Method and device for correcting current state of charge, medium, electronic device and program product

Abstract

The invention discloses a current charge state correction method and device, a medium, an electronic device and a program product, and relates to the technical field of batteries, and the method comprises the steps: determining the corresponding relation between historical charge states and historical battery parameters at different moments, the historical battery parameters at least comprise one of historical battery expansion force and historical expansion force change slope, and the historical expansion force change slope represents the change slope of the historical battery expansion force along with the change of the historical charge state; determining a target filtering model constructed based on the corresponding relationship, and determining a predicted battery parameter corresponding to the current battery parameter by using the target filtering model; and correcting the current state of charge by using a correction coefficient determined by the predicted battery parameters to obtain a target state of charge.

Description

Technical Field

[0001] This application relates to the technical field of batteries, and more specifically, to a method, apparatus, medium, electronic device, and program product for correcting the current state of charge. Background Technology

[0002] In related technologies, methods for estimating SOC (State of Charge) include the ampere-hour integration method and the open-circuit voltage method. These methods infer SOC based on charge exchange during charging and discharging and voltage changes during rest, respectively. However, when the battery is near full or low charge, these methods fail to accurately reflect the dynamic trend of SOC changes because the voltage variation amplitude significantly decreases in this range, leading to SOC estimation errors. Furthermore, the correction coefficients of these methods rely on the direct correlation between OCV (Open Circuit Voltage) and SOC. In the OCV-SOC plateau region, or in areas where OCV does not change significantly with SOC, they cannot effectively correct for SOC errors, reducing the accuracy of SOC correction.

[0003] Regarding the technical problem of how to improve the accuracy of SOC correction in related technologies, no effective solution has yet been proposed. Summary of the Invention

[0004] This application provides a method, apparatus, medium, electronic device, and program product for correcting the current state of charge (SOC), in order to at least solve the technical problem of how to improve the accuracy of SOC correction in related technologies.

[0005] According to one embodiment of this application, a method for correcting the current state of charge is provided, comprising: determining the correspondence between historical states of charge and historical battery parameters at different times, wherein the historical battery parameters include at least one of the following: historical battery expansion force, historical expansion force change slope, wherein the historical expansion force change slope represents the change slope of the historical battery expansion force as the historical state of charge changes; determining a target filtering model constructed based on the correspondence, and using the target filtering model to determine the predicted battery parameters corresponding to the current battery parameters; and using the correction coefficient determined by the predicted battery parameters to correct the current state of charge to obtain the target state of charge.

[0006] In an exemplary embodiment, determining a target filtering model constructed based on the correspondence includes: creating an observation equation and a state equation based on the correspondence, and generating the target filtering model according to the observation equation and the state equation, wherein the observation equation is used to describe the mapping relationship between the observation and the state quantity to be estimated, the state equation is used to describe the updated state quantity of the state quantity to be estimated, the observation represents the current battery parameter, and the state quantity to be estimated represents the predicted battery parameter.

[0007] In an exemplary embodiment, determining the correspondence between historical states of charge and historical battery parameters at different times includes at least one of the following: if the historical battery parameters also include historical voltage, determining a first correspondence between historical states of charge and historical voltage at different times; determining a second correspondence between historical states of charge and the slope of the historical expansion force change at different times; and determining a third correspondence between historical states of charge and the second derivative of the historical battery expansion force with respect to the historical states of charge at different times.

[0008] In an exemplary embodiment, creating an observation equation based on the correspondence includes: establishing a first observation sub-equation corresponding to the historical voltage based on the first correspondence; establishing a second observation sub-equation corresponding to the historical expansion force change slope based on the second correspondence; establishing a third observation sub-equation corresponding to the historical battery expansion force based on the third correspondence; and determining the observation equation based on the first observation sub-equation, the second observation equation, and the third observation equation.

[0009] In an exemplary embodiment, creating a state equation based on the correspondence includes: establishing a first state sub-equation based on the state of charge value at the previous moment and the ratio of the battery capacity at the previous moment; establishing a second state sub-equation based on the polarization voltage at the previous moment; and determining the state equation based on the first state sub-equation and the second state sub-equation.

[0010] In an exemplary embodiment, determining the predicted battery parameters corresponding to the current battery parameters using the target filtering model includes: calculating the new state of charge value corresponding to the state of charge value at the previous moment using the first state sub-equation, and calculating the new polarization voltage corresponding to the polarization voltage at the previous moment using the second state sub-equation; and determining the predicted battery parameters based on the new state of charge value and the new polarization voltage.

[0011] In one exemplary embodiment, the method further includes: in the event that the state variable to be estimated is updated, determining a new observation using the updated state variable through the observation equation, and determining the predicted battery parameters based on the new observation.

[0012] In an exemplary embodiment, determining the predicted battery parameters based on the new observation includes: determining the partial derivative of the new observation with respect to the updated state quantity, and determining a target filter gain based on the partial derivative; if the observation represents the battery expansion force, determining a first state vector corresponding to the new battery expansion force based on the updated state quantity; and determining the predicted battery expansion force based on the expansion force correction term corresponding to the target filter gain and the first state vector, wherein the predicted battery parameters include the predicted battery expansion force.

[0013] In one exemplary embodiment, the method further includes: determining a second state vector corresponding to a new expansion force change slope based on the updated state quantity when the observed quantity represents the expansion force change slope; and determining a predicted expansion force change slope based on the expansion force slope correction term corresponding to the target filter gain and the second state vector, wherein the predicted battery parameters include the predicted expansion force change slope.

[0014] In one exemplary embodiment, the predicted battery parameters include at least one of the following: predicted voltage, predicted battery expansion force, and predicted expansion force change slope; before correcting the current state of charge using correction coefficients determined by the predicted battery parameters, the method further includes one of the following: determining a first correction coefficient based on the predicted voltage and the current state of charge, wherein the correction coefficient includes at least the first correction coefficient; determining a second correction coefficient based on the predicted expansion force change slope, wherein the correction coefficient includes at least the second correction coefficient; determining a third correction coefficient based on the second derivative of the predicted battery expansion force with respect to the current state of charge, wherein the correction coefficient includes at least the third correction coefficient; and determining a fourth correction coefficient based on the predicted expansion force change slope and / or the second derivative of the predicted battery expansion force with respect to the current state of charge, wherein the correction coefficient includes at least the fourth correction coefficient.

[0015] In an exemplary embodiment, before correcting the current state of charge using the correction coefficient determined by the predicted battery parameters, the method further includes: determining the current state of charge based on the ratio of the initial state of charge to the battery capacity at the first sampling time, wherein the battery capacity ratio represents the ratio between the first sampled charge and the battery capacity in the previous sampling period, and the first sampled charge represents the product between the current and the sampling time interval at the previous sampling time.

[0016] In an exemplary embodiment, the current battery parameters include the current voltage, and the method further includes one of the following: determining the initial state of charge based on the last recorded historical state of charge; determining the initial state of charge based on the battery's preset state of charge; obtaining the initial state of charge set by the target object; and determining the initial state of charge corresponding to the current voltage based on a first correspondence.

[0017] In one exemplary embodiment, correcting the current state of charge (SOC) using correction coefficients determined by the predicted battery parameters to obtain a target SOC includes one of the following: when the predicted battery parameters include the predicted voltage and the predicted battery expansion force, correcting the first SOC value of the current SOC using voltage correction values ​​and expansion force correction values ​​to obtain a second SOC value of the target SOC; when the predicted battery parameters include the predicted voltage and the predicted expansion force change slope, correcting the first SOC value of the current SOC using voltage correction values ​​and expansion force slope correction values ​​to obtain a second SOC value of the target SOC; when the predicted battery parameters include the predicted voltage, the predicted battery expansion force, and the predicted expansion force change slope, correcting the first SOC value of the current SOC using one of the expansion force correction values ​​and the expansion force slope correction values, along with the voltage correction value, to obtain a second SOC value of the target SOC.

