CN108802624A - A kind of lithium battery SOC methods of estimation - Google Patents
A kind of lithium battery SOC methods of estimation Download PDFInfo
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- CN108802624A CN108802624A CN201810626156.9A CN201810626156A CN108802624A CN 108802624 A CN108802624 A CN 108802624A CN 201810626156 A CN201810626156 A CN 201810626156A CN 108802624 A CN108802624 A CN 108802624A
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Abstract
The invention discloses a kind of lithium battery SOC methods of estimation, main control module obtains parameter information, and for the expanded Kalman filtration algorithm of ternary lithium battery and acquires lithium battery SOC value with iteration thinking by execution；The following state equation of the algorithm performs and measurement equation：State equation：Measurement equation：yn=g (xn,μn)+γn.The present invention uses specific SOC algorithms, improves the accuracy to data sampling.
Description
Technical field
The present invention relates to lithium battery SOC methods of estimation field more particularly to a kind of lithium battery SOC methods of estimation.
Background technology
Lithium battery SOC methods of estimation BMS mainly serves for ensuring safety, increase of the battery in charge and discharge and storing process
The available capacity of battery improves battery utilization rate, and intuitively provides battery various parameters for user.BMS mainly manages object
For secondary cell, different secondary cells because all there are some defects in battery structure characteristic difference, as operating temperature requirements are harsh,
Service life is short, capacity is low etc..Lithium battery is as current new secondary battery, compared to traditional lead-acid battery, ni-mh electricity
Pond etc., capacity, terminal voltage, energy density etc. all have a clear superiority.But because of its small volume, connection in series-parallel is at large capacity electricity
Chi Bao needs battery more, causes its complicated battery management configuration, sampling precision deficiency, cost higher, is not easy large-scale promotion.
The SOC methods of estimation of the prior art are all not enough to completely describe cell operating status：Estimated with discharge test method
It counts according to accurate, but real-time online measuring and can not take long；Internal resistance method is suitable for the battery that internal resistance changes greatly, system choosing
Use lithium battery as experimental subjects, internal resistance changes unobvious during the work time, therefore internal resistance method be not suitable for lithium battery into
Row SOC estimations；Ensure that the premise of open circuit voltage method precision is that battery terminal voltage is approximately equal to battery open circuit voltage, needs to disconnect electricity
Pond circuit measures, and is unable to real-time online estimation SOC；Although current integration method is currently most reliable, using most common one
Kind evaluation method, but it is high to the required precision of three primary quantities, and there are iterative process；Estimated using neural network
Calculator has high precision, but the data of enormous amount is needed to compare and analyze, and not enough then precision is inadequate for data volume.
Therefore in view of the defects existing in the prior art, it is really necessary to propose a kind of technical solution to overcome lacking for the prior art
It falls into.
Invention content
In order to overcome the above-mentioned deficiencies of the prior art, the present invention provides a kind of lithium battery SOC methods of estimation, to improve
SOC measurement accuracy.
Above-mentioned technical problem is solved, the invention adopts a technical scheme as：
A kind of lithium battery SOC methods of estimation, main control module obtain parameter information, and by execution for ternary lithium battery
Expanded Kalman filtration algorithm simultaneously acquires lithium battery SOC value with iteration thinking；
The following state equation of the algorithm performs and measurement equation：
State equation：
Measurement equation：
yn=g (xn,μn)+γn；
Wherein, xnThe SOC value of battery at the n-th moment；Δ Q indicates the electric quantity change amount in a period of time；Q0Indicate present battery
Total capacity, value are utilized and are acquired for the modified Peukert equations of ternary lithium battery：
K=In-1*K0=I-0.04203*e0.75113=1.0138*I-0.04203*K0,
In above formula, K0Capacity when 1C electric discharges is carried out for battery, I is discharge current, and t is discharge time；
ηiIndicate charging and discharging lithium battery multiplying power penalty coefficient；ηTIndicate temperature compensation coefficient；η0Indicate compensation of ageing coefficient；
inIndicate that the electric current at the n-th moment, value are obtained by battery SOC estimation block measurement；Δ t is the sampling time；ωnIt is for the n-th moment
System procedure activation noise, is the random function of a Normal Distribution；ynIt indicates to measure obtained cell voltage；γnIt is n-th
Moment observation noise is the random function of a Normal Distribution；g(xn,μn) it is the SOC and battery established by battery model
Relationship between voltage, wherein battery model formula is：
It is interior for a period of time that battery is calculated according to current information by battery SOC estimation block as a preferred technical solution,
Electric quantity change amount Δ Q and the n-th moment electric current inAnd it is sent to the main control module.
