Battery voltage model construction method, battery voltage model, device and equipment

Abstract

The invention provides a construction method of a battery voltage model, the battery voltage model, a device and equipment. The method comprises the following steps: acquiring a candidate battery voltage model of a to-be-modeled battery object; acquiring a reference terminal voltage of the battery object; obtaining a historical battery parameter set of the battery object, and obtaining a measurement terminal voltage of the battery object based on the historical battery parameter set through the candidate battery voltage model; and adjusting and optimizing the candidate battery voltage model according to the reference terminal voltage and the measurement terminal voltage to obtain a target battery voltage model of the battery object. According to the method, the accuracy and the efficiency of the terminal voltage obtained by measuring and calculating the battery object through the target battery voltage model are improved, the measuring and calculating precision of the target battery voltage model is improved, accurate data support is provided for downstream tasks of the battery object, the precision and the efficiency of abnormal monitoring of the battery object are improved, and the reliability of abnormal monitoring of the battery object is improved. And the running safety and stability of the battery object are optimized.

Description

Technical Field

[0001] The present disclosure relates to the field of bionic robots, and in particular to a method for constructing a battery voltage model, a battery voltage model, a device and equipment. Background Art

[0002] With the development of technology, people can monitor the operating status of batteries through battery management systems to monitor battery abnormalities. A corresponding battery voltage model can be built for the battery to monitor battery abnormalities.

[0003] In the related art, the corresponding battery voltage model can be constructed through an equivalent circuit model, but the accuracy is poor if the model is only built through abstract circuit elements corresponding to the battery. Summary of the invention

[0004] The present disclosure aims to solve one of the technical problems in the related art at least to some extent.

[0005] To this end, the first aspect of the present disclosure proposes a method for constructing a battery voltage model.

[0006] A second aspect of the present disclosure provides a battery voltage model.

[0007] A third aspect of the present disclosure provides a device for constructing a battery voltage model.

[0008] A fourth aspect of the present disclosure provides an electronic device.

[0009] A fifth aspect of the present disclosure provides a computer-readable storage medium.

[0010] A first aspect of the present disclosure proposes a method for constructing a battery voltage model, the method comprising: obtaining a candidate battery voltage model of a battery object to be modeled; obtaining a reference terminal voltage of the battery object; obtaining a historical battery parameter set of the battery object, and obtaining a measured terminal voltage of the battery object based on the historical battery parameter set through the candidate battery voltage model; adjusting and optimizing the candidate battery voltage model according to the reference terminal voltage and the measured terminal voltage to obtain a target battery voltage model of the battery object.

[0011] In addition, the method for constructing the battery voltage model proposed in the first aspect of the present disclosure may also have the following additional technical features:

[0012] According to an embodiment of the present disclosure, obtaining the reference terminal voltage of the battery object includes: obtaining an open circuit voltage of the battery object in a scenario without an external load, and determining the open circuit voltage as the reference terminal voltage of the battery object.

[0013] According to an embodiment of the present disclosure, the acquiring of the historical battery parameter set of the battery object, and obtaining the calculated terminal voltage of the battery object based on the historical battery parameter set through the candidate battery voltage model, includes: acquiring the first historical current and the historical battery temperature of the battery object to obtain the historical battery parameter set of the battery object; acquiring the reference charge voltage curve graph of the battery object, and obtaining the calculated open circuit voltage of the battery object based on the first historical current and the reference charge voltage curve graph through the candidate battery voltage model, wherein the reference charge voltage curve graph is obtained based on the reference battery state of charge and the reference open circuit voltage of the battery object; acquiring the calculated voltage difference of the battery object based on the first historical current and the historical battery temperature of the battery object through the candidate battery voltage model; and obtaining the calculated terminal voltage of the battery object output by the candidate battery voltage model based on the calculated open circuit voltage and the calculated voltage difference.

[0014] According to an embodiment of the present disclosure, the method of obtaining a reference charge voltage curve graph of the battery object, and obtaining a calculated open circuit voltage of the battery object according to the first historical current and the reference charge voltage curve graph through the candidate battery voltage model, wherein the reference charge voltage curve graph is obtained based on a reference battery state of charge and a reference open circuit voltage of the battery object, comprises: obtaining a calculated ampere-hour integral of the battery object based on the first historical current through the candidate battery voltage model; obtaining a calculated battery state of charge of the battery object based on the calculated ampere-hour integral; and obtaining an open circuit voltage corresponding to the calculated battery state of charge from the reference charge voltage curve graph as the calculated open circuit voltage of the battery object under the calculated battery state of charge.

[0015] According to an embodiment of the present disclosure, the calculated voltage difference of the battery object is obtained through the candidate battery voltage model according to the first historical current and the historical battery temperature of the battery object, including: performing low-pass filtering on the first historical current to obtain a processed second historical current set; and obtaining the calculated voltage difference of the battery object based on the first historical current, the second historical current set, the historical battery temperature and the calculated battery state of charge through the candidate battery voltage model.

[0016] According to an embodiment of the present disclosure, the low-pass filtering of the first historical current to obtain a processed second historical current set includes: obtaining a low-pass filtering time constant set corresponding to the first historical current; based on each low-pass filtering time constant in the low-pass filtering time constant set, respectively low-pass filtering the first historical current to obtain each second historical current of the first historical current, so as to obtain the second historical current set.

[0017] According to one embodiment of the present disclosure, obtaining the measured terminal voltage of the battery object output by the candidate battery voltage model based on the measured open circuit voltage and the measured voltage difference includes: obtaining the sum of the measured open circuit voltage and the measured voltage difference, and demultiplexing the sum to convert it into the measured terminal voltage output by the candidate battery voltage model.

[0018] According to an embodiment of the present disclosure, the candidate battery voltage model is adjusted and optimized according to the reference terminal voltage and the measured terminal voltage to obtain the target battery voltage model of the battery object, including: obtaining a measurement error of the measured terminal voltage based on the reference terminal voltage; in response to the measurement error not falling within a preset error interval, adjusting and optimizing the candidate battery voltage model based on the measurement error until an adjustment and optimization termination condition is met, thereby terminating the adjustment and optimization of the candidate battery voltage model and obtaining the target battery voltage model of the battery object.

[0019] The second aspect of the present disclosure proposes a battery voltage model, comprising: a data input terminal, an ampere-hour integral extraction unit, a low-pass filter processing unit, a reference charged voltage curve query unit, a pressure difference acquisition unit, a summing unit and a data output terminal, wherein the output terminal of the ampere-hour integral extraction unit is connected to the input terminal of the reference charged voltage curve query unit, and the output terminal of the reference charged voltage curve query unit is connected to the input terminal of the summing unit; the output terminal of the low-pass filter processing unit is connected to the input terminal of the pressure difference acquisition unit, and the output terminal of the pressure difference acquisition unit is connected to the input terminal of the summing unit; the data input terminal is respectively connected to the input terminal of the ampere-hour integral extraction unit, the input terminal of the low-pass filter processing unit and the input terminal of the pressure difference acquisition unit; the output terminal of the summing unit is connected to the data output terminal; wherein the battery voltage model is obtained based on the battery voltage model construction method proposed in the first aspect.

