CN107958136A - A kind of battery model construction method, system and device based on model migration - Google Patents
A kind of battery model construction method, system and device based on model migration Download PDFInfo
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- CN107958136A CN107958136A CN201711189810.6A CN201711189810A CN107958136A CN 107958136 A CN107958136 A CN 107958136A CN 201711189810 A CN201711189810 A CN 201711189810A CN 107958136 A CN107958136 A CN 107958136A
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Abstract
The invention discloses a kind of battery model construction method, system and device based on model migration, method includes building benchmark model according to test experiment data；Conversion process is carried out to benchmark model according to some experimental data of target battery, obtains the complete model of target battery；System includes benchmark model structure module and object module structure module；Device includes memory and processor.The present invention builds benchmark model by test experiment data, then conversion process is carried out to benchmark model according to some experimental data of target battery, obtain the complete model of target battery, present invention only requires the complete model construction that the experimental data using part carries out target battery, the time cost of model construction is greatly reduced；In addition, the complete model for the target battery that the present invention is built, substantially increases model accuracy, ensure that the reliability of battery management system.It the composite can be widely applied to prediction model field.
Description
Technical field
The present invention relates to model construction field, especially a kind of battery model construction method based on model migration, system
And device.
Background technology
Existing charging battery of electric vehicle technology is divided into two major classes, and one kind is directly to charge to the battery on car, is filled
Between when the electric time is generally small to 10 when 2 is small；Another kind of is to remove the battery that electricity on car exhausts, and is charged by charging station,
And the battery of electricity is filled with charging station replacement.Compared to the method for plug-in, the scheme of battery is replaced in charging station
Substantially have the characteristics that efficiently quick.But for electric automobile, due to having replaced new battery, the argument section of battery or
All unknown, this can seriously affect protection of the battery management system to battery, using optimization and the decision-making of course continuation mileage or comment
Estimate ability.
In general, a models that are accurate, considering different use environments are established to target battery, it is necessary to up to several weeks reality
Test the cycle, time cost is very high；And if merely using the battery model that manufacturer provides when dispatching from the factory, its model accuracy is poor,
Especially when cell degradation is serious, it cannot be used substantially by the use of the initial model of battery as battery protection, control and optimization
Criterion.Therefore, full working scope (especially total temperature scope and full aging zone) model of a battery is built, to improving cell tube
The reliability of reason system has vital effect.
The content of the invention
In order to solve the above technical problems, first purpose of the present invention is：There is provided that a kind of time cost is low, precision is high and
Reliability is high, the battery model construction method based on model migration.
Second object of the present invention is：There is provided that a kind of time cost is low, precision is high and reliability is high, based on model
The battery model structure system of migration.
Third object of the present invention is：There is provided that a kind of time cost is low, precision is high and reliability is high, based on model
The battery model construction device of migration.
First technical solution being taken of the present invention be：
A kind of battery model construction method based on model migration, comprises the following steps：
Benchmark model is built according to test experiment data；
Conversion process is carried out to benchmark model according to some experimental data of target battery, obtains the complete mould of target battery
Type；
Wherein, some experimental data refers to a part of data rather than total data in all experimentss data.
Further, described the step for building benchmark model according to test experiment data, comprise the following steps：
By test experiment, battery data is obtained；
According to the battery data of acquisition, the benchmark model of battery is established using off-line modeling method.
Further, the benchmark model of the battery includes any of interpolation model and neural network model.
Further, some experimental data according to target battery carries out conversion process to benchmark model, obtains target
The step for complete model of battery, comprise the following steps：
Obtain some experimental data of target battery；
According to some experimental data of acquisition, conversion process is carried out to benchmark model；
According to the benchmark model after conversion process, the complete model parameter of target battery is calculated；
The complete model of target battery is built according to the complete model parameter of calculating.
Further, the step for some experimental data of the acquisition target battery, comprise the following steps：
Respectively according to temperature of the target battery in charging stage and service stage, using coulomb integration method or Kalman filtering
Method calculates corresponding state-of-charge；
According to the temperature and state-of-charge of target battery, the DC internal resistance of target battery is calculated.
Further, the experimental data according to acquisition, to benchmark model carry out conversion process the step for, be specially：
According to the experimental data of acquisition, benchmark model is become using linear transformation method or neutral net approximating method
Change processing.
Further, the benchmark model according to after conversion process, calculates the complete model parameter of target battery this step
Suddenly, it is specially：
The complete model parameter of target battery is calculated using linear transformation method, the calculation formula of the model parameter is：
R=f (T, SOC)+a*T+b*SOC+c, wherein, a, b and c are three model parameters to be solved, and a represents temperature system
Number, b represent state-of-charge coefficient, and c is constant, represents the fixation difference of performance between target battery and reference battery, and r represents direct current
Internal resistance, T represent the temperature of target battery, and SOC represents the state-of-charge of target battery, the mathematical description function of model on the basis of f.
