Polar coordinate-based SOC correction method and system, vehicle and electronic equipment

Abstract

The invention relates to the technical field of battery management systems, in particular to an SOC correction method and system based on polar coordinates, a vehicle and electronic equipment, and the method comprises the steps: building a terminal voltage estimation model; collecting the battery terminal voltage, the battery current, the battery temperature and the sampling point time of the battery under the N sampling points, and calculating the battery charge state and the battery health state corresponding to each sampling point; estimating a battery terminal voltage corresponding to each sampling point through the terminal voltage calculation model; respectively converting the actually acquired mapping relation between the battery end voltage and the battery state of charge and the estimated mapping relation between the battery end voltage and the battery state of charge into a polar coordinate system, and calculating the polar radius and polar angle of each sampling point under the polar coordinate system; solving an optimal battery charge state at a preset moment, and calculating a first battery charge state; and correcting a second battery state of charge based on the first battery state of charge. According to the invention, the state of charge of the battery can be effectively calibrated.

Description

Technical Field

[0001] The present invention relates to the technical field of battery management systems, and in particular to a polar coordinate-based SOC correction method, system, vehicle, and electronic equipment. Background Art

[0002] Accurate state-of-charge (SOC) estimation is a core function of a battery management system (BMS), directly impacting the safety, range, and lifespan of lithium iron phosphate batteries. High-precision SOC estimation optimizes charge and discharge strategies, effectively preventing overcharging or over-discharging, thereby extending battery life and providing users with reliable remaining charge information.

[0003] However, lithium iron phosphate batteries exhibit a low voltage slope in the plateau region. This means the curve between the open circuit voltage (OCV) and the SOC is very flat in the plateau region, with minimal voltage variation (typically only 2mV-3mV). This characteristic results in significant errors in the traditional open circuit voltage method when estimating SOC, making it difficult to meet the requirements for high-precision estimation. Furthermore, model parameter offsets caused by factors such as polarization effects, temperature drift, and aging during battery charge and discharge further exacerbate the cumulative error in SOC estimation in the plateau region.

[0004] To overcome this accuracy bottleneck, researchers have proposed a variety of methods for dynamic model correction and real-time parameter identification. However, existing technologies still have the following limitations:

[0005] Insufficient sensitivity under the low slope characteristics of the platform area: Due to the flat voltage-SOC curve in the platform area, the traditional OCV lookup table method causes small voltage changes to be amplified into large SOC estimation errors, which cannot meet the requirements of high-precision estimation.

[0006] Limited correction triggering conditions: Some existing technologies rely on users to frequently perform partial charging and discharging or manual intervention to trigger SOC correction, which does not match the user's actual usage pattern and limits the practical application scope of the technology.

[0007] Therefore, it is necessary to develop a new SOC correction method, system, vehicle and electronic equipment based on polar coordinates. Summary of the Invention

[0008] The purpose of the present invention is to provide a polar coordinate-based SOC correction method, system, vehicle, and electronic device to achieve high-precision SOC estimation and correction, improve the battery management system's monitoring accuracy of the battery status, extend the battery life, and provide users with more reliable remaining power information.

[0009] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0010] In a first aspect, the present invention provides a polar coordinate-based SOC correction method, comprising the following steps:

[0011] Establishing a terminal voltage estimation model, wherein the terminal voltage calculation model is used to characterize the mapping relationship between the battery terminal voltage and the battery state of charge, battery current, battery temperature, battery health status, and operating time;

[0012] Collect the battery terminal voltage, battery current, battery temperature and sampling point time at N sampling points, and calculate the battery state of charge corresponding to each sampling point through the ampere-hour integration method, and obtain the battery health status corresponding to each sampling point;

[0013] Based on the battery current, battery temperature, sampling point time, battery state of charge, and battery health status corresponding to each sampling point, the terminal voltage calculation model is used to estimate the battery terminal voltage corresponding to each sampling point;

[0014] The mapping relationship between the actual collected battery terminal voltage and the battery state of charge, and the mapping relationship between the estimated battery terminal voltage and the battery state of charge are converted into polar coordinate systems respectively, and the polar diameter and polar angle of each sampling point in polar coordinates are calculated;

[0015] Calculate the optimal battery state of charge at a preset time using the polar diameter and polar angle in polar coordinates;

[0016] Calculating a first battery state of charge by an ampere-hour integration method based on the optimal battery state of charge at the preset moment;

[0017] The second battery state of charge is corrected based on the first battery state of charge.

