CN110333456A - Evaluation method and device, the vehicle of power battery SOC - Google Patents
Evaluation method and device, the vehicle of power battery SOC Download PDFInfo
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- CN110333456A CN110333456A CN201910667738.6A CN201910667738A CN110333456A CN 110333456 A CN110333456 A CN 110333456A CN 201910667738 A CN201910667738 A CN 201910667738A CN 110333456 A CN110333456 A CN 110333456A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/374—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC] with means for correcting the measurement for temperature or ageing
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
- G01R31/3842—Arrangements for monitoring battery or accumulator variables, e.g. SoC combining voltage and current measurements
Abstract
This disclosure relates to the evaluation method and device, vehicle of a kind of power battery SOC.The described method includes: the current value in the power battery under uncharged and non-discharge scenario in the power battery is obtained, as current offset value；In the power battery charging or discharge process, the SOC value of the power battery is estimated according to the equivalent-circuit model of the power battery and Extended Kalman filter method, wherein process noise parameter and measurement noise parameters are determined according to the current offset value.In such manner, it is possible to according to the error of the SOC as caused by current offset value is corrected to a certain extent, to keep the estimation of power battery SOC more acurrate.
Description
Technical field
This disclosure relates to power battery field, and in particular, to a kind of evaluation method and device, vehicle of power battery SOC
?.
Background technique
With the continuous aggravation of environmental pollution got worse with energy crisis, electric vehicle is increasingly by everybody pass
Note, core component of the power battery as electric vehicle accurately estimates its state-of-charge (State of Charge, SOC), right
The ability for giving full play to power battery, prevents super-charge super-discharge from having very important significance.And the SOC of power battery is healthy shape
The basis that state (StateofHealth, SOH), power rating (StateofPower, SOP) are estimated, estimation precision seem especially
It is important.
Currently, there are mainly two types of the evaluation methods of power battery SOC: current integration method and Extended Kalman filter method.?
In current integration method, in the case where the SOC of last moment is known in advance, battery in a period of time is filled with, is released electricity
It is counted, to obtain current SOC.Current integration method, which compares, relies on current sensor precision and SOC initial value, calculating process
In can not correct initial SOC error, and accumulated error can be generated because of current sensor error.It is filtered with spreading kalman
Wave estimation SOC can be modified initial SOC error, and overcome accumulated error caused by sensor error, but sometimes
Also it is difficult to ensure that the estimation precision of SOC.
Summary of the invention
Purpose of this disclosure is to provide a kind of accurate, the higher power battery SOC of precision evaluation methods and device, vehicle
?.
To achieve the goals above, the disclosure provides the evaluation method of power battery SOC a kind of, which comprises obtains
The current value in the power battery under uncharged and non-discharge scenario in the power battery is taken, as current offset value；?
In the power battery charging or discharge process, according to the equivalent-circuit model of the power battery and Extended Kalman filter method
Estimate the SOC value of the power battery, wherein process noise parameter is with measurement noise parameters according to the current offset value come really
It is fixed.
Optionally, process noise parameter and measurement noise parameters are determined according to the current offset value, comprising:
If the current offset value is less than or equal to scheduled bias, battery balanced not open, and the power battery
Temperature be greater than or equal to preset temperature threshold, then the process noise parameter is determined as scheduled first process noise and joined
Number, and the measurement noise parameters are determined as scheduled first and measure noise parameters, in the first process noise parameter,
W1With W2The ratio between be scheduled first ratio, W1For the process noise of state variable SOC (k), SOC (k) is power described in the k moment
The SOC value of battery, W2For state variable V1(k) process noise, V1It (k) is the voltage value at k moment first resistor both ends, wherein
In the equivalent-circuit model of the power battery, connect after the first resistor and capacitor parallel connection with second resistance, after series connection
The both ends for being electrically connected to the power battery.
Optionally, process noise parameter and measurement noise parameters are determined according to the current offset value, further includes:
If the current offset value is greater than the scheduled bias, the process noise parameter is determined as scheduled
Second process noise parameter, and the measurement noise parameters are determined as scheduled second and measure noise parameters, described second
In process noise parameter, W1With W2The ratio between be scheduled second ratio, second ratio is greater than first ratio, described the
Two, which measure noise parameters, is less than the first measurement noise parameters.
Optionally, process noise parameter and measurement noise parameters are determined according to the current offset value, further includes:
If the current offset value is less than or equal to the scheduled bias, and battery balanced unlatching, then by the mistake
Journey noise parameters are determined as scheduled third process noise parameter, and the measurement noise parameters are determined as scheduled third amount
Survey noise parameters, in the third process noise parameter, W1With W2The ratio between be scheduled third ratio, the third ratio is small
In first ratio, the third measures noise parameters and is greater than the first measurement noise parameters.