Further, the step for some experimental data of the acquisition target battery, the temperature according to target battery is further included
Degree and state-of-charge, the step for calculating the polarization resistance and polarization capacity of target battery.
Second technical solution that the present invention takes be：
A kind of battery model based on model migration builds system, including：
Benchmark model builds module, for building benchmark model according to test experiment data；
Complete model construction module, carries out at conversion benchmark model for some experimental data according to target battery
Reason, obtains the complete model of target battery；
Wherein, some experimental data refers to a part of data rather than total data in all experimentss data.
The 3rd technical solution that the present invention takes be：
A kind of battery model construction device based on model migration, including：
Memory, for storage program；
Processor, loads described program, to perform a kind of electricity based on model migration as described in first technical solution
Pool model construction method.
The beneficial effects of the method for the present invention is：The method of the present invention builds benchmark model by test experiment data, so
Conversion process is carried out to benchmark model according to some experimental data of target battery afterwards, you can obtain the complete mould of target battery
Type, this method only need to carry out the complete model construction of target battery using the experimental data of part, greatly reduce model structure
The time cost built simultaneously improves work efficiency；In addition, the complete model of the target battery of this method structure contains target electricity
Whole real time datas in pond, substantially increase the reliability of model accuracy and battery management system.
The beneficial effect of system of the present invention is：The system of the present invention builds module construction benchmark mould by benchmark model
Type, then builds the complete model of module construction target battery by object module, and the system only needs the experimental data of part
The complete model construction of target battery is carried out, greatly reduces the time cost of model construction；In addition, the target of the system structure
The complete model of battery contains whole real time datas of target battery, substantially increases model accuracy and battery management system
Reliability.
The beneficial effect of the device of the invention is：The device of the invention builds benchmark model by processor, then leads to again
The complete model of processor structure target battery is crossed, the present apparatus only needs the experimental data of part to carry out the complete mould of target battery
Type is built, and compared to the experimental period that existing method is up to several weeks, greatly reduces the time cost of model construction；In addition, this
The complete model of the target battery of device structure contains whole real time datas of target battery, substantially increase model accuracy and
The reliability of battery management system.
Brief description of the drawings
Fig. 1 is a kind of step flow chart of the battery model construction method based on model migration of the present invention；
Fig. 2 is the distribution signal of target battery DC internal resistance under different temperatures and state-of-charge in the embodiment of the present invention one
Figure；
Fig. 3 is the distribution schematic diagram of target battery course continuation mileage at different temperatures in the embodiment of the present invention two.
Embodiment
With reference to Fig. 1, a kind of battery model construction method based on model migration, comprises the following steps：
Benchmark model is built according to test experiment data；
Conversion process is carried out to benchmark model according to some experimental data of target battery, obtains the complete mould of target battery
Type.
Wherein, the target battery refers to the new battery replaced during battery use, new battery with benchmark model
Battery properties it is close, but not fully identical, battery parameter is unknown, it is therefore desirable to new mould is built according to benchmark model
Type.The experimental data of the part refers under several different use conditions the model of (such as temperature and remaining capacity etc.)
Parameter information.The complete model (i.e. full working scope model) refers to, all experimentss data comprising target battery, one kind description
The model of battery characteristics.
It is further used as preferred embodiment, described the step for building benchmark model according to test experiment data, bag
Include following steps：
By test experiment, battery data is obtained；
According to the battery data of acquisition, the benchmark model of battery is established using off-line modeling method.
Wherein, the off-line modeling method refers to all experimentss data for by offline experiment, obtaining battery, extraction electricity
Pool model parameter under different specified conditions (such as battery temperature, battery dump energy etc.) change information.
Preferred embodiment is further used as, the benchmark model of the battery includes interpolation model and neural network model
Any of.
Preferred embodiment is further used as, some experimental data according to target battery carries out benchmark model
Conversion process, the step for obtaining the complete model of target battery, comprises the following steps：
Obtain some experimental data of target battery；
According to some experimental data of acquisition, conversion process is carried out to benchmark model；
According to the benchmark model after conversion process, the complete model parameter of target battery is calculated；
The complete model of target battery is built according to the complete model parameter of calculating.