[0020] The third aspect of the present disclosure proposes a device for constructing a battery voltage model, which includes: a first acquisition module, used to obtain a candidate battery voltage model of a battery object to be modeled; a second acquisition module, used to obtain a reference terminal voltage of the battery object; a third acquisition module, used to obtain a historical battery parameter set of the battery object, and obtain a measured terminal voltage of the battery object based on the historical battery parameter set through the candidate battery voltage model; and an adjustment module, used to adjust and optimize the candidate battery voltage model according to the reference terminal voltage and the measured terminal voltage, to obtain a target battery voltage model of the battery object.

[0021] In addition, the battery voltage model construction device proposed in the third aspect of the present disclosure may also have the following additional technical features:

[0022] According to an embodiment of the present disclosure, the second acquisition module is further used to: acquire the open circuit voltage of the battery object in a scenario without an external load, and determine the open circuit voltage as the reference terminal voltage of the battery object.

[0023] According to one embodiment of the present disclosure, the third acquisition module is further used to: acquire the first historical current and the historical battery temperature of the battery object to obtain the historical battery parameter set of the battery object; acquire the reference charge voltage curve graph of the battery object, and obtain the calculated open circuit voltage of the battery object according to the first historical current and the reference charge voltage curve graph through the candidate battery voltage model, wherein the reference charge voltage curve graph is obtained based on the reference battery state of charge and the reference open circuit voltage of the battery object; acquire the calculated pressure difference of the battery object according to the first historical current and the historical battery temperature of the battery object through the candidate battery voltage model; and obtain the calculated terminal voltage of the battery object output by the candidate battery voltage model based on the calculated open circuit voltage and the calculated pressure difference.

[0024] According to one embodiment of the present disclosure, the third acquisition module is further used to: obtain the calculated ampere-hour integral of the battery object based on the first historical current through the candidate battery voltage model; obtain the calculated battery state of charge of the battery object based on the calculated ampere-hour integral; and obtain the corresponding open circuit voltage of the calculated battery state of charge from the reference charge voltage curve as the calculated open circuit voltage of the battery object under the calculated battery state of charge.

[0025] According to one embodiment of the present disclosure, the third acquisition module is further used to: perform low-pass filtering on the first historical current to obtain a processed second historical current set; and obtain a calculated voltage difference of the battery object based on the first historical current, the second historical current set, the historical battery temperature and the calculated battery state of charge through the candidate battery voltage model.

[0026] According to one embodiment of the present disclosure, the third acquisition module is also used to: obtain a set of low-pass filter time constants corresponding to the first historical current; based on each low-pass filter time constant in the set of low-pass filter time constants, perform low-pass filtering on the first historical current respectively to obtain each second historical current of the first historical current, so as to obtain the second historical current set.

[0027] According to an embodiment of the present disclosure, the third acquisition module is further used to: obtain the sum of the measured open circuit voltage and the measured voltage difference, and convert the sum into the measured terminal voltage output by the candidate battery voltage model.

[0028] According to one embodiment of the present disclosure, the adjustment module is also used to: obtain a measurement error of the measured terminal voltage based on the reference terminal voltage; in response to the measurement error not falling within a preset error interval, adjust and optimize the candidate battery voltage model based on the measurement error until an adjustment and optimization termination condition is met, thereby terminating the adjustment and optimization of the candidate battery voltage model and obtaining the target battery voltage model of the battery object.

[0029] A fourth aspect of the present disclosure proposes an electronic device, comprising: a processor; a memory for storing executable instructions of the processor; wherein the processor is configured to execute instructions to implement the method for constructing a battery voltage model as proposed in the first aspect above.

[0030] A fifth aspect of the present disclosure proposes a computer-readable storage medium. When instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the method for constructing a battery voltage model as proposed in the first aspect above.

[0031] The method and device for constructing a battery voltage model proposed in the present disclosure obtain a candidate battery voltage model and a reference terminal voltage of a battery object, input a historical battery parameter set of the battery object into the candidate battery voltage model to obtain a measured terminal voltage of the battery object, and then adjust and optimize the candidate battery voltage model based on the measured terminal voltage and the reference terminal voltage, thereby obtaining a target battery voltage model of the battery object. In the present disclosure, the candidate battery voltage model is adjusted and optimized by the measured terminal voltage and the reference terminal voltage to obtain a target battery voltage model of the battery object, thereby improving the accuracy and efficiency of the measured terminal voltage obtained by the target battery voltage model for measuring the battery object, and compared with the battery voltage model obtained by modeling only through the abstract circuit elements corresponding to the battery in the related art, the measurement accuracy of the target battery voltage model is improved, and accurate data support is provided for the downstream tasks of the battery object. In the scenario of abnormal monitoring of the battery object based on the output result of the target battery voltage model, the accuracy and efficiency of abnormal monitoring of the battery object are improved, thereby improving the abnormal processing efficiency of the battery object, optimizing the safety and stability of the battery object operation, and optimizing the safety and stability of the system operation.

[0032] It should be understood that the contents described in the present disclosure are not intended to identify the key or important features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The above and / or additional aspects and advantages of the present disclosure will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0034] Figure 1 A schematic diagram of a process of constructing a battery voltage model according to an embodiment of the present disclosure;

[0035] Figure 2 A schematic diagram of a flow chart of a method for constructing a battery voltage model according to another embodiment of the present disclosure;

[0036] Figure 3 A schematic diagram of a flow chart of a method for constructing a battery voltage model according to another embodiment of the present disclosure;

[0037] Figure 4 is a schematic diagram of a battery voltage model according to an embodiment of the present disclosure;

[0038] Figure 5 (a) is a schematic diagram of inputting the target battery voltage model and the actual sampled values ​​of the current of the battery object during a 125-hour simulation experiment according to an embodiment of the present disclosure;

[0039] Figure 5 (b) is a schematic diagram of actual sampled values ​​of the SOC input into the target battery voltage model during a 125-hour simulation experiment according to an embodiment of the present disclosure;

[0040] Figure 5 (c) is a schematic diagram showing a comparison between a simulated terminal voltage output by a target battery voltage model and a collected value of an actual terminal voltage of a battery object corresponding to the target battery voltage model during a 125-hour simulation experiment of an embodiment of the present disclosure;

[0041] Figure 5 (d) is a schematic diagram of a single actual sampling value of the input target battery voltage model and the current of the battery object during a 125-hour simulation experiment according to an embodiment of the present disclosure;

[0042] Figure 5 (e) is a schematic diagram of a single actual sampling value of the SOC input into the target battery voltage model during a 125-hour simulation experiment according to an embodiment of the present disclosure;

[0043] Figure 5 (f) is a schematic diagram showing a comparison between a single simulated terminal voltage output by a target battery voltage model and a single acquired value of an actual terminal voltage of a battery object corresponding to the target battery voltage model during a 125-hour simulation experiment according to an embodiment of the present disclosure;

[0044] Figure 6 A schematic diagram of the structure of a device for constructing a battery voltage model according to an embodiment of the present disclosure;

[0045] Figure 7 A block diagram of an electronic device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0046] Embodiments of the present disclosure are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present disclosure, and should not be construed as limiting the present disclosure.