[0018] In a possible implementation, the terminal voltage estimation model is:

[0019] U=f(SOC,I,T,SOH,t)

[0020] Where U is the battery terminal voltage, SOC is the battery state of charge, I is the battery current, T is the battery temperature, SOH is the battery state of health, and t is the operating time. This voltage estimation model is used to characterize the mapping relationship between the battery terminal voltage and the battery state of charge, battery current, battery temperature, battery state of health, and operating time. By comprehensively considering multiple factors that affect the battery terminal voltage, it can more comprehensively and accurately reflect the actual state of the battery, providing a more reliable model foundation for subsequent SOC estimation and correction. This helps to improve the accuracy of SOC estimation, especially under dynamic operating conditions, and can better adapt to the impact of factors such as temperature and current changes on the battery state.

[0021] One possible implementation involves collecting the battery terminal voltage, battery current, battery temperature, and sampling time at N sampling points during a plug-in charging scenario. The current is relatively constant in plug-in charging scenarios, ensuring the accuracy of subsequent calculations.

[0022] In one possible implementation, the sampling points are selected when the current remains stable for at least one minute and the current fluctuation range does not exceed ±5A. This ensures the stability and reliability of the collected data and reduces errors caused by current fluctuations. This data provides accurate foundational data for subsequent model estimation and polar coordinate conversion, helping to improve the accuracy of SOC estimation.

[0023] One possible implementation method is to convert the mapping relationship between the actual collected battery terminal voltage and the battery state of charge, and the mapping relationship between the estimated battery terminal voltage and the battery state of charge into a polar coordinate system, specifically including:

[0024] Convert the mapping relationship between the terminal battery voltage and the battery state of charge from a rectangular coordinate system to a polar coordinate system;

[0025] The rectangular coordinate system includes a first and second perpendicular axis. The first axis represents the battery terminal voltage, while the second axis represents the battery state of charge. (0, the battery upper limit voltage) of the rectangular coordinate system serves as the polar coordinate origin. In the polar coordinate system, the voltage-SOC curve, which would normally appear flat in the rectangular coordinate system, can now exhibit linear characteristics. This allows for clearer visualization of small voltage changes and improves the sensitivity of SOC estimation in plateau regions.

[0026] One possible implementation method is to calculate the polar diameter and polar angle of each sampling point in polar coordinates, specifically:

[0027] θi=arctan[(3.65-Ui) / SOCi]

[0028] Wherein, ri is the polar radius of the mapping relationship between the actual collected battery terminal voltage and the battery state of charge at the i-th sampling point converted into polar coordinates, θi is the polar angle of the mapping relationship between the actual collected battery terminal voltage and the battery state of charge at the i-th sampling point converted into polar coordinates, SOCi is the battery state of charge corresponding to the i-th sampling point, and Ui is the actual collected battery terminal voltage at the i-th sampling point;

[0029] θ set i=arctan[(3.65-U set i) / SOCi]

[0030] Among them, r seti is the mapping relationship between the estimated battery terminal voltage and the battery state of charge corresponding to the i-th sampling point converted to the polar coordinates, θ set i is the polar angle corresponding to the mapping relationship between the estimated battery terminal voltage and the battery state of charge at the i-th sampling point, and Uesti is the estimated battery terminal voltage. Calculating the polar diameter and polar angle of each sampling point in polar coordinates provides key parameters for minimizing the objective function and solving for the optimal SOC.

[0031] In one possible implementation, the method for calculating the optimal battery state of charge at the preset time is:

[0032] Set the minimum RMS deviation of the voltage pole angle and pole diameter at the objective function terminal, Loss. The expression of Loss is as follows:

[0033]

[0034] Solve the SOCx that minimizes Loss, then SOCx is the optimal battery state of charge at the preset time,

[0035] Where k1 is the first weight coefficient and k2 is the second weight coefficient. This method comprehensively considers the deviation of the polar diameter and polar angle, and can more comprehensively measure the difference between the actual collected data and the estimated data. By minimizing the objective function, the optimal battery state of charge is found.

