CN109946613A - The internal resistance On-line Estimation and life detecting method of Vehicular dynamic battery - Google Patents
The internal resistance On-line Estimation and life detecting method of Vehicular dynamic battery Download PDFInfo
- Publication number
- CN109946613A CN109946613A CN201910274490.7A CN201910274490A CN109946613A CN 109946613 A CN109946613 A CN 109946613A CN 201910274490 A CN201910274490 A CN 201910274490A CN 109946613 A CN109946613 A CN 109946613A
- Authority
- CN
- China
- Prior art keywords
- jump
- current
- voltage
- battery
- vehicular dynamic
- 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
Landscapes
- Secondary Cells (AREA)
Abstract
The present invention provides the internal resistance On-line Estimations and life detecting method of a kind of Vehicular dynamic battery, include the following steps: step S1, and acquisition obtains the battery parameter data of Vehicular dynamic battery；Step S2 carries out data cleansing to battery parameter data and obtains voltage and current data；Step S3 is screened to obtain the period that Vehicular dynamic battery is in multistage constant-current charge state to voltage and current data；Step S4 finds electric current and meets the two neighboring stage of scheduled charging current condition as micro- section of current-jump；Step S5 extracts two electric currents before and after obtaining the jump in micro- section of current-jump respectively as electric current after electric current before jumping and jump, jumps two voltages of front and back respectively as voltage after voltage before jumping and jump；Step S6 is calculated electric current before jumping and reacts the life situations of Vehicular dynamic battery relative to ratio of the voltage relative to the difference of voltage after jump before the difference and jump of electric current after jump, and using the ratio as the internal resistance of Vehicular dynamic battery.
Description
Technical field
The invention belongs to technical field of battery management, and in particular to a kind of internal resistance On-line Estimation of Vehicular dynamic battery and longevity
Order detection method.
Background technique
With the continuous improvement of China's new-energy automobile sales volume, new-energy automobile development strategy already rises to national war
Slightly.China's new-energy automobile volume of production and marketing is at 1,000,000 or so within 2018, it is contemplated that arrives the year two thousand twenty, pure electric automobile and plug-in mixed
Close power vehicle production capacity up to 2,000,000, accumulative volume of production and marketing be more than 5,000,000, therefore the raising certainty of electric car sales volume
Drive the batch production of Vehicular dynamic battery.And the power battery in electric car use process, as its energy part
It can be a big influence index of electric automobile whole power performance.
The batteries such as temperature, humidity, use intensity, habit are not in power battery material, manufacturing process and use environment
Consistency will become the main shadow for influencing vehicle course continuation mileage or even service life from the use of new energy vehicle at the beginning
The factor of sound.It is grasped different from the rule of traditional more than 100 years mechanical deteriorations of vehicle and huge data supports that power battery is
It is extremely complex into the deterioration rule for using link later, the detection of the performance after power battery use, assessment there is no at present
Effective technological means.According to the goal-setting currently to guarantee in power battery 6 years or so, without the power electric of plant maintenance
Pond is using 6 years or so, can be retired in batches, is to arrangement New Energy Industry to efficiency and ability that the echelon of battery utilizes
Eco-power inspection.And it is current, echelon utilizes the detection for determining quick economy in other words in link to the state of battery
And grouping and a problem.Therefore, the research of the quick consistency sorting processing method of power battery for battery maintenance,
Life prediction, raising sorting economy are of great significance.
There is two kinds of potential solutions in Vehicles Collected from Market to handle the grouping of power battery conformity classification and service life
The problem of estimation:
1) it is based on BMS online data
Method based on the processing of BMS online data specifically: directly logical by Original Engineering Manufacturing quotient or battery pack enterprise
The charge and discharge electrographic recording for crossing BMS provides battery PACK, the state of mould group or battery core, voltage, electric current, SOC etc..The disadvantage is that nothing
Method carries out total evaluation and life prediction to PACK.
2) processing method based on offline big data
It is the big data algorithm based on car networking data, solves battery using this big data method mostly currently on the market
Life prediction evaluates and tests problem, it is characterised in that utilizes the data in a large amount of historical data analysis long period scales.Its disadvantage exists
In: lack fuel cell modelling, data dynamic is longer, it can only carry out steady-state analysis, precision relative mistake, and to data mass-sensitive.