[0047] A method for constructing a battery voltage model, a battery voltage model, a device and an apparatus according to an embodiment of the present disclosure will be described below with reference to the accompanying drawings.

[0048] Figure 1 FIG. 1 is a flow chart of a method for constructing a battery voltage model according to an embodiment of the present disclosure. Figure 1 As shown, the method includes:

[0049] S101, obtaining a candidate battery voltage model of a battery object to be modeled.

[0050] During the daily operation of the system, the operating status of the battery needs to be monitored to improve the safety and stability of battery operation.

[0051] Optionally, a corresponding simulation model may be constructed for the battery to be monitored, and the operating state of the battery to be monitored may be evaluated by the operating state of the simulation model, wherein the battery for which the simulation model needs to be constructed may be marked as a battery object to be modeled.

[0052] In the disclosed embodiment, the charge state and remaining power and other related status information of the battery object can be obtained, so as to realize the evaluation of the operating status of the battery object. In this scenario, a corresponding battery voltage model can be constructed for the battery object, and the constructed battery voltage model can be adjusted and optimized to obtain a simulation model of the battery object.

[0053] The battery voltage model to be optimized may be marked as a candidate battery voltage model of the battery object.

[0054] S102, obtaining a reference terminal voltage of the battery object.

[0055] In the embodiment of the present disclosure, in the process of adjusting and optimizing the candidate battery voltage model, there is corresponding reference data, wherein the parameter data may include the terminal voltage of the battery object in a set scenario, and the terminal voltage may be marked as the reference terminal voltage of the battery object.

[0056] S103, obtaining a historical battery parameter set of the battery object, and obtaining a measured terminal voltage of the battery object based on the historical battery parameter set through a candidate battery voltage model.

[0057] In the disclosed embodiment, the measured data of the output of the candidate battery voltage model may be obtained, and the measured data and the obtained reference data may be compared and analyzed, and then the candidate battery voltage model may be adjusted and optimized according to the comparison and analysis results.

[0058] Optionally, the battery state parameters of the battery object within a historical time range can be obtained to obtain a historical battery parameter set of the battery object, and the historical battery parameter set is input into a candidate battery voltage model, and the historical battery parameter set is algorithmically processed by the candidate battery voltage model to obtain its output measurement result.

[0059] In the scenario where the candidate battery voltage model is adjusted based on the reference terminal voltage, the historical battery parameter set can be input into the candidate battery voltage model, and each historical battery parameter in the historical battery parameter set is algorithmically processed by the candidate battery voltage model to obtain the terminal voltage calculated by the candidate battery voltage model as its output measured terminal voltage.

[0060] S104, adjusting and optimizing the candidate battery voltage model according to the reference terminal voltage and the measurement terminal voltage to obtain a target battery voltage model of the battery object.

[0061] In the disclosed embodiment, the measurement terminal voltage can be compared with the reference terminal voltage to obtain the voltage distance between the measurement terminal voltage and the reference terminal voltage, and then the candidate battery voltage model of the output measurement terminal voltage can be identified based on the obtained voltage distance to determine whether it needs to be adjusted and optimized.

[0062] Optionally, when it is identified based on the comparison result that the candidate battery voltage model of the output measurement terminal voltage needs to be adjusted and optimized, a preset adjustment and optimization strategy for the candidate battery voltage model can be obtained, and the candidate battery voltage model can be adjusted and optimized according to the obtained adjustment and optimization strategy until the adjustment and optimization is completed.

[0063] Among them, the adjusted measured terminal voltage output by the adjusted and optimized candidate battery voltage model can be obtained. When it is identified that the adjusted candidate battery voltage model does not need to continue to be adjusted and optimized based on the voltage distance corresponding to the adjusted measured terminal voltage, it can be determined that the adjustment and optimization of the candidate battery voltage model is completed, and the model obtained after the adjustment and optimization can be determined as the target battery voltage model of the battery object.

[0064] In the disclosed embodiments, by adjusting the optimized target battery voltage model, the management and abnormality monitoring of the battery object can be realized. For example, the target battery voltage model can be configured in the battery management system (Battery Management System, BMS) of the battery object, so as to realize the monitoring and management of the BMS for the charge state, health state, life span and other related information of the battery object. The target battery voltage model can be used to control the charging and discharging process of the battery object, so as to improve the efficiency and life span of the battery object. The target battery voltage model can also be used to monitor the battery object for abnormalities, so as to realize the monitoring of abnormal problems such as over-discharge, over-charging and increased internal resistance of the battery object. The target battery voltage model can also be used to optimize the parameter design of the battery object, so as to realize the optimization of battery performance and stability. No specific limitation is made here.

[0065] The method for constructing a battery voltage model proposed in the present disclosure obtains a candidate battery voltage model and a reference terminal voltage of a battery object, inputs a historical battery parameter set of the battery object into the candidate battery voltage model to obtain a measured terminal voltage of the battery object, and then adjusts and optimizes the candidate battery voltage model based on the measured terminal voltage and the reference terminal voltage, thereby obtaining a target battery voltage model of the battery object. In the present disclosure, the candidate battery voltage model is adjusted and optimized by the measured terminal voltage and the reference terminal voltage to obtain a target battery voltage model of the battery object, thereby improving the accuracy and efficiency of the measured terminal voltage obtained by the target battery voltage model for measuring the battery object, and compared with the battery voltage model obtained by modeling only through the abstract circuit elements corresponding to the battery in the related art, the measurement accuracy of the target battery voltage model is improved, and accurate data support is provided for the downstream tasks of the battery object. In the scenario where the abnormal monitoring of the battery object is performed based on the output result of the target battery voltage model, the accuracy and efficiency of the abnormal monitoring of the battery object are improved, thereby improving the abnormal handling efficiency of the battery object, optimizing the safety and stability of the battery object operation, and optimizing the safety and stability of the system operation.

[0066] In the above embodiment, the target battery voltage model can be obtained by combining Figure 2 Further understanding, Figure 2 FIG. 1 is a flow chart of a method for constructing a battery voltage model in another embodiment of the present disclosure. Figure 2 As shown, the method includes:

[0067] S201, obtaining an open circuit voltage of a battery object in a scenario without an external load, and determining the open circuit voltage as a reference terminal voltage of the battery object.

