CN110806540B - Cell test data processing method, device, system and storage medium - Google Patents
Cell test data processing method, device, system and storage medium Download PDFInfo
- Publication number
- CN110806540B CN110806540B CN201810865974.4A CN201810865974A CN110806540B CN 110806540 B CN110806540 B CN 110806540B CN 201810865974 A CN201810865974 A CN 201810865974A CN 110806540 B CN110806540 B CN 110806540B
- Authority
- CN
- China
- Prior art keywords
- test data
- equivalent circuit
- battery cell
- open
- parameters
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000012360 testing method Methods 0.000 title claims abstract description 121
- 238000003672 processing method Methods 0.000 title claims abstract description 19
- 238000012545 processing Methods 0.000 claims abstract description 63
- 238000000034 method Methods 0.000 claims abstract description 45
- 238000004590 computer program Methods 0.000 claims description 20
- 238000007726 management method Methods 0.000 claims description 13
- 230000010287 polarization Effects 0.000 claims description 7
- 238000000605 extraction Methods 0.000 claims description 6
- 238000012546 transfer Methods 0.000 claims description 6
- 230000005540 biological transmission Effects 0.000 claims description 4
- 238000013524 data verification Methods 0.000 claims description 4
- 238000004422 calculation algorithm Methods 0.000 abstract description 35
- 238000011161 development Methods 0.000 abstract description 13
- 239000000284 extract Substances 0.000 abstract description 5
- 238000004458 analytical method Methods 0.000 abstract description 3
- 238000013075 data extraction Methods 0.000 abstract description 3
- 230000000284 resting effect Effects 0.000 abstract 2
- 238000010586 diagram Methods 0.000 description 9
- 238000007599 discharging Methods 0.000 description 5
- 238000013461 design Methods 0.000 description 4
- 230000003068 static effect Effects 0.000 description 4
- 238000012795 verification Methods 0.000 description 4
- 230000005611 electricity Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 2
- 230000001360 synchronised effect Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000013502 data validation Methods 0.000 description 1
- 210000001503 joint Anatomy 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
Images
Landscapes
- Tests Of Electric Status Of Batteries (AREA)
- Secondary Cells (AREA)
Abstract
本申请涉及一种电芯测试数据处理方法、装置、系统和存储介质，所述方法包括：对电芯测试数据进行处理，得到基本性能参数；对基本性能参数中的开路电压随静置时间变化曲线进行拟合，得到电芯等效电路模型参数，电芯测试数据处理方法不仅提取了电芯测试数据中的基本性能参数，还对基本性能参数中的开路电压静置时间变化曲线进行拟合分析得到电芯等效电路模型参数，因而为车载电池管理系统的均衡算法提供了更加全面且更加深入的参数，进而为均衡算法的开发提供了强有力的支持，加快了均衡算法的开发并提高了均衡算法的可靠性，而且避免了人工提取数据提高了电芯测试数据的处理效率。
The present application relates to a cell test data processing method, device, system and storage medium. The method includes: processing cell test data to obtain basic performance parameters; changing the open circuit voltage in the basic performance parameters with resting time The curve is fitted to obtain the model parameters of the equivalent circuit of the cell. The cell test data processing method not only extracts the basic performance parameters in the cell test data, but also fits the open-circuit voltage resting time variation curve in the basic performance parameters. The parameters of the cell equivalent circuit model are obtained by analysis, thus providing more comprehensive and in-depth parameters for the equalization algorithm of the vehicle battery management system, which in turn provides a strong support for the development of the equalization algorithm, which accelerates the development of the equalization algorithm and improves the The reliability of the equalization algorithm is improved, and manual data extraction is avoided to improve the processing efficiency of cell test data.
Description
Technical Field
The present application relates to the field of battery technologies, and in particular, to a method, an apparatus, a system, and a storage medium for processing electrical core test data.
Background
The material system and design of the battery cell are updated very quickly, and before the battery cell is actually put into use, a large number of tests, such as charge/discharge tests or open-circuit voltage tests at different multiplying powers, are required to be performed on the battery cell, and test data is processed to obtain battery cell performance data for supporting development of a control algorithm (e.g., a balancing algorithm) of a battery management system.
At present, methods for processing battery cell test data include manual extraction, excel tool extraction, and code extraction. However, in the implementation process, the inventor finds that at least the following problems exist in the conventional technology: the battery cell performance data obtained according to the traditional processing method cannot meet the requirements of a control algorithm of a battery management system and cannot support the development of the control algorithm.
Disclosure of Invention
In view of the foregoing, it is necessary to provide a cell test data processing method, device, system and storage medium capable of supporting development of a control algorithm of a battery management system.
In one aspect, an embodiment of the present invention provides a method for processing battery cell test data, including the following steps:
processing the cell test data to obtain basic performance parameters;
and fitting the open-circuit voltage variation curve along with the standing time in the basic performance parameters to obtain the battery cell equivalent circuit model parameters.