[0018] In one exemplary embodiment, correcting a first state of charge value of the current state of charge using a voltage correction value and an expansion force correction value to obtain a second state of charge value of the target state of charge includes: obtaining a voltage difference between the predicted voltage and the current voltage, and determining the voltage correction value based on the product of the first correction coefficient and the voltage difference; obtaining an expansion force difference between the predicted battery expansion force and the current battery expansion force, and determining the expansion force correction value based on the product of the second correction coefficient and the expansion force difference; and determining the second state of charge value based on the sum of the first state of charge value, the voltage correction value, and the expansion force correction value.

[0019] In an exemplary embodiment, correcting a first state of charge value of the current state of charge using a voltage correction value and an expansion force slope correction value to obtain a second state of charge value of the target state of charge includes: obtaining a voltage difference between the predicted voltage and the current voltage, and determining the voltage correction value based on the product of the first correction coefficient and the voltage difference; obtaining an expansion force slope difference between the predicted expansion force change slope and the current expansion force change slope, and determining the expansion force slope correction value based on the product of the third correction coefficient and the expansion force slope difference; and determining the second state of charge value based on the sum of the first state of charge value, the voltage correction value, and the expansion force slope correction value.

[0020] In one exemplary embodiment, correcting a first state of charge value of the current state of charge using one of an expansion force correction value and an expansion force slope correction value, along with a voltage correction value, to obtain a second state of charge value of the target state of charge includes: obtaining a voltage difference between the predicted voltage and the current voltage, and determining the voltage correction value based on the product of the first correction coefficient and the voltage difference; obtaining an expansion force difference between the predicted battery expansion force and the current battery expansion force, and determining the expansion force correction value based on the product of the fourth correction coefficient and the expansion force difference; and determining the second state of charge value based on the sum of the first state of charge value, the voltage correction value, and the expansion force correction value.

[0021] In one exemplary embodiment, correcting a first state of charge value of the current state of charge using one of an expansion force correction value and an expansion force slope correction value, along with a voltage correction value, to obtain a second state of charge value of the target state of charge includes: obtaining a voltage difference between the predicted voltage and the current voltage, and determining the voltage correction value based on the product of the first correction coefficient and the voltage difference; obtaining an expansion force slope difference between the predicted expansion force change slope and the current expansion force change slope; determining the expansion force slope correction value based on the product of the fourth correction coefficient and the expansion force slope difference; and determining the second state of charge value based on the sum of the first state of charge value, the voltage correction value, and the expansion force slope correction value.

[0022] In an exemplary embodiment, the historical battery parameters further include the historical equivalent polarization resistance, historical battery capacity, and historical battery temperature at the sampling time. The method further includes: if it is determined that the predicted battery parameters do not conform to a preset parameter range, inputting the current equivalent polarization resistance, current battery capacity, and current battery temperature into a target prediction model to obtain the target voltage, target battery expansion force, and target expansion force change slope output by the target prediction model; determining the predicted battery parameters based on the target voltage, target battery expansion force, and target expansion force change slope; wherein the target prediction model is a prediction model obtained by training the historical equivalent polarization resistance, historical battery capacity, and historical battery temperature at different sampling times as input samples, and the historical voltage corresponding to the historical state of charge at different sampling times, the historical expansion force change slope corresponding to the historical state of charge, and the second derivative of the historical battery expansion force with respect to the historical state of charge as output samples.

[0023] According to another aspect of the embodiments of this application, a current state of charge correction device is also provided, comprising: a first determining module, configured to determine the correspondence between historical states of charge and historical battery parameters at different times, wherein the historical battery parameters include at least one of the following: historical battery expansion force, historical expansion force change slope, the historical expansion force change slope representing the change slope of the historical battery expansion force as the historical state of charge changes; a second determining module, configured to determine a target filtering model constructed based on the correspondence, and use the target filtering model to determine the predicted battery parameters corresponding to the current battery parameters; and a obtaining module, configured to correct the current state of charge using the correction coefficient determined by the predicted battery parameters to obtain the target state of charge.

[0024] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, wherein a computer program is stored in the computer program, and the computer program is configured to execute the above-described current state of charge correction method when running.

[0025] According to another aspect of the embodiments of this application, an electronic device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the above-described current state of charge correction method through the computer program.

[0026] According to another aspect of the embodiments of this application, a computer program product is also provided, including a computer program that, when executed by a processor, implements the above-described method for correcting the current state of charge.

[0027] In this embodiment, the correspondence between historical state of charge (SOC) and historical battery parameters at different times is determined. The historical battery parameters include at least one of the following: historical battery expansion force and historical expansion force change slope, where the historical expansion force change slope represents the slope of the historical battery expansion force as the historical SOC changes. A target filtering model is constructed based on the correspondence, and the target filtering model is used to determine the predicted battery parameters corresponding to the current battery parameters. The correction coefficient determined by the predicted battery parameters is used to correct the current SOC to obtain the target SOC. This application, by determining the correspondence between historical SOC and historical battery parameters (including historical expansion force and historical expansion force change slope), constructs a target filtering model, then uses the target filtering model to obtain predicted battery parameters, and then uses the correction coefficient obtained based on the predicted battery parameters to adjust the current SOC, obtaining a more accurate target SOC. This technical solution solves the technical problem of how to improve the accuracy of SOC correction, improves the accuracy of SOC correction, and also improves the correction efficiency and accuracy of SOC in the plateau region or insignificant change region of the battery OCV-SOC curve. Attached Figure Description

[0028] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0029] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0030] Figure 1 This is a flowchart of a method for correcting the current state of charge according to an embodiment of this application;

[0031] Figure 2 This is a flowchart illustrating a method for correcting the current state of charge according to an embodiment of this application.

[0032] Figure 3 This is a flowchart illustrating a method for correcting the current state of charge according to an embodiment of this application;

[0033] Figure 4 This is a simulation diagram (a) of a current state of charge correction method according to an embodiment of this application.

[0034] Figure 5 This is a simulation diagram (II) of a current state of charge correction method according to an embodiment of this application;

[0035] Figure 6 This is a simulation diagram (III) showing the correction result of the current state of charge according to an embodiment of this application;

[0036] Figure 7 This is a structural block diagram of a current state of charge correction device according to an embodiment of this application. Detailed Implementation

[0037] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0038] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0039] The following appropriately discloses an embodiment of a battery according to this application. However, unnecessary detailed descriptions may be omitted. For example, detailed descriptions of well-known matters and repetitive descriptions of practically identical structures may be omitted. This is to avoid making the following description unnecessarily lengthy and to facilitate understanding by those skilled in the art. Furthermore, the following description is provided to enable those skilled in the art to fully understand this application and is not intended to limit the subject matter of the claims.

[0040] The battery in this application is a secondary battery, also known as a rechargeable battery or storage battery, which refers to a battery that can be used again after being discharged by recharging to activate the active materials.

[0041] Typically, a secondary battery includes an electrode assembly, an electrolyte, and an outer casing. The electrode assembly consists of a positive electrode, a negative electrode, and a separator. The electrode assembly and electrolyte are assembled inside the outer casing. During charging and discharging, active ions (such as lithium ions) move back and forth between the positive and negative electrodes, inserting and extracting. The separator, positioned between the positive and negative electrodes, primarily prevents short circuits while allowing active ions to pass through. The electrolyte, located between the positive and negative electrodes, mainly serves to conduct active ions.

[0042] This embodiment provides a method for correcting the current state of charge. Figure 1 This is a flowchart illustrating a method for correcting the current state of charge according to an embodiment of this application. The process includes the following steps:

[0043] Step S102: Determine the correspondence between historical state of charge and historical battery parameters at different times, wherein the historical battery parameters include at least one of the following: historical battery expansion force, historical expansion force change slope, wherein the historical expansion force change slope represents the change slope of the historical battery expansion force as the historical state of charge changes;

[0044] Step S104: Determine the target filtering model constructed based on the correspondence, and use the target filtering model to determine the predicted battery parameters corresponding to the current battery parameters;

[0045] Step S106: Correct the current state of charge using the correction coefficient determined by the predicted battery parameters to obtain the target state of charge.