Optionally, process noise parameter and measurement noise parameters are determined according to the current offset value, further includes:
If the current offset value is less than or equal to the scheduled bias, battery balanced not open, and the power
The temperature of battery is less than the preset temperature threshold, then by the process noise parameter, W1With W2The ratio between be determined as it is scheduled
4th ratio, and the measurement noise parameters are determined as the scheduled 4th and measure noise parameters, wherein the 4th ratio is small
In first ratio, the described 4th, which measures noise parameters, is greater than the first measurement noise parameters.
The disclosure also provides the estimation device of power battery SOC a kind of, and described device includes:
Module is obtained, for obtaining the electricity in the power battery under uncharged and non-discharge scenario in the power battery
Flow valuve, as current offset value；
Estimation block is used in the power battery charging or discharge process, according to the equivalent electricity of the power battery
Road model and Extended Kalman filter method estimate the SOC value of the power battery, wherein process noise parameter and measurement noise ginseng
Number is determined according to the current offset value.
Optionally, the estimation block includes:
First determine submodule, if for the current offset value be less than or equal to scheduled bias, it is battery balanced not
It opens, and the temperature of the power battery is greater than or equal to preset temperature threshold, then is determined as the process noise parameter
Scheduled first process noise parameter, and the measurement noise parameters are determined as scheduled first and measure noise parameters, in institute
It states in the first process noise parameter, W1With W2The ratio between be scheduled first ratio, W1For the process noise of state variable SOC (k),
SOC (k) is the SOC value of power battery described in the k moment, W2For state variable V1(k) process noise, V1It (k) is the k moment first
The voltage value at resistance both ends, wherein in the equivalent-circuit model of the power battery, after the first resistor and capacitor parallel connection
It connects with second resistance, the both ends for being electrically connected to the power battery after series connection.
Optionally, the estimation block further include:
Second determines submodule, if being greater than the scheduled bias for the current offset value, by the process
Noise parameters are determined as scheduled second process noise parameter, and the measurement noise parameters are determined as scheduled second and are measured
Noise parameters, in the second process noise parameter, W1With W2The ratio between be scheduled second ratio, second ratio is greater than
First ratio, described second, which measures noise parameters, is less than the first measurement noise parameters.
Optionally, the estimation block further include:
Third determines submodule, if being less than or equal to the scheduled bias, and battery for the current offset value
Equilibrium is opened, then the process noise parameter is determined as scheduled third process noise parameter, and the measurement noise is joined
Number is determined as scheduled third and measures noise parameters, in the third process noise parameter, W1With W2The ratio between be scheduled third
Ratio, the third ratio are less than first ratio, and the third measures noise parameters and is greater than the first measurement noise ginseng
Number.
Optionally, the estimation block further include:
4th determines submodule, if being less than or equal to the scheduled bias for the current offset value, battery is equal
Weighing apparatus is not opened, and the temperature of the power battery is less than the preset temperature threshold, then is determined the process noise parameter
For scheduled 4th process noise parameter, and the measurement noise parameters are determined as the scheduled 4th and measure noise parameters,
In the 4th process noise parameter, W1With W2The ratio between be scheduled 4th ratio, the 4th ratio be less than it is described first ratio
Example, the described 4th, which measures noise parameters, is greater than the first measurement noise parameters.
The disclosure also provides a kind of vehicle, the estimation device including the above-mentioned power battery SOC that the disclosure provides.
Through the above technical solutions, dynamic being estimated according to the equivalent-circuit model and Extended Kalman filter method of power battery
When the SOC value of power battery, process noise parameter is adjusted according to current offset value and measures noise parameters.In such manner, it is possible to according to
The error of the SOC as caused by current offset value is corrected to a certain extent, to keep the estimation of power battery SOC more acurrate.
Other feature and advantage of the disclosure will the following detailed description will be given in the detailed implementation section.