In one embodiment, the step of processing the cell test data to obtain the basic performance parameters includes;
performing feature extraction on the battery cell test data to obtain feature data;
and classifying the characteristic data to obtain basic performance parameters.
In one embodiment, the method further comprises the following steps:
transmitting the basic performance parameters and the cell equivalent circuit model parameters to a balancing module; the basic performance parameters and the cell equivalent circuit model parameters are used for indicating the equalization module to obtain characteristic parameters representing the cell characteristics.
In one embodiment, before the step of transmitting the basic performance parameters and the cell equivalent circuit model parameters to the balancing module, the method further includes:
verifying the prediction error of the battery cell equivalent circuit model parameter;
and if the prediction error is smaller than or equal to the preset threshold value, transmitting the parameters of the cell equivalent circuit model to the balancing module.
In one embodiment, the step of verifying the prediction error of the cell equivalent circuit model parameter includes:
obtaining the open-circuit voltage at any standing time according to a fitting relation obtained by fitting a curve of the open-circuit voltage changing along with the standing time;
obtaining a predicted electric quantity of the battery cell corresponding to the open-circuit voltage according to the open-circuit voltage and a curve of the open-circuit voltage in the basic performance parameters changing along with the electric quantity of the battery cell;
and taking the absolute value of the difference value between the predicted electric quantity of the electric core and the actually measured electric quantity of the electric core in the test data at the standing time as a prediction error.
In one embodiment, the method further comprises the following steps:
and if the prediction error is larger than the preset threshold value, acquiring the shortest standing time in the test data, and transmitting the shortest standing time to the balancing module.
In one embodiment, the step of fitting an open-circuit voltage variation curve along with standing time in the basic performance parameters to obtain cell equivalent circuit model parameters includes: and fitting the open-circuit voltage variation curve along with standing time in the basic performance parameters by adopting a least square method to obtain the parameters of the cell equivalent circuit model.
In one embodiment, the cell equivalent circuit model parameter is a zero-order equivalent circuit model parameter, a first-order equivalent circuit model parameter or a second-order equivalent circuit model parameter;
and when the core equivalent circuit model parameters are second-order equivalent circuit model parameters, the core equivalent circuit model parameters comprise charge transfer internal resistance, polarization internal resistance, charge transfer capacitance and polarization capacitance.
On the other hand, an embodiment of the present invention further provides a device for processing battery cell test data, including:
the data processing module is used for processing the battery cell test data to obtain basic performance parameters;
and the model parameter acquisition module is used for fitting an open-circuit voltage variation curve along with standing time in the basic performance parameters to obtain the battery cell equivalent circuit model parameters.
In another aspect, an embodiment of the present invention further provides an electrical core test data processing system, including electrical core test data processing equipment connected to a battery management system on a vehicle;
the battery cell test data processing equipment comprises a memory and a processor, wherein the memory stores a computer program, and the battery cell test data processing equipment is characterized in that the processor executes the computer program to realize the following steps:
processing the cell test data to obtain basic performance parameters;
and fitting the open-circuit voltage variation curve along with the standing time in the basic performance parameters to obtain the battery cell equivalent circuit model parameters.
In still another aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the following steps:
processing the cell test data to obtain basic performance parameters;
and fitting the open-circuit voltage variation curve along with the standing time in the basic performance parameters to obtain the battery cell equivalent circuit model parameters.
One of the above technical solutions has the following advantages and beneficial effects:
classifying the battery cell test data obtained by testing the battery cell to obtain basic performance parameters; the method for processing the battery cell test data not only extracts the basic performance parameters in the battery cell test data, but also performs fitting analysis on the open-circuit voltage standing time variation curve in the basic performance parameters to obtain the battery cell equivalent circuit model parameters, so that more comprehensive and deeper parameters are provided for the equalization algorithm of the vehicle-mounted battery management system, powerful support is provided for the development of the equalization algorithm, the development of the equalization algorithm is accelerated, the reliability of the equalization algorithm is improved, manual data extraction is avoided, and the processing efficiency of the battery cell test data is improved.
Drawings
Fig. 1 is a schematic diagram illustrating a parameter acquisition flow of a battery cell test data processing method according to an embodiment of the present invention;
fig. 2 is a schematic flow chart illustrating a transmission step of the method for processing cell test data according to the embodiment of the present invention;
fig. 3 is a schematic diagram illustrating a flow of verification steps of the method for processing battery cell test data according to an embodiment of the present invention;
fig. 4 is a first block diagram of a cell test data processing apparatus according to an embodiment of the present invention;
fig. 5 is a second block diagram of the cell test data processing apparatus according to the embodiment of the present invention;
fig. 6 is a third structural block diagram of the cell test data processing apparatus according to the embodiment of the present invention;
fig. 7 is a block diagram illustrating a data verification module in the electrical core test data processing apparatus according to an embodiment of the present invention;
fig. 8 is an internal structural diagram of a cell test data processing system according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
In order to solve the problem that the cell performance data obtained according to the conventional processing method cannot meet the requirement of the control algorithm of the battery management system and cannot support the development of the control algorithm, in an embodiment, as shown in fig. 1, a cell test data processing method is provided, which includes the following steps:
step S110, the cell test data is processed to obtain basic performance parameters.