[0046] Through the above steps, the correspondence between historical state of charge (SOC) and historical battery parameters at different times is determined. The historical battery parameters include at least one of the following: historical battery expansion force and historical expansion force change slope, where the historical expansion force change slope represents the slope of the historical battery expansion force as the historical SOC changes. A target filtering model is constructed based on the correspondence, and the target filtering model is used to determine the predicted battery parameters corresponding to the current battery parameters. The correction coefficient determined by the predicted battery parameters is used to correct the current SOC to obtain the target SOC. This application, by determining the correspondence between historical SOC and historical battery parameters (including historical expansion force and historical expansion force change slope), constructs a target filtering model, then uses the target filtering model to obtain predicted battery parameters, and then uses the correction coefficient obtained based on the predicted battery parameters to adjust the current SOC, obtaining a more accurate target SOC. This technical solution solves the technical problem of how to improve the accuracy of SOC correction, improves the accuracy of SOC correction, and also improves the correction efficiency and accuracy of SOC in the plateau region or insignificant change region of the battery OCV-SOC curve.

[0047] In an exemplary embodiment, determining a target filtering model based on the correspondence includes: creating observation equations and state equations based on the correspondence, and generating the target filtering model according to the observation equations and the state equations. The observation equations describe the mapping relationship between observed quantities and state variables to be estimated, and the state equations describe the updated state variables of the state variables to be estimated. The observed quantities characterize the current battery parameters, and the state variables to be estimated characterize the predicted battery parameters. This embodiment refines the construction process of the target filtering model by establishing observation equations and state equations, ensuring that the model can accurately describe the relationship between battery parameters and SOC. The observation equations and state equations respectively describe the relationship between observed quantities and state variables to be estimated, as well as the evolution law of the state variables themselves, thereby enhancing the model's predictive and error correction capabilities.

[0048] Optionally, current battery parameters may include, but are not limited to, battery voltage, battery expansion force, or slope of expansion force change.

[0049] Optionally, state variables may include battery state of charge and battery voltage, and predicted battery parameters may include predicted voltage, predicted battery expansion force, predicted slope of expansion force change, etc., but are not limited to these.

[0050] In an exemplary embodiment, determining the correspondence between historical state of charge (SOC) and historical battery parameters at different times includes at least one of the following: if the historical battery parameters also include historical voltage, determining a first correspondence between historical SOC and historical voltage at different times; determining a second correspondence between historical SOC and the slope of historical expansion force change at different times; and determining a third correspondence between historical SOC and the second derivative of historical battery expansion force with respect to historical SOC at different times. This embodiment explicitly states that the construction of the correspondence covers the first correspondence between historical SOC and historical voltage, the second correspondence with the slope of historical expansion force change, and the third correspondence with the second derivative of historical battery expansion force. By introducing the influencing factors of the slope of expansion force change and battery expansion force, further specific correspondences are set, which can more meticulously reflect the characteristics of the battery under different SOCs, providing a solid data foundation for high-precision correction of SOC.

[0051] Optionally, regarding the voltage in the aforementioned battery parameters, this application does not limit the battery state when measuring the voltage value. The battery state can be charging, discharging, or open circuit. The open circuit voltage when the battery state is open circuit represents the voltage at which the battery is not charging or discharging, i.e., there is no current input or output relationship between the battery and the external circuit. The correspondence established in this embodiment can be understood as utilizing the influence of the historical open circuit voltage on the slope of the SOC change, and further inferring the first correction coefficient corresponding to the state of charge based on the change of the historical open circuit voltage. However, the open circuit voltage must be indirectly calculated based on the directly measured voltage value.

[0052] In an exemplary embodiment, creating an observation equation based on the correspondence includes: establishing a first observation sub-equation corresponding to the historical voltage based on the first correspondence; establishing a second observation sub-equation corresponding to the historical expansion force change slope based on the second correspondence; establishing a third observation sub-equation corresponding to the historical battery expansion force based on the third correspondence; and determining the observation equation based on the first, second, and third observation sub-equations. This embodiment details how to transform historical battery parameters into the basis for model prediction by establishing observation equations based on the first, second, and third correspondences respectively. This approach enables the filtering model to learn more directly from historical battery state data, improving the accuracy and reliability of the target filtering model's predictions.

[0053] In an exemplary embodiment, creating a state equation based on the correspondence includes: establishing a first state sub-equation based on the state of charge (SOC) value and the battery capacity ratio at the previous time step; establishing a second state sub-equation based on the polarization voltage at the previous time step; and determining the state equation based on the first and second state sub-equations. This embodiment introduces a method for constructing the state equation, utilizing parameters such as the SOC value, battery capacity ratio, and polarization voltage at the previous time step to predict the current SOC and polarization voltage state, thereby enabling real-time adjustments based on the dynamic characteristics of the battery and improving the accuracy of SOC prediction.

[0054] In an exemplary embodiment, determining the predicted battery parameters corresponding to the current battery parameters using the target filtering model includes: calculating the new state of charge (SOC) value corresponding to the previous state of charge (SOC) value using the first state equation, and calculating the new polarization voltage corresponding to the previous polarization voltage using the second state equation; and determining the predicted battery parameters based on the new SOC value and the new polarization voltage. This embodiment further refines the SOC prediction process by using state equations to calculate the new SOC value and the new polarization voltage value, and further determines the predicted battery parameters based on the new state variables, which facilitates real-time reflection of battery state changes and improves the real-time performance and accuracy of SOC prediction.

[0055] In one exemplary embodiment, the method further includes: when the state variable to be estimated is updated, determining a new observation using the updated state variable through the observation equation, and determining the predicted battery parameters based on the new observation. This embodiment determines the new observation through the observation equation when the state variable is updated, and corrects the predicted battery parameters with the latest state variable information. This allows for real-time dynamic prediction of battery parameters through the model, enabling a faster and more accurate response to changes in battery state.

[0056] In an exemplary embodiment, determining the predicted battery parameters based on the new observation includes: determining the partial derivative of the new observation with respect to the updated state quantity, and determining a target filter gain based on the partial derivative; if the observation represents the battery expansion force, determining a first state vector corresponding to the new battery expansion force based on the updated state quantity; and determining the predicted battery expansion force based on the expansion force correction term corresponding to the target filter gain and the first state vector, wherein the predicted battery parameters include the predicted battery expansion force. This embodiment, by determining the partial derivative of the new observation with respect to the updated state quantity, calculating the target filter gain, and determining the predicted battery expansion force based on the expansion force correction term corresponding to the target filter gain and the first state vector, and then correcting the predicted battery expansion force based on the measured value of the battery expansion force, can effectively correct SOC errors in the battery OCV-SOC platform region and enhance the reliability of the prediction.

[0057] In one exemplary embodiment, the method further includes: determining a second state vector corresponding to a new expansion force change slope based on the updated state quantity, provided that the observed quantity represents the expansion force change slope; and determining a predicted expansion force change slope based on the expansion force slope correction term corresponding to the target filter gain and the second state vector, wherein the predicted battery parameters include the predicted expansion force change slope. This embodiment expands the types of observed quantities by introducing the battery expansion force change slope as an observed quantity, and then corrects the predicted expansion force change slope through the target filter gain, effectively improving the accuracy and stability of SOC correction.

[0058] In an exemplary embodiment, the predicted battery parameters include at least one of the following: predicted voltage, predicted battery expansion force, and predicted expansion force change slope. Before correcting the current state of charge (SOC) using correction coefficients determined by the predicted battery parameters, the method further includes one of the following: determining a first correction coefficient based on the predicted voltage and the current SOC, wherein the correction coefficient includes at least the first correction coefficient; determining a second correction coefficient based on the predicted expansion force change slope, wherein the correction coefficient includes at least the second correction coefficient; determining a third correction coefficient based on the second derivative of the predicted battery expansion force with respect to the current SOC, wherein the correction coefficient includes at least the third correction coefficient; and determining a fourth correction coefficient based on the predicted expansion force change slope and / or the second derivative of the predicted battery expansion force with respect to the current SOC, wherein the correction coefficient includes at least the fourth correction coefficient. This embodiment determines correction coefficients based on different observations (such as battery voltage, battery expansion force, and expansion force change slope), making the SOC correction method more flexible and adaptable to different types of batteries and operating conditions, significantly improving the accuracy and adaptability of SOC correction.