All there is its limitation in the predictor method of above two market potential life-span, fast speed and high economy and deposit one
The sorting of cause property is solved with life prediction problems demand.
Summary of the invention
To solve the above problems, the object of the present invention is to provide a kind of internal resistance On-line Estimation of Vehicular dynamic battery and service life
Detection method can calculate the internal resistance of Vehicular dynamic battery using the current-jump of charge period, reflect power train in vehicle application electricity with this
The life situations in pond.
Present invention employs following technical solutions:
The present invention provides the internal resistance On-line Estimations and life detecting method of a kind of Vehicular dynamic battery, which is characterized in that
Include the following steps: step S1, what acquisition obtained Vehicular dynamic battery includes the battery parameter data of voltage and current；Step
S2 carries out data cleansing to battery parameter data and obtains voltage and current data；Step S3 screen to voltage and current data
The period of multistage constant-current charge state is in Vehicular dynamic battery；Step S4 finds electric current and meets scheduled charging current
The two neighboring stage of condition is as micro- section of current-jump；Step S5, extraction obtain before and after the jump in micro- section of current-jump
Two electric currents extract two voltages point before and after obtaining the jump in micro- section respectively as electric current after electric current before jumping and jump
Voltage and voltage after jump before Zuo Wei not jumping；Difference of the electric current relative to electric current after jump before jump is calculated in step S6
With jump before ratio of the voltage relative to the difference of voltage after jump, and using the ratio as the internal resistance of Vehicular dynamic battery, and
The life situations of Vehicular dynamic battery are reacted by the internal resistance.
The internal resistance On-line Estimation and life detecting method of Vehicular dynamic battery provided by the invention can also have such
Feature: where multistage constant-current charge state is to keep electric current constant simultaneously within each stage when Vehicular dynamic battery charging
In the different stages with the state of different electric currents.
The internal resistance On-line Estimation and life detecting method of Vehicular dynamic battery provided by the invention can also have such
Feature: where screening cleaning is carried out to battery parameter data according to Python algorithm in step s 2, parameter number after being cleaned
According to supplemental characteristic includes time and corresponding electric current and voltage after cleaning.
The internal resistance On-line Estimation and life detecting method of Vehicular dynamic battery provided by the invention can also have such
Feature: where in step s3, be in multistage constant-current charge for battery is filtered out in supplemental characteristic importing MATLAB after cleaning
The period of state.
The internal resistance On-line Estimation and life detecting method of Vehicular dynamic battery provided by the invention can also have such
Feature: where scheduled charging current condition are as follows:
IK< -75A
- 60A < IK+1< -30A
IKFor k-th of stage corresponding electric current, IK+1For+1 stage of kth corresponding electric current.
The internal resistance On-line Estimation and life detecting method of Vehicular dynamic battery provided by the invention can also have such
Feature: where in step S1, acquired by battery management system platform and obtain battery parameter data.
The action and effect of invention
The internal resistance On-line Estimation and life detecting method of the Vehicular dynamic battery provided according to the present invention, because utilizing battery
Management system acquisition includes the battery parameter data of voltage and current, then carries out data cleansing to battery parameter data and gone through
History and real-time voltage and current data, then to voltage and current data carry out screening obtain multistage constant-current charge state when
Section, and find electric current in the period and meet the two neighboring stage of scheduled charging current condition as the micro- of current-jump
Section, so as to, come the internal resistance for estimating battery, be easy to implement, comment the detection of battery using the voltage and current jump in this micro- section
Rapidly and efficiently, economy is high for valence.
Moreover, battery is in use, internal resistance can become larger, the service life can also decay, therefore can reflect electricity by internal resistance
The life situations in pond provide the method for high-efficiency and economic with assessment to detect to battery life.
Detailed description of the invention
Fig. 1 is the flow chart of the internal resistance On-line Estimation and life detecting method of Vehicular dynamic battery in the embodiment of the present invention；
Fig. 2 is the schematic diagram for importing the charge period generated in MATLAB in the embodiment of the present invention after data cleansing；And
Fig. 3 is the schematic diagram of the voltage and current jump in constant-current charge period multistage of the embodiment of the present invention.