Each single lithium battery voltage in lithium battery module 4 is acquired by voltage sample module as a preferred technical solution,
And information of voltage is sent to by the main control module by communication isolation module.
The temperature on lithium battery pack module surface acquired by temperature sampling module as a preferred technical solution, and by temperature
Information is sent to the main control module.
The current information of lithium battery pack module is acquired by current sampling module as a preferred technical solution, and will be electric
Stream information is sent to the main control module.
The current sampling module is sampled using resistance sampling or direct current hall device as a preferred technical solution,.
Further include that lithium battery SOC value is shown by data disaply moudle as a preferred technical solution,.
The battery SOC estimation block is realized using chip DS2780 as a preferred technical solution,.
The voltage sample module is realized using chip AD7280A as a preferred technical solution,.
The main control module is using control chip MSP430F149IPM as a preferred technical solution,.
It is compared for the prior art, the present invention is using the specific circuit structure of battery SOC estimation block and the benefit of internal setting
The accuracy that coefficient improves measurement is repaid, in combination with the expanded Kalman filtration algorithm designed for ternary lithium battery, experiment
It measures estimation precision and is less than 3%.
Description of the drawings
Fig. 1 is the overall structure block diagram of the present invention；
Fig. 2 is lithium battery matched curve and actual value curve in the present invention.
Fig. 3 is revised matched curve.
Fig. 4 is based on expanded Kalman filtration algorithm estimation curve.
Fig. 5 is the circuit diagram that battery SOC estimation block is connect with power supply circuit in the present invention.
Fig. 6 is the circuit diagram that battery SOC estimation block, power supply circuit and the main control module of the present invention connects.
Reference numeral meaning in figure is as follows：1-battery balanced module, 2-voltage sample modules, 3-communication isolating moulds
Block, 4-lithium battery pack modules, 5-power supply circuits, 6-temperature sampling modules, 7-battery SOC estimation blocks, 8-current samples
Module, 9-main control modules, 10-protection circuits, 11-data disaply moudles.
Specific implementation mode
Technical solution provided by the invention is described further below with reference to attached drawing.
Referring to Fig. 1, it show a kind of structure diagram of lithium battery SOC methods of estimation of the present invention, including battery balanced module
1, voltage sample module (2), communication isolation module 3, lithium battery pack module 4, power supply circuit 5, temperature sampling module 6, battery SOC
Estimation block 7, current sampling module 8, main control module 9, protection module 10, data disaply moudle 11；Wherein, described battery balanced
Module 1 carries out equilibrium treatment, signal input part and voltage for 2 signal of receiving voltage acquisition module to lithium battery pack module 4
2 output end of acquisition module is connected；The voltage sample module (2) is used to acquire each single battery inside lithium battery pack module
Voltage, voltage sample module (2) signal input part connect 4 signal output end of lithium battery pack module, voltage sample module (2) with
Two-way communication is carried out by communication isolation module 3 between main control module 9；The communication isolation module 3 is sampled for isolation voltage
Module (2) and main control module 9, prevent big voltage or high current to be flowed into main control module 9；Its anode of the lithium battery pack module 4
5 input terminal of power supply circuit, 2 input terminal of voltage acquisition module are connected, cathode connects 8 input terminal of current sampling module, and surface connects temperature
Sampling module 6 is spent, internal single battery connects 1 input terminal of battery balanced module；The power supply circuit 5 is respectively main control module 9, temperature
Sampling module 6, protection module 10, battery SOC estimation block 7, data disaply moudle 11 and communication isolation module 3 is spent to power；Institute
Temperature sampling module 6 is stated for acquiring 4 inside single battery surface temperature of battery module, and temperature signal is converted into voltage
Signal carries out two-way communication with main control module 9；The battery SOC estimation block 7, signal input part and current sample mould
8 output end of block is connected, and the SOC value of current lithium battery pack module 4 is calculated by the way that inner parameter is arranged；The current sampling module 8
For acquiring the electric current on battery module 4, and voltage signal is converted the current to, signal output end connects battery SOC estimation
Module 7；For the main control module 9 for data processing and control protection module 10, signal output end passes sequentially through communication isolating
Module 3, temperature sampling module 6, data disaply moudle 11 and protection module 10；10 signal input part of the protection module and master control
9 output end of module is connected, and is controlled by main control module 9 and disconnects or be connected lithium battery pack module operating circuit；The data show mould
Block 11, signal input part are connected with 9 signal output end of main control module, the data transmitted for showing main control module 9.