[0068] In the embodiment of the present disclosure, a separate open circuit voltage measurement may be performed on a battery object, wherein a scenario in which the battery object is not connected to a load may be marked as a scenario of the battery object without an external load.

[0069] In this scenario, the open circuit voltage of the battery object may be measured, and the measured open circuit voltage may be determined as the reference terminal voltage of the battery object.

[0070] S202: Acquire a first historical current and a historical battery temperature of a battery object to obtain a historical battery parameter set of the battery object.

[0071] In the embodiment of the present disclosure, historical current parameters of a battery object within a set historical time range may be obtained, and each historical current parameter obtained within the time period may be marked as each first historical current of the battery object.

[0072] Furthermore, the temperature parameters of the battery object within a set historical time range may be obtained, and the temperature parameters obtained within the time period may be marked as the historical battery temperatures of the battery object.

[0073] Optionally, the current parameters of the battery object within a historical time range can be monitored and data collected based on a preset current value acquisition device to obtain the first historical current of the battery object, and the temperature parameters of the battery object within a historical time range can be monitored and data collected through a preset temperature acquisition device to obtain the historical battery temperature of the battery object.

[0074] Furthermore, a parameter set consisting of each first historical current and each historical battery temperature is marked as a historical battery parameter set of the battery object.

[0075] It should be noted that there is a corresponding relationship between each first historical current and each historical battery temperature. The timestamp of each first historical current and the timestamp of each historical battery temperature can be obtained respectively. Among them, the first historical current and historical battery temperature collected at the same timestamp can be obtained, and the two data are the first historical current and historical battery temperature that have a corresponding relationship.

[0076] S203, obtaining a reference charge voltage curve of the battery object, and obtaining a measured open circuit voltage of the battery object according to the first historical current and the reference charge voltage curve through a candidate battery voltage model, wherein the reference charge voltage curve is obtained based on a reference battery state of charge and a reference open circuit voltage of the battery object.

[0077] In the disclosed embodiment, the relevant data of the historical battery state of charge and the relevant data of the historical open circuit voltage can be drawn based on the relevant data of the historical battery state of charge of the battery object within a set historical time range and the historical open circuit voltage data within the same time range, and based on the drawing method of the state of charge-open circuit voltage curve line graph (State of Charge-Open Circuit Voltage Curve line graph, SOC-OCV curve line graph) in the related technology, and the drawn curve line graph is determined as the reference charge voltage curve line graph (SCO-OCV curve line graph) of the battery object.

[0078] Optionally, through the candidate battery voltage model, a calculated ampere-hour integral of the battery object is obtained based on the first historical current, and a calculated battery state of charge of the battery object is obtained based on the calculated ampere-hour integral.

[0079] In the disclosed embodiments, an ampere-hour integral calculation algorithm may be configured for a candidate battery voltage model, wherein the candidate battery voltage model may be configured based on an ampere-hour integral extraction algorithm in the related art, or may be configured based on other preset methods that can implement ampere-hour integral extraction, which is not specifically limited here.

[0080] Furthermore, the first historical current is algorithmically processed by the ampere-hour integral calculation algorithm configured by the candidate battery voltage model, so as to obtain the ampere-hour integral corresponding to the first historical current according to the result of the algorithm processing, and mark it as the calculated ampere-hour integral corresponding to the first historical current.

[0081] In the disclosed embodiment, there is a certain degree of correlation between the ampere-hour integral of the battery object and the state of charge of the battery object. In this scenario, the state of charge of the battery object under the measured ampere-hour integral can be obtained based on the correlation and the measured ampere-hour integral obtained by the candidate battery voltage model, and marked as the calculated battery state of charge of the battery object.

[0082] Among them, an algorithm for obtaining the battery state of charge based on the ampere-hour integral can be configured for the candidate battery voltage model, and the calculated ampere-hour integral can be algorithmically processed based on the algorithm configured for the candidate battery voltage model, so as to obtain the calculated battery state of charge of the battery object based on the result of the algorithm processing.

[0083] Optionally, a corresponding open circuit voltage for calculating the battery state of charge is obtained from a reference charge voltage curve diagram as the calculated open circuit voltage of the battery object when calculating the battery state of charge.

[0084] In the embodiment of the present disclosure, the correspondence between each historical battery state of charge and each historical open circuit voltage of the battery object can be determined by referring to the charge voltage curve graph. In this scenario, the measured battery state of charge can be used as a search keyword to perform information retrieval on the reference charge voltage curve graph, and the open circuit voltage recorded in the retrieved reference charge voltage curve graph that has a corresponding relationship with the measured battery state of charge can be determined as the measured open circuit voltage corresponding to the measured battery state of charge.

[0085] S204, obtaining a calculated voltage difference of the battery object according to the candidate battery voltage model and the first historical current and the historical battery temperature of the battery object.

[0086] In the disclosed embodiment, the candidate battery voltage model is configured with a corresponding algorithm for obtaining the pressure difference, and the input data of the candidate battery voltage model can be processed based on the algorithm to obtain the pressure difference output by the candidate battery voltage model, which is marked as the measured pressure difference.

[0087] It should be noted that the calculated voltage difference can be understood as the voltage difference between the calculated terminal voltage and the calculated open circuit voltage of the battery object calculated by the candidate battery voltage model.

[0088] Optionally, low-pass filtering is performed on the first historical current to obtain a processed second historical current set.

[0089] Among them, a low-pass filter time constant set corresponding to the first historical current can be obtained, and based on each low-pass filter time constant in the low-pass filter time constant set, the first historical current is low-pass filtered respectively to obtain each second historical current of the first historical current, so as to obtain the second historical current set.

[0090] In the disclosed embodiment, the first historical current may be subjected to multiple low-pass filtering processes, wherein the low-pass filtering time constants used in the multiple low-pass filtering processes may be different. Then, a set of multiple low-pass filtering time constants used in the low-pass filtering processes may be marked as a set of low-pass filtering time constants corresponding to the first historical current.

[0091] As an example, Figure 3 As shown, set Figure 3 The 30S and 600S shown are two low-pass filter time constants corresponding to the first historical current, which can be obtained by Figure 3 The 30S low-pass filtering processing model shown performs low-pass filtering on the first historical current based on the low-pass filtering time constant of 30S to obtain a second historical current obtained based on the low-pass filtering time constant of 30S of the first historical current.

[0092] And, you can Figure 3The 600S low-pass filtering processing model shown performs low-pass filtering on the first historical current based on the low-pass filtering time constant of 600S to obtain a second historical current obtained based on the low-pass filtering time constant of 600S of the first historical current.

[0093] Furthermore, a second historical current set in this example consisting of the first historical current composed of the two second historical currents is obtained.

[0094] As another example, the algorithm for performing low-pass filtering on the first historical current can be understood in combination with the following formula:

[0095]

[0096] In the above formula, CH t+1 Indicates the second historical current corresponding to time t+1, CH t represents the second historical current corresponding to time t, Δt represents the model calculation period, τ represents the low-pass filter time constant, I t Indicates the first historical current.