[0059] In an exemplary embodiment, before correcting the current state of charge (SOC) using the correction coefficient determined by the predicted battery parameters, the method further includes: determining the current SOC based on the ratio of the initial SOC to the battery capacity at the first sampling time, wherein the battery capacity ratio represents the ratio between the first sampled charge and the battery capacity in the previous sampling period, and the first sampled charge represents the product of the current and the sampling time interval at the previous sampling time. This embodiment determines the initial SOC based on the battery capacity ratio at the first sampling time, providing an initial benchmark for SOC correction, improving the accuracy of the corrected data, and reducing the probability of error accumulation due to improper initial state settings.

[0060] Optionally, the above battery capacity ratio can be calculated, for example, by the formula ΔSOC=ΔQ / Q, where ΔSOC represents the battery capacity ratio, ΔQ represents the first sampled charge, and Q represents the battery capacity.

[0061] Optionally, when taking the initial state of charge at the sampling time, the battery capacity ratio specifically refers to the ratio between the first sampled charge of the previous sampling period and the battery capacity at this sampling time. The battery capacity is generally a fixed value, determined by the battery model and battery material type at the time of manufacture.

[0062] In one exemplary embodiment, the current battery parameters include the current voltage, and the method further includes one of the following: determining the initial state of charge (SOC) based on the last recorded historical SOC; determining the initial SOC based on a preset SOC of the battery; obtaining the initial SOC set by the target object; and determining the initial SOC corresponding to the current voltage based on a first correspondence. This embodiment provides multiple methods for determining the initial SOC, specifically including methods based on historical SOC, preset SOC, target object settings, or determined through an OCV-SOC table, improving the richness and practicality of the methods and enabling flexible adaptation to SOC correction needs in different scenarios.

[0063] In one exemplary embodiment, correcting the current state of charge (SOC) using correction coefficients determined by the predicted battery parameters to obtain a target SOC includes one of the following: when the predicted battery parameters include the predicted voltage and the predicted battery expansion force, correcting the first SOC value of the current SOC using voltage correction values ​​and expansion force correction values ​​to obtain a second SOC value of the target SOC; when the predicted battery parameters include the predicted voltage and the predicted expansion force change slope, correcting the first SOC value of the current SOC using voltage correction values ​​and expansion force slope correction values ​​to obtain a second SOC value of the target SOC; when the predicted battery parameters include the predicted voltage, the predicted battery expansion force, and the predicted expansion force change slope, correcting the first SOC value of the current SOC using one of the expansion force correction values ​​and the expansion force slope correction values, along with the voltage correction value, to obtain a second SOC value of the target SOC. This embodiment corrects the State of Charge (SOC) based on different predicted battery parameters (voltage, battery expansion force, and expansion force change slope). By combining voltage correction values ​​and expansion force correction values ​​(or expansion force slope correction values), multi-dimensional correction of SOC is achieved, improving the accuracy and stability of the correction results.

[0064] In an exemplary embodiment, correcting a first state of charge (SOC) value of the current state of charge using a voltage correction value and an expansion force correction value to obtain a second SOC value of the target state of charge includes: obtaining the voltage difference between the predicted voltage and the current voltage, and determining the voltage correction value based on the product of the first correction coefficient and the voltage difference; obtaining the expansion force difference between the predicted battery expansion force and the current battery expansion force, and determining the expansion force correction value based on the product of the second correction coefficient and the expansion force difference; and determining the second SOC value based on the sum of the first SOC value, the voltage correction value, and the expansion force correction value. This embodiment uses the voltage difference and expansion force difference, combined with a correction coefficient, for SOC correction. This effectively utilizes changes in expansion force to correct SOC when the battery is operating in the OCV-SOC plateau region, avoiding accuracy reduction due to long-term accumulation of SOC errors and improving overall accuracy.

[0065] In an exemplary embodiment, a first state of charge (SOC) value of the current state of charge is corrected using a voltage correction value and an expansion force slope correction value to obtain a second SOC value of the target SOC value. This includes: obtaining the voltage difference between the predicted voltage and the current voltage, and determining the voltage correction value based on the product of the first correction coefficient and the voltage difference; obtaining the expansion force slope difference between the predicted expansion force change slope and the current expansion force change slope, and determining the expansion force slope correction value based on the product of the third correction coefficient and the expansion force slope difference; and determining the second SOC value based on the sum of the first SOC value, the voltage correction value, and the expansion force slope correction value. This embodiment can correct SOC errors quickly by combining the expansion force slope difference and the voltage difference in the OCV-SOC plateau region or regions with insignificant changes, utilizing the characteristic of the battery expansion force change slope to improve the stability and accuracy of SOC estimation.

[0066] In one exemplary embodiment, a first state of charge (SOC) value of the current state of charge is corrected using one of an expansion force correction value and an expansion force slope correction value, along with a voltage correction value, to obtain a second SOC value of the target state of charge. This includes: obtaining the voltage difference between the predicted voltage and the current voltage, and determining the voltage correction value based on the product of the first correction coefficient and the voltage difference; obtaining the expansion force difference between the predicted battery expansion force and the current battery expansion force, and determining the expansion force correction value based on the product of the fourth correction coefficient and the expansion force difference; and determining the second SOC value based on the sum of the first SOC value, the voltage correction value, and the expansion force correction value. This embodiment, by selectively combining an expansion force correction value or an expansion force slope correction value, and then performing SOC correction with a voltage correction value, provides a more flexible SOC correction strategy under different operating conditions. This allows for flexible selection of the most effective correction method based on the battery state, improving the efficiency and accuracy of SOC correction.

[0067] In an exemplary embodiment, a first state of charge (SOC) value of the current state of charge is corrected using one of an expansion force correction value and an expansion force slope correction value, along with a voltage correction value, to obtain a second SOC value of the target state of charge. This includes: obtaining the voltage difference between the predicted voltage and the current voltage, and determining the voltage correction value based on the product of the first correction coefficient and the voltage difference; obtaining the expansion force slope difference between the predicted expansion force change slope and the current expansion force change slope; determining the expansion force slope correction value based on the product of the fourth correction coefficient and the expansion force slope difference; and determining the second SOC value based on the sum of the first SOC value, the voltage correction value, and the expansion force slope correction value. In this embodiment, when the predicted parameters do not conform to a preset range, a target prediction model is introduced. Based on real-time parameters such as equivalent polarization resistance, battery capacity, and temperature, the voltage, battery expansion force, and expansion force change slope are re-predicted, ensuring the rationality of the predicted parameters, avoiding SOC correction errors caused by model prediction bias, and improving the robustness and accuracy of the overall system.

[0068] In an exemplary embodiment, the historical battery parameters further include the historical equivalent polarization resistance, historical battery capacity, and historical battery temperature at the sampling time. The method further includes: if it is determined that the predicted battery parameters do not conform to a preset parameter range, inputting the current equivalent polarization resistance, current battery capacity, and current battery temperature into a target prediction model to obtain the target voltage, target battery expansion force, and target expansion force change slope output by the target prediction model; determining the predicted battery parameters based on the target voltage, target battery expansion force, and target expansion force change slope; wherein the target prediction model is a prediction model obtained by training the historical equivalent polarization resistance, historical battery capacity, and historical battery temperature at different sampling times as input samples, and the historical voltage corresponding to the historical state of charge at different sampling times, the historical expansion force change slope corresponding to the historical state of charge, and the second derivative of the historical battery expansion force with respect to the historical state of charge as output samples. In this embodiment, when the predicted battery parameters output by the Kalman filter model do not conform to the preset parameter range, a new model is introduced. A target prediction model is constructed using a neural network, and the model is trained using historical data. This enables the model to predict battery state parameters based on real-time equivalent polarization resistance, battery capacity, and temperature. By combining the predictive power of machine learning with highly adaptive battery characteristics, the intelligence and accuracy of SOC correction are improved. Furthermore, by utilizing the richness and diversity of historical data, the model can more comprehensively cover various battery operating states, enhancing the generalization ability and stability of the SOC correction method.

[0069] It should be noted that in this application, the Kalman filter model is preferably used to output the predicted battery parameters, and other models are secondarily selected to output the predicted battery parameters. By using multiple models, the situation where the correction fails due to the lack of effective predicted battery parameters can be avoided, thereby improving the robustness of the battery SOC correction in the embodiments of this application.

