CN109256834A - Battery pack active equalization method based on cell health state and state-of-charge - Google Patents
Battery pack active equalization method based on cell health state and state-of-charge Download PDFInfo
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- CN109256834A CN109256834A CN201811187147.0A CN201811187147A CN109256834A CN 109256834 A CN109256834 A CN 109256834A CN 201811187147 A CN201811187147 A CN 201811187147A CN 109256834 A CN109256834 A CN 109256834A
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- 230000015556 catabolic process Effects 0.000 description 4
- 238000006731 degradation reaction Methods 0.000 description 4
- 239000000178 monomer Substances 0.000 description 4
- 239000004065 semiconductor Substances 0.000 description 4
- 229910052493 LiFePO4 Inorganic materials 0.000 description 3
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Classifications
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/0013—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries acting upon several batteries simultaneously or sequentially
- H02J7/0014—Circuits for equalisation of charge between batteries
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
- H01M10/44—Methods for charging or discharging
- H01M10/441—Methods for charging or discharging for several batteries or cells simultaneously or sequentially
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/34—Parallel operation in networks using both storage and other DC sources, e.g. providing buffering
- H02J7/342—The other DC source being a battery actively interacting with the first one, i.e. battery to battery charging
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/0047—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries with monitoring or indicating devices or circuits
- H02J7/0048—Detection of remaining charge capacity or state of charge [SOC]
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/10—Energy storage using batteries
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/70—Energy storage systems for electromobility, e.g. batteries
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- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Manufacturing & Machinery (AREA)
- Chemical & Material Sciences (AREA)
- Chemical Kinetics & Catalysis (AREA)
- Electrochemistry (AREA)
- General Chemical & Material Sciences (AREA)
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Abstract
本发明公开了一种基于电池健康状态和荷电状态的电池组主动均衡方法，所述方法首先获取电池组中各个单体电池的SOH和SOC，并以各个单体电池的SOH*SOC作为均衡系数，设计能量直接转移型主动均衡电路，将均衡系数作为初始条件输入到主动均衡电路中的均衡电路控制模块，均衡电路控制模块根据预先写入的程序控制电路通路的闭合，形成相应的能量转移通道直至各个单体电池的剩余电量的差异达到设定的阈值。该方法能够有效降低电池组的不一致性对动力电池功率、寿命的负面影响，有利于提升纯电动汽车的动力性，经济性。
The invention discloses an active balancing method for a battery pack based on the state of health and state of charge of the battery. The method first obtains the SOH and SOC of each single cell in the battery pack, and uses the SOH*SOC of each single cell as the balance Coefficient, design an active equalization circuit with direct energy transfer, input the equalization coefficient as an initial condition to the equalization circuit control module in the active equalization circuit, and the equalization circuit control module controls the closing of the circuit path according to the pre-written program to form the corresponding energy transfer channel until the difference in the remaining power of each single cell reaches a set threshold. The method can effectively reduce the negative impact of the inconsistency of the battery pack on the power and life of the power battery, and is beneficial to improving the power and economy of the pure electric vehicle.
Description
Technical field
The present invention relates to battery capacities to estimate field, and in particular to a kind of electricity based on cell health state and state-of-charge
Pond group active equalization method.
Background technique
Due to manufacture and use environment etc., form battery pack capacity, voltage it is inconsistent be objective reality so that
Single battery is unable to synchronous charging/discharging in battery pack, if effective equilibrium cannot be carried out to inconsistency, will affect power battery
Service life and output power, and then lead to being short of power for pure electric automobile, economic performance decline.
Research for battery pack inconsistency equalization methods is broadly divided into two classes, and one kind is will be remaining by series resistance
The passive equilibrium that the high battery capacity of electricity dissipates；It is another kind of, it is the active equalization shifted by energy in internal battery pack.
Either passive balanced or active equalization, requires the real surplus electricity for accurately obtaining battery, and application at present is most
It is the remaining capacity of battery to be indicated with state-of-charge (SOC), but SOC will accurately indicate that the premise of each battery dump energy is false
Actual capacity is identical in use for fixed each single battery, not in view of the change of battery actual capacity caused by cell degradation
Change.Therefore, it is necessary to be introduced into the SOH for reflecting cell degradation into the equilibrium of battery pack, the SOH of battery is the actual capacity of battery
Than upper rated capacity, since the rated capacity of each single battery is identical, it can be used cell health state (SOH) reflection each
The actual capacity of single battery, in conjunction with the state-of-charge of battery, the residue for calculating single battery that can be more accurate is electric
Amount.