[0036] In one possible implementation, the method for calculating the state of charge of the first battery is:

[0037]

[0038] Where Q is the battery's current maximum available capacity; SOCt is the first battery state of charge, representing the target battery state of charge at the current time t; I is the battery current; t0 is the preset time; and t is the current time. This step combines the optimal battery state of charge at the preset time with the ampere-hour integration method to update the optimal battery state of charge at the current time in real time, enabling dynamic estimation and correction of the SOC, ensuring the accuracy and real-time nature of the SOC value.

[0039] In a possible implementation, the preset time is the time of the first sampling point to simplify calculation.

[0040] In a second aspect, the present invention provides a polar coordinate-based SOC correction system, comprising:

[0041] A terminal voltage estimation model establishment module is used to establish a terminal voltage estimation model, wherein the terminal voltage estimation model is used to characterize the mapping relationship between the battery terminal voltage and the battery state of charge, battery current, battery temperature, battery health status, and operating time;

[0042] The data acquisition module is used to collect the battery terminal voltage, battery current, battery temperature and sampling point time of the battery at N sampling points, and calculate the battery state of charge corresponding to each sampling point through the ampere-hour integration method, and at the same time obtain the battery health status corresponding to each sampling point;

[0043] a terminal voltage estimation module, which estimates the battery terminal voltage corresponding to each sampling point through the terminal voltage estimation model based on the battery current, battery temperature, sampling point time, battery state of charge, and battery health status corresponding to each sampling point;

[0044] A polar coordinate conversion module is used to convert the mapping relationship between the actual collected battery terminal voltage and the battery state of charge, and the mapping relationship between the estimated battery terminal voltage and the battery state of charge into a polar coordinate system, and calculate the polar diameter and polar angle of each sampling point in the polar coordinate system;

[0045] The optimal SOC solution module is used to solve the optimal battery state of charge at a preset time using the polar diameter and polar angle in polar coordinates;

[0046] a target SOC calculation module, configured to calculate a first battery state of charge by an ampere-hour integration method based on the optimal battery state of charge at the preset moment;

[0047] The SOC correction module is configured to correct the second battery state of charge based on the first battery state of charge.

[0048] In a third aspect, a vehicle according to the present invention adopts the polar coordinate-based SOC correction system according to the present invention.

[0049] In a fourth aspect, an electronic device according to the present invention includes a processor and a memory, wherein at least one computer program is stored in the memory, and when the at least one computer program is loaded and executed by the processor, the steps of the polar coordinate-based SOC correction method provided in the above-mentioned method embodiments can be implemented.

[0050] It should be noted that various possible implementations of any of the above aspects can be combined under the premise that the solutions are not contradictory.

[0051] The present invention has the following beneficial effects:

[0052] (1) Solve the problem of insufficient sensitivity under low slope characteristics in the platform area

[0053] The present invention converts the mapping relationship between the actual collected battery terminal voltage and the battery state of charge, and the mapping relationship between the estimated battery terminal voltage and the battery state of charge, respectively, into a polar coordinate system. In the polar coordinate system, the voltage-SOC curve, which is originally flat in the rectangular coordinate system, can be linearized, making small voltage changes more clearly reflected in the polar coordinate system, thereby improving the sensitivity of SOC estimation in the plateau region. By solving the optimal battery state of charge at a preset time by using the polar diameter and polar angle in the polar coordinate system, it can effectively reduce the SOC estimation error and meet the requirements of high-precision estimation.