[0070] Optionally, the aforementioned equivalent polarization internal resistance, battery capacity, and battery temperature can be obtained, for example, from a battery parameter table, which may include, for example, a Ri-SOC table, a battery capacity-SOC table, and a battery temperature-SOC table, where i is a positive integer.

[0071] To better understand the process of the above-described method for correcting the current state of charge, the implementation flow of the above-described method for correcting the current state of charge will be described below in conjunction with optional embodiments, but this is not intended to limit the technical solutions of the embodiments of this application.

[0072] In one embodiment, combined Figure 2 The amendment process in this application is explained. For example... Figure 2As shown, the current SOC1 (corresponding to the first state of charge value of the current state of charge) is calculated using the initial SOC (corresponding to the initial state of charge value mentioned above). Based on the voltage observation, the battery expansion force or the slope of the battery expansion force with respect to SOC is further introduced as an observation. Simultaneously, the expansion force or the slope of the expansion force with respect to SOC is introduced into the correction coefficient, thereby increasing the SOC correction coefficient component Kf. The correction formula SOC2 = SOC1 + Ku is then used. (U_test–U_cal)+Kf (F_test–F_cal) performs a secondary correction on the current SOC1, improving the accuracy of SOC estimation. This way, when the battery operates in the OCV-SOC plateau region, the SOC can be effectively corrected based on changes in expansion force, effectively correcting the battery SOC error. This avoids lithium plating caused by unreasonable charging current due to SOC error, which affects battery life and safety, thus significantly improving SOC estimation accuracy and enhancing battery life and safety. SOC2 corresponds to the second state of charge value of the aforementioned target state of charge. Ku (U_test–U_cal) corresponds to the voltage correction value mentioned above, Kf (F_test–F_cal) corresponds to the aforementioned expansion force correction value or expansion force slope correction value. U_test represents the test voltage, and U_cal represents the predicted value of the battery voltage; F_test represents the battery expansion force or the slope of the battery expansion force with SOC (i.e., the expansion force change slope). When F_test represents the battery expansion force, F_cal is the predicted value of the battery expansion force; when F_test represents the slope of the battery expansion force with SOC, F_cal is the predicted slope value of the rate of change of the battery expansion force with SOC.

[0073] This embodiment provides a method for correcting the current state of charge. Figure 3 This is a flowchart illustrating a method for correcting the current state of charge according to an embodiment of this application, as shown below. Figure 3 As shown, the specific steps are as follows:

[0074] Step S301: Establish the OCV (Open Circuit Voltage)-SOC table B1, the dF / dSOC-SOC relationship table B2, and the d2F / dSOC2-SOC relationship table B3.

[0075] Step S302: Construct a Kalman filter model using Tables B1, B2, and B3.

[0076] Step S303: Estimate SOC and SOC1.

[0077] In step S303, SOC1 = SOC + I For T / Q, at the first sampling time, SOC is the SOC value recorded at the end of the last sampling, or a default value such as the SOC value when the battery manufacturing line comes off, or a value dynamically assigned by other methods when SOC is missing, such as assigning an initial SOC value by looking up the SOC-OCV table based on the current OCV. T / Q represents the battery capacity ratio, where I is the current at the previous moment, T is the sampling time interval, and Q is the battery capacity.

[0078] Step S304: Input battery characteristic parameters P1, battery SOC, battery charging and discharging current, temperature and other battery parameters into the Kalman filter model, and use the Kalman filter model to output the predicted battery voltage, battery expansion force, and slope of battery expansion force change (representing the slope of battery expansion force change with SOC).

[0079] Step S305: Calculate the correction coefficients Ku (corresponding to the first correction coefficient) and Kf (corresponding to the second, third, or fourth correction coefficient), and perform secondary correction.

[0080] in, , ,or , or Kf=f4( , ).

[0081] fj() denotes a function, where j takes the value [1, 4].

[0082] Furthermore, the prediction process for the Kalman filter model (corresponding to the target filter model mentioned above) can be referenced as follows.

[0083] Step 1: Determine the state equations and observation equations of the Kalman filter model. The state equations describe the transition and update process of the state variables, while the observation equations describe the mapping relationship between the observed quantities and the state variables to be estimated. The state variables are represented as follows: .

[0084] The state equations include the following formulas. Formula (1) represents the first state sub-equation, and formula (2) represents the state sub-equation.

[0085] (1).

[0086] (2).

[0087] Among them, SOC k Let SOC be the state of matter at time k. k-1 Let SOC be at time k-1. This represents the ratio of battery capacity at the previous moment, where T is the sampling period, Q is the battery capacity, and I is the battery capacity. k-1Let U be the current at time k-1. p，k U is the polarization voltage at time k. p，k-1 R is the polarization voltage at time k-1. p，k-1 Let Cp be the equivalent polarization resistance at time k-1, and Cp be the equivalent polarization capacitance.

[0088] The observation equations include the voltage observation equation (corresponding to the first observation sub-equation), the expansion force observation equation (corresponding to the third observation sub-equation), and the expansion force slope observation equation (corresponding to the second observation sub-equation).

[0089] The voltage observation equation is as follows.

[0090] (3).

[0091] Among them, U k Let I be the battery voltage at time k, R0 be the battery's internal resistance in ohms, and I be the internal resistance of the battery. k Let be the battery current at time k.

[0092] The equation for observing expansion force is as follows.

[0093] (4).

[0094] Among them, F k Let K be the battery expansion force at time k.

[0095] The equation for observing the slope of the expansion force is as follows.

[0096] (5).

[0097] in, The slope of the expansion force change is calculated based on the expansion force measured under different SOCs.

[0098] Step 2: Update the state vector according to equations (1) and (2).

[0099] (6).

[0100] (7).

[0101] in, The SOC of the previous time step (i.e., time step k-1) The SOC predicted for the current time (i.e., time k). This represents the polarization voltage at the previous time step (i.e., time step k-1). This is the polarization voltage predicted at the current time (i.e., time k).

[0102] The predicted value of the state covariance was calculated. .

[0103] (8).

[0104] in, Q is the system noise covariance.

[0105] Step 3: Calculate the predicted values ​​of the observations according to equations (3), (4) and (5).

[0106] (9).

[0107] in, The voltage predicted at the current time (i.e., time k). The estimated value of OCV can be obtained by directly looking up the table based on the SOC predicted at the current time (i.e., time k), or it can be obtained by calculating the estimated value of OCV based on the SOC predicted at the current time (i.e., time k) using the OCV-SOC curve or the OCV-SOC function.

[0108] When the observable is expansion force: .

[0109] in, This represents the estimated value of F. This means that the estimated value of F can be obtained by directly looking up the table based on the SOC predicted at the current time (i.e., time k), or it can be the estimated value of F obtained by calculating the SOC predicted at the current time (i.e., time k) based on the F-SOC curve or F-SOC function.

[0110] When the observed quantity is the slope of the expansion force:

[0111] .

[0112] in, This represents the estimated value of dF / dSOC. This represents the estimated value of dF / dSOC obtained by directly looking up the table based on the SOC predicted at the current time (i.e., time k). Alternatively, it can be the estimated value of dF / dSOC obtained by calculating the SOC predicted at the current time (i.e., time k) based on the dF / dSOC-SOC curve or the dF / dSOC-SOC function.

[0113] Step 4: Calculate the first-order partial derivative matrix of the observation with respect to the state variables (corresponding to the partial derivatives mentioned above) H. k .

[0114] If we take expansion force as the second objective, then .

[0115] If the slope of the expansion force is taken as the second observation, then .

[0116] in, The slope of the OCV-SOC curve at the current SOC. This represents the slope of F-SOC at the current SOC, which is the slope of the expansion force as a function of SOC, calculated based on the measured expansion force values ​​and records of SOC changes. It is the second derivative of F-SOC at the current SOC.

[0117] Step 5, calculate the Kalman filter gain K. K .

[0118] (10).

[0119] Where R is the observation noise covariance.

[0120] Step 6: Update the predicted battery parameters.

[0121] When the observed quantity is the expansion force F.

[0122] .

[0123] in, This is a correction term for expansion force. This is the first state vector.