Be further used as preferred embodiment, it is described obtain target battery some experimental data the step for, including
Following steps：
Respectively according to temperature of the target battery in charging stage and service stage, using coulomb integration method or Kalman filtering
Method calculates corresponding state-of-charge；
According to the temperature and state-of-charge of target battery, the DC internal resistance of target battery is calculated.
Preferred embodiment is further used as, the experimental data according to acquisition, carries out at conversion benchmark model
The step for reason, be specially：
According to the experimental data of acquisition, benchmark model is become using linear transformation method or neutral net approximating method
Change processing.
Preferred embodiment is further used as, the benchmark model according to after conversion process, calculates target battery
The step for complete model parameter, be specially：
The complete model parameter of target battery is calculated using linear transformation method, the calculation formula of the model parameter is：r
=f (T, SOC)+a*T+b*SOC+c, wherein, a, b and c are three model parameters to be solved, and a represents temperature coefficient, and b is represented
State-of-charge coefficient, c are constants, represent the fixation difference of performance between target battery and reference battery, and r represents DC internal resistance, T generations
The temperature of table target battery, SOC represent the state-of-charge of target battery, the mathematical description function of model on the basis of f.
Be further used as preferred embodiment, it is described obtain target battery some experimental data the step for, also wrap
The step for including the temperature and state-of-charge according to target battery, calculating the polarization resistance and polarization capacity of target battery.
Corresponding with the method for Fig. 1, a kind of battery model based on model migration of the present invention builds system, including：
Benchmark model builds module, for building benchmark model according to test experiment data；
Complete model construction module, carries out at conversion benchmark model for some experimental data according to target battery
Reason, obtains the complete model of target battery；
Wherein, some experimental data refers to a part of data rather than total data in all experimentss data.
It is corresponding with the method for Fig. 1, a kind of battery model construction device based on model migration of the present invention, including：
Memory, for storage program；
Processor, loads described program, to perform a kind of battery model structure side based on model migration as shown in Figure 1
Method.
The present invention is made further explanation and description with reference to Figure of description and specific embodiment.
Embodiment one
Due to protection of the battery management system to battery, using optimization and the decision-making of course continuation mileage or evaluation capacity very
Full working scope (especially total temperature scope and full aging zone) model of a battery is depended in big degree.It is and existing to target
Battery establishes the method for a model that is accurate, considering different use environments, it is necessary to up to the experimental period of several weeks, takes
Substantial amounts of time cost；If merely using the battery model that manufacturer provides when dispatching from the factory, its model accuracy is poor, especially works as electricity
When pond aging is serious, as battery protection, control and the criterion that use cannot be optimized by the use of the initial model of battery substantially.For
The above problem, the present invention propose a kind of battery model construction method, system and device based on model migration.The present invention passes through
Test experiment data build benchmark model, then carry out migration change to benchmark model according to some experimental data of target battery
Change, you can obtain the complete model of target battery, present invention only requires the complete of the experimental data structure target battery using part
Standby model, greatly reduces the time cost of model construction；In addition, the complete model of target battery that builds of the present invention compared to
The battery initial model that manufacturer provides, contains whole real time datas of target battery, substantially increases model accuracy, ensure that
The reliability of battery management system.
During replacing target battery, battery management system is stayed in car, in case of not replaced together with battery pack,
A kind of specific workflow of the battery model construction method based on model migration of the present invention comprises the following steps：
Step 1：Build benchmark model：According to use demand, a complete battery is established by the means of off-line modeling
Benchmark model.
DC internal resistance information of the present embodiment according to battery under different temperature in use (T) and state-of-charge (SOC), tool
The data of body benchmark model, can to the data not included in model as shown in Fig. 2, the storage mode of the model is look-up table
Tried to achieve using interpolation method, the expression formula of the model is：R=f (T, SOC), wherein, a kind of mathematical description of model, r on the basis of f
DC internal resistance is represented, T represents the temperature of target battery, and SOC represents the state-of-charge of target battery.
Step 2：Build the complete model of target battery.
The step, which can be specifically divided into, obtains experimental data and complete the two sub-steps of model of structure.
Wherein, the step for obtaining experimental data specifically includes following steps：
Target battery temperature when just starting to charge up is 10 degree, calculate at this time state-of-charge equal to 5%, according to temperature
DC internal resistance data when just starting to charge up that degree and state-of-charge calculate；
Target battery in charging process the state-of-charge of battery and temperature all can respective change, with the charging of pulse charge
Exemplified by method, can obtaining data of the battery under different temperatures and state-of-charge, (such as temperature is 35 degree, state-of-charge is
The DC internal resistance data that 50% DC internal resistance data and temperature are 25 degree, state-of-charge is 90%)；
Target battery is after charging complete, and the Wen Duxiajiang of battery returns to room temperature, is replaced on target vehicle, target
During vehicle launch, state-of-charge can be obtained 90%, DC internal resistance data of the temperature at 10 degree.