In a preferred embodiment, the voltage sample modules A D7280A, the control chip model are
MSP430F149IPM, the linear voltage decreasing chip are LM2576HV, and it is DS18B20 that the temperature, which measures chip, the communication every
Chip model from module 3 is PC4D10S.Battery SOC estimation block 7 is using special chip DS2780, and DS2780 is as profession
SOC estimation chips, be arranged by inner parameter, can be integrated with the time to flowing through ohmically electric current, and and battery
SOC, battery rated capacity operation obtain current SOC value before work.The internal clocking of the included high-precisions of DS2780, high stability,
It can be used for measuring lithium battery voltage, temperature and electric current, while calculating battery current residual electricity.The battery behavior parameter sampled
It is stored on piece EEPROM with the parameter after calculating, user can call corresponding instruction, obtain related data.And
DS2780 can set battery temperature coefficient, discharge rate, aging coefficient etc., in conjunction with ampere-hour method and open circuit voltage method to battery electricity
Amount variable quantity and battery rated capacity are calculated, and the processing of follow-up logarithm is facilitated.Estimated value includes as unit of mAh
The SOC value of remaining capacity and percents.DS2780 is connected using 1-Wire bus interface with microcontroller, and it is difficult to reduce wiring
Degree and electromagnetic interference.1-Wire bus principles are to realize that the half-duplex bidirectional of host and slave is logical by a common data line
Letter.
Further, the voltage sample module (2) is for acquiring each single lithium battery voltage in lithium battery module 4, and leads to
It crosses communication isolation module 3 and information of voltage is sent to the main control module 9；
The battery balanced module 1 is connected with voltage acquisition module 2, the electricity sampled according to the voltage acquisition module 2
Information is pressed to start with balanced each single battery；
The temperature sampling module 6 is used to acquire the temperature on 4 surface of lithium battery pack module and temperature information is sent to institute
State main control module 9；
The current sampling module 8 is used to acquire the current value of lithium battery pack module 4, and current information is sent to described
Main control module 9 and battery SOC estimation block 7；
The battery SOC estimation block 7 is used to calculate battery electric quantity change amount Δ Q interior for a period of time according to current information
With the electric current i at the n-th momentnAnd it is sent to the main control module 9；
The main control module 9 is connected with voltage sample module (2), temperature sampling module 6, battery SOC estimation block 7,
For the expanded Kalman filtration algorithm of ternary lithium battery and lithium battery SOC value is acquired with iteration thinking by execution；
The following state equation of the algorithm performs and measurement equation：
State equation：
Measurement equation：
yn=g (xn,μn)+γn (2)
Wherein, xnThe SOC value of battery at the n-th moment；Δ Q indicates the electric quantity change amount in a period of time；Q0Indicate present battery
Total capacity, value are utilized and are acquired for the modified Peukert equations of ternary lithium battery：
K=In-1*K0=I-0.04203*e0.75113=1.0138*I-0.04203*K0 (3)
In above formula (3), K0Capacity when 1C electric discharges is carried out for battery, I is discharge current, and t is discharge time.It is described below
How the present invention obtains formula (3).
Pass through reality in of the invention to make it preferably describe ternary lithium battery capacity and the relationship between electric current, time
Test amount ternary lithium battery carries out 0.25C, 0.5C, 1C, 2C discharge time under the conditions of full capacity, shown in table 1.
The discharge time of the different discharge currents of table 1
It is capacity when battery carries out 1C electric discharges to enable K0=I*t, wherein K0, and I is discharge current, and t is discharge time.It substitutes into
To being obtained in standard Peukert equations：
Logarithm is taken to above formula both sides and abbreviation obtains：
Ln (K)=(n-1) ln (I)+ln (K0)
Data in table 1 are updated to above formula, and with ln (I) for x-axis, ln (K) maps for y-axis, and linear fit is carried out to it
It is -0.04203 to obtain slope, then it is 0.95797, ln (K that can obtain n0) it is 0.75113, it is compared to obtain with test value
Residual sum of squares (RSS) is 2.6682E-4.By n and ln (K0) be updated to after formula (4) and obtain ternary lithium battery Peukert equations and be：
K=In-1*K0=I-0.04203*e0.75113=1.0138*I-0.04203*K0
Further, in formula (1), ηiIndicate charging and discharging lithium battery multiplying power penalty coefficient；ηTIndicate temperature compensation coefficient；
η0Indicate compensation of ageing coefficient；inIndicate that the electric current at the n-th moment, value are obtained by battery SOC estimation block measurement；Δ t is sampling
Time；ωnIt is the random function of a Normal Distribution for the n-th moment system process excitation noise；ynIt indicates to measure and obtain
Cell voltage；γnIt is the random function of a Normal Distribution for the n-th moment observation noise；g(xn,μn) it is by battery
Relationship between the SOC and cell voltage of model foundation, wherein battery model formula is：
In above-mentioned battery model formula (5), the present invention goes out battery virtual voltage using composite battery models fitting and is closed with SOC
It is formula, the output equation of wherein composite battery model is that formula is：
In formula (6), y (t) indicates that battery measurement voltage, R indicate that the equivalent internal resistance of battery, i (t) indicate battery charging and discharging electricity
Stream, Δ t are charge and discharge time, Q0Indicate battery rated capacity, K0、K1、K2、K3、K4It is model coefficient, it can be by calculating
It arrives.