[0124] When the observed quantity is the slope of the expansion force dF / dSOC.

[0125] .

[0126] Optionally, refer to Figures 4 to 6 This application describes the revised state of charge. Figures 4 to 6 In the diagram, the blue curve represents the change in the actual SOC of the battery during discharge, the gray curve represents the SOC error estimated by the traditional method, and the orange curve represents the SOC error estimated by the method of this application. Figure 4 In the previous example, the battery SOC was discharged from 73% to 67% within 4000 seconds, with an initial error of -10%. It is evident that the traditional method has a very slow error convergence speed in the OCV plateau region; after 3000 seconds of discharge, the error is still greater than 5%. However, the method of this application, under the same discharge conditions, can correct the error to below 5% within the first 24 seconds. Figure 5 In the previous example, the battery SOC was discharged from 73% to 67% in 4000 seconds with an initial error of +10%. It is evident that the traditional method has a very slow error convergence speed in the OCV plateau region; after 4000 seconds of discharge, the error is still greater than 8%. However, the method of this application, under the same conditions, can correct the error to approximately 0% within the first 1000 seconds and maintains stable error in subsequent discharges. Figure 6In the previous method, the battery SOC was discharged from 65% to 36% within 20,000s, with an initial error of +15%. It can be seen that the traditional method showed effective error convergence in the first 2261s, but the error convergence speed was very slow. During the continuous discharge process, the error of the traditional algorithm gradually increased to a negative deviation, and the deviation gradually increased. In contrast, the solution of this application controlled the error within 2% during the continuous discharge process.

[0127] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of this application.

[0128] Figure 7 This is a structural block diagram of a current state of charge correction device according to an embodiment of this application; as shown... Figure 7 As shown, it includes:

[0129] The first determining module 72 is used to determine the correspondence between the historical state of charge and the historical battery parameters at different times. The historical battery parameters include at least one of the following: historical battery expansion force and historical expansion force change slope. The historical expansion force change slope represents the change slope of the historical battery expansion force as the historical state of charge changes.

[0130] The second determining module 74 is used to determine the target filtering model constructed based on the correspondence, and to use the target filtering model to determine the predicted battery parameters corresponding to the current battery parameters.

[0131] The module 76 is used to correct the current state of charge using the correction coefficients determined by the predicted battery parameters, so as to obtain the target state of charge.

[0132] The above-described apparatus determines the correspondence between historical state of charge (SOC) and historical battery parameters at different times. The historical battery parameters include at least one of the following: historical battery expansion force and historical expansion force change slope, where the historical expansion force change slope represents the rate at which the historical battery expansion force changes with the historical SOC. A target filtering model is constructed based on this correspondence, and the target filtering model is used to determine the predicted battery parameters corresponding to the current battery parameters. The correction coefficients determined by the predicted battery parameters are used to correct the current SOC, resulting in the target SOC. This application, by determining the correspondence between historical SOC and historical battery parameters (including historical expansion force and historical expansion force change slope), constructs a target filtering model, then uses the target filtering model to obtain predicted battery parameters, and finally uses the correction coefficients obtained based on the predicted battery parameters to adjust the current SOC, thus obtaining a more accurate target SOC. This technical solution solves the technical problem of how to improve the accuracy of SOC correction, improves the accuracy of SOC correction, and also improves the correction efficiency and accuracy of SOC in the plateau region or insignificant change region of the battery OCV-SOC curve.

[0133] In an exemplary embodiment, the second determining module is further configured to: create an observation equation and a state equation based on the correspondence, and generate the target filtering model according to the observation equation and the state equation, wherein the observation equation is used to describe the mapping relationship between the observed quantity and the state quantity to be estimated, the state equation is used to describe the updated state quantity of the state quantity to be estimated, the observed quantity represents the current battery parameter, and the state quantity to be estimated represents the predicted battery parameter.

[0134] In an exemplary embodiment, the second determining module is further configured to perform at least one of the following: when the historical battery parameters also include historical voltage, determining a first correspondence between historical state of charge and historical voltage at different times; determining a second correspondence between historical state of charge and the slope of historical expansion force change at different times; and determining a third correspondence between historical state of charge and the second derivative of historical battery expansion force with respect to historical state of charge at different times.

[0135] In an exemplary embodiment, the second determining module is further configured to: establish a first observation sub-equation corresponding to the historical voltage based on the first correspondence; establish a second observation sub-equation corresponding to the historical expansion force change slope based on the second correspondence; establish a third observation sub-equation corresponding to the historical battery expansion force based on the third correspondence; and determine the observation equation according to the first observation sub-equation, the second observation equation, and the third observation equation.

[0136] In an exemplary embodiment, the second determining module is further configured to: establish a first state sub-equation based on the state of charge value at the previous moment and the battery capacity ratio at the previous moment; establish a second state sub-equation based on the polarization voltage at the previous moment; and determine the state equation according to the first state sub-equation and the second state sub-equation.

[0137] In an exemplary embodiment, the second determining module is further configured to: calculate a new state of charge value corresponding to the state of charge value at the previous moment using the first state sub-equation, and calculate a new polarization voltage corresponding to the polarization voltage at the previous moment using the second state sub-equation; and determine the predicted battery parameters based on the new state of charge value and the new polarization voltage.

[0138] In an exemplary embodiment, the second determining module is further configured to: determine new observations using the updated state quantities through the observation equations when the state quantities to be estimated are updated, and determine the predicted battery parameters based on the new observations.

[0139] In an exemplary embodiment, the second determining module is further configured to: determine the partial derivative of the new observation with respect to the updated state quantity, and determine a target filter gain based on the partial derivative; if the observation represents the battery expansion force, determine a first state vector corresponding to the new battery expansion force according to the updated state quantity; and determine a predicted battery expansion force based on the expansion force correction term corresponding to the target filter gain and the first state vector, wherein the predicted battery parameters include the predicted battery expansion force.

[0140] In an exemplary embodiment, the second determining module is further configured to: determine a second state vector corresponding to a new expansion force change slope based on the updated state quantity when the observed quantity represents the expansion force change slope; and determine a predicted expansion force change slope based on the expansion force slope correction term corresponding to the target filter gain and the second state vector, wherein the predicted battery parameters include the predicted expansion force change slope.

[0141] In an exemplary embodiment, the obtaining module is further configured to determine the current state of charge based on the ratio of the initial state of charge at the first sampling time to the battery capacity before correcting the current state of charge using the correction coefficient determined by the predicted battery parameters, wherein the battery capacity ratio represents the ratio between the first sampled charge and the battery capacity in the previous sampling period, and the first sampled charge represents the product between the current and the sampling time interval in the previous sampling time.

[0142] In an exemplary embodiment, the current battery parameters include the current voltage. The module is further configured to perform one of the following: determine the initial state of charge based on the last recorded historical state of charge; determine the initial state of charge based on the battery's preset state of charge; obtain the initial state of charge set by the target object; and determine the initial state of charge corresponding to the current voltage based on a first correspondence.

[0143] In an exemplary embodiment, the predicted battery parameters include at least one of the following: predicted voltage, predicted battery expansion force, and predicted expansion force change slope; the obtaining module is further configured to, before correcting the current state of charge using correction coefficients determined by the predicted battery parameters, perform one of the following: determining a first correction coefficient based on the predicted voltage and the current state of charge, wherein the correction coefficient includes at least the first correction coefficient; determining a second correction coefficient based on the predicted expansion force change slope, wherein the correction coefficient includes at least the second correction coefficient; determining a third correction coefficient based on the second derivative of the predicted battery expansion force with respect to the current state of charge, wherein the correction coefficient includes at least the third correction coefficient; and determining a fourth correction coefficient based on the predicted expansion force change slope and / or the second derivative of the predicted battery expansion force with respect to the current state of charge, wherein the correction coefficient includes at least the fourth correction coefficient.