[0097] Optionally, the calculated voltage difference of the battery object is obtained through the candidate battery voltage model based on the first historical current, the second historical current set, the historical battery temperature and the calculated battery state of charge.

[0098] As an example, Figure 3 As shown, Figure 3 The voltage difference acquisition module shown is a configuration module of the voltage difference acquisition algorithm configured in the candidate battery voltage model. Figure 3 In the scenario shown, you can Figure 3 The first historical current shown, the second historical current obtained based on the low-pass filter time constant of 30S, and the second historical current obtained based on the low-pass filter time constant of 600S are composed of the second historical current set, the historical battery temperature, and the calculated battery state of charge input to Figure 3 The pressure difference acquisition module shown in the figure performs algorithm processing on each input data through the pressure difference acquisition module, and then outputs the result of the algorithm processing. Figure 3 Calculated differential pressure is shown.

[0099] Among them, the pressure difference acquisition algorithm configured by the pressure difference acquisition module can be obtained based on the voltage difference acquisition algorithm in the related art, and can also be configured based on a preset pressure difference acquisition model, which is not specifically limited here.

[0100] S205, based on the measured open circuit voltage and the measured voltage difference, obtaining the measured terminal voltage of the battery object output by the candidate battery voltage model.

[0101] Optionally, a sum of the calculated open circuit voltage and the calculated voltage difference is obtained, and the sum is multi-functionalized as a calculated terminal voltage output by the candidate battery voltage model.

[0102] As an example, Figure 3 As shown, it can be Figure 3 The summing module shown performs summing processing on the measured open circuit voltage and the measured pressure difference, thereby obtaining the sum of the measured open circuit voltage and the measured pressure difference, and then determining the sum as Figure 3 The measured terminal voltage output by the candidate battery voltage model is shown.

[0103] S206, adjusting and optimizing the candidate battery voltage model according to the reference terminal voltage and the measurement terminal voltage to obtain a target battery voltage model of the battery object.

[0104] Optionally, a measurement error of the measured terminal voltage based on the reference terminal voltage is obtained, and in response to the measurement error not falling within a preset error interval, the candidate battery voltage model is adjusted and optimized based on the measurement error until the adjustment and optimization end conditions are met, and the adjustment and optimization of the candidate battery voltage model is ended to obtain the target battery voltage model of the battery object.

[0105] In the embodiment of the present disclosure, the measurement terminal voltage and the reference terminal voltage can be algorithmically processed based on the error algorithm in the relevant technology, and then the error of the measurement terminal voltage based on the reference terminal voltage is obtained according to the result of the algorithm processing as the measurement error of the candidate battery voltage model.

[0106] In this scenario, the measured error can be compared with the preset error range. If the measured error falls within the error range, it can be determined that the model accuracy of the candidate battery voltage model obtained by obtaining the measured error meets the preset accuracy condition, and the current candidate battery voltage model can be determined as the target battery voltage model of the battery object.

[0107] Accordingly, if the measured error does not fall within the preset error range, it can be determined that the model accuracy of the candidate battery voltage model that obtains the measured error does not meet the preset accuracy condition. In this scenario, the candidate battery voltage model needs to be further adjusted and optimized.

[0108] Optionally, a preset adjustment optimization strategy may be obtained, and the candidate battery voltage model may be adjusted based on the obtained strategy, wherein the parameters of the candidate battery voltage model may be adjusted, or the framework of the candidate battery voltage model may be adjusted, which is not specifically limited here.

[0109] Furthermore, the adjustment and optimization termination conditions of the candidate battery voltage model are obtained, and the adjusted measured voltage difference obtained based on the adjusted measured terminal voltage output by the adjusted candidate battery voltage model is compared with the adjustment and optimization termination conditions. When it is identified that the adjusted measured terminal voltage satisfies the adjustment and optimization termination conditions, the adjustment and optimization of the candidate battery voltage model can be terminated, and the model obtained by the last adjustment and optimization is determined as the target battery voltage model of the battery object.

[0110] The method for constructing a battery voltage model proposed in the present invention adjusts and optimizes the candidate battery voltage model by measuring the terminal voltage and the reference terminal voltage to obtain a target battery voltage model of the battery object, thereby improving the accuracy and efficiency of the measured terminal voltage obtained by measuring the battery object using the target battery voltage model. Compared with the battery voltage model obtained by modeling only through abstract circuit elements corresponding to the battery in the related art, the measurement accuracy of the target battery voltage model is improved, and accurate data support is provided for downstream tasks of the battery object. In the scenario of abnormal monitoring of the battery object based on the output result of the target battery voltage model, the accuracy and efficiency of abnormal monitoring of the battery object are improved, thereby improving the abnormal handling efficiency of the battery object, optimizing the safety and stability of the battery object operation, and optimizing the safety and stability of the system operation.

[0111] The present disclosure also proposes a battery voltage model that can be combined with Figure 4 understand, Figure 4 Schematic diagram of a battery voltage model according to an embodiment of the present disclosure. Figure 4 As shown, the battery voltage model 400 includes a data input terminal 41, an ampere-hour integral extraction unit 42, a low-pass filter processing unit 43, a reference charge voltage curve query unit 44, a pressure difference acquisition unit 45, a summing unit 46 and a data output terminal 47.

[0112] The output end of the ampere-hour integral extraction unit 42 is connected to the input end of the reference charge voltage curve diagram query unit 44, and the output end of the reference charge voltage curve diagram query unit 44 is connected to the input end of the summing unit 46;

[0113] The output end of the low-pass filter processing unit 43 is connected to the input end of the pressure difference acquisition unit 45, and the output end of the pressure difference acquisition unit 45 is connected to the input end of the summing unit 46;

[0114] The data input terminal 41 is connected to the input terminal of the ampere-hour integral extraction unit 42, the input terminal of the low-pass filter processing unit 43 and the input terminal of the pressure difference acquisition unit 45 respectively;

[0115] The output terminal of the summing unit 46 is connected to the data output terminal 47;

[0116] Among them, the battery voltage model is based on the above Figures 1 to 3 The method proposed in the embodiment is obtained.

[0117] In the disclosed embodiment, Figure 4 The data input terminals 41 are shown to be connected to Figure 4 The input end of the ampere-hour integral extraction unit 42, the input end of the low-pass filter processing unit 43, and the input end of the pressure difference acquisition unit 45 are respectively connected.

[0118] exist Figure 4 In the scenario shown, the data input terminal 41 can input the first historical current of the input battery voltage model 400 received into Figure 4 The ampere-hour integral extraction unit 42 shown in the figure can extract the calculated ampere-hour integral corresponding to the first historical current, and then obtain the calculated battery charge state corresponding to the first historical current based on the extracted calculated ampere-hour integral, such as Figure 4 As shown, the input end of the reference charge voltage curve query unit 44 is connected to the output end of the ampere-hour integral extraction unit 42, and the calculated battery state of charge extracted by the ampere-hour integral extraction unit 42 can be transmitted to the reference charge voltage curve query unit 44, and the reference charge voltage curve query unit 44 determines the calculated open circuit voltage corresponding to the calculated battery state of charge from the reference charge voltage curve.