Specific embodiment
It is real below in order to be easy to understand the technical means, the creative features, the aims and the efficiencies achieved by the present invention
Example combination attached drawing is applied to be specifically addressed the present invention.
Fig. 1 is the flow chart of the internal resistance On-line Estimation and life detecting method of Vehicular dynamic battery in the embodiment of the present invention.
As shown in Figure 1, the internal resistance On-line Estimation of the Vehicular dynamic battery in the present embodiment and life detecting method core are former
Reason is that big data is handled with voltage and current jump when being charged using Vehicular dynamic battery to estimate ohmic internal resistance, reacts electricity with this
Pond life situations.Data are obtained first with BMS platform, the electric current electricity of Vehicular dynamic battery is extracted by big data processing method
History and the real time datas such as pressure, and then Current Voltage real-time curve is generated by MATLAB and is analyzed, it is taken by data screening
Effective charge period out, and then ohmic internal resistance is estimated using voltage and current jump, it is automobile-used so as to reflect and detect
The life situations of power battery.Specifically, the internal resistance On-line Estimation of the Vehicular dynamic battery includes following with life detecting method
Step:
Step S1 is acquired in historical time section or in real time automobile-used using the BMS battery management system of Vehicular dynamic battery
The battery parameter data of power battery obtains the battery parameter data by car networking platform.Wherein, battery parameter data includes
Electric current, temperature, the time, sensor states parameter, charging reaction value, further includes many meaningless return values at voltage.
Step S2 rejects a large amount of hashes (such as null value, duplicate number using Python algorithm to battery parameter data
According to, messy code and data of dislocation etc.), it obtains needed for internal resistance of cell estimation comprising voltage, electric current, temperature and the electricity of time
Piezoelectricity flow data.
Voltage and current data are imported and generate Current Voltage real-time curve in MATLAB by step S3, and screening obtains automobile-used dynamic
Power battery is in the period of multistage constant-current charge state.
Fig. 2 is the schematic diagram for importing the charge period generated in MATLAB in the embodiment of the present invention after data cleansing.
As shown in Fig. 2, electricity consumption galvanic electricity pressure real-time curve carries out current integration method and obtains the change of battery dump energy at any time
Change curve, curve descending branch indicates that remaining capacity reduces in figure, as the electric discharge period；The curve ascent stage indicates that remaining capacity increases
Add, i.e., required charge period.
Step S4 finds electric current and meets the two neighboring stage of scheduled charging current condition as the micro- of current-jump
Section.Wherein, scheduled charging current condition are as follows:
IK< -- 75A
- 60A < IK+1< -30A
IKFor the corresponding electric current of k-th of stage (before jumping), IK+1For the corresponding electricity of+1 stage (after jumping) of kth
Stream.
Fig. 3 is the schematic diagram of the voltage and current jump in constant-current charge period multistage of the embodiment of the present invention.
As shown in figure 3, IK=-125A, IK+1=-42A.Remaining capacity (SOC) in micro- section of Vehicular dynamic battery is about
It is 50%, internal resistance at this time can represent the average level of the internal resistance of cell substantially.
Step S5 extracts two electric currents before and after obtaining the jump in micro- section respectively as electricity after electric current before jumping and jump
Stream, and two voltages before and after obtaining the jump in micro- section are extracted respectively as voltage after voltage before jumping and jump.
As shown in figure 3, voltage is denoted as U before jumpingA, electric current is denoted as I before jumpingA；Voltage is denoted as UB after jump, after jump
Electric current is denoted as IB, then IA=-125A, IB=-42A, UA=4.05V, UB=3.97V.
Step S6 is calculated and jumps preceding electric current relative to the difference of electric current after jump and jump preceding voltage relative to jump
The ratio of the difference of voltage afterwards, and using the ratio as the internal resistance r of Vehicular dynamic battery.The calculation formula of internal resistance r sees below formula
(1):
The internal resistance r being calculated is battery in the current-jump moment corresponding internal resistance predicted value, resistance value here
The average level of the internal resistance of cell can be represented substantially.In use, internal resistance can become larger, the service life can also decay battery, therefore can be with
The life situations of battery at this moment are predicted according to the resistance value.