The electric core test data is obtained by performing various tests on the electric core, and specifically includes test absolute time, test relative time per step, voltage, current, temperature, state signals (including charging, discharging, standing and stopping), electric quantity of the electric core, and the like.
The basic performance parameters are used for characterizing basic characteristics of the cell. The basic performance parameters are obtained by processing cell test data. For example, in one example, the step of processing the cell test data to obtain the basic performance parameters includes; performing feature extraction on the battery cell test data to obtain feature data; and classifying the characteristic data to obtain the basic performance parameters. Specifically, test data about the same test item in the battery cell test data is extracted and stored separately, so that characteristic data is obtained, the characteristic data is classified to obtain basic performance parameters, and the specific classification process can be as follows: a certain data in the characteristic data can be extracted as an abscissa, and another data can be used as an ordinate to draw a curve, for example, a curve of the open-circuit voltage in the basic performance parameter along with the electric quantity of the battery cell, that is, the open-circuit voltage is used as the ordinate, the electric quantity of the battery cell is used as the abscissa, and the corresponding relationship between the open-circuit voltage and the electric quantity of the battery cell can be determined by testing the absolute time. In addition, the characteristic data can be obtained by extracting two items of data in the characteristic data for operation, for example, the cell internal resistance in the basic performance parameters can be obtained by obtaining the ratio of the voltage difference to the current difference in the characteristic data. Further, the basic performance parameters include the cell internal resistance, the change curve of the open-circuit voltage with the cell electric quantity, the relationship between the cell capacity and the charge/discharge multiplying power and the temperature, the change curve of the open-circuit voltage with the standing time under different cell electric quantities, the open-circuit voltage under different charge/discharge multiplying powers, different temperatures and different cell electric quantities, and the like.
And step S120, fitting an open-circuit voltage variation curve along with standing time in the basic performance parameters to obtain the battery cell equivalent circuit model parameters.
And the cell equivalent circuit model parameters are parameters for constructing a cell model. The cell equivalent circuit model parameters and the basic performance parameters are used for representing the cell characteristics. The cell equivalent circuit model parameters are obtained by fitting a curve of open-circuit voltage changing along with standing time in the basic performance parameters. In one example, a least square method is adopted to fit an open-circuit voltage variation curve along with standing time in the basic performance parameters to obtain the battery cell equivalent circuit model parameters. Of course, other fitting methods may be adopted to fit the open-circuit voltage curve along with the standing time, which are not described herein.
Specifically, the cell equivalent circuit model parameter is a zero-order equivalent circuit model parameter, a first-order equivalent circuit model parameter or a second-order equivalent circuit model parameter, and can be actually selected according to the requirement of an equalization algorithm in the battery management system on parameter precision. Further, when the cell equivalent circuit model parameters are second-order equivalent circuit model parameters, the cell equivalent circuit model parameters include charge transfer internal resistance, polarization internal resistance, charge transfer capacitance, and polarization capacitance. In one example, it is verified whether the cell equivalent circuit model parameter meets the condition for developing the equalization algorithm, and specifically, when it is determined that the sum of squares of the cell equivalent circuit model parameter obtained by fitting and the cell equivalent circuit model parameter in the actual working state of the cell is smaller than a given threshold, it is determined that the cell equivalent circuit model parameter obtained by fitting meets the condition for developing the equalization module.
The battery cell test data processing method classifies the battery cell test data obtained by various tests of the battery cell to obtain basic performance parameters; the method for processing the battery cell test data not only extracts the basic performance parameters in the battery cell test data, but also performs fitting analysis on the open-circuit voltage standing time variation curve in the basic performance parameters to obtain the battery cell equivalent circuit model parameters, so that more comprehensive and deeper parameters are provided for the equalization algorithm of the vehicle-mounted battery management system, powerful support is provided for the development of the equalization algorithm, the development of the equalization algorithm is accelerated, the reliability of the equalization algorithm is improved, manual data extraction is avoided, and the processing efficiency of the battery cell test data is improved.
In one embodiment, as shown in fig. 2, the cell test data processing method includes the steps of:
step S210, the cell test data is processed to obtain basic performance parameters.
And step S220, fitting an open-circuit voltage variation curve along with standing time in the basic performance parameters to obtain the battery cell equivalent circuit model parameters.
Step S230, transmitting the basic performance parameters and the battery cell equivalent circuit model parameters to a balancing module; the basic performance parameters and the cell equivalent circuit model parameters are used for indicating the equalization module to obtain characteristic parameters representing the cell characteristics.
The steps S210 and S220 are as described in the previous embodiment, and are not described herein again.