Although above-mentioned model (6) can describe the certain parameters of battery, due to lithium battery structure, electrolyte etc.,
Battery model (6) is not enough to completely describe cell operating status, this becomes the fatal disadvantage of Kalman filtering.
Therefore, it in order to improve measurement accuracy, needs to be fitted composite battery model, the present invention proposes to be applicable in as a result,
In the Extended Kalman filter of charging and discharging lithium battery system.
In formula (6), there are multiple unknown parameter K0、K1、K2、K3、K4, their value is by drawing tool OriginPro 8.5
Lithium battery measurement voltage is fitted with SOC relational graphs and is acquired, the optimal fitting value acquired is as shown in table 2：
2 fit parameter values of table
| K0 | K1 | K2 | K3 | K4 |
| 3.72258 | -2.80417*10-4 | 0.0605 | 0.14269 | -0.12195 |
Matched curve and actual value curve as shown in Fig. 2, figure it is seen that matched curve is preferable in mid-term fitting,
Fitting is poor in a bit of time in early period and later stage, and the residual sum of squares (RSS) between matched curve and actual value is 0.0762.It goes
Fall before 5% with 90% after data after obtain curve shown in Fig. 3, K0、K1、K2、K3、K4Value is as shown in table 3.
3 modified fit parameter values of table
| K0 | K1 | K2 | K3 | K4 |
| 3.49107 | 0.01273 | -0.05534 | -0.03117 | -0.19297 |
At this point, the residual sum of squares (RSS) between matched curve and actual value is 3.05919E-5, hence it is evident that precision improves many.
Similarly using fitting between 0~5% and 90%~100%.To sum up obtaining battery model formula is：
The process that lithium battery SOC value is obtained using iteration thinking solution formula (1) and (2) is described in detail again below.Wherein, Q0It can
It is acquired by formula (3), g (xn,μn) it is relationship between the SOC and cell voltage established by battery model (formula 5), previous portion
Formula of grading is the normal equation of Extended Kalman filter, behind a part be based on practical lithium battery model foundation.First
Filter state is initialized：
Wherein, the "+" in subscript indicates that maximum likelihood estimate, "-" indicate predicted value.The iterative equation of Extended Kalman filter
Formula is shown in formula (8)：
Wherein, DωAnd Dγω is indicated respectivelynAnd γnVariance, value size is related to system acquisition precision.When system is logical
It crosses measurement and obtains yn' when, by formula (8) operation to predicted value xn -And Pn -It is modified, obtains maximum likelihood estimate xn +And Pn +。
Whole SOC estimates that thinking is：First by measuring battery terminal voltage, an initial value x is provided using battery model0, further according to
Peukert update equations and current integration method find out the state equation of extended Kalman filter, then utilize spreading kalman
Filtering algorithm carries out error analysis and compensation to state equation, to realize SOC estimation on line.Fig. 4 is shown according to above-mentioned side
The estimation curve figure that method is drawn using MATLAB.Wherein, simulated battery obtains actual value with constant-current discharge to blanking voltage, in figure
Line is " --- ", and "-" is to obtain optimum prediction value using said program, and it is 0.0059 to seek covariance to two curves, and precision has
Prodigious raising, it is more accurate that this so that this method carries out SOC estimations to lithium battery.
Using above-mentioned technical proposal, present invention combination hardware design and Software for Design, by ternary charging and discharging lithium battery
It carries out experimental verification and obtains battery SOC estimation precision reachable 3% or so；The present invention can manage multisection lithium battery simultaneously, can
For electric vehicle, backup power supply etc., practicability is high, highly reliable.