[0054] (2) Improve adaptability to dynamic working conditions

[0055] The terminal voltage estimation model established in the present invention is used to characterize the mapping relationship between the battery terminal voltage and the battery state of charge, battery current, battery temperature, battery state of health, and operating time. During the calculation process, the battery terminal voltage, battery current, battery temperature, and sampling time at multiple sampling points are collected, and the battery state of health corresponding to each sampling point is obtained. The battery terminal voltage corresponding to each sampling point is estimated using the terminal voltage estimation model. This model and calculation method, which considers multiple influencing factors, can better adapt to polarization effects caused by temperature and current changes under dynamic operating conditions, thereby improving the accuracy of SOC estimation under dynamic conditions.

[0056] 3. Overcoming the problem of limited correction trigger conditions

[0057] This invention establishes a terminal voltage estimation model, collects battery-related data, and uses polar coordinate transformation and objective function minimization to determine the optimal battery state of charge. Based on this optimal battery state of charge, the first battery state of charge is calculated using the ampere-hour integration method, and the second battery state of charge is corrected. This entire process is automated based on the battery's operating data and model calculations, eliminating the need for frequent partial charge and discharge or manual intervention to trigger corrections. This process aligns with actual user usage patterns, expanding the technology's practical application.

[0058] 4. Solve the problem of large cumulative error caused by the inability to calibrate SOC in the platform area

[0059] The present invention establishes a terminal voltage estimation model that includes multiple influencing factors, and comprehensively considers factors such as battery current, battery temperature, sampling point time, battery state of charge, and battery health status during the calculation process. In the polar coordinate system, the optimal battery state of charge is solved by minimizing the objective function, and then the first battery state of charge is calculated based on the optimal battery state of charge, and the second battery state of charge is corrected using the first battery state of charge. This method can effectively calibrate the SOC, reduce the cumulative error of the SOC estimation in the platform area caused by model parameter offsets caused by factors such as polarization effects, temperature drift, and aging, and achieve high-precision SOC estimation in the platform area. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 is a flow chart of the SOC correction method based on polar coordinates described in an embodiment of the present application;

[0061] Figure 2 This is a schematic diagram of the conversion between rectangular coordinates and polar coordinates in the embodiment of the present application;

[0062] Figure 3 is the linear relationship in the polar coordinate system in the embodiment of the present application (i.e., the relationship between SOC and polar diameter);

[0063] Figure 4 This is a calculation deviation distribution diagram of the lithium iron phosphate battery verification algorithm in the embodiment of the present application;

[0064] Figure 5 is a flow chart of the SOC correction system based on polar coordinates described in an embodiment of the present application;

[0065] Figure 6 is a principle block diagram of an electronic device in an embodiment of the present application;

[0066] In the figure: 1. Voltage terminal voltage estimation model establishment module, 2. Data acquisition module, 3. Terminal voltage estimation module, 4. Terminal voltage estimation module, 5. Optimal SOC solution module, 6. Target SOC calculation module, 7. SOC correction module, 8. Memory, 9. Processor. DETAILED DESCRIPTION

[0067] The following will describe the embodiments of the present invention with reference to the accompanying drawings and preferred embodiments. Those skilled in the art will be able to understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be understood that the preferred embodiments are only for the purpose of illustrating the present invention and are not intended to limit the scope of protection of the present invention.

[0068] In the embodiments of the present application, in order to clearly describe the technical solutions of the embodiments of the present application, words such as "first" and "second" are used to distinguish between identical or similar items with substantially the same functions and effects. Those skilled in the art will understand that words such as "first" and "second" do not limit the quantity or execution order, and words such as "first" and "second" do not necessarily mean different. There is no order of precedence or priority between the technical features described by "first" and "second".

[0069] In the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of this application should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner to facilitate understanding.

[0070] In the embodiments of the present application, at least one can also be described as one or more, and multiple can be two, three, four or more, which is not limited in this application.

[0071] like Figure 1 As shown, in an embodiment of the present application, a polar coordinate-based SOC correction method includes the following steps:

[0072] Step 1. Establish a terminal voltage estimation model. The terminal voltage calculation model is used to characterize the mapping relationship between the battery terminal voltage and the battery state of charge, battery current, battery temperature, battery health status, and operating time.

[0073] Step 2. Collect the battery terminal voltage, battery current, battery temperature and sampling point time at N sampling points, and calculate the battery state of charge corresponding to each sampling point by the ampere-hour integration method, and obtain the battery health status corresponding to each sampling point.