The equalizing module is arranged in a battery management system in a vehicle and used for ensuring that the voltage deviation of the battery cells in the battery pack is kept within an expected range, so that each single battery cell is kept in a similar state in normal use, and the condition of overcharge or overdischarge is avoided. Further, the balancing module comprises a balancing algorithm. Specifically, the basic performance parameters and the cell equivalent circuit parameters are transmitted to the equalization module, that is, the basic performance parameters and the cell equivalent circuit parameters are transmitted to the equalization module, and the basic performance parameters and the cell equivalent circuit parameters characterize the cell characteristics in the equalization algorithm, that is, the equalization algorithm obtains the relationship between the open-circuit voltage and the current of the cell and the relationship between the temperature and the electric quantity of the cell according to the basic performance parameters and the cell equivalent circuit parameters.
The specific working process of the balancing module is as follows: and the equalizing module predicts the predicted open-circuit voltage and the battery electric quantity of the battery cells of the vehicle in a running or stopping state according to the characteristic parameters obtained by the basic performance parameters and the battery cell equivalent circuit parameters, and controls the balance opening among the battery cells when the maximum value of the difference between the predicted open-circuit voltages of the battery cells in the battery pack is greater than a preset threshold value or the difference between the predicted electric quantities of the battery cells is greater than the preset threshold value.
According to the cell test data processing method, after the basic performance parameters and the cell equivalent circuit parameters are transmitted to the balancing module, the balancing module obtains the characteristic parameters representing the cell characteristics according to the basic performance parameters and the cell equivalent circuit parameters, and accordingly, the open-circuit voltage of the circuit is predicted, and the balance among the cells is accurately controlled. Just because the high-quality basic performance parameters and the cell equivalent circuit parameters are provided for the balancing module, the balancing module can be ensured to accurately predict the open-circuit voltage of the cells, and further, the balance among the cells is better ensured. In addition, the processing method of the cell test data is continuously changed due to different models adopted in the design of the equalization algorithm in the equalization module, and the cell test data processing method can deeply analyze the cell test data to obtain relevant model parameters according to the requirements of the equalization algorithm development, so that the design and development efficiency of the equalization algorithm is improved.
In one embodiment, before the step of transmitting the basic performance parameters and the cell equivalent circuit model parameters to the balancing module, the method further includes:
verifying the prediction error of the battery cell equivalent circuit model parameter;
and if the prediction error is smaller than or equal to the preset threshold value, transmitting the parameters of the cell equivalent circuit model to the balancing module.
And if the prediction error is larger than the preset threshold value, acquiring the shortest standing time in the test data, and transmitting the shortest standing time to the balancing module.
Before the parameters of the cell equivalent circuit model are transmitted to the equalization module, the prediction error of the parameters of the cell equivalent circuit model is required. In one example, different standing times can be selected as nodes for verifying the prediction error of the battery cell equivalent circuit model parameter, and the accuracy of the battery cell equivalent circuit model parameter is further ensured through multiple times of verification. In another example, different battery cell electricity quantity points at the same standing time can be selected as nodes for verifying prediction errors of the battery cell equivalent circuit model parameters, for example, 100% electricity quantity is divided into 20 charging steps, and each charging step is 5%, twenty electricity quantity points are divided: 5% and 10% … … 100.
Because the polarization phenomenon exists in the battery cell in the charging or discharging process, the open-circuit voltage of the battery cell can be gradually changed along with the extension of the standing time, so the shortest standing time is the time interval from the time when the battery cell is changed from charging or discharging to standing to the time when the open-circuit voltage tends to be stable.
According to the battery cell test data processing method, the prediction error of the battery cell equivalent circuit model parameter needs to be fully verified before the battery cell equivalent circuit model parameter is transmitted to the equalization algorithm, so that the design precision of the equalization algorithm is ensured.
In an embodiment, as shown in fig. 3, the step of verifying the prediction error of the cell equivalent circuit model parameter includes:
and 310, obtaining the fitted open-circuit voltage at any standing time according to the fitted relation obtained by fitting the curve of the open-circuit voltage changing along with the standing time.
In this embodiment, the electric quantity of the battery cell is used as a reference value for the prediction error determination, because the battery cell is not charged or discharged during the standing process of the battery cell, and the electric quantity of the battery cell is a constant value. Specifically, a fitting relationship is obtained by fitting a curve of the open-circuit voltage changing along with the standing time, any one of the fitting relationships is selected to be the standing time, and the open-circuit voltage under the standing time is obtained. In one example, a least squares fit may be used to fit a curve of open circuit voltage versus rest time.
And step 320, obtaining the predicted electric quantity of the battery cell corresponding to the fitted open-circuit voltage according to the open-circuit voltage and the change curve of the open-circuit voltage in the basic performance parameters along with the electric quantity of the battery cell.
The battery cell test data are processed, so that a curve of the open-circuit voltage changing along with the electric quantity of the battery cell can be obtained, and the fitted open-circuit voltage is substituted into the curve of the open-circuit voltage changing along with the electric quantity of the battery cell, so that the electric quantity of the battery cell corresponding to the fitted open-circuit voltage can be obtained.