The step for building complete model be specially：
The complete model parameter of target battery is calculated using linear transformation method, the calculation formula of the model parameter is：
R=f (T, SOC)+a*T+b*SOC+c, wherein, a, b and c are three model parameters to be solved, and r is represented in direct current
Resistance, T represent the temperature of target battery, and SOC represents the state-of-charge of target battery, a kind of mathematical description of model on the basis of f.Should
At least can in the step for 3 unknown parameters are included in the calculation formula of model parameter, and experimental data is obtained in the present embodiment
4 groups of experimental datas for including temperature, state-of-charge and DC internal resistance are enough obtained, therefore the equation can solve, and can specifically use warp
The least square solution inconsistent equation group of allusion quotation is realized.
Then, the temperature and the DC internal resistance of state-of-charge not included in experimental data for target battery, Ke Yiyong
The above-mentioned model for having calculated parameter a, b and c is directly assessed.
Linear method in the present embodiment, can be taken by the nonlinear method of including but not limited to neutral net fitting etc.
Generation.
Similarly, the present invention can calculate polarization resistance and polarization capacity of the battery under the conditions of different temperatures and state-of-charge
Data, and then build the complete model of corresponding target battery.
Battery model data intactly typing of the present embodiment by target battery under different temperatures and state-of-charge (SOC)
Battery management system (BMS), when electric automobile replaces the battery without electricity in battery-exchange station, the present invention only needs to obtain new
A small amount of parameter of the battery of replacement, it is possible to battery of the battery under condition of different temperatures is calculated according to " benchmark model " and is joined
Number, without a large amount of extra experiments, reduces plenty of time cost and improves work efficiency.Since BMS can use mesh
The newest complete model of battery is marked, no matter all using the scheme of initial reference model compared to the battery to which kind of newness degree,
The reliability and control performance of vehicle can be all remarkably enhanced；Meanwhile battery management also can more precisely, so as to extend
The service life of battery pack.
Embodiment two
During replacing battery pack, battery management system also can battery pack be disassembled, in-car only leaves the situation of vehicle master control
Exemplified by, model building method of the present embodiment based on the present invention, there is provided a kind of to utilize the information recorded in battery management system
To estimate the scheme of the battery that is newly replaced maximum course continuation mileage under various circumstances, the program specifically includes following steps：
Step 1：Build benchmark model：According to use demand, a complete battery is established by the means of off-line modeling
Benchmark model.
The vehicle course continuation mileage information that the present embodiment is provided according to battery under different temperature in use (T), specific benchmark mould
The data of type are as shown in figure 3, the storage mode of the model is look-up table, to the data not included in model, using interpolation method
Try to achieve, the expression formula of the model is：D=f (T), wherein, D is the course continuation mileage information of vehicle, a kind of number of model on the basis of f
Description is learned, T represents the temperature of target battery.
Step 2：Build the complete model of target battery.
The step, which can be specifically divided into, obtains experimental data and complete the two sub-steps of model of structure.
Wherein, it is specially the step for acquisition experimental data：Battery management system provides the data of battery to be replaced
Vehicle master control, specifically includes the course continuation mileage data of the recent battery under different temperatures, such as in battery temperature is 20 degree and 30
Course continuation mileage data under the conditions of degree.
The step for building complete model be specially：
The complete model parameter of target battery, the calculation formula of the model parameter are calculated using the method for linear transformation
For：
D=f (T, SOC)+a*T+b, wherein, a and b are two model parameters to be solved, a kind of number of model on the basis of f
Description is learned, T represents the temperature of target battery, and SOC represents the state-of-charge of target battery, and D is course continuation mileage.The model parameter
2 groups of bags can be at least obtained in the step for 2 unknown parameters are included in calculation formula, and experimental data is obtained in the present embodiment
Temperature and the experimental data of course continuation mileage are included, therefore the equation can solve, and specifically be to solve for a linear equation in two unknowns group.
Then, can be by upper for the course continuation mileage of target battery (such as temperature be 0 degree or 60 degree) in extreme circumstances
State the model for having calculated parameter a and b directly to try to achieve, without carrying out extra experiment.
Linear method in the present embodiment, can be taken by the nonlinear method of including but not limited to neutral net fitting etc.
Generation.