[0074] Step 3. Based on the battery current, battery temperature, sampling point time, battery state of charge, and battery state of health corresponding to each sampling point, estimate the battery terminal voltage corresponding to each sampling point through the terminal voltage calculation model.

[0075] Step 4. Convert the mapping relationship between the actual collected battery terminal voltage and the battery state of charge, and the mapping relationship between the estimated battery terminal voltage and the battery state of charge into a polar coordinate system, and calculate the polar diameter and polar angle of each sampling point in the polar coordinate system.

[0076] Step 5. Calculate the optimal battery state of charge at a preset time using the polar diameter and polar angle in polar coordinates.

[0077] Step 6. Based on the optimal battery state of charge at a preset time, calculate a first battery state of charge by using an ampere-hour integration method.

[0078] Step 7: Correct the second battery state of charge based on the first battery state of charge.

[0079] In the embodiment of the present application, the first battery state of charge is the target battery state of charge at the current moment (i.e., obtained through steps 1 to 6). The second battery state of charge is the current battery state of charge (i.e., the battery state of charge calculated in real time by the vehicle-side battery management system using the ampere-hour integration method).

[0080] This method first converts the mapping relationship between the actual collected and estimated battery terminal voltage and battery state of charge into a polar coordinate system. In the rectangular coordinate system, the voltage-SOC (battery state of charge) curve of the lithium iron phosphate battery is relatively flat in the platform area (see Figure 2 ), small voltage changes are difficult to show, but after conversion to the polar coordinate system, the curve can show linear characteristics (see Figure 3 ), which significantly improves the sensitivity of SOC estimation in the platform area. This method constructs a terminal voltage estimation model that includes multiple influencing factors such as battery current, battery temperature, sampling point time, battery state of charge and battery health status. In the polar coordinate system, the optimal battery state of charge at the preset moment is solved by minimizing the objective function. This process can effectively reduce the SOC estimation error and meet the needs of high-precision estimation. Subsequently, based on the optimal battery state of charge at the preset moment, the ampere-hour integration method is used to calculate the first battery state of charge, and the current battery state of charge (i.e., the second battery state of charge) is corrected accordingly. This method can effectively calibrate the battery state of charge, reduce the model parameter offset caused by factors such as polarization effect, temperature drift and battery aging, thereby reducing the cumulative error of SOC estimation in the platform area and achieving high-precision SOC estimation in the platform area.

[0081] The following is a detailed description of each step in the embodiment of the present application:

[0082] In a possible embodiment, step 1 is specifically as follows:

[0083] By testing and simulating the battery cells, data related to the battery terminal voltage, battery state of charge, battery current, battery temperature, battery health status, and operating time are obtained.

[0084] Establish a terminal voltage estimation model that characterizes the mapping relationship between battery terminal voltage and battery state of charge, battery current, battery temperature, battery health status, and operating time:

[0085] U=f(SOC,I,T,SOH,t) (1)

[0086] Among them, U is the battery terminal voltage, SOC is the battery state of charge, I is the battery current, T is the battery temperature, SOH is the battery health state, and t is the operating time.

[0087] The terminal voltage estimation model not only considers the static relationship between battery state of charge and voltage, but also dynamic factors (such as battery current, battery temperature, and battery health status), making it adaptable to battery behavior under different operating conditions. This multi-factor modeling improves the accuracy of the terminal voltage estimation model by considering various factors that affect the battery terminal voltage.

[0088] The mathematical model of this mapping relationship includes but is not limited to an analytical model, a discrete numerical model, etc.

[0089] In a possible embodiment, step 2 is specifically as follows:

[0090] To ensure high accuracy in estimating the battery terminal voltage, it is necessary to select scenarios with constant current, such as plug-in charging and sentry scenarios. The smaller the current fluctuation, the more accurate the data collection.

[0091] Taking a plug-in charging scenario as an example, during actual vehicle charging, the battery voltage, current, and temperature are filtered to remove sensor noise and improve data quality. Depending on the specific situation, the battery voltage, current, and temperature are collected at regular intervals over a specific time span, resulting in N sampling points. The battery current, voltage, and temperature at the i-th sampling point are denoted as Ii, Ui, and Ti, respectively, where i = 1, 2, ..., N.