In a preferred embodiment, main control module carries out parameter to voltage sample chip and battery SOC estimation chip
Setting, voltage sample chip carries out sampling to the voltage of the often section single battery in lithium battery pack module and it is determined whether to enable equal
Weigh module, and temperature sensor module samples the temperature on the often section single battery surface in lithium battery pack module, above-mentioned to adopt
The data collected are all sent to main control module；Current sample chip samples lithium battery pack module operating current, then will
Collected information sends battery SOC estimation block to, and current electricity is obtained by carrying out calculation process with preset parameter
The SOC value of pond group module, while main control module reads all data of battery SOC inside modules, main control module obtains above-mentioned whole
Judge whether lithium battery pack module is in abnormality, whether needs to open protection circuit etc., and finally, main control module will after data
The total data of above-mentioned gained is shown in data disaply moudle 11.
Referring to Fig. 5 and Fig. 6, it show the circuit diagram that battery SOC estimation block is connect with power supply circuit in the present invention
And the circuit diagram of battery SOC estimation block, power supply circuit and main control module connection, including the first chip U1, the second core
Piece U2, third chip P1, first resistor R1, second resistance R2,3rd resistor R3, the 4th resistance R4, the 5th resistance R5, the 6th electricity
Hinder R6, the 7th resistance R7, the 8th resistance R8, the 9th resistance R9, the tenth resistance R10, the first capacitance C1, the second capacitance C2, third
Capacitance C3, the 4th capacitance C4, the 5th capacitance C5, the 6th capacitance C6, the 7th capacitance C7, the 8th capacitance C8, the 9th capacitance C9, first
Inductance L1, the first diode D1, the second diode D2, first switch S1, the first crystal oscillator X1 and current sampling module 8, it is described
The pin 1 of first chip is vacant, does not need external circuits, the connection of the first chip pin 2 the 6, first electricity of first chip pin
Hold the one end C1, second one end capacitance C2, the one end third capacitance C3, the 4th one end capacitance C4, the 5th one end capacitance C5, the 5th resistance
The one end R5, the tenth one end resistance R10,8 one end of current acquisition module, the second chip pin 3, the second chip pin 5 and first
Diode D1 cathode, first chip pin 3 connect the 4th one end resistance R4, the 5th resistance R5 other ends, first core
Piece pin 4 connects 3rd resistor R3) one end, the third capacitance C3 other ends, first chip pin 5 connects first resistor R1 mono-
End and third chip pin 12, first chip pin 7 connect 8 other end of current acquisition module and charge and discharge cathode,
First chip pin 8 connects the one end second resistance R2 and third chip pin 13, the connection of the second chip pin 1 the
The four resistance R4 other ends, the anode of lithium battery pack module 4, the first capacitance C1 other ends and the 4th capacitance C4 other ends, described the
Two chip pins 2 connection the first diode D1 anodes, first one end inductance L1, second chip pin 4 connect first resistor
The R1 other ends, the second resistance R2 other ends, the first inductance L1 other ends, the 5th capacitance C5 other ends, the second capacitance C2 other ends,
The 3rd resistor R3 other ends, the 8th one end resistance R8, the 6th one end capacitance C6, the 9th one end resistance R9, the second diode D2 are just
Pole and third chip pin 1, the third chip pin 2, pin 4, pin 5, pin 6, pin 7, pin 8, draw pin 3
Foot 9, pin 15, pin 16, pin 17, pin 18, pin 19, pin 20, pin 21, pin 22, pin 23, draws pin 14
Foot 24, pin 26, pin 27, pin 28, pin 29, pin 30, pin 31, pin 32, pin 33, pin 34, draws pin 25
Foot 35, pin 37, pin 38, pin 39, pin 40, pin 41, pin 42, pin 43, pin 44, pin 45, draws pin 36
Foot 46, pin 48, pin 49, pin 50, pin 51, pin 52, pin 55, pin 56, pin 57, pin 58, draws pin 47
Foot 59, pin 60, pin 61 are vacant, and the third chip pin 10 connects the 6th one end resistance R6, the third chip pin
11 the 7th one end resistance R7 of connection, the third chip pin 53 connect first one end crystal oscillator X1 and the 9th one end capacitance C9,
The third chip pin 54 connects the first crystal oscillator X1 other ends and the 8th one end capacitance C8, and the third chip pin 58 connects
Connect the second diode D2 cathode, the 9th resistance R9 other ends, the one end first switch S1 and the 7th one end capacitance C7, the third
Chip pin 62 connect third chip pin 63, the resistance R10 other ends, the 6th resistance R6 other ends, the 7th resistance R7 other ends,
The 6th capacitance C6 other ends, the 7th capacitance other end, the first switch S1 other ends, the 8th capacitance C8 other ends and the 9th capacitance
The C9 other ends, the third chip pin 64 connect the 8th one end resistance R8.