Summary of the invention
It is an object of the invention to improve the precision of existing estimation method of battery dump energy, and in such remaining battery
On the basis of electricity estimation method, a kind of battery pack active equalization side based on cell health state and state-of-charge is provided
Method, the method using SOH*SOC as equalizing coefficient (Equal Coefficient) estimate cell degradation after residual capacity, with
The equalizing coefficient of each single battery is as balanced index, so that equalizing coefficient, that is, each battery dump energy difference after equilibrium
The different threshold value for reaching setting overcomes the problem low with SOC estimation battery dump energy precision after cell degradation.
The purpose of the present invention can be achieved through the following technical solutions:
A kind of battery pack active equalization method based on cell health state and state-of-charge, the method obtain electricity first
The SOH and SOC of each single battery in the group of pond, and using the SOH*SOC of each single battery as equalizing coefficient, design energy is straight
Transfevent active equalization circuit is connect, is input to the control of the equalizing circuit in active equalization circuit for equalizing coefficient as primary condition
Module, equalizing circuit control module form corresponding energy transfer according to the closure for the sequence circuit access being previously written
Channel is until the difference of the remaining capacity of each single battery reaches the threshold value of setting.
Further, the SOH acquisition methods of each single battery are as follows: each monomer electricity in real-time monitoring battery pack
Preceding n times charging/discharging voltage, electric current, temperature and the corresponding battery capacity in pond are simultaneously stored in the library dataset, before record
N times charging/discharging voltage, electric current, the data volume of temperature and corresponding battery capacity are excessive, to reduce operand and reducing data
Reading error pre-processes data: every ten groups of data being taken to be a unit and number, the charge and discharge in per unit data in order
Piezoelectric voltage, electric current, temperature and battery capacity take mean value after removal maximum value and minimum value, pre-process the per unit sequence of output
Number be used as charge and discharge cycles number, corresponding data mean value is as the charging/discharging voltage of the cycle battery, electric current, temperature and appearance
Amount；The initial cycles point of battery capacity prediction is set as N, selects MODEL C=f (V, I, T) of battery capacity prediction, wherein C generation
Table battery capacity, V represent impulse electricity voltage, and I represents charging and discharging currents, and T represents environment temperature, determine model parameter number, root
First group of data of Data preprocess, initialization model parameter are input, battery capacity with charging/discharging voltage, electric current, temperature data
Data are that output Training Support Vector Machines SVM updates model parameter, and updated parameter is substituted into model, predicts battery capacity,
Until the battery capacity finally estimated is in error range, training terminates；By the voltage, the electricity that monitor battery impulse electricity process
Stream, temperature, C=f (V, I, T) model after being conducted into Support vector regression training, obtain battery in a charge and discharge in real time
Capacity after electricity circulation；The battery capacity estimated is obtained into the SOH of each single battery than upper battery rated capacity, and is made
For result output.
Further, the SOC acquisition methods of each single battery are as follows: by single battery each in battery pack with first
Beginning SOC value 0.1,0.2,0.3 ... 1.0 carries out multiple discharge experiment, records each single battery putting under different initial SOC values
Piezoelectric voltage, then the discharge voltage that identical initial SOC value many experiments obtain is taken into mean value, it is initial at one group finally to obtain battery
The table of the corresponding discharge voltage of SOC value 0.1,0.2,03 ... 1.0；Finally resulting table number is fitted using matlab or cftool
According to obtaining a discharge voltage-state-of-charge relation curve；It is obtained in real time respectively by monitoring cell voltage in conjunction with matched curve
The SOC of a single battery, and exported as result.
Compared with the prior art, the invention has the following advantages and beneficial effects:
1, the battery pack active equalization method provided by the invention based on cell health state and state-of-charge introduces each
The SOH*SOC of single battery indicates each single battery residual charge of battery pack after aging occurs for battery as equalizing coefficient
The percentage of amount, precision are higher compared with the precision of the percentage of the SOC each single battery residual charge amount indicated.