[0092] To ensure the accuracy of the battery terminal voltage estimation and the accuracy of the final battery state of charge calculation value, the sampling points and the number of sampling points are determined based on meeting specific current and voltage conditions. Among them, the sampling point selection conditions are: the current remains stable for at least 1 minute and the current fluctuation range does not exceed ±5A. For example, subsequent calculations are based on 10 sampling points that meet the requirements. The selected sampling points can be distributed in the voltage platform area of the lithium iron phosphate battery.

[0093] For example, the battery state of charge corresponding to each sampling point is calculated by the ampere-hour integration method, specifically:

[0094] Select a certain moment, such as the first sampling point in the sampling interval corresponds to time t0. Assume that the battery state of charge at time t0 is SOC0. Based on this assumption, the battery state of charge of each other sampling point can be calculated. The specific calculation formula is as follows:

[0095]

[0096] Among them, SOCi is the battery state of charge at the i-th sampling point, ti is the sampling time corresponding to the i-th sampling point, Q is the current maximum available capacity of the battery, and I is the battery current.

[0097] At the same time, the battery health status corresponding to each sampling point is obtained. The calculation of the battery health status is an existing technology and will not be described in detail in the embodiments of this application.

[0098] In a possible embodiment, step 3 is specifically as follows:

[0099] Estimate the battery terminal voltage at each sampling point based on the terminal voltage estimation model established in step 1, specifically:

[0100] Uesti=f(SOCi,Ii,Ti,SOH,ti) (3)

[0101] Among them, Uesti is the estimated battery terminal voltage. That is, SOCi, Ii, Ti, SOH and ti corresponding to the sampling point i are substituted into the terminal voltage estimation model to estimate the battery terminal voltage corresponding to the sampling point i.

[0102] In a possible embodiment, step 4 comprises:

[0103] like Figure 2 As shown, the mapping relationship between the estimated battery terminal voltage and the battery state of charge, and the mapping relationship between the actually collected battery terminal voltage and the battery state of charge, are respectively converted into a polar coordinate system to describe the relationship between the battery terminal voltage and the battery state of charge. The rectangular coordinate system includes a first axis and a second axis that are perpendicular to each other. The first axis is used to represent the battery terminal voltage; the second axis is used to represent the battery state of charge. The rectangular coordinate system (0, the battery upper limit voltage) is used as the polar coordinate origin. For example, the battery upper limit voltage is 3.65V.

[0104] Points in the polar coordinate system are described by polar angles and polar diameters. The polar diameters and polar angles of each sampling point in polar coordinates are calculated as follows:

[0105] θi=arctan[(3.65-Ui) / SOCi]

[0106] Wherein, ri is the polar radius of the mapping relationship between the actual collected battery terminal voltage and the battery state of charge at the i-th sampling point converted into polar coordinates, θi is the polar angle of the mapping relationship between the actual collected battery terminal voltage and the battery state of charge at the i-th sampling point converted into polar coordinates, SOCi is the battery state of charge corresponding to the i-th sampling point, and Ui is the actual collected battery terminal voltage at the i-th sampling point;

[0107] θ set i=arctan[(3.65-Uesti) / SOCi]

[0108] Among them, r seti is the mapping relationship between the estimated battery terminal voltage and the battery state of charge corresponding to the i-th sampling point converted to the polar coordinates, θ set i is the polar angle converted from the mapping relationship between the estimated battery terminal voltage and the battery state of charge corresponding to the i-th sampling point to the polar coordinates.

[0109] like Figure 3 As shown in the figure, after the rectangular coordinate system is converted into the polar coordinate system, the battery state of charge and the polar diameter in the polar coordinate system in the voltage platform area in the rectangular coordinate system show an obvious linear correlation. This feature can be used to accurately calculate the battery state of charge in the lithium iron phosphate platform area and correct the battery state of charge.