Battery model data complete typing of the present embodiment by target battery under different temperatures and state-of-charge (SOC)
Battery management system (BMS), when electric automobile replaces the battery without electricity in battery-exchange station, the present invention only needs to obtain new
A small amount of parameter of the battery of replacement, it is possible to which the battery is calculated in the traveling under condition of different temperatures according to " benchmark model "
The performance indicators such as journey, maximum course continuation mileage scheme under various circumstances is provided for target battery, without a large amount of extra experiments,
Reduce plenty of time cost and improve work efficiency.Since BMS can use the newest complete model of target battery, compare
No matter all using the scheme of initial reference model in the battery to which kind of newness degree, the reliability and control performance of vehicle all can
It is remarkably enhanced；Meanwhile battery management also can more precisely, so as to extend the service life of battery pack.
Above is the preferable of the present invention is implemented to be illustrated, but the present invention is not limited to the embodiment, and it is ripe
A variety of equivalent variations or replacement can also be made on the premise of without prejudice to spirit of the invention by knowing those skilled in the art, this
Equivalent deformation or replacement are all contained in the application claim limited range a bit.
Claims (10)
- A kind of 1. battery model construction method based on model migration, it is characterised in that：Comprise the following steps：Benchmark model is built according to test experiment data；Conversion process is carried out to benchmark model according to some experimental data of target battery, obtains the complete model of target battery；Wherein, some experimental data refers to a part of data rather than total data in all experimentss data.
- A kind of 2. battery model construction method based on model migration according to claim 1, it is characterised in that：Described The step for building benchmark model according to test experiment data, comprises the following steps：By test experiment, battery data is obtained；According to the battery data of acquisition, the benchmark model of battery is established using off-line modeling method.
- A kind of 3. battery model construction method based on model migration according to claim 2, it is characterised in that：The electricity The benchmark model in pond includes any of interpolation model and neural network model.
- A kind of 4. battery model construction method based on model migration according to claim 1, it is characterised in that：Described Conversion process is carried out to benchmark model according to some experimental data of target battery, obtains the complete model of target battery this step Suddenly, comprise the following steps：Obtain some experimental data of target battery；According to some experimental data of acquisition, conversion process is carried out to benchmark model；According to the benchmark model after conversion process, the complete model parameter of target battery is calculated；The complete model of target battery is built according to the complete model parameter of calculating.
- A kind of 5. battery model construction method based on model migration according to claim 4, it is characterised in that：It is described to obtain The step for taking some experimental data of target battery, comprises the following steps：Respectively according to temperature of the target battery in charging stage and service stage, using coulomb integration method or Kalman filtering method meter Calculate corresponding state-of-charge；According to the temperature and state-of-charge of target battery, the DC internal resistance of target battery is calculated.
- A kind of 6. battery model construction method based on model migration according to claim 4, it is characterised in that：Described According to the experimental data of acquisition, the step for conversion process is carried out to benchmark model, it is specially：According to the experimental data of acquisition, benchmark model is carried out at conversion using linear transformation method or neutral net approximating method Reason.
- A kind of 7. battery model construction method based on model migration according to claim 4, it is characterised in that：Described According to the benchmark model after conversion process, the step for calculating the complete model parameter of target battery, it is specially：The complete model parameter of target battery is calculated using linear transformation method, the calculation formula of the model parameter is：R=f (T, SOC)+a*T+b*SOC+c, wherein, a, b and c are three model parameters to be solved, and a represents temperature coefficient, and b represents charged Coefficient of regime, c are constants, represent the fixation difference of performance between target battery and reference battery, and r represents DC internal resistance, and T represents mesh The temperature of battery is marked, SOC represents the state-of-charge of target battery, the mathematical description function of model on the basis of f.
- A kind of 8. battery model construction method based on model migration according to claim 5, it is characterised in that：It is described to obtain The step for taking some experimental data of target battery, further includes temperature and state-of-charge according to target battery, calculates target The step for polarization resistance and polarization capacity of battery.
- 9. a kind of battery model based on model migration builds system, it is characterised in that：Including：Benchmark model builds module, for building benchmark model according to test experiment data；Complete model construction module, carries out conversion process to benchmark model for some experimental data according to target battery, obtains To the complete model of target battery；Wherein, some experimental data refers to a part of data rather than total data in all experimentss data.
- A kind of 10. battery model construction device based on model migration, it is characterised in that：Including：Memory, for storage program；Processor, loads described program, to perform such as a kind of battery based on model migration of claim 1-8 any one of them Model building method.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109146115A (en) * | 2018-06-11 | 2019-01-04 | 广州市香港科大霍英东研究院 | Battery life predicting method, system and device based on model migration |
| WO2022170671A1 (en) * | 2021-02-10 | 2022-08-18 | 广州汽车集团股份有限公司 | Method and device for optimizing battery management system |
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