battery heating means and battery management system based on BV equations |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| EE01 | Entry into force of recordation of patent licensing contract |
Application publication date: 20160217 Assignee: CHONGQING CHANGAN NEW ENERGY AUTOMOBILE TECHNOLOGY Co.,Ltd. Assignor: Chongqing Changan Automobile Co.,Ltd.|CHONGQING CHANG'AN NEW ENERGY AUTOMOBILE Co.,Ltd. Contract record no.: 2018500000019 Denomination of invention: Method for online evaluating state of health of lithium ion battery License type: Exclusive License Record date: 20181126 |
|
| EE01 | Entry into force of recordation of patent licensing contract | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20190102 Address after: 401133 room 208, 2 house, 39 Yonghe Road, Yu Zui Town, Jiangbei District, Chongqing Applicant after: CHONGQING CHANGAN NEW ENERGY AUTOMOBILE TECHNOLOGY Co.,Ltd. Address before: 400023, No. 260, Jianxin East Road, Jiangbei District, Chongqing Applicant before: Chongqing Changan Automobile Co.,Ltd. Applicant before: CHONGQING CHANG'AN NEW ENERGY AUTOMOBILE Co.,Ltd. |
|
| TA01 | Transfer of patent application right | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CP01 | Change in the name or title of a patent holder |
Address after: 401133 room 208, 2 house, 39 Yonghe Road, Yu Zui Town, Jiangbei District, Chongqing Patentee after: Deep Blue Automotive Technology Co.,Ltd. Address before: 401133 room 208, 2 house, 39 Yonghe Road, Yu Zui Town, Jiangbei District, Chongqing Patentee before: CHONGQING CHANGAN NEW ENERGY AUTOMOBILE TECHNOLOGY Co.,Ltd. |
|
| CP01 | Change in the name or title of a patent holder |