Detailed description of the invention
Attached drawing is and to constitute part of specification for providing further understanding of the disclosure, with following tool
Body embodiment is used to explain the disclosure together, but does not constitute the limitation to the disclosure.In the accompanying drawings:
Fig. 1 is the flow chart of the evaluation method for the power battery SOC that an exemplary embodiment provides；
Fig. 2 is the schematic diagram of the equivalent-circuit model for the power battery that an exemplary embodiment provides；
Fig. 3 is the flow chart for the SOC with Extended Kalman filter method estimation power battery that an exemplary embodiment provides；
Fig. 4 is the determination process noise parameter that an exemplary embodiment provides and the flow diagram for measuring noise parameters；
Fig. 5 is the flow chart of the evaluation method for the power battery SOC that another exemplary embodiment provides；
Fig. 6 is the flow chart of the evaluation method for the power battery SOC that another exemplary embodiment provides；
Fig. 7 is the flow chart of the evaluation method for the power battery SOC that another exemplary embodiment provides；
Fig. 8 is the flow chart of the evaluation method for the power battery SOC that another exemplary embodiment provides；
Fig. 9 is the block diagram of the estimation device for the power battery SOC that an exemplary embodiment provides；
Figure 10 is the block diagram of the estimation device for the power battery SOC that another exemplary embodiment provides；
Figure 11 is the block diagram of the estimation device for the power battery SOC that another exemplary embodiment provides；
Figure 12 is the block diagram of the estimation device for the power battery SOC that another exemplary embodiment provides；
Figure 13 is the block diagram of the estimation device for the power battery SOC that another exemplary embodiment provides；
Figure 14 is the block diagram of a kind of electronic equipment shown in an exemplary embodiment.
Specific embodiment
It is described in detail below in conjunction with specific embodiment of the attached drawing to the disclosure.It should be understood that this place is retouched
The specific embodiment stated is only used for describing and explaining the disclosure, is not limited to the disclosure.
Fig. 1 is the flow chart of the evaluation method for the power battery SOC that an exemplary embodiment provides.As shown in Figure 1, described
Method may comprise steps of.
Step S1 obtains the current value in power battery under uncharged and non-discharge scenario in power battery, as electric current
Bias.
Step S2, in power battery charging or discharge process, according to the equivalent-circuit model and expansion card of power battery
Kalman Filtering method estimation power battery SOC value, wherein process noise parameter and measure noise parameters according to current offset value come
It determines.
Wherein, in the case where power battery does not charge without electric discharge yet, electric current is collected, then the power battery collected
In current value be current offset value.It under normal circumstances, is that collect electric current, it is, the current offset value
It is under normal circumstances zero.Current offset be due to aging of current sensor etc. caused by.
Through the above technical solutions, dynamic being estimated according to the equivalent-circuit model and Extended Kalman filter method of power battery
When the SOC value of power battery, process noise parameter is adjusted according to current offset value and measures noise parameters.In such manner, it is possible to according to
The error of the SOC as caused by current offset value is corrected to a certain extent, to keep the estimation of power battery SOC more acurrate.
In one embodiment, the equivalent-circuit model of power battery can be single order RC equivalent-circuit model.
Fig. 2 is the schematic diagram of the equivalent-circuit model for the power battery that an exemplary embodiment provides.As shown in Fig. 2, the
It is gone here and there after one resistance R1 (charge-transfer resistance) and capacitor C (for example, electric double layer capacitance) is in parallel with second resistance R2 (Ohmic resistance)
Connection, the both ends for being electrically connected to power battery after series connection.V is the voltage value at power battery both ends, and OCV is power battery both ends
Open-circuit voltage values, can detect to obtain by test experiment.
In Extended Kalman filter method, state equation can be with are as follows:
Measurement equation can be with are as follows:
V (k)=OCV (k)+V1(k)+I(k)R2 (2)
Wherein, SOC (k) is the SOC value of k moment power battery, V1It (k) is the voltage value at k moment first resistor both ends, I
(k) current value of power battery is flowed through for the k moment, Δ t is the step-length of time, QcFor the capacity of power battery, R1For first resistor
Resistance value, R2For the resistance value of second resistance, C1For the capacitance of capacitor, V (k) is the voltage at k moment power battery both ends
Value, OCV (k) are the open-circuit voltage values at k moment power battery both ends.
In Extended Kalman filter method, the time update equation of error co-variance matrix can be with are as follows:
P(k)-=A (k) P (k-1)+A(k)T+Q(k) (3)
Kalman gain equation are as follows:
K (k)=P (k)-H(k)T(H(k)P(k)-H(k)T+R(k))-1 (4)
Wherein, P (k)-It is updated for the time of k moment error co-variance matrix, A (k) is obtained according to state equation (1)
The Jacobian matrix at k moment, P (k-1)+It is updated for the measurement of k-1 moment error co-variance matrix, Q (k) is the process at k moment
Noise parameters, K (k) are kalman gain, and H (k) is the Jacobian matrix obtained according to measurement equation (2), and R (k) is the k moment
Measure noise parameters.*TFor transposed matrix.
In Extended Kalman filter method, the measurement renewal equation of state parameter can be with are as follows:
X(k)+=X (k)-+K(k)(Z(k)-Z(k)-) (5)
Error co-variance matrix measures renewal equation can be with are as follows:
P(k)+=(E-K (k) H (k)) P (k)- (6)
Wherein, X (k) is state variable [SOC (k)；V1(k)], X (k)-It is updated for the time of X (k), X (k)+For X's (k)
It measures and updates, Z (k) is the voltage value at the power battery both ends of measurement, Z (k)-For the cell voltage predicted in measurement equation, P
(k)+It is updated for the measurement of k moment error co-variance matrix, P (k)-It is updated for the time of k moment error co-variance matrix, E is single
Bit matrix.