[0119] like Figure 4 As shown, the output end of the reference charge voltage curve diagram query unit 44 is connected to the input end of the summing unit 46 , and the obtained measured open circuit voltage can be transmitted to the summing unit 46 .

[0120] In the embodiment of the present disclosure, the data input terminal 41 is connected to Figure 4 The input terminal of the low-pass filter processing unit 43 is connected to Figure 4 In the scenario shown, the data input terminal 41 can transmit the first historical current to the low-pass filter processing unit 43, such as Figure 4 As shown, the low-pass filter processing unit 43 includes Figure 4 The 30S low-pass filter subunit 431 and the 600S low-pass filter subunit 432 shown can perform low-pass filtering on the first historical current respectively through the low-pass filter time constants configured by the 30S low-pass filter subunit 431 and the 600S low-pass filter subunit 432, so as to obtain the second historical current corresponding to the first historical current output by the 30S low-pass filter subunit 431 and the second historical current corresponding to the first historical current output by the 600S low-pass filter subunit 432, and then obtain the second historical current set obtained by the first historical current based on the low-pass filtering processing unit 43.

[0121] like Figure 4As shown, the data input terminal 41 is connected to the input terminal of the pressure difference acquisition unit 45, the output terminal of the low-pass filter processing unit 43 is connected to the input terminal of the pressure difference acquisition unit 45, and the output terminal of the ampere-hour integral extraction unit 42 is connected to the input terminal of the pressure difference acquisition unit 45. Figure 4 In the scenario shown, the data input terminal 41 can transmit the first historical current and the historical battery temperature to the pressure difference acquisition unit 45, the time integration extraction unit 42 can transmit the output measured battery state of charge to the pressure difference acquisition unit 45, and the low-pass filtering processing unit 43 can transmit its output second historical current set to the pressure difference acquisition unit 45.

[0122] Furthermore, the pressure difference acquisition unit 45 can calculate the pressure difference based on the various data input therein, and then obtain Figure 4 The calculated pressure difference shown is Figure 4 As shown, the output end of the pressure difference acquisition unit 45 is connected to the input end of the summing unit 46, and the measured pressure difference outputted by the summing unit 46 can be transmitted to the Figure 4 In the summing unit 46 shown.

[0123] As a possible implementation, the pressure difference acquisition unit 45 is configured with an algorithm that can realize the acquisition of the measured pressure difference, and performs algorithmic processing on various data input therein through its pre-configured algorithm, so as to output the corresponding measured pressure difference.

[0124] As another possible implementation method, the pressure difference acquisition unit 45 is configured with a trained pressure difference acquisition model, and the pressure difference acquisition model can be constructed based on the feedforward neural network (FNN) model in the relevant technology, wherein the pressure difference acquisition model can be configured with an input layer, a hidden layer and an output layer. Based on the basic working principle of the FNN model, the pressure difference acquisition model can pass the received data layer by layer in each layer within the model, so as to obtain the final output result and output it as the measured pressure difference.

[0125] It should be noted that the pressure difference acquisition model can be trained based on the model training method in the relevant technology, and the model parameters can be adjusted and optimized during the training process based on the back propagation algorithm in the relevant technology, so as to obtain a trained pressure difference acquisition model and configure it in the pressure difference acquisition unit 45 of the battery voltage model 400.

[0126] like Figure 4 As shown, after receiving the measured open circuit voltage and the measured pressure difference, the adding unit 46 can perform algorithm processing on the measured open circuit voltage and the measured pressure difference based on its own configured algorithm to obtain the corresponding algorithm processing result, and transmit the result to Figure 4The result is output through the data output terminal 47 and marked as the estimated terminal voltage output by the battery voltage model 400 .

[0127] The battery voltage model proposed in the present disclosure includes a data input terminal, an ampere-hour integral extraction unit, a low-pass filter processing unit, a reference charge voltage curve query unit, a pressure difference acquisition unit, a summing unit and a data output terminal. The output terminal of the ampere-hour integral extraction unit is connected to the input terminal of the reference charge voltage curve query unit, and the output terminal of the reference charge voltage curve query unit is connected to the input terminal of the summing unit; the output terminal of the low-pass filter processing unit is connected to the input terminal of the pressure difference acquisition unit, and the output terminal of the pressure difference acquisition unit is connected to the input terminal of the summing unit; the data input terminal is respectively connected to the input terminal of the ampere-hour integral extraction unit, the input terminal of the low-pass filter processing unit and the input terminal of the pressure difference acquisition unit; the output terminal of the summing unit is connected to the data output terminal. In the present disclosure, based on Figure 4 The architecture shown obtains a battery voltage model, which improves the matching degree between the battery voltage model and the battery object, and reduces the error degree between the measured terminal voltage output by the battery voltage model and the actual terminal voltage of the battery object, compared with the battery voltage model obtained by modeling the abstract circuit elements corresponding to the battery without considering other parameters in the related art. In the scenario of abnormal monitoring of the battery object based on the output result of the battery voltage model, the accuracy and efficiency of abnormal monitoring of the battery object are improved, thereby improving the abnormal handling efficiency of the battery object, optimizing the safety and stability of the battery object operation, and optimizing the safety and stability of the system operation.

[0128] To better understand the above embodiment, it can be understood in combination with the simulation experiment results of the target battery voltage model, such as Figure 5 As shown, Figure 5 (a) shows the actual sampled values ​​of the input target battery voltage model and the current of the battery object during the 125-hour simulation experiment. Figure 5 (b) shows the actual sampled value of SOC input into the target battery voltage model during the 125-hour simulation experiment. Figure 5 (c) shows the comparison between the simulated terminal voltage output by the target battery voltage model and the collected value of the actual terminal voltage of the battery object corresponding to the target battery voltage model during the 125-hour simulation experiment.

[0129] Figure 5 (d) shows a single actual sampling value of the input target battery voltage model and the current of the battery object during the 125-hour simulation experiment. Figure 5 (e) shows a single actual sampling value of the SOC input into the target battery voltage model during the 125-hour simulation experiment. Figure 5(f) shows the comparison between the single simulation terminal voltage output by the target battery voltage model and the single acquisition value of the actual terminal voltage of the battery object corresponding to the target battery voltage model during the 125-hour simulation experiment.

[0130] in, Figure 5 (a) and Figure 5 The horizontal axis of (d) represents the input current time, and the vertical axis represents the input current value. Figure 5 (b) and Figure 5 (e) The horizontal axis represents the input time of SOC, and the vertical axis represents the input SOC value, and Figure 5 (c) and Figure 5 (f) The horizontal axis represents the output time of the simulated terminal voltage and the actual terminal voltage, and the vertical axis represents the voltage value.