2, the battery pack active equalization method provided by the invention based on cell health state and state-of-charge, with SOH*
Balanced index of the SOC balance coefficient as equalizing circuit, the residual charge amount of each single battery is more nearly after equilibrium, balanced
Effect is more preferable, and the direct transfevent equalizing circuit of energy that the method proposes is, it can be achieved that direct from the high battery of remaining capacity
The battery transfer low to remaining capacity, time for balance is short, and the inconsistency of battery pack can be effectively reduced to power battery power, longevity
The negative effect of life is conducive to the dynamic property for promoting pure electric automobile, economy.
Detailed description of the invention
Fig. 1 is discharge voltage-state-of-charge graph of relation in the embodiment of the present invention.
Fig. 2 is battery pack active equalization method process of the embodiment of the present invention based on cell health state and state-of-charge
Figure.
Fig. 3 is the equalization scheme artificial circuit figure in the embodiment of the present invention by taking 4 concatenated battery packs of single battery as an example.
Fig. 4 is the control module figure of equalization scheme artificial circuit in the embodiment of the present invention.
Specific embodiment
Present invention will now be described in further detail with reference to the embodiments and the accompanying drawings, but embodiments of the present invention are unlimited
In this.
Embodiment:
A kind of battery pack active equalization method based on cell health state and state-of-charge is present embodiments provided, it is described
The flow chart of method as shown in Fig. 2, obtain the SOH and SOC of each single battery in battery pack first, and with each single battery
SOH*SOC as equalizing coefficient, the direct transfevent active equalization circuit of design energy is defeated using equalizing coefficient as primary condition
Enter the equalizing circuit control module into active equalization circuit, equalizing circuit control module is according to the process control electricity being previously written
The closure of road access forms corresponding energy transfer channel until the difference of the remaining capacity of each single battery reaches setting
Threshold value.
Specifically, the SOH acquisition methods of each single battery are as follows: each single battery in real-time monitoring battery pack
Preceding n times charging/discharging voltage, electric current, temperature and corresponding battery capacity and be stored in the library dataset, due to the preceding N of record
Secondary charging/discharging voltage, electric current, the data volume of temperature and corresponding battery capacity are excessive, read to reduce operand and reducing data
Error is taken, data are pre-processed: every ten groups of data being taken to be a unit and number, the charge and discharge in per unit data in order
Voltage, electric current, temperature and battery capacity take mean value after removal maximum value and minimum value, pre-process the per unit serial number of output
As charge and discharge cycles number, corresponding data mean value is as the charging/discharging voltage of the cycle battery, electric current, temperature and capacity；
The initial cycles point of battery capacity prediction is set as N, selects MODEL C=f (V, I, T) of battery capacity prediction, wherein C represents electricity
Tankage, V represent impulse electricity voltage, and I represents charging and discharging currents, and T represents environment temperature, model parameter number are determined, according to pre-
First group of data of processing, initialization model parameter are input, battery capacity data with charging/discharging voltage, electric current, temperature data
Model parameter is updated for output Training Support Vector Machines SVM, updated parameter is substituted into model, predicts battery capacity, until
In error range, training terminates the battery capacity finally estimated；By the voltage, the electric current, temperature that monitor battery impulse electricity process
Degree, C=f (V, I, T) model after being conducted into Support vector regression training, obtains battery in a charge and discharge cycles in real time
Capacity afterwards；The battery capacity estimated is obtained into the SOH of each single battery than upper battery rated capacity, and as result
Output.
The SOC acquisition methods of each single battery are as follows: by single battery each in battery pack with initial SOC value
0.1,0.2,0.3 ... 1.0 carries out multiple discharge experiment, records discharge voltage of each single battery under different initial SOC values,
The discharge voltage that identical initial SOC value many experiments obtain is taken into mean value again, finally obtains battery in one group of initial SOC value 0.1,
The table of 0.2,03 ... 1.0 corresponding discharge voltage；It finally is fitted resulting list data using matlab or cftool, obtains one
Discharge voltage-state-of-charge relation curve；Obtain each monomer electricity in real time in conjunction with matched curve by monitoring cell voltage
The SOC in pond, and exported as result.