Fig. 3 is the flow chart for the SOC with Extended Kalman filter method estimation power battery that an exemplary embodiment provides.
As shown in figure 3, may comprise steps of with the method for the SOC of Extended Kalman filter method estimation power battery:
S21, algorithm calculating start, and the SOC and error co-variance matrix of last stored can be read inside EEPROM；
S22 measures initial cell voltage, battery current, battery temperature；
S23 calculates initial state variable (including SOC and V1), initial error covariance square is set；
S24 measures cell voltage, battery current, battery temperature；
S25, setting up procedure noise parameters measure noise parameters (according at least to current offset value)；
S26 carries out the update of state parameter time according to above-mentioned formula (1)；
S27 carries out the update of error co-variance matrix time according to above-mentioned formula (3)；
S28 predicts output parameter cell voltage according to above-mentioned formula (2)；
S29 calculates kalman gain according to above-mentioned formula (4)；
S30 carries out state parameter according to above-mentioned formula (5) and measures update；
S31 carries out error co-variance matrix according to above-mentioned formula (6) and measures update；
S32, whether terminate, as (keyoff) electric under vehicle, calculating terminates if judging to calculate；
S33 is saved data (SOC and error co-variance matrix).
Wherein, in above-mentioned S25, process noise parameter and measure noise parameters, can according to current offset value and its
He is because being usually arranged.Fig. 4 is that the determination process noise parameter that an exemplary embodiment provides is shown with the process for measuring noise parameters
It is intended to.As shown in figure 4, process noise parameter and measurement noise parameters are determined according to current offset value, comprising:
Situation (1) if, current offset value be less than or equal to scheduled bias I0, it is battery balanced not open, and power electric
The temperature in pond is greater than or equal to preset temperature threshold T0, then process noise parameter is determined as scheduled first process noise and joined
Number Q1, and noise parameters will be measured and be determined as scheduled first measurement noise parameters r1.In the first process noise parameter Q1In, W1
With W2The ratio between for scheduled first ratio a1 wherein, W1For the process noise of state variable SOC (k), W2For state variable V1(k)
Process noise.
Wherein, current offset value is less than or equal to scheduled bias I0, it is battery balanced not open, and the temperature of power battery
Degree is greater than or equal to preset temperature threshold T0, it is believed that it is normal condition, for example, the first process noise can be set at this time
ParameterWherein, the first ratio a1=100, first measures noise parameters r1=2.
Situation (2), current offset value are greater than scheduled bias I0, then process noise parameter is determined as scheduled second
Process noise parameter Q2, and noise parameters will be measured and be determined as scheduled second measurement noise parameters r2.In the second process noise
Parameter Q2In, W1With W2The ratio between be determined as scheduled second ratio a2.Wherein, the second ratio a2 is greater than the first ratio a1, the second amount
It surveys noise parameters r2 and measures noise parameters r1 less than first.
It is greater than scheduled bias I in current offset value0When, illustrate electric current inaccuracy, it can be by increasing process
Noise, and reduce measurement noise, Lai Tigao SOC precision.W can be increased on the basis of above-mentioned normal condition at this time1With W2's
Ratio, while measurement noise parameters are reduced, to reduce the confidence level to current sensor, and improve the trust to battery model
Degree.For example, the second process noise parameter can be setWherein, the second ratio
A2=1000, second measures noise parameters r2=1.
Situation (3) if, current offset value be less than or equal to scheduled bias I0, and battery balanced unlatching, then by process
Noise parameters are determined as scheduled third process noise parameter Q3, and measurement noise parameters are determined as scheduled third measurement and are made an uproar
Sound parameter r3, in third process noise parameter Q3In, W1With W2The ratio between be determined as scheduled third ratio a3.Wherein, third ratio
Less than the first ratio a1, third measures noise parameters r3 and is greater than the first measurement noise parameters r1 a3.
If current offset value is less than or equal to scheduled bias I0, and when equilibrium, voltage inaccuracy can reduce
Process noise increases and measures noise, Lai Tigao SOC precision.At this time W can be reduced on the basis of above-mentioned normal condition1With W2
Ratio, while increasing measurement noise parameters, improve the confidence level to current sensor, and reduce the letter to voltage sensor
Rely degree.For example, third process noise parameter can be setWherein, third ratio
Example a3=20, third measure noise parameters r3=8.