[0110] In a possible embodiment, step 5 is specifically as follows:

[0111] By using a numerical solution method, the SOCx that best matches the estimated battery terminal voltage with the actual collected battery terminal voltage is solved. For example, the objective function is set to minimize the root mean square deviation of the terminal voltage polar angle and polar diameter. The expression of Loss is as follows:

[0112]

[0113] Solve the SOCx that minimizes Loss, then SOCx is the optimal battery state of charge at the preset time.

[0114] Wherein, k1 is the first weight coefficient, and k2 is the second weight coefficient.

[0115] In a possible embodiment, step 6 is specifically as follows:

[0116] According to the optimal battery state of charge at the preset time, the first battery state of charge is calculated by the ampere-hour integration method, specifically:

[0117]

[0118] Wherein, Q is the current maximum available capacity of the battery; SOCt is the first battery state of charge, indicating the target battery state of charge at the current time t; I is the battery current; t0 is the preset time; and t is the current time.

[0119] For example, in order to simplify calculation, the time of the first sampling point is generally selected as the preset time.

[0120] In a possible embodiment, step 7 is specifically as follows:

[0121] The second battery state of charge is corrected based on the first battery state of charge.

[0122] The current battery state of charge (ie, the second battery state of charge) is corrected according to the calculated target battery state of charge (ie, the first battery state of charge) at the current time t, thus completing the current SOC calibration logic.

[0123] In an embodiment of the present application, the vehicle-side battery management system (BMS) continuously calculates the battery's state of charge (SOC) in real time using the ampere-hour integration method. To ensure timely and accurate information about the remaining battery charge, the BMS typically performs this calculation at a higher frequency (e.g., every second or every few seconds). In contrast, the frequency at which this method calculates the target battery SOC is significantly lower than the conventional calculation frequency of the BMS. This is because the target battery SOC is primarily used to correct and calibrate the battery SOC calculated by the BMS.

[0124] like Figure 4 As shown in the figure, this solution is simulated and verified based on a charging test of a lithium iron phosphate power battery cell. The data contains test data of 120 battery cell samples starting to charge at different battery states of charge. The battery state of charge is calculated according to the above steps 1 to 7, and the verification results show that the estimation error of the battery state of charge is within ±3%, which can achieve the effect of accurately estimating the battery state of charge in the lithium iron phosphate platform area.

[0125] like Figure 5As shown, in an embodiment of the present application, a polar coordinate-based SOC correction system includes a voltage terminal voltage estimation model establishment module 1, a data acquisition module 2, a terminal voltage estimation module 3, a polar coordinate conversion module 4, an optimal SOC solution module 5, a target SOC calculation module 6, and an SOC correction module 7. The voltage terminal voltage estimation model establishment module 1 is used to establish a terminal voltage estimation model, which is used to characterize the mapping relationship between the battery terminal voltage and the battery state of charge, battery current, battery temperature, battery health status, and operating time. The data acquisition module 2 is used to collect the battery terminal voltage, battery current, battery temperature, and sampling point time of the battery at N sampling points, and calculate the battery state of charge corresponding to each sampling point using the ampere-hour integration method, while also obtaining the battery health status corresponding to each sampling point. The terminal voltage estimation module 3 estimates the battery terminal voltage corresponding to each sampling point using the terminal voltage estimation model based on the battery current, battery temperature, sampling point time, battery state of charge, and battery health status corresponding to each sampling point. The polar coordinate conversion module 4 is used to convert the mapping relationship between the actual collected battery terminal voltage and the battery state of charge, and the mapping relationship between the estimated battery terminal voltage and the battery state of charge into a polar coordinate system, and calculate the polar diameter and polar angle of each sampling point in the polar coordinate system. The optimal SOC solution module 5 is used to solve the optimal battery state of charge at a preset time using the polar diameter and polar angle in the polar coordinate system. The target SOC calculation module 6 is used to calculate the first battery state of charge based on the optimal battery state of charge at the preset time using the ampere-hour integration method. The SOC correction module 7 is used to correct the second battery state of charge based on the first battery state of charge.

[0126] In an embodiment of the present application, a vehicle adopts the polar coordinate-based SOC correction system as described in the embodiment of the present application.