And 330, taking the absolute value of the difference value between the predicted electric quantity of the electric core and the actually measured electric quantity of the electric core in the test data at the standing time as a prediction error.
According to the method for processing the battery cell test data, the accuracy of the battery cell equivalent circuit model parameters is verified by taking the battery cell electric quantity as the reference value, the accuracy of the verification process is ensured because the battery cell electric quantity is a constant value in the standing process, and the verification method is simple and easy to implement.
To further explain the scheme of each embodiment of the method for processing battery cell test data of the present invention, particularly taking the example of processing battery cell charging process data of the method for processing battery cell test data in practical application as an example, the implementation process of each embodiment of the present invention is described as follows:
specifically, when the state signal is identified to be converted from the static state to the charging state, the charging electric quantity in the process step is tracked until the state signal is converted from the charging state to the static state, the total charging electric quantity in the process step can be obtained through the electric quantity at the node of the corresponding step, and the voltage, the current and the temperature of the state signal when the state signal is converted from the charging state to the static state can also be obtained; when the state signal is converted from a charging state to a standing state and stands for a certain time (for example, 1 hour), the voltage of the battery cell is stable, the voltage of the battery cell after the working step stands for the certain time in the battery cell test data is extracted as an open-circuit voltage, a curve of the open-circuit voltage changing along with the standing time is recorded at the same time, and the charging electric quantity of each working step before the open-circuit voltage is counted to obtain the accumulated charging electric quantity of the battery cell as the electric quantity of the battery cell; after counting the cell test data in the charging process, a curve of the open-circuit voltage changing along with the electric quantity of the cell, the relationship between the capacity of the cell and the charging/discharging multiplying power and the temperature, a curve of the open-circuit voltage changing along with the standing time under different electric quantities, and the open-circuit voltage under different charging/discharging multiplying powers, different temperatures and different electric quantities of the cell can be obtained; converting the state signal from the charging signal into voltage and current in a standing state and open-circuit voltage after standing for a certain time, and taking the ratio of the difference value of the voltage and the open-circuit voltage to the current as the internal resistance of the cell;
according to the precision requirement of the equalization algorithm, different models can be selected, such as a zero-order equivalent circuit model, a first-order equivalent circuit model, a second-order equivalent circuit model and the like, and further, when the equalization algorithm adopts a second-order equivalent circuit model, a least square method is adopted to fit an open-circuit voltage and standing time change curve to obtain a battery cell equivalent circuit model parameter;
verifying the prediction error of the battery cell equivalent circuit model parameters, specifically, obtaining the fitted open-circuit voltage at any standing time according to the fitted relation obtained by fitting the open-circuit voltage variation curve along with the standing time; obtaining the predicted electric quantity of the battery cell corresponding to the fitted open-circuit voltage according to the change curve of the open-circuit voltage along with the electric quantity of the battery cell and the fitted open-circuit voltage; and taking the absolute value of the difference value between the predicted electric quantity of the electric core and the actually measured electric quantity of the electric core in the test data at the standing time as a prediction error.
The method for processing the battery cell test data can extract the basic performance parameters of the battery cell from the battery cell test data, simultaneously extracts the battery cell equivalent circuit model parameters of the butt joint equalization algorithm, and verifies the errors of the battery cell equivalent circuit model parameters, thereby providing an automatic self-energy processing method of the battery cell test data, providing more comprehensive and more accurate parameters for the equalization algorithm, and improving the development efficiency of the equalization algorithm.
It should be understood that although the various steps in the flow charts of fig. 1-3 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 1-3 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternating with other steps or at least some of the sub-steps or stages of other steps.
In one embodiment, as shown in fig. 4, there is provided a cell test data processing apparatus, including:
the data processing module 410 is configured to process the cell test data to obtain basic performance parameters;
and the model parameter obtaining module 420 is configured to fit an open-circuit voltage variation curve along with standing time in the basic performance parameters to obtain a cell equivalent circuit model parameter.
In an embodiment, as shown in fig. 5, a cell test data processing apparatus further includes:
the data transmission module 510 is configured to transmit the basic performance parameters and the cell equivalent circuit model parameters to the equalization module; the basic performance parameters and the cell equivalent circuit model parameters are used for indicating the equalization module to obtain characteristic parameters representing the cell characteristics.
In an embodiment, as shown in fig. 6, a cell test data processing apparatus further includes:
the data verification module 610 is used for verifying the prediction error of the battery cell equivalent circuit model parameter;
and a data transmission module 510, configured to transmit the cell equivalent circuit model parameter to the balancing module if the prediction error is smaller than or equal to a preset threshold.