[0144] In one exemplary embodiment, the module is further configured to implement one of the following: when the predicted battery parameters include the predicted voltage and the predicted battery expansion force, correcting the first state of charge value of the current state of charge using a voltage correction value and an expansion force correction value to obtain a second state of charge value of the target state of charge; when the predicted battery parameters include the predicted voltage and the predicted expansion force change slope, correcting the first state of charge value of the current state of charge using a voltage correction value and an expansion force slope correction value to obtain a second state of charge value of the target state of charge; when the predicted battery parameters include the predicted voltage, the predicted battery expansion force, and the predicted expansion force change slope, correcting the first state of charge value of the current state of charge using one of the expansion force correction value and the expansion force slope correction value, as well as a voltage correction value, to obtain a second state of charge value of the target state of charge.

[0145] In an exemplary embodiment, the obtaining module is further configured to: obtain a voltage difference between the predicted voltage and the current voltage, and determine a voltage correction value based on the product of the first correction coefficient and the voltage difference; obtain an expansion force difference between the predicted battery expansion force and the current battery expansion force, and determine the expansion force correction value based on the product of the second correction coefficient and the expansion force difference; and determine a second state of charge value based on the sum of the first state of charge value, the voltage correction value, and the expansion force correction value.

[0146] In an exemplary embodiment, the obtaining module is further configured to: acquire the voltage difference between the predicted voltage and the current voltage, and determine the voltage correction value based on the product of the first correction coefficient and the voltage difference; acquire the expansion force slope difference between the predicted expansion force change slope and the current expansion force change slope, and determine the expansion force slope correction value based on the product of the third correction coefficient and the expansion force slope difference; and determine the second state of charge value based on the sum of the first state of charge value, the voltage correction value, and the expansion force slope correction value.

[0147] In an exemplary embodiment, the obtaining module is further configured to: obtain a voltage difference between the predicted voltage and the current voltage, and determine a voltage correction value based on the product of the first correction coefficient and the voltage difference; obtain an expansion force difference between the predicted battery expansion force and the current battery expansion force, and determine the expansion force correction value based on the product of the fourth correction coefficient and the expansion force difference; and determine a second state of charge value based on the sum of the first state of charge value, the voltage correction value, and the expansion force correction value.

[0148] In an exemplary embodiment, the obtaining module is further configured to: acquire the voltage difference between the predicted voltage and the current voltage, and determine the voltage correction value based on the product of the first correction coefficient and the voltage difference; acquire the expansion force slope difference between the predicted expansion force change slope and the current expansion force change slope; determine the expansion force slope correction value based on the product of the fourth correction coefficient and the expansion force slope difference; and determine the second state of charge value based on the sum of the first state of charge value, the voltage correction value, and the expansion force slope correction value.

[0149] In an exemplary embodiment, the historical battery parameters further include the historical equivalent polarization resistance, historical battery capacity, and historical battery temperature at the sampling time. The device further includes a third determining module, which is configured to, when it is determined that the predicted battery parameters do not conform to a preset parameter range, input the current equivalent polarization resistance, current battery capacity, and current battery temperature into a target prediction model to obtain a target voltage, target battery expansion force, and target expansion force change slope output by the target prediction model; and determine the predicted battery parameters based on the target voltage, target battery expansion force, and target expansion force change slope; wherein the target prediction model is a prediction model obtained by training the historical equivalent polarization resistance, historical battery capacity, and historical battery temperature at different sampling times as input samples, and the historical voltage corresponding to the historical state of charge at different sampling times, the historical expansion force change slope corresponding to the historical state of charge, and the second derivative of the historical battery expansion force with respect to the historical state of charge as output samples.

[0150] Embodiments of this application also provide a storage medium including a stored program, wherein the program executes any of the methods described above when it is run.

[0151] Optionally, in this embodiment, the storage medium may be configured to store program code for performing the following steps:

[0152] S1, determine the correspondence between the historical state of charge and the historical battery parameters at different times, wherein the historical battery parameters include at least one of the following: historical battery expansion force, historical expansion force change slope, wherein the historical expansion force change slope represents the change slope of the historical battery expansion force as the historical state of charge changes;

[0153] S2, determine the target filtering model constructed based on the correspondence, and use the target filtering model to determine the predicted battery parameters corresponding to the current battery parameters;

[0154] S3, use the correction coefficient determined by the predicted battery parameters to correct the current state of charge to obtain the target state of charge.

[0155] Embodiments of this application also provide an electronic device including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

[0156] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor and the input / output device is connected to the processor.

[0157] Optionally, in this embodiment, the processor can be configured to perform the following steps via a computer program:

[0158] S1, determine the correspondence between the historical state of charge and the historical battery parameters at different times, wherein the historical battery parameters include at least one of the following: historical battery expansion force, historical expansion force change slope, wherein the historical expansion force change slope represents the change slope of the historical battery expansion force as the historical state of charge changes;

[0159] S2, determine the target filtering model constructed based on the correspondence, and use the target filtering model to determine the predicted battery parameters corresponding to the current battery parameters;

[0160] S3, use the correction coefficient determined by the predicted battery parameters to correct the current state of charge to obtain the target state of charge.

[0161] Optionally, in this embodiment, the storage medium may include, but is not limited to, various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0162] Optionally, embodiments of this application also provide a computer program product, which includes a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0163] Optionally, embodiments of this application also provide another computer program product, including a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0164] Optionally, embodiments of this application also provide a computer program, which includes computer instructions stored in a computer-readable storage medium; a processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the steps in any of the above method embodiments.

[0165] Optionally, specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementations, and will not be repeated here.

[0166] Obviously, those skilled in the art should understand that the modules or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented here, or they can be fabricated as separate integrated circuits, or multiple modules or steps can be fabricated as a single integrated circuit. Thus, this application is not limited to any particular hardware and software combination.

[0167] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for correcting the current state of charge, characterized in that, At least including: Determine the correspondence between historical state of charge and historical battery parameters at different times, wherein the historical battery parameters include at least one of the following: historical battery expansion force and historical expansion force change slope, wherein the historical expansion force change slope represents the change slope of the historical battery expansion force as the historical state of charge changes; Determine the target filtering model constructed based on the correspondence, and use the target filtering model to determine the predicted battery parameters corresponding to the current battery parameters; The current state of charge is corrected using the correction coefficients determined by the predicted battery parameters to obtain the target state of charge.

2. The method for correcting the current state of charge according to claim 1, characterized in that, Determining the target filtering model based on the correspondence includes: Based on the correspondence, observation equations and state equations are created, and the target filtering model is generated according to the observation equations and the state equations. The observation equations are used to describe the mapping relationship between the observed quantity and the state quantity to be estimated, and the state equations are used to describe the updated state quantity of the state quantity to be estimated. The observed quantity represents the current battery parameter, and the state quantity to be estimated represents the predicted battery parameter.

3. The method for correcting the current state of charge according to claim 2, characterized in that, Determine the correspondence between historical state of charge and historical battery parameters at different times, including at least one of the following: If the historical battery parameters also include historical voltage, a first correspondence between historical state of charge and historical voltage at different times is determined. Determine a second correspondence between the historical state of charge at different times and the slope of the historical expansion force change; A third correspondence is determined between the historical state of charge at different times and the second derivative of the historical battery expansion force with respect to the historical state of charge.

4. The method for correcting the current state of charge according to claim 3, characterized in that, Based on the aforementioned correspondence, an observation equation is created, including: Based on the first correspondence, establish the first observation sub-equation corresponding to the historical voltage; Based on the second correspondence, establish the second observation sub-equation corresponding to the slope of the historical expansion force change; Based on the third correspondence, establish the third observation sub-equation corresponding to the historical battery expansion force; The observation equation is determined based on the first observation sub-equation, the second observation sub-equation, and the third observation sub-equation.

5. The method for correcting the current state of charge according to claim 3, characterized in that, Based on the aforementioned correspondence, state equations are created, including: The first state sub-equation is established based on the state of charge value of the previous time step and the battery capacity ratio of the previous time step. The second state sub-equation is established based on the polarization voltage of the previous moment; The state equation is determined based on the first state sub-equation and the second state sub-equation.

6. The method for correcting the current state of charge according to claim 5, characterized in that, The target filtering model is used to determine the predicted battery parameters corresponding to the current battery parameters, including: The first state sub-equation is used to calculate the new state of charge corresponding to the state of charge value at the previous moment, and the second state sub-equation is used to calculate the new polarization voltage corresponding to the polarization voltage at the previous moment. The predicted battery parameters are determined based on the new state of charge and the new polarization voltage.