Situation (4) if, current offset value be less than or equal to scheduled bias I0, it is battery balanced not open, and power electric
The temperature in pond is less than preset temperature threshold T0, then process noise parameter is determined as scheduled 4th process noise parameter Q4, and
Noise parameters will be measured and be determined as scheduled 4th measurement noise parameters r4, in the 4th process noise parameter Q4In, W1With W3The ratio between
It is determined as scheduled 4th ratio a4.Wherein, the 4th ratio a4 is less than the first ratio a1, and the 4th, which measures noise parameters r4, is greater than the
One measures noise parameters r1.
If current offset value is less than or equal to scheduled bias I0, battery balanced not open, the temperature of power battery is small
In preset temperature threshold T0, it may be considered that battery parameter is inaccurate, process noise is reduced, increases and measures noise, to mention
High SOC precision.At this time W can be reduced on the basis of above-mentioned normal condition1With W2Ratio, while increase measure noise ginseng
Number improves the confidence level to current sensor, and reduces the confidence level to battery model.For example, the 4th mistake can be set
Journey noise parametersWherein, third ratio a4=10, the 4th measures noise parameters r4
=4.
Wherein, can be without direct relationship between a2, a3, a4, it can also be without direct relationship between r2, r3, r4.
By it is above-mentioned to process noise parameter and measure noise parameters adjustment, reduce due to current sensor exist compared with
Error caused by high current biasing, battery balanced unlatching, temperature of powered cell are lower, so that SOC estimation precision is higher.
Fig. 5-8 is the flow chart of the evaluation method for the power battery SOC that four kinds of exemplary embodiments provide.Wherein, Fig. 5 shows
The embodiment of above situation (1) is gone out, Fig. 6 shows above situation (1)+situation (2) embodiment, and Fig. 7 shows above-mentioned feelings
Condition (1)+situation (3) embodiment, Fig. 8 show above situation (1)+situation (4) embodiment.
The disclosure also provides the estimation device of power battery SOC a kind of.Fig. 9 is the power electric that an exemplary embodiment provides
The block diagram of the estimation device of pond SOC.As shown in figure 9, the estimation device 10 of power battery SOC may include obtaining module 11 and estimating
Calculate module 12.
It obtains module 11 to be used to obtain the current value in power battery under uncharged and non-discharge scenario in power battery, make
For current offset value.
Estimation block 12 is used in power battery charging or discharge process, according to the equivalent-circuit model of power battery and
The SOC value of Extended Kalman filter method estimation power battery, wherein process noise parameter and measurement noise parameters are inclined according to electric current
Value is set to determine.
Figure 10 is the block diagram of the estimation device for the power battery SOC that another exemplary embodiment provides.In this embodiment,
Estimation block 12 may include the first determining submodule 121.
If first determines that submodule 121 is less than or equal to scheduled bias for current offset value, battery balanced not open
It opens, and the temperature of power battery is greater than or equal to preset temperature threshold, then process noise parameter is determined as scheduled first
Process noise parameter, and noise parameters will be measured and be determined as scheduled first measurement noise parameters, in the first process noise parameter
In, W1With W2The ratio between be scheduled first ratio, W1For the process noise of state variable SOC (k), SOC (k) is k moment power electric
The SOC value in pond, W2For state variable V1(k) process noise, V1It (k) is the voltage value at k moment first resistor both ends, wherein
In the equivalent-circuit model of power battery, connect after first resistor and capacitor parallel connection with second resistance, the circuit connection after series connection
At the both ends of power battery.
Figure 11 is the block diagram of the estimation device for the power battery SOC that another exemplary embodiment provides.In this embodiment,
On the basis of Figure 10, estimation block 12 can also include the second determining submodule 122.
If second determines that submodule 122 is greater than scheduled bias for current offset value, and process noise parameter is true
It is set to scheduled second process noise parameter, and noise parameters will be measured is determined as scheduled second and measure noise parameters, the
In two process noise parameters, W1With W2The ratio between be scheduled second ratio, the second ratio be greater than the first ratio, second measure noise
Parameter measures noise parameters less than first.
Figure 12 is the block diagram of the estimation device for the power battery SOC that another exemplary embodiment provides.In this embodiment,
On the basis of Figure 10, estimation block 12 can also include that third determines submodule 123.
If third determines that submodule 123 is less than or equal to scheduled bias for current offset value, and battery balanced opens
Open, then process noise parameter be determined as scheduled third process noise parameter, and will measure noise parameters be determined as it is scheduled
Third measures noise parameters, in third process noise parameter, W1With W2The ratio between be scheduled third ratio, third ratio is less than
First ratio, third measure noise parameters and are greater than the first measurement noise parameters.
Figure 13 is the block diagram of the estimation device for the power battery SOC that another exemplary embodiment provides.In this embodiment,
On the basis of Figure 10, estimation block 12 can also include the 4th determining submodule 124.