The battery pack for selecting 4 monomer LiFePO4 ion batteries to be connected in series is balanced object, to the method
It is described in detail:
Step1: record 1500 charging/discharging voltages of monomer LiFePO4 ion battery, electric current, temperature and correspondence
Battery capacity and be stored in the library dataset, (take every ten groups of data in order is a unit and to number, every list to data prediction
Charging/discharging voltage, electric current, temperature and battery capacity in the data of position take mean value after removal maximum value and minimum value, pre-process
The per unit serial number of output as charge and discharge cycles number, corresponding data mean value as the cycle battery charging/discharging voltage,
Electric current, temperature and capacity), the prediction initial cycles N=1500 of battery capacity is set, MODEL C=f of battery capacity prediction is selected
(V, I, T), wherein C represents battery capacity, and V represents impulse electricity voltage, and I represents charging and discharging currents, and T represents environment temperature, determines
Model parameter number, according to pretreated first group of data, initialization model parameter, with charging/discharging voltage, electric current, temperature data
For input, battery capacity data is that output Training Support Vector Machines (SVM) updates model parameter, and updated parameter is substituted into mould
Type predicts battery capacity, until the battery capacity finally estimated is in error range, training terminates.The punching of real-time measurement battery is put
The voltage of electric process, electric current, temperature data, and C=f (V, I, T) model after support vector machines training is imported, electricity is obtained in real time
Capacity of the pond after a charge and discharge cycles；The battery capacity estimated is obtained into SOH than upper battery rated capacity, is input to equilibrium
Circuit control module.
Step2: by each single battery of one group of LiFePO4 ion battery group with initial SOC value 0.1,0.2,
0.3 ... 1.0 carries out discharge test, records each single battery in the discharge voltage of different initial SOC values, then will be identical initial
SOC value battery multiple discharge voltage takes mean value, the 1.0 corresponding discharge voltages that obtain battery in initial SOC value 0.1,0.2,0.3 ...
It is worth table；It finally is fitted experimental data using matlab/cftool, it is bent to obtain discharge voltage-state-of-charge (SOC) relationship
Line (as shown in Figure 1)；Battery SOC can be obtained in real time in conjunction with matched curve by monitoring cell voltage, and as result
It is input to equalizing circuit control module.
Step3: it according to the SOH value and SOC value of Step1 and Step2 4 the single batteries B1, B2, B3, B4 obtained, obtains
The equalizing coefficient SOH*SOC value of each battery and the battery voltage value of real-time measurement.As shown in Figure 3, Figure 4, every by what is obtained
The equalizing coefficient value of a battery is input to control unit CU1, and each battery voltage value is input to control unit CU2, control unit
The more each unit cell voltage value of CU2, when reaching the threshold value of default (such as there are the voltage difference of certain two or more battery
Shown in Fig. 3, in this programme 0.001) threshold pressure differential is set as, and CU2 exports a low level signal g, and three gate signal inputs are g
Metal-oxide-semiconductor disconnect, 4 single batteries of series-connected cell group disconnect, and circuit of battery pack balancing is started to work, control unit
CU1 is according to the equalizing coefficient values of 4 batteries, according to the program being previously written, by output signal g 1, g2, and g3, g4, g5, g6's
Level height, controls the on-off of MOS in equalizing circuit, selects the optimal path of energy transfer, control the channel of energy transfer.Example
Such as: when the equalizing coefficient of 4 single batteries sorts from large to small as B1, B3, B2, when B4, control unit CU2 exports g1, g2 high
Level signal, g3, g4 low level signal, g5, g6 high level signal.The metal-oxide-semiconductor of g1 at this time, g2 control is closed, circuit conducting,
The metal-oxide-semiconductor of g3, g4 control disconnects, and circuit disconnects, and the metal-oxide-semiconductor of g5, g6 control is closed, and circuit conducting, battery B1 passes through electricity at this time
Road is charged to battery B2, and battery B3 is charged by circuit to battery B4, each at this time when the equalizing coefficient of each battery is close
The voltage of battery also can close to (cell voltage can accordingly increase with the increase of battery capacity), when cell voltage difference reaches threshold value,
Equalization control module terminates equilibrium, and the equalizing coefficient difference of each single battery of battery pack reaches target value at this time, and equilibrium terminates.