7. The method for correcting the current state of charge according to claim 6, characterized in that, The method further includes: In the case of an update to the state variable to be estimated, the new observation is determined using the updated state variable through the observation equation, and the predicted battery parameters are determined based on the new observation.

8. The method for correcting the current state of charge according to claim 7, characterized in that, Determining the predicted battery parameters based on the new observations includes: Determine the partial derivative of the new observation with respect to the updated state quantity, and determine the target filter gain based on the partial derivative; Given that the observed quantity represents the battery expansion force, a first state vector corresponding to the new battery expansion force is determined based on the updated state quantity. The predicted battery expansion force is determined based on the expansion force correction term corresponding to the target filter gain and the first state vector, wherein the predicted battery parameters include the predicted battery expansion force.

9. The method for correcting the current state of charge according to claim 8, characterized in that, The method further includes: Given that the observed quantity represents the slope of the expansion force change, a second state vector corresponding to the new expansion force change slope is determined based on the updated state quantity. The predicted expansion force change slope is determined based on the expansion force slope correction term corresponding to the target filter gain and the second state vector, wherein the predicted battery parameters include the predicted expansion force change slope.

10. The method for correcting the current state of charge according to claim 1, characterized in that, Before correcting the current state of charge using the correction coefficients determined by the predicted battery parameters, the method further includes: The current state of charge is determined based on the ratio of the initial state of charge at the first sampling time to the battery capacity, wherein the battery capacity ratio represents the ratio between the first sampled charge and the battery capacity in the previous sampling period, and the first sampled charge represents the product of the current at the previous sampling time and the sampling time interval.

11. The method for correcting the current state of charge according to claim 10, characterized in that, The current battery parameters include the current voltage, and the method further includes one of the following: The initial state of charge is determined based on the last recorded historical state of charge. The initial state of charge is determined based on the battery's preset state of charge. Obtain the initial charge state set by the target object; The initial state of charge corresponding to the current voltage is determined based on the first correspondence.

12. The method for correcting the current state of charge according to claim 1, characterized in that, The predicted battery parameters include at least one of the following: predicted voltage, predicted battery expansion force, and predicted expansion force change slope; before correcting the current state of charge using correction coefficients determined by the predicted battery parameters, the method further includes one of the following: A first correction factor is determined based on the predicted voltage and the current state of charge, wherein the correction factor includes at least the first correction factor; A second correction coefficient is determined based on the predicted slope of the expansion force change, wherein the correction coefficient includes at least the second correction coefficient; A third correction coefficient is determined based on the second derivative of the predicted battery expansion force with respect to the current state of charge, wherein the correction coefficient includes at least the third correction coefficient. A fourth correction coefficient is determined based on the slope of the predicted expansion force change and / or the second derivative of the predicted battery expansion force with respect to the current state of charge, wherein the correction coefficient includes at least the fourth correction coefficient.

13. The method for correcting the current state of charge according to claim 12, characterized in that, The current state of charge is corrected using the correction coefficients determined by the predicted battery parameters to obtain a target state of charge, including one of the following: When the predicted battery parameters include the predicted voltage and the predicted battery expansion force, the first state of charge value of the current state of charge is corrected using the voltage correction value and the expansion force correction value to obtain the second state of charge value of the target state of charge. When the predicted battery parameters include the predicted voltage and the predicted expansion force change slope, the first state of charge value of the current state of charge is corrected using the voltage correction value and the expansion force slope correction value to obtain the second state of charge value of the target state of charge. When the predicted battery parameters include the predicted voltage, the predicted battery expansion force, and the predicted expansion force change slope, the first state of charge value of the current state of charge is corrected using one of the expansion force correction value and the expansion force slope correction value, as well as the voltage correction value, to obtain the second state of charge value of the target state of charge.

14. The method for correcting the current state of charge according to claim 13, characterized in that, The first state of charge value of the current state of charge is corrected using voltage correction values ​​and expansion force correction values ​​to obtain the second state of charge value of the target state of charge, including: Obtain the voltage difference between the predicted voltage and the current voltage, and determine the voltage correction value based on the product of the first correction coefficient and the voltage difference; Obtain the expansion force difference between the predicted battery expansion force and the current battery expansion force, and determine the expansion force correction value based on the product of the second correction coefficient and the expansion force difference; The second state of charge value is determined based on the sum of the first state of charge value, the voltage correction value, and the expansion force correction value.

15. The method for correcting the current state of charge according to claim 13, characterized in that, The first state of charge value of the current state of charge is corrected using voltage correction values ​​and expansion force slope correction values ​​to obtain the second state of charge value of the target state of charge, including: Obtain the voltage difference between the predicted voltage and the current voltage, and determine the voltage correction value based on the product of the first correction coefficient and the voltage difference; Obtain the difference in expansion force slope between the predicted expansion force change slope and the current expansion force change slope, and determine the expansion force slope correction value based on the product of the third correction coefficient and the difference in expansion force slope; The second state of charge value is determined based on the sum of the first state of charge value, the voltage correction value, and the expansion force slope correction value.

16. The method for correcting the current state of charge according to claim 13, characterized in that, The first state of charge value of the current state of charge is corrected using one of the expansion force correction value and the expansion force slope correction value, as well as the voltage correction value, to obtain the second state of charge value of the target state of charge, including: Obtain the voltage difference between the predicted voltage and the current voltage, and determine the voltage correction value based on the product of the first correction coefficient and the voltage difference; Obtain the expansion force difference between the predicted battery expansion force and the current battery expansion force, and determine the expansion force correction value based on the product of the fourth correction coefficient and the expansion force difference; The second state of charge value is determined based on the sum of the first state of charge value, the voltage correction value, and the expansion force correction value.

17. The method for correcting the current state of charge according to claim 13, characterized in that, The first state of charge value of the current state of charge is corrected using one of the expansion force correction value and the expansion force slope correction value, as well as the voltage correction value, to obtain the second state of charge value of the target state of charge, including: Obtain the voltage difference between the predicted voltage and the current voltage, and determine the voltage correction value based on the product of the first correction coefficient and the voltage difference; Obtain the difference in expansion force slope between the predicted expansion force change slope and the current expansion force change slope; The expansion force slope correction value is determined by the product of the fourth correction coefficient and the expansion force slope difference; The second state of charge value is determined based on the sum of the first state of charge value, the voltage correction value, and the expansion force slope correction value.

18. The method for correcting the current state of charge according to claim 1, characterized in that, The historical battery parameters also include the historical equivalent polarization resistance, historical battery capacity, and historical battery temperature at the sampling time. The method further includes: If the predicted battery parameters do not meet the preset parameter range, the current equivalent polarization internal resistance, current battery capacity and current battery temperature are input into the target prediction model to obtain the target voltage, target battery expansion force and target expansion force change slope output by the target prediction model. The predicted battery parameters are determined based on the target voltage, the target battery expansion force, and the slope of the target expansion force change. The target prediction model is a prediction model obtained by training the historical equivalent polarization internal resistance, historical battery capacity and historical battery temperature at different sampling times as input samples, and the historical voltage corresponding to the historical state of charge at different sampling times, the slope of the historical expansion force change corresponding to the historical state of charge and the second derivative of the historical battery expansion force with respect to the historical state of charge as output samples.

19. A device for correcting the current state of charge, characterized in that, include: The first determining module is used to determine the correspondence between the historical state of charge and the historical battery parameters at different times. The historical battery parameters include at least one of the following: historical battery expansion force and historical expansion force change slope. The historical expansion force change slope represents the change slope of the historical battery expansion force as the historical state of charge changes. The second determining module is used to determine the target filtering model constructed based on the correspondence, and to use the target filtering model to determine the predicted battery parameters corresponding to the current battery parameters. The module is used to correct the current state of charge using the correction coefficients determined by the predicted battery parameters, thereby obtaining the target state of charge.

20. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein the program, when executed, performs the method according to any one of claims 1 to 18.

21. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to execute the method described in any one of claims 1 to 18 through the computer program.

22. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method described in any one of claims 1 to 18.

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