The action and effect of embodiment
According to the internal resistance On-line Estimation and life detecting method of Vehicular dynamic battery provided in this embodiment, because utilizing electricity
Management system acquisition in pond includes the battery parameter data of voltage and current, then carries out data cleansing to battery parameter data and obtain
History and real-time voltage and current data, then to voltage and current data carry out screening obtain multistage constant-current charge state when
Section, and find electric current in the period and meet the two neighboring stage of scheduled charging current condition as the micro- of current-jump
Section, so as to, come the internal resistance for estimating battery, be easy to implement, comment the detection of battery using the voltage and current jump in this micro- section
Rapidly and efficiently, economy is high for valence.
Moreover, battery is in use, internal resistance can become larger, the service life can also decay, therefore can be reflected by the internal resistance of cell
The life situations of battery out provide the method for high-efficiency and economic with assessment to detect to battery life.
In addition, being rejected because obtaining battery parameter data by the acquisition of battery management system platform using Python algorithm
A large amount of hashes combine the online data facture based on BMS with the processing method based on offline big data, sufficiently send out
The advantage for having waved different detection modes improves the internal resistance estimated efficiency of Vehicular dynamic battery.
In addition, a large amount of historical datas can be collected by battery management system platform, it can also be online to automobile-used
Power electric is assessed in real time.
Above-described embodiment is only used for the specific embodiment illustrated the present invention, but the present invention is not limited to the above embodiments
Described range, those of ordinary skill in the art do not need what creative work can be made within the scope of the appended claims
Various deformations or amendments still belong to the protection scope of this patent.
Claims (6)
1. the internal resistance On-line Estimation and life detecting method of a kind of Vehicular dynamic battery, which comprises the steps of:
Step S1, what acquisition obtained the Vehicular dynamic battery includes the battery parameter data of voltage and current；
Step S2 carries out data cleansing to the battery parameter data and obtains voltage and current data；
The voltage and current data are screened to obtain the Vehicular dynamic battery and are in multistage constant-current charge shape by step S3
The period of state；
Step S4, find the electric current meet scheduled charging current condition the two neighboring stage it is micro- as current-jump
Section；
Step S5 extracts two electric currents before and after obtaining the jump in micro- section of the current-jump respectively as electricity before jump
Electric current after stream and jump, and two voltages before and after obtaining the jump in described micro- section are extracted respectively as voltage before jumping
With voltage after jump；
Difference of the electric current relative to electric current after the jump and voltage phase before the jump before the jump is calculated in step S6
For the ratio of the difference of voltage after the jump, and using the ratio as the internal resistance of the Vehicular dynamic battery, and by being somebody's turn to do
The life situations of the Vehicular dynamic battery are reacted in internal resistance.
2. the internal resistance On-line Estimation and life detecting method of Vehicular dynamic battery according to claim 1, it is characterised in that:
Wherein, the multistage constant-current charge state is to keep within each stage when Vehicular dynamic battery charging
The electric current is constant and has the state of different electric currents in the different stages.
3. the internal resistance On-line Estimation and life detecting method of Vehicular dynamic battery according to claim 1, it is characterised in that:
Wherein, screening cleaning is carried out to the battery parameter data according to Python algorithm in the step S2, obtained described
Supplemental characteristic after cleaning, supplemental characteristic includes the time and the corresponding electric current and the voltage after the cleaning.
4. the internal resistance On-line Estimation and life detecting method of Vehicular dynamic battery according to claim 1, it is characterised in that:
Wherein, in the step S3, supplemental characteristic after the cleaning is imported in MATLAB and filters out battery in described more
The period of stage constant-current charge state.
5. the internal resistance On-line Estimation and life detecting method of Vehicular dynamic battery according to claim 1, it is characterised in that:
Wherein, the scheduled charging current condition are as follows:
IK< -75A
- 60A < IK+1< -30A
The IKFor k-th of stage corresponding electric current,
The IK+1For kth+1 stage corresponding electric current.