[0131] Corresponding to the methods for constructing the battery voltage model proposed in the above-mentioned embodiments, an embodiment of the present disclosure further proposes a device for constructing a battery voltage model. Since the device for constructing the battery voltage model proposed in the embodiment of the present disclosure corresponds to the methods for constructing the battery voltage model proposed in the above-mentioned embodiments, the implementation method of the above-mentioned method for constructing the battery voltage model is also applicable to the device for constructing the battery voltage model proposed in the embodiment of the present disclosure, and will not be described in detail in the following embodiments.

[0132] Figure 6 FIG. 1 is a schematic diagram of a structure of a device for constructing a battery voltage model according to an embodiment of the present disclosure. Figure 6 As shown, the battery voltage model construction device 600 includes a first acquisition module 61, a second acquisition module 62, a third acquisition module 63 and an adjustment module 64, wherein:

[0133] A first acquisition module 61 is used to acquire a candidate battery voltage model of a battery object to be modeled;

[0134] A second acquisition module 62, used to acquire a reference terminal voltage of a battery object;

[0135] A third acquisition module 63 is used to acquire a historical battery parameter set of the battery object, and obtain a measured terminal voltage of the battery object based on the historical battery parameter set through a candidate battery voltage model;

[0136] The adjustment module 64 is used to adjust and optimize the candidate battery voltage model according to the reference terminal voltage and the measurement terminal voltage to obtain a target battery voltage model of the battery object.

[0137] In the embodiment of the present disclosure, the second acquisition module 62 is further used to: acquire the open circuit voltage of the battery object in a scenario without an external load, and determine the open circuit voltage as the reference terminal voltage of the battery object.

[0138] In the disclosed embodiment, the third acquisition module 63 is further used to: acquire a first historical current and a historical battery temperature of the battery object to obtain a historical battery parameter set of the battery object; acquire a reference charge voltage curve of the battery object, and acquire a measured open circuit voltage of the battery object according to the first historical current and the reference charge voltage curve through a candidate battery voltage model, wherein the reference charge voltage curve is acquired based on a reference battery state of charge and a reference open circuit voltage of the battery object; acquire a measured pressure difference of the battery object according to the first historical current and the historical battery temperature of the battery object through the candidate battery voltage model; and acquire a measured terminal voltage of the battery object output by the candidate battery voltage model based on the measured open circuit voltage and the measured pressure difference.

[0139] In the disclosed embodiment, the third acquisition module 63 is further used to: obtain the calculated ampere-hour integral of the battery object based on the first historical current through the candidate battery voltage model; obtain the calculated battery state of charge of the battery object based on the calculated ampere-hour integral; and obtain the corresponding open circuit voltage of the calculated battery state of charge from the reference charge voltage curve as the calculated open circuit voltage of the battery object under the calculated battery state of charge.

[0140] In the disclosed embodiment, the third acquisition module 63 is further used to: perform low-pass filtering on the first historical current to obtain a processed second historical current set; and obtain a calculated voltage difference of the battery object based on the first historical current, the second historical current set, the historical battery temperature and the calculated battery state of charge through a candidate battery voltage model.

[0141] In the disclosed embodiment, the third acquisition module 63 is also used to: obtain a set of low-pass filter time constants corresponding to the first historical current; based on each low-pass filter time constant in the low-pass filter time constant set, perform low-pass filtering on the first historical current respectively to obtain each second historical current of the first historical current, so as to obtain the second historical current set.

[0142] In the embodiment of the present disclosure, the third acquisition module 63 is further used to: obtain the sum of the measured open circuit voltage and the measured voltage difference, and convert the sum into the measured terminal voltage output by the candidate battery voltage model.

[0143] In the disclosed embodiment, the adjustment module 64 is further used to: obtain a measurement error of the measured terminal voltage based on the reference terminal voltage; in response to the measurement error not falling within a preset error interval, adjust and optimize the candidate battery voltage model based on the measurement error until the adjustment and optimization end condition is met, end the adjustment and optimization of the candidate battery voltage model, and obtain the target battery voltage model of the battery object.

[0144] The battery voltage model construction device proposed in the present disclosure obtains the candidate battery voltage model and the reference terminal voltage of the battery object, inputs the historical battery parameter set of the battery object into the candidate battery voltage model to obtain the measured terminal voltage of the battery object, and then adjusts and optimizes the candidate battery voltage model based on the measured terminal voltage and the reference terminal voltage, thereby obtaining the target battery voltage model of the battery object. In the present disclosure, the candidate battery voltage model is adjusted and optimized by the measured terminal voltage and the reference terminal voltage to obtain the target battery voltage model of the battery object, thereby improving the accuracy and efficiency of the measured terminal voltage obtained by the target battery voltage model for measuring the battery object, and compared with the battery voltage model obtained by modeling only the abstract circuit elements corresponding to the battery in the related art, the measurement accuracy of the target battery voltage model is improved, and accurate data support is provided for the downstream tasks of the battery object. In the scenario of abnormal monitoring of the battery object based on the output result of the target battery voltage model, the accuracy and efficiency of abnormal monitoring of the battery object are improved, thereby improving the abnormal processing efficiency of the battery object, optimizing the safety and stability of the battery object operation, and optimizing the safety and stability of the system operation.

[0145] To achieve the above embodiments, the present disclosure also provides an electronic device, a computer-readable storage medium, and a computer program product.

[0146] Figure 7 is a block diagram of an electronic device 700 according to an embodiment of the present disclosure, as shown in Figure 7 As shown, the electronic device 700 includes a memory 701, a processor 702, and a computer program stored in the memory 701 and executable on the processor 702. When the processor 702 executes the program instructions, the method for constructing the battery voltage model provided in the above embodiment is implemented.

[0147] The method for constructing a battery voltage model proposed in the present disclosure obtains a candidate battery voltage model and a reference terminal voltage of a battery object, inputs a historical battery parameter set of the battery object into the candidate battery voltage model to obtain a measured terminal voltage of the battery object, and then adjusts and optimizes the candidate battery voltage model based on the measured terminal voltage and the reference terminal voltage, thereby obtaining a target battery voltage model of the battery object. In the present disclosure, the candidate battery voltage model is adjusted and optimized by the measured terminal voltage and the reference terminal voltage to obtain a target battery voltage model of the battery object, thereby improving the accuracy and efficiency of the measured terminal voltage obtained by the target battery voltage model for measuring the battery object, and compared with the battery voltage model obtained by modeling only through the abstract circuit elements corresponding to the battery in the related art, the measurement accuracy of the target battery voltage model is improved, and accurate data support is provided for the downstream tasks of the battery object. In the scenario where the abnormal monitoring of the battery object is performed based on the output result of the target battery voltage model, the accuracy and efficiency of the abnormal monitoring of the battery object are improved, thereby improving the abnormal handling efficiency of the battery object, optimizing the safety and stability of the battery object operation, and optimizing the safety and stability of the system operation.