In foregoing circuit, the first chip U1 is SOC chip DS2780, and the second chip U2 is linear voltage decreasing chip
LM2576HV, chip P1 chip MSP430F149IPM in order to control.
The explanation of above example is only intended to facilitate the understanding of the method and its core concept of the invention.It should be pointed out that pair
For those skilled in the art, without departing from the principle of the present invention, the present invention can also be carried out
Some improvements and modifications, these improvement and modification are also fallen within the protection scope of the claims of the present invention.
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 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 range caused.
Claims (10)
1. a kind of lithium battery SOC methods of estimation, which is characterized in that
Main control module obtains parameter information, and by execution for the expanded Kalman filtration algorithm of ternary lithium battery and with iteration
Thinking acquires lithium battery SOC value；
The following state equation of the algorithm performs and measurement equation：
State equation：
Measurement equation：
yn=g (xn,μn)+γn；
Wherein, xnThe SOC value of battery at the n-th moment；Δ Q indicates the electric quantity change amount in a period of time；Q0Indicate that present battery always holds
Amount, value are utilized and are acquired for the modified Peukert equations of ternary lithium battery：
K=In-1*K0=I-0.04203*e0.75113=1.0138*I-0.04203*K0,
In above formula, K0Capacity when 1C electric discharges is carried out for battery, I is discharge current, and t is discharge time；
ηiIndicate charging and discharging lithium battery multiplying power penalty coefficient；ηTIndicate temperature compensation coefficient；η0Indicate compensation of ageing coefficient；inIt indicates
The electric current at the n-th moment, value are obtained by battery SOC estimation block measurement；Δ t is the sampling time；ωnEtching system mistake when being n-th
Journey excitation noise is the random function of a Normal Distribution；ynIt indicates to measure obtained cell voltage；γnFor the n-th moment
Observation noise is the random function of a Normal Distribution；g(xn,μn) it is the SOC and cell voltage established by battery model
Between relationship, wherein battery model formula is：
2. lithium battery SOC methods of estimation according to claim 1, which is characterized in that by battery SOC estimation block according to
Current information calculate battery for a period of time in electric quantity change amount Δ Q and the n-th moment electric current inAnd it is sent to the master control mould
Block.
3. lithium battery SOC methods of estimation according to claim 1 or 2, which is characterized in that acquired by voltage sample module
Each single lithium battery voltage in lithium battery module 4, and information of voltage is sent to by the main control module by communication isolation module.
4. lithium battery SOC methods of estimation according to claim 1 or 2, which is characterized in that acquired by temperature sampling module
Temperature information is simultaneously sent to the main control module by the temperature on lithium battery pack module surface.
5. lithium battery SOC methods of estimation according to claim 1 or 2, which is characterized in that acquired by current sampling module
The current information of lithium battery pack module, and current information is sent to the main control module.
6. lithium battery SOC methods of estimation according to claim 5, which is characterized in that the current sampling module is using electricity
Resistance sampling or the sampling of direct current hall device.
7. lithium battery SOC methods of estimation according to claim 1 or 2, which is characterized in that further include showing mould by data
Block shows lithium battery SOC value.
8. lithium battery SOC methods of estimation according to claim 2, which is characterized in that the battery SOC estimation block uses
Chip DS2780 is realized.
9. lithium battery SOC methods of estimation according to claim 3, which is characterized in that the voltage sample module uses core
Piece AD7280A is realized.
10. lithium battery SOC methods of estimation according to claim 1 or 2, which is characterized in that the main control module is using control
Coremaking piece MSP430F149IPM.
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| CN105140981A (en) * | 2015-06-17 | 2015-12-09 | 广西科技大学 | Lithium battery active equalization control method |
| CN107368619A (en) * | 2017-06-02 | 2017-11-21 | 华南理工大学 | EKF SOC estimation method based on battery hysteresis voltage characteristic and resilience voltage characteristic |
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| CN110673052A (en) * | 2019-10-18 | 2020-01-10 | 湖南小步科技有限公司 | SOC estimation method and device of power battery and battery management system |
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