6. the internal resistance On-line Estimation and life detecting method of Vehicular dynamic battery according to claim 1, it is characterised in that:
Wherein, in the step S1, the battery parameter data is obtained by the acquisition of battery management system platform.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910274490.7A CN109946613A (en) | 2019-04-08 | 2019-04-08 | The internal resistance On-line Estimation and life detecting method of Vehicular dynamic battery |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910274490.7A CN109946613A (en) | 2019-04-08 | 2019-04-08 | The internal resistance On-line Estimation and life detecting method of Vehicular dynamic battery |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109946613A true CN109946613A (en) | 2019-06-28 |
Family
ID=67013920
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910274490.7A Pending CN109946613A (en) | 2019-04-08 | 2019-04-08 | The internal resistance On-line Estimation and life detecting method of Vehicular dynamic battery |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109946613A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112180274A (en) * | 2020-09-28 | 2021-01-05 | 上海理工大学 | Rapid detection and evaluation method for power battery pack |
| CN113093038A (en) * | 2021-03-03 | 2021-07-09 | 同济大学 | Power battery internal resistance composition analysis method based on pulse charge and discharge test |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105759124A (en) * | 2016-04-29 | 2016-07-13 | 赵建和 | Method for on-line detection on internal resistance of power battery |
| CN107187328A (en) * | 2017-05-17 | 2017-09-22 | 宁波普瑞均胜汽车电子有限公司 | Lithium ion battery management system and battery core monomer essential resistance on-line measurement diagnostic method |
| CN107209229A (en) * | 2015-02-09 | 2017-09-26 | 微软技术许可有限责任公司 | Estimate battery unit parameter |
| CN107490770A (en) * | 2017-07-31 | 2017-12-19 | 惠州市蓝微新源技术有限公司 | The internal resistance estimating system and method for a kind of energy-storage system |
| CN107861070A (en) * | 2017-10-25 | 2018-03-30 | 北京交通大学 | A kind of health state of lithium ion battery inline diagnosis method |
| JP2018096803A (en) * | 2016-12-13 | 2018-06-21 | 住友電気工業株式会社 | Internal resistance calculation device, method for calculating internal resistance, and internal resistance calculation program |
| CN108254700A (en) * | 2018-01-29 | 2018-07-06 | 深圳市睿德电子实业有限公司 | Battery DC internal resistance measuring method |
| CN108267696A (en) * | 2018-04-09 | 2018-07-10 | 广东电网有限责任公司 | A kind of accumulator capacity shallow discharge detection device |
| CN108336427A (en) * | 2017-01-18 | 2018-07-27 | 三星电子株式会社 | battery management method and device |
| CN108663634A (en) * | 2018-07-10 | 2018-10-16 | 深圳市科列技术股份有限公司 | A kind of determination method and apparatus of power battery internal resistance |
| CN108982969A (en) * | 2017-06-01 | 2018-12-11 | 重庆无线绿洲通信技术有限公司 | A kind of Vehicular battery internal resistance measurement method and device |
| US20190081501A1 (en) * | 2017-09-11 | 2019-03-14 | Toyota Jidosha Kabushiki Kaisha | Battery output monitoring device and battery output monitoring method |
-
2019
- 2019-04-08 CN CN201910274490.7A patent/CN109946613A/en active Pending
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107209229A (en) * | 2015-02-09 | 2017-09-26 | 微软技术许可有限责任公司 | Estimate battery unit parameter |
| CN105759124A (en) * | 2016-04-29 | 2016-07-13 | 赵建和 | Method for on-line detection on internal resistance of power battery |
| JP2018096803A (en) * | 2016-12-13 | 2018-06-21 | 住友電気工業株式会社 | Internal resistance calculation device, method for calculating internal resistance, and internal resistance calculation program |
| CN108336427A (en) * | 2017-01-18 | 2018-07-27 | 三星电子株式会社 | battery management method and device |
| CN107187328A (en) * | 2017-05-17 | 2017-09-22 | 宁波普瑞均胜汽车电子有限公司 | Lithium ion battery management system and battery core monomer essential resistance on-line measurement diagnostic method |
| CN108982969A (en) * | 2017-06-01 | 2018-12-11 | 重庆无线绿洲通信技术有限公司 | A kind of Vehicular battery internal resistance measurement method and device |
| CN107490770A (en) * | 2017-07-31 | 2017-12-19 | 惠州市蓝微新源技术有限公司 | The internal resistance estimating system and method for a kind of energy-storage system |