[0148] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0149] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0150] The program code for implementing the method itself can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0151] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0152] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0153] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a grid browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication grid). Examples of communication grids include: a local area network (LAN), a wide area network (WAN), the Internet, and a blockchain grid.

[0154] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication grid. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services ("Virtual Private Server", or "VPS" for short). The server may also be a server for a distributed system, or a server combined with a blockchain.

[0155] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0156] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of the present disclosure, "plurality" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0157] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present disclosure includes additional implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present disclosure belong.

[0158] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute the instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or otherwise processing in a suitable manner if necessary, and then stored in a computer memory.

[0159] It should be understood that the various parts of the present disclosure can be implemented in hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0160] A person skilled in the art may understand that all or part of the steps in the above-mentioned embodiment method may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0161] In addition, each functional unit in each embodiment of the present disclosure may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0162] The storage medium mentioned above may be a read-only memory, a disk or an optical disk, etc. Although the embodiments of the present disclosure have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations of the present disclosure. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present disclosure.

[0163] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0164] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for constructing a battery voltage model, characterized in that: The method comprises: Obtain a candidate battery voltage model of a battery object to be modeled; Obtaining a reference terminal voltage of the battery object; Acquire a historical battery parameter set of the battery object, and obtain a measured terminal voltage of the battery object based on the historical battery parameter set through the candidate battery voltage model; The candidate battery voltage model is adjusted and optimized according to the reference terminal voltage and the measured terminal voltage to obtain a target battery voltage model of the battery object.

2. The method according to claim 1, characterized in that The obtaining the reference terminal voltage of the battery object includes: An open circuit voltage of the battery object in a scenario without an external load is obtained, and the open circuit voltage is determined as the reference terminal voltage of the battery object.

3. The method according to claim 1, characterized in that The acquiring a historical battery parameter set of the battery object, and obtaining the measured terminal voltage of the battery object based on the historical battery parameter set by using the candidate battery voltage model, includes: Acquire a first historical current and a historical battery temperature of the battery object to obtain the historical battery parameter set of the battery object; Acquire a reference charge voltage curve graph of the battery object, and obtain a measured open circuit voltage of the battery object according to the first historical current and the reference charge voltage curve graph through the candidate battery voltage model, wherein the reference charge voltage curve graph is obtained based on a reference battery state of charge and a reference open circuit voltage of the battery object; Obtaining a measured voltage difference of the battery object according to the candidate battery voltage model and the first historical current and the historical battery temperature of the battery object; The measured terminal voltage of the battery object output by the candidate battery voltage model is obtained based on the measured open circuit voltage and the measured voltage difference.

4. The method according to claim 3, characterized in that The step of obtaining a reference charge voltage curve graph of the battery object, and obtaining a measured open circuit voltage of the battery object according to the first historical current and the reference charge voltage curve graph through the candidate battery voltage model, wherein the reference charge voltage curve graph is obtained based on a reference battery state of charge and a reference open circuit voltage of the battery object, comprises: Obtaining, by means of the candidate battery voltage model, a measured ampere-hour integral of the battery object based on the first historical current; Obtaining a calculated battery state of charge of the battery object based on the calculated ampere-hour integral; The corresponding open circuit voltage of the calculated battery state of charge is obtained from the reference charge voltage curve diagram as the calculated open circuit voltage of the battery object under the calculated battery state of charge.

5. The method according to claim 3, characterized in that: The obtaining, by using the candidate battery voltage model and according to the first historical current and the historical battery temperature of the battery object, a measured voltage difference of the battery object includes: Performing low-pass filtering on the first historical current to obtain a processed second historical current set; The calculated voltage difference of the battery object is obtained through the candidate battery voltage model based on the first historical current, the second historical current set, the historical battery temperature and the calculated battery state of charge.

6. The method according to claim 5, characterized in that The low-pass filtering the first historical current to obtain a processed second historical current set includes: Obtaining a set of low-pass filter time constants corresponding to the first historical current; Based on each low-pass filter time constant in the low-pass filter time constant set, low-pass filter processing is performed on the first historical currents to obtain each second historical current of the first historical current, so as to obtain the second historical current set.

7. The method according to claim 3, characterized in that The step of obtaining the measured terminal voltage of the battery object output by the candidate battery voltage model based on the measured open circuit voltage and the measured voltage difference comprises: The sum of the measured open circuit voltage and the measured voltage difference is obtained, and the sum is multi-functionalized into the measured terminal voltage output by the candidate battery voltage model.

8. The method according to claim 1, characterized in that The step of adjusting and optimizing the candidate battery voltage model according to the reference terminal voltage and the measured terminal voltage to obtain a target battery voltage model of the battery object includes: Obtaining a measurement error of the measured terminal voltage based on the reference terminal voltage; In response to the measurement error not falling within a preset error interval, the candidate battery voltage model is adjusted and optimized based on the measurement error until an adjustment and optimization termination condition is met, thereby terminating the adjustment and optimization of the candidate battery voltage model and obtaining the target battery voltage model of the battery object.

9. A battery voltage model, characterized in that: The model includes a data input terminal, an ampere-hour integral extraction unit, a low-pass filter processing unit, a reference charge voltage curve query unit, a pressure difference acquisition unit, a summing unit and a data output terminal. The output end of the ampere-hour integral extraction unit is connected to the input end of the reference charged voltage curve diagram query unit, and the output end of the reference charged voltage curve diagram query unit is connected to the input end of the summing unit; The output end of the low-pass filter processing unit is connected to the input end of the pressure difference acquisition unit, and the output end of the pressure difference acquisition unit is connected to the input end of the summing unit; The data input terminal is connected to the input terminal of the ampere-hour integral extraction unit, the input terminal of the low-pass filter processing unit and the input terminal of the pressure difference acquisition unit respectively; The output end of the summing unit is connected to the data output end; Wherein, the battery voltage model is obtained based on the method proposed in any one of claims 1 to 8 above.

10. A device for constructing a battery voltage model, characterized in that: The device comprises: A first acquisition module, used to acquire a candidate battery voltage model of a battery object to be modeled; A second acquisition module, used to acquire the reference terminal voltage of the battery object; A third acquisition module, configured to acquire a historical battery parameter set of the battery object, and obtain a measured terminal voltage of the battery object based on the historical battery parameter set through the candidate battery voltage model; An adjustment module is used to adjust and optimize the candidate battery voltage model according to the reference terminal voltage and the measured terminal voltage to obtain a target battery voltage model of the battery object.

11. An electronic device, characterized in that: include: processor; a memory for storing executable instructions for the processor; The processor is configured to execute instructions to implement the method as claimed in any one of claims 1 to 8.

12. A computer-readable storage medium, when instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the method according to any one of claims 1 to 8.

Images