In one embodiment, as shown in FIG. 7, the data validation module includes:
an open-circuit voltage obtaining unit 710, configured to obtain an open-circuit voltage at any standing time according to a fitting relationship obtained by fitting a curve of the open-circuit voltage changing with the standing time;
the electric quantity predicting unit 720 is used for obtaining the predicted electric quantity of the battery cell corresponding to the open-circuit voltage according to the open-circuit voltage and the change curve of the open-circuit voltage in the basic performance parameters along with the electric quantity of the battery cell;
the prediction error obtaining unit 730 is configured to use an absolute value of a difference between the predicted electric quantity of the battery cell and the actually measured electric quantity of the battery cell in the test data at the standing time as a prediction error.
For specific limitations of the cell test data processing apparatus, reference may be made to the above limitations of the cell test data processing method, which is not described herein again. All or part of each module in the battery cell test data processing device can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a cell test data processing system is provided, which includes a cell test data processing apparatus connected to a battery management system on a vehicle, wherein an internal structure diagram of the cell test data processing apparatus may be as shown in fig. 8. The battery cell test data processing equipment comprises a processor, a memory, a network interface and a database which are connected through a system bus. The processor of the cell test data processing equipment is used for providing calculation and control capacity. The memory of the battery cell test data processing equipment comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the battery cell test data processing equipment is used for storing battery cell test data, basic performance parameters and battery cell equivalent circuit model parameters. The network interface of the electric core test data processing equipment is used for being connected and communicated with a battery management system through a network, the battery management system comprises a balancing module, and the balancing module comprises a balancing algorithm. The computer program is executed by a processor to implement a method of processing cell test data.
It will be understood by those skilled in the art that the structure shown in fig. 8 is a block diagram of only a part of the structure related to the present application, and does not constitute a limitation to the cell test data processing apparatus to which the present application is applied, and a specific cell test data processing apparatus may include more or less components than those shown in the figure, or combine some components, or have a different arrangement of components.
In one embodiment, a cell test data processing apparatus is provided, which includes a memory and a processor, where the memory stores a computer program, and the processor implements the following steps when executing the computer program:
processing the cell test data to obtain basic performance parameters;
and fitting the open-circuit voltage variation curve along with the standing time in the basic performance parameters to obtain the battery cell equivalent circuit model parameters.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
transmitting the basic performance parameters and the cell equivalent circuit model parameters to a balancing module; the basic performance parameters and the cell equivalent circuit model parameters are used for indicating the equalization module to obtain characteristic parameters representing the cell characteristics.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
verifying the prediction error of the battery cell equivalent circuit model parameter;
and if the prediction error is smaller than or equal to the preset threshold value, transmitting the parameters of the cell equivalent circuit model to the balancing module.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
the step of verifying the prediction error of the battery cell equivalent circuit model parameters comprises the following steps:
obtaining the open-circuit voltage at any standing time according to a fitting relation obtained by fitting a curve of the open-circuit voltage changing along with the standing time;
obtaining a predicted electric quantity of the battery cell corresponding to the open-circuit voltage according to the open-circuit voltage and a curve of the open-circuit voltage in the basic performance parameters changing along with the electric quantity of the battery cell;
and taking the absolute value of the difference value between the predicted electric quantity of the electric core and the actually measured electric quantity of the electric core in the test data at the standing time as a prediction error.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
processing the cell test data to obtain basic performance parameters;
and fitting the open-circuit voltage variation curve along with the standing time in the basic performance parameters to obtain the battery cell equivalent circuit model parameters.
In one embodiment, the computer program when executed by the processor further performs the steps of:
transmitting the basic performance parameters and the cell equivalent circuit model parameters to a balancing module; the basic performance parameters and the cell equivalent circuit model parameters are used for indicating the equalization module to obtain characteristic parameters representing the cell characteristics.
In one embodiment, the computer program when executed by the processor further performs the steps of:
verifying the prediction error of the battery cell equivalent circuit model parameter;
and if the prediction error is smaller than or equal to the preset threshold value, transmitting the parameters of the cell equivalent circuit model to the balancing module.
In one embodiment, the computer program when executed by the processor further performs the steps of:
the step of verifying the prediction error of the battery cell equivalent circuit model parameters comprises the following steps:
obtaining the open-circuit voltage at any standing time according to a fitting relation obtained by fitting a curve of the open-circuit voltage changing along with the standing time;
obtaining a predicted electric quantity of the battery cell corresponding to the open-circuit voltage according to the open-circuit voltage and a curve of the open-circuit voltage in the basic performance parameters changing along with the electric quantity of the battery cell;
and taking the absolute value of the difference value between the predicted electric quantity of the electric core and the actually measured electric quantity of the electric core in the test data at the standing time as a prediction error.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A battery core test data processing method is characterized by comprising the following steps:
processing the cell test data to obtain basic performance parameters; transmitting the basic performance parameters to a balancing module;
fitting an open-circuit voltage variation curve along with standing time in the basic performance parameters to obtain a battery cell equivalent circuit model parameter;
verifying the prediction error of the battery cell equivalent circuit model parameter;
if the prediction error is smaller than or equal to a preset threshold value, transmitting the battery cell equivalent circuit model parameters to the balancing module; the basic performance parameters and the cell equivalent circuit model parameters are used for indicating the equalization module to obtain characteristic parameters representing the cell characteristics;
and if the prediction error is larger than a preset threshold value, acquiring the shortest standing time in the test data, and transmitting the shortest standing time to the balancing module.