The above, only the invention patent preferred embodiment, but the scope of protection of the patent of the present invention is not limited to
This, anyone skilled in the art is in the range disclosed in the invention patent, according to the present invention the skill of patent
Art scheme and its patent of invention design are subject to equivalent substitution or change, belong to the scope of protection of the patent of the present invention.
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| CN109802188A (en) * | 2019-02-25 | 2019-05-24 | 北京长城华冠汽车科技股份有限公司 | A kind of method and system that multiple battery units are carried out with load balancing control |
| CN109904542A (en) * | 2019-02-28 | 2019-06-18 | 深圳猛犸电动科技有限公司 | Capacity update method, device and the terminal device of lithium ion battery packet |
| CN109946616A (en) * | 2019-04-26 | 2019-06-28 | 厦门金龙联合汽车工业有限公司 | A kind of evaluation method of lithium iron phosphate battery system capacity inequality extent |
| CN111193306A (en) * | 2020-02-20 | 2020-05-22 | 山东大学 | Battery health state balancing method and system of modular energy storage battery grid-connected system |
| CN111354989A (en) * | 2020-02-21 | 2020-06-30 | 中南大学 | Reconfigurable battery pack control method and system and storage medium |
| CN111497685A (en) * | 2020-03-26 | 2020-08-07 | 明创佳联(浙江)新能源科技有限公司 | Automobile lithium battery charging management method and system |
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| CN114400387A (en) * | 2022-01-18 | 2022-04-26 | 北京智芯微电子科技有限公司 | Battery equalization management method and system based on multi-agent game |
| CN115000543A (en) * | 2022-07-11 | 2022-09-02 | 吉林大学 | An active equalization method considering battery aging in low temperature environment |
| CN116131400A (en) * | 2023-01-11 | 2023-05-16 | 广州锐速智能科技股份有限公司 | Battery management method, device, equipment and medium for energy storage system |
| CN116840699A (en) * | 2023-08-30 | 2023-10-03 | 上海泰矽微电子有限公司 | Battery health state estimation method and device, electronic equipment and medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104297690A (en) * | 2014-09-22 | 2015-01-21 | 北汽福田汽车股份有限公司 | Lithium battery SOC-OCV curve determination method |
| CN105226744A (en) * | 2015-09-10 | 2016-01-06 | 广西大学 | A kind of power battery pack balance charge/discharge control method based on SOC and system |
| CN106711530A (en) * | 2015-11-18 | 2017-05-24 | 三星电子株式会社 | Method and apparatus for battery equalization, and battery pack using the same |
| CN107037374A (en) * | 2017-05-04 | 2017-08-11 | 广东电网有限责任公司电力科学研究院 | A kind of SOC and SOH combined estimation methods of lithium ion battery |
| WO2018090678A1 (en) * | 2016-11-21 | 2018-05-24 | 华中科技大学 | Method and apparatus for monitoring state of charge and health state of lithium-ion battery |
-
2018
- 2018-10-12 CN CN201811187147.0A patent/CN109256834B/en not_active Expired - Fee Related
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104297690A (en) * | 2014-09-22 | 2015-01-21 | 北汽福田汽车股份有限公司 | Lithium battery SOC-OCV curve determination method |
| CN105226744A (en) * | 2015-09-10 | 2016-01-06 | 广西大学 | A kind of power battery pack balance charge/discharge control method based on SOC and system |
| CN106711530A (en) * | 2015-11-18 | 2017-05-24 | 三星电子株式会社 | Method and apparatus for battery equalization, and battery pack using the same |
| WO2018090678A1 (en) * | 2016-11-21 | 2018-05-24 | 华中科技大学 | Method and apparatus for monitoring state of charge and health state of lithium-ion battery |
| CN107037374A (en) * | 2017-05-04 | 2017-08-11 | 广东电网有限责任公司电力科学研究院 | A kind of SOC and SOH combined estimation methods of lithium ion battery |
Non-Patent Citations (1)
| Title |
|---|
| 李昌 等: "结合支持向量机的卡尔曼预测算法在VRLA蓄电池状态监测中的应用", 《电工技术学报》 * |
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