If the 4th determines that submodule 124 is less than or equal to scheduled bias for current offset value, battery balanced not open
It opens, and the temperature of power battery is less than preset temperature threshold, then process noise parameter is determined as scheduled 4th process and made an uproar
Sound parameter, and noise parameters will be measured and be determined as scheduled 4th measurement noise parameters, in the 4th process noise parameter, W1With
W2The ratio between be scheduled 4th ratio, less than the first ratio, the 4th measures noise parameters is greater than first and measures noise the 4th ratio
Parameter.
About the device in above-described embodiment, wherein modules execute the concrete mode of operation in related this method
Embodiment in be described in detail, no detailed explanation will be given here.
Through the above technical solutions, dynamic being estimated according to the equivalent-circuit model and Extended Kalman filter method of power battery
When the SOC value of power battery, process noise parameter is adjusted according to current offset value and measures noise parameters.In such manner, it is possible to according to
The error of the SOC as caused by current offset value is corrected to a certain extent, to keep the estimation of power battery SOC more acurrate.
The disclosure also provides a kind of vehicle, the estimation device 10 including the above-mentioned power battery SOC that the disclosure provides.
Figure 14 is the block diagram of a kind of electronic equipment shown in an exemplary embodiment.As shown in figure 14, the electronic equipment
1400 may include: processor 1401, memory 1402.The electronic equipment 1400 can also include multimedia component 1403, defeated
Enter/export one or more of (I/O) interface 1404 and communication component 1405.
Wherein, processor 1401 is used to control the integrated operation of the electronic equipment 1400, to complete above-mentioned power battery
All or part of the steps in the evaluation method of SOC.Memory 1402 is for storing various types of data to support in the electricity
The operation of sub- equipment 1400, these data for example may include any application program for operating on the electronic equipment 1400
Or the instruction and the relevant data of application program of method, such as contact data, the message of transmitting-receiving, picture, audio, video
Etc..The memory 1402 can realize by any kind of volatibility or non-volatile memory device or their combination,
Such as static random access memory (Static Random Access Memory, abbreviation SRAM), electrically erasable is only
It reads memory (Electrically Erasable Programmable Read-Only Memory, abbreviation EEPROM), it is erasable
Except programmable read only memory (Erasable Programmable Read-Only Memory, abbreviation EPROM), may be programmed only
It reads memory (Programmable Read-Only Memory, abbreviation PROM), read-only memory (Read-Only Memory,
Abbreviation ROM), magnetic memory, flash memory, disk or CD.Multimedia component 1403 may include screen and audio component.
Wherein screen for example can be touch screen, and audio component is used for output and/or input audio signal.For example, audio component can be with
Including a microphone, microphone is for receiving external audio signal.The received audio signal can be further stored in
Memory 1402 is sent by communication component 1405.Audio component further includes at least one loudspeaker, for exporting audio letter
Number.I/O interface 1404 provides interface between processor 1401 and other interface modules, other above-mentioned interface modules can be key
Disk, mouse, button etc..These buttons can be virtual push button or entity button.Communication component 1405 is used for the electronic equipment
Wired or wireless communication is carried out between 1400 and other equipment.Wireless communication, such as Wi-Fi, bluetooth, near-field communication (Near
Field Communication, abbreviation NFC), 2G, 3G, 4G, NB-IOT, eMTC or other 5G etc. or they one of
Or several combinations, it is not limited here.Therefore the corresponding communication component 1405 may include: Wi-Fi module, bluetooth mould
Block, NFC module etc..
In one exemplary embodiment, electronic equipment 1400 can be by one or more application specific integrated circuit
(Application Specific Integrated Circuit, abbreviation ASIC), digital signal processor (Digital
Signal Processor, abbreviation DSP), digital signal processing appts (Digital Signal Processing Device,
Abbreviation DSPD), programmable logic device (Programmable Logic Device, abbreviation PLD), field programmable gate array
(Field Programmable Gate Array, abbreviation FPGA), controller, microcontroller, microprocessor or other electronics member
Part is realized, for executing the evaluation method of above-mentioned power battery SOC.
In a further exemplary embodiment, a kind of computer readable storage medium including program instruction is additionally provided, it should
The step of evaluation method of above-mentioned power battery SOC is realized when program instruction is executed by processor.For example, this is computer-readable
Storage medium can be the above-mentioned memory 1402 including program instruction, and above procedure instruction can be by the processing of electronic equipment 1400
Device 1401 is executed to complete the evaluation method of above-mentioned power battery SOC.
The preferred embodiment of the disclosure is described in detail in conjunction with attached drawing above, still, the disclosure is not limited to above-mentioned reality
The detail in mode is applied, in the range of the technology design of the disclosure, a variety of letters can be carried out to the technical solution of the disclosure
Monotropic type, these simple variants belong to the protection scope of the disclosure.