| US20190081501A1 (en) * | 2017-09-11 | 2019-03-14 | Toyota Jidosha Kabushiki Kaisha | Battery output monitoring device and battery output monitoring method |
| CN107861070A (en) * | 2017-10-25 | 2018-03-30 | 北京交通大学 | A kind of health state of lithium ion battery inline diagnosis method |
| CN108254700A (en) * | 2018-01-29 | 2018-07-06 | 深圳市睿德电子实业有限公司 | Battery DC internal resistance measuring method |
| CN108267696A (en) * | 2018-04-09 | 2018-07-10 | 广东电网有限责任公司 | A kind of accumulator capacity shallow discharge detection device |
| CN108663634A (en) * | 2018-07-10 | 2018-10-16 | 深圳市科列技术股份有限公司 | A kind of determination method and apparatus of power battery internal resistance |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112180274A (en) * | 2020-09-28 | 2021-01-05 | 上海理工大学 | Rapid detection and evaluation method for power battery pack |
| CN112180274B (en) * | 2020-09-28 | 2023-06-27 | 上海理工大学 | Rapid detection and evaluation method for power battery pack |
| CN113093038A (en) * | 2021-03-03 | 2021-07-09 | 同济大学 | Power battery internal resistance composition analysis method based on pulse charge and discharge test |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Lai et al. | Sorting, regrouping, and echelon utilization of the large-scale retired lithium batteries: A critical review | |
| Song et al. | Intelligent state of health estimation for lithium-ion battery pack based on big data analysis | |
| Hong et al. | Online accurate state of health estimation for battery systems on real-world electric vehicles with variable driving conditions considered | |
| Guo et al. | Lithium-ion battery operation, degradation, and aging mechanism in electric vehicles: An overview | |
| CN109655754B (en) | Battery performance evaluation method based on multi-dimensional grading of charging process | |
| CN106443475A (en) | Retired power battery dismounting-free reuse screening method based on operation big data | |
| CN109932663A (en) | Cell health state appraisal procedure, device, storage medium and electronic device | |
| CN113064939B (en) | New energy vehicle three-electric system safety feature database construction method | |
| CN112904219B (en) | Big data-based power battery health state prediction method | |
| CN106371027A (en) | Testing method for echelon recycling and utilization of decommissioning batteries | |
| CN116626505B (en) | Battery pack consistency anomaly detection method based on Internet of vehicles big data | |
| CN113176511A (en) | Energy storage charging and discharging optimization method and system considering health state | |
| CN109946613A (en) | The internal resistance On-line Estimation and life detecting method of Vehicular dynamic battery | |
| CN106959422B (en) | A kind of detection method of battery life time early warning device | |
| CN116572799B (en) | Power battery charge duration prediction method, system and terminal based on deep learning | |
| CN115219913A (en) | Power battery full-life-cycle management system based on capacity increment method | |
| CN114646888A (en) | Assessment method and system for capacity attenuation of power battery | |
| CN110297185A (en) | A kind of new energy car battery dynamic state of parameters monitoring system | |
| CN113505932A (en) | Power battery capacity algorithm based on big data technology evaluation | |
| CN114036647A (en) | Power battery safety risk assessment method based on real vehicle data | |
| CN117665620A (en) | New energy automobile data-based battery health evaluation method | |
| CN111239607A (en) | Big data extraction and calculation method for imbalance degree of system capacity of lithium iron phosphate battery | |
| CN115656831A (en) | Multi-step advanced prediction and fault diagnosis method for single battery voltage | |
| Li et al. | SOH Estimation of Power Battery Based on the Real Vehicle Multi-feature and LightGBM Algorithm | |
| CN115389948B (en) | Method for establishing health state evaluation model of power battery of battery replacement station |
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 | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20190628 |
|
| WD01 | Invention patent application deemed withdrawn after publication |