2. The method according to claim 1, wherein the step of processing the cell test data to obtain the basic performance parameters includes:
performing feature extraction on the battery cell test data to obtain feature data;
and classifying the characteristic data to obtain the basic performance parameters.
3. The cell test data processing method according to claim 1 or 2, wherein the step of verifying the prediction error of the cell equivalent circuit model parameters includes:
obtaining the open-circuit voltage at any standing time according to a fitting relation obtained by fitting the curve of the open-circuit voltage changing along with the standing time;
obtaining a predicted electric quantity of the battery cell corresponding to the open-circuit voltage according to the open-circuit voltage and a curve of the open-circuit voltage in the basic performance parameters changing along with the electric quantity of the battery cell;
and taking the absolute value of the difference value between the predicted electric quantity of the electric core and the actually measured electric quantity of the electric core in the test data under the standing time as the prediction error.
4. The method according to claim 1, wherein the step of fitting an open-circuit voltage variation curve with standing time in the basic performance parameters to obtain cell equivalent circuit model parameters includes: and fitting the open-circuit voltage variation curve along with standing time in the basic performance parameters by adopting a least square method to obtain the battery cell equivalent circuit model parameters.
5. The method according to claim 1, wherein the cell equivalent circuit model parameter is a zero-order equivalent circuit model parameter, a first-order equivalent circuit model parameter, or a second-order equivalent circuit model parameter;
and when the core equivalent circuit model parameters are second-order equivalent circuit model parameters, the core equivalent circuit model parameters comprise charge transfer internal resistance, polarization internal resistance, charge transfer capacitance and polarization capacitance.
6. The utility model provides a battery cell test data processing apparatus which characterized in that includes:
the data processing module is used for processing the battery cell test data to obtain basic performance parameters;
the model parameter acquisition module is used for fitting an open-circuit voltage variation curve along with standing time in the basic performance parameters to obtain a battery cell equivalent circuit model parameter;
the data verification module is used for verifying the prediction error of the battery cell equivalent circuit model parameter;
the data transmission module is used for transmitting the basic performance parameters to the balancing module; if the prediction error is smaller than or equal to a preset threshold value, transmitting the battery cell equivalent circuit model parameters to the balancing module; the basic performance parameters and the cell equivalent circuit model parameters are used for indicating the equalization module to obtain characteristic parameters representing the cell characteristics; and if the prediction error is larger than a preset threshold value, acquiring the shortest standing time in the test data, and transmitting the shortest standing time to the balancing module.
7. The cell test data processing apparatus of claim 6,
the data processing module is used for extracting the characteristics of the battery cell test data to obtain characteristic data; and classifying the characteristic data to obtain the basic performance parameters.
8. The cell test data processing apparatus according to claim 6 or 7, wherein the data verification module includes:
the open-circuit voltage acquisition unit is used for acquiring the open-circuit voltage at any standing time according to a fitting relation obtained by fitting the curve of the open-circuit voltage changing along with the standing time;
the predicted electric quantity unit of the battery cell is used for obtaining the predicted electric quantity of the battery cell corresponding to the open-circuit voltage according to the open-circuit voltage and the change curve of the open-circuit voltage in the basic performance parameters along with the electric quantity of the battery cell;
and the prediction error acquisition unit is used for taking an absolute value of a difference value between the predicted electric quantity of the electric core and the actually measured electric quantity of the electric core in the test data under the standing time as the prediction error.