It is further to note that specific technical features described in the above specific embodiments, in not lance
In the case where shield, it can be combined in any appropriate way.In order to avoid unnecessary repetition, the disclosure to it is various can
No further explanation will be given for the combination of energy.
In addition, any combination can also be carried out between a variety of different embodiments of the disclosure, as long as it is without prejudice to originally
Disclosed thought equally should be considered as disclosure disclosure of that.
Claims (11)
1. a kind of evaluation method of power battery SOC, which is characterized in that the described method includes:
The current value in the power battery under uncharged and non-discharge scenario in the power battery is obtained, as current offset
Value；
In the power battery charging or discharge process, according to the equivalent-circuit model and spreading kalman of the power battery
Filter method estimates the SOC value of the power battery, wherein process noise parameter and measurement noise parameters are according to the current offset
Value determines.
2. the method according to claim 1, wherein process noise parameter and measurement noise parameters are according to the electricity
Bias is flowed to determine, comprising:
If the current offset value is less than or equal to scheduled bias, battery balanced not open, and the temperature of the power battery
Degree is greater than or equal to preset temperature threshold, then the process noise parameter is determined as scheduled first process noise parameter,
And the measurement noise parameters are determined as scheduled first and measure noise parameters, in the first process noise parameter, W1
With W2The ratio between be scheduled first ratio, W1For the process noise of state variable SOC (k), SOC (k) is power electric described in the k moment
The SOC value in pond, W2For state variable V1(k) process noise, V1It (k) is the voltage value at k moment first resistor both ends, wherein
In the equivalent-circuit model of the power battery, connect after the first resistor and capacitor parallel connection with second resistance, after series connection
It is electrically connected to the both ends of the power battery.
3. according to the method described in claim 2, it is characterized in that, process noise parameter and measurement noise parameters are according to the electricity
Bias is flowed to determine, further includes:
If the current offset value is greater than the scheduled bias, the process noise parameter is determined as scheduled second
Process noise parameter, and the measurement noise parameters are determined as scheduled second and measure noise parameters, in second process
In noise parameters, W1With W2The ratio between be scheduled second ratio, second ratio be greater than first ratio, second amount
It surveys noise parameters and is less than the first measurement noise parameters.
4. according to the method described in claim 2, it is characterized in that, process noise parameter and measurement noise parameters are according to the electricity
Bias is flowed to determine, further includes:
If the current offset value is less than or equal to the scheduled bias, and battery balanced unlatching, then the process is made an uproar
Sound parameter is determined as scheduled third process noise parameter, and the measurement noise parameters are determined as scheduled third measurement and are made an uproar
Sound parameter, in the third process noise parameter, W1With W2The ratio between be scheduled third ratio, the third ratio be less than institute
The first ratio is stated, the third measures noise parameters and is greater than the first measurement noise parameters.
5. according to the method described in claim 2, it is characterized in that, process noise parameter and measurement noise parameters are according to the electricity
Bias is flowed to determine, further includes:
If the current offset value is less than or equal to the scheduled bias, battery balanced not open, and the power battery
Temperature be less than the preset temperature threshold, then the process noise parameter is determined as scheduled 4th process noise and joined
Number, and the measurement noise parameters are determined as the scheduled 4th and measure noise parameters, in the 4th process noise parameter,
W1With W2The ratio between be scheduled 4th ratio, the 4th ratio be less than first ratio, it is described 4th measure noise parameters it is big
Noise parameters are measured in described first.
6. a kind of estimation device of power battery SOC, which is characterized in that described device includes:
Module is obtained, for obtaining the electric current in the power battery under uncharged and non-discharge scenario in the power battery
Value, as current offset value；
Estimation block is used in the power battery charging or discharge process, according to the equivalent circuit mould of the power battery
Type and Extended Kalman filter method estimate the SOC value of the power battery, wherein process noise parameter and measurement noise parameters root
It is determined according to the current offset value.
7. device according to claim 6, which is characterized in that the estimation block includes:
First determines submodule, battery balanced not open if being less than or equal to scheduled bias for the current offset value,
And the temperature of the power battery is greater than or equal to preset temperature threshold, then is determined as the process noise parameter scheduled
First process noise parameter, and the measurement noise parameters are determined as scheduled first and measure noise parameters, described first
In process noise parameter, W1With W2The ratio between be scheduled first ratio, W1For the process noise of state variable SOC (k), SOC (k)
For the SOC value of power battery described in the k moment, W2For state variable V1(k) process noise, V1It (k) is k moment first resistor two
The voltage value at end, wherein in the equivalent-circuit model of the power battery, with second after the first resistor and capacitor are in parallel
Resistance series connection, the both ends for being electrically connected to the power battery after series connection.