9. A kind of electric core tests the data handling system, including connecting the electric core of the battery management system on the vehicle to test the data handling equipment;
the cell test data processing device comprises a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 5 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810865974.4A CN110806540B (en) | 2018-08-01 | 2018-08-01 | Cell test data processing method, device, system and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810865974.4A CN110806540B (en) | 2018-08-01 | 2018-08-01 | Cell test data processing method, device, system and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110806540A CN110806540A (en) | 2020-02-18 |
| CN110806540B true CN110806540B (en) | 2021-03-19 |
Family
ID=69486782
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810865974.4A Active CN110806540B (en) | 2018-08-01 | 2018-08-01 | Cell test data processing method, device, system and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110806540B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112798901B (en) * | 2020-12-29 | 2023-01-10 | 成都沃特塞恩电子技术有限公司 | Equipment calibration system and method |
| CN114914491B (en) * | 2021-02-07 | 2024-03-26 | 广州汽车集团股份有限公司 | Fuel cell voltage monitoring method, device and computer storage medium |
| CN114720896B (en) * | 2022-02-28 | 2023-10-24 | 福建星云检测技术有限公司 | Battery test step identification method and system |
| CN115436823B (en) * | 2022-10-10 | 2023-07-04 | 深圳市卓讯达科技发展有限公司 | Battery cell testing method and testing equipment |
| CN118965852A (en) * | 2024-10-21 | 2024-11-15 | 云储新能源科技有限公司 | A method for generating large-scale battery data |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103887853A (en) * | 2014-03-18 | 2014-06-25 | 浙江大学城市学院 | Balance control method of lithium-ion battery set |
| CN105759212A (en) * | 2016-01-27 | 2016-07-13 | 惠州市蓝微新源技术有限公司 | Battery pack fault simulation method and fault detection method |
| CN105912807A (en) * | 2016-04-29 | 2016-08-31 | 惠州市蓝微新源技术有限公司 | Modeling method of power battery pack |
| CN107167741A (en) * | 2017-06-06 | 2017-09-15 | 浙江大学 | A kind of lithium battery SOC observation procedures based on neutral net |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP3455917B1 (en) * | 2016-05-13 | 2022-02-16 | Vito NV | Method and apparatus of a modular management system for energy storage cells |
| CN108663619B (en) * | 2017-03-27 | 2020-11-17 | 宁德时代新能源科技股份有限公司 | Method, device and equipment for determining battery working voltage curve |
-
2018
- 2018-08-01 CN CN201810865974.4A patent/CN110806540B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103887853A (en) * | 2014-03-18 | 2014-06-25 | 浙江大学城市学院 | Balance control method of lithium-ion battery set |
| CN105759212A (en) * | 2016-01-27 | 2016-07-13 | 惠州市蓝微新源技术有限公司 | Battery pack fault simulation method and fault detection method |
| CN105912807A (en) * | 2016-04-29 | 2016-08-31 | 惠州市蓝微新源技术有限公司 | Modeling method of power battery pack |
| CN107167741A (en) * | 2017-06-06 | 2017-09-15 | 浙江大学 | A kind of lithium battery SOC observation procedures based on neutral net |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110806540A (en) | 2020-02-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110806540B (en) | Cell test data processing method, device, system and storage medium | |
| US11408942B2 (en) | Method for predicting service life of retired power battery | |
| CN114072684B (en) | Characterizing rechargeable batteries on the server side | |
| CN108254696B (en) | Battery health state evaluation method and system | |
| Pan et al. | State of charge estimation of lithium-ion batteries using a grey extended Kalman filter and a novel open-circuit voltage model | |
| JP7497432B2 (en) | Battery performance prediction | |
| CN111448467B (en) | Method and system for modeling and estimating battery capacity | |
| CN107533105B (en) | Lithium-ion battery state of charge estimation method and device | |
| KR102343967B1 (en) | Method and apparatus for estimating state of battery | |
| CN118251603A (en) | Battery state of health estimation system, parameter extraction system and method for same | |
| JP6234946B2 (en) | Battery state estimation device | |
| CN110376536B (en) | SOH detection method and device for battery system, computer equipment and storage medium | |
| CN113111508B (en) | Evaluation method, device and server for consistency of battery cells | |
| CN109799463A (en) | The estimation and prediction technique of power battery SOC/SOH/SOP under actual operating mode based on big data method | |
| CN111175666A (en) | SOH detection method and device | |
| Sadabadi et al. | Model-based state of health estimation of a lead-acid battery using step-response and emulated in-situ vehicle data | |
| CN113777510A (en) | Method and device for estimating state of charge of lithium battery | |
| CN114994539A (en) | A method, device and system for detecting battery health status | |
| CN113589174A (en) | Method and device for predicting consistency of battery cells of lithium ion power battery system | |
| EP4311718A1 (en) | Method and a device for predicting state of health of battery, electronic equipment and readable storage medium | |
| CN113125965B (en) | Method, device and equipment for detecting lithium separation of battery and storage medium | |
| Petricca et al. | Automated generation of battery aging models from datasheets | |
| CN114264969A (en) | Method and device for evaluating self-discharge performance of battery cell | |
| CN108761347B (en) | Processing method and device and electronic equipment | |
| CN111856286A (en) | DP-RC model-based battery power estimation method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20211229 Address after: 511434 No. 36, Longying Road, Shilou Town, Panyu District, Guangzhou City, Guangdong Province Patentee after: GAC AION New Energy Vehicle Co.,Ltd. Address before: 510030 23 building, Cheng Yue mansion 448-458, Dongfeng Middle Road, Yuexiu District, Guangzhou, Guangdong. Patentee before: GUANGZHOU AUTOMOBILE GROUP Co.,Ltd. |
|
| TR01 | Transfer of patent right | ||
| CP03 | Change of name, title or address |
Address after: No. 36 Longying Road, Shilou Town, Panyu District, Guangzhou City, Guangdong Province Patentee after: GAC AION NEW ENERGY AUTOMOBILE Co.,Ltd. Country or region after: China Address before: No. 36 Longying Road, Shilou Town, Panyu District, Guangzhou City, Guangdong Province Patentee before: GAC AION New Energy Vehicle Co.,Ltd. Country or region before: China |
|
| CP03 | Change of name, title or address |