8. device according to claim 7, which is characterized in that the estimation block further include:
Second determines submodule, if being greater than the scheduled bias for the current offset value, by the process noise
Parameter is determined as scheduled second process noise parameter, and the measurement noise parameters are determined as scheduled second and measure noise
Parameter, in the second process noise parameter, W1With W2The ratio between be scheduled second ratio, second ratio is greater than described
First ratio, described second, which measures noise parameters, is less than the first measurement noise parameters.
9. device according to claim 7, which is characterized in that the estimation block further include:
Third determines submodule, if being less than or equal to the scheduled bias for the current offset value, and battery balanced
It opens, then the process noise parameter is determined as scheduled third process noise parameter, and the measurement noise parameters are true
It is set to scheduled third and measures noise parameters, in the third process noise parameter, W1With W2The ratio between be scheduled third ratio
Example, the third ratio are less than first ratio, and the third measures noise parameters and is greater than the first measurement noise parameters.
10. device according to claim 7, which is characterized in that the estimation block further include:
4th determine submodule, if for the current offset value be less than or equal to the scheduled bias, it is battery balanced not
It opens, and the temperature of the power battery is less than the preset temperature threshold, then is determined as the process noise parameter pre-
The 4th fixed process noise parameter, and the measurement noise parameters are determined as the scheduled 4th and measure noise parameters, described
In 4th process noise parameter, W1With W2The ratio between be scheduled 4th ratio, the 4th ratio be less than first ratio, institute
It states the 4th measurement noise parameters and is greater than the first measurement noise parameters.
11. a kind of vehicle, which is characterized in that including power battery SOC's described in any claim in claim 6-10
Estimate device.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110873841A (en) * | 2019-11-05 | 2020-03-10 | 北京匠芯电池科技有限公司 | Battery life prediction method based on combination of data driving and battery characteristics |
| CN114301135A (en) * | 2021-12-30 | 2022-04-08 | 西安领充创享新能源科技有限公司 | Charging and discharging control method and device for charging and discharging pile, main control unit and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140218040A1 (en) * | 2013-02-01 | 2014-08-07 | Samsung Sdi Co., Ltd. | Method for estimating the state of charge of a battery, and battery management system using the method |
| CN107192961A (en) * | 2017-07-12 | 2017-09-22 | 江苏维科新能源科技有限公司 | Novel power battery SOC estimation method |
| CN108490356A (en) * | 2018-03-06 | 2018-09-04 | 福建工程学院 | A kind of lithium battery SOC estimation method for improving EKF algorithms |
| WO2019074221A1 (en) * | 2017-10-10 | 2019-04-18 | 주식회사 엘지화학 | Apparatus for estimating state-of-charge of secondary battery and method thereof |
| CN109895657A (en) * | 2019-03-22 | 2019-06-18 | 芜湖职业技术学院 | A kind of power battery SOC estimation device, automobile and method |
-
2019
- 2019-07-23 CN CN201910667738.6A patent/CN110333456A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140218040A1 (en) * | 2013-02-01 | 2014-08-07 | Samsung Sdi Co., Ltd. | Method for estimating the state of charge of a battery, and battery management system using the method |
| CN107192961A (en) * | 2017-07-12 | 2017-09-22 | 江苏维科新能源科技有限公司 | Novel power battery SOC estimation method |
| WO2019074221A1 (en) * | 2017-10-10 | 2019-04-18 | 주식회사 엘지화학 | Apparatus for estimating state-of-charge of secondary battery and method thereof |
| CN108490356A (en) * | 2018-03-06 | 2018-09-04 | 福建工程学院 | A kind of lithium battery SOC estimation method for improving EKF algorithms |
| CN109895657A (en) * | 2019-03-22 | 2019-06-18 | 芜湖职业技术学院 | A kind of power battery SOC estimation device, automobile and method |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110873841A (en) * | 2019-11-05 | 2020-03-10 | 北京匠芯电池科技有限公司 | Battery life prediction method based on combination of data driving and battery characteristics |
| CN110873841B (en) * | 2019-11-05 | 2021-12-07 | 蓝谷智慧(北京)能源科技有限公司 | Battery life prediction method based on combination of data driving and battery characteristics |
| CN114301135A (en) * | 2021-12-30 | 2022-04-08 | 西安领充创享新能源科技有限公司 | Charging and discharging control method and device for charging and discharging pile, main control unit and storage medium |
| CN114301135B (en) * | 2021-12-30 | 2023-09-26 | 西安领充创享新能源科技有限公司 | Charging and discharging control method and device for charging and discharging pile, main control unit and storage medium |
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