[0127] The vehicle may be, but is not limited to, a pure electric vehicle (Pure Electric Vehicle / Battery Electric Vehicle, PEV / BEV), a hybrid electric vehicle (Hybrid Electric Vehicle, HEV), a range extended electric vehicle (Range Extended Electric Vehicle, REEV), a plug-in hybrid electric vehicle (Plug-in Hybrid Electric Vehicle, PHEV), a new energy vehicle (New Energy Vehicle), etc.

[0128] like Figure 6 As shown, on the other hand, an electronic device is provided, which includes a processor 9 and a memory 8, wherein the memory 8 stores at least one computer program, and when the at least one computer program is loaded and executed by the processor 9, the steps of the polar coordinate-based SOC correction method provided in the above-mentioned method embodiments can be implemented.

[0129] On the other hand, a computer-readable storage medium is provided, in which at least one computer program is stored. When the at least one computer program is loaded and executed by a processor, the polar coordinate-based SOC correction method provided in the above-mentioned method embodiments can be implemented.

[0130] On the other hand, a computer program product is provided. The computer program product includes a computer program or instructions. When the computer program or instructions are executed by a processor, the polar coordinate-based SOC correction method provided in the above method embodiments can be implemented.

[0131] It should be noted that when the instructions in the above-mentioned computer-readable storage medium or one or more instructions in the computer program product are executed by the processor of the electronic device, the various processes of the above-mentioned method embodiment are implemented and the same technical effect as the above-mentioned method can be achieved. To avoid repetition, they will not be repeated here.

[0132] Through the description of the above implementation methods, technical personnel in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete the full classification or partial functions described above.

[0133] The above embodiments are preferred implementation modes of the present invention, but the implementation modes of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications that do not deviate from the spirit and principles of the present invention should be considered as equivalent replacement methods and are included in the scope of protection of the present invention.

Claims

1. A SOC correction method based on polar coordinates, characterized in that: The following steps are involved: Establishing a terminal voltage estimation model, wherein the terminal voltage calculation model is used to characterize the mapping relationship between the battery terminal voltage and the battery state of charge, battery current, battery temperature, battery health status, and operating time; Collect the battery terminal voltage, battery current, battery temperature and sampling point time at N sampling points, and calculate the battery state of charge corresponding to each sampling point through the ampere-hour integration method, and obtain the battery health status corresponding to each sampling point; Based on the battery current, battery temperature, sampling point time, battery state of charge, and battery health status corresponding to each sampling point, the terminal voltage calculation model is used to estimate the battery terminal voltage corresponding to each sampling point; The mapping relationship between the actual collected battery terminal voltage and the battery state of charge, and the mapping relationship between the estimated battery terminal voltage and the battery state of charge are converted into polar coordinate systems, and the polar diameter and polar angle of each sampling point in polar coordinates are calculated; Calculate the optimal battery state of charge at a preset time using the polar diameter and polar angle in polar coordinates; Calculating a first battery state of charge by an ampere-hour integration method based on the optimal battery state of charge at the preset moment; The second battery state of charge is corrected based on the first battery state of charge.

2. The SOC correction method based on polar coordinates according to claim 1, characterized in that: The terminal voltage estimation model is: U=f(SOC,I,T,SOH,t) Among them, U is the battery terminal voltage, SOC is the battery state of charge, I is the battery current, T is the battery temperature, SOH is the battery health state, and t is the operating time.

3. The SOC correction method based on polar coordinates according to claim 1, characterized in that: In the plug-in charging scenario, the battery terminal voltage, battery current, battery temperature and sampling point time of the power battery at N sampling points are collected.

4. The SOC correction method based on polar coordinates according to claim 3, characterized in that: The sampling point selection conditions are: the current remains stable for at least 1 minute, and the current fluctuation range does not exceed ±5A.

5. The SOC correction method based on polar coordinates according to claim 1, characterized in that: The mapping relationship between the actual collected battery terminal voltage and the battery state of charge, and the mapping relationship between the estimated battery terminal voltage and the battery state of charge are converted into polar coordinate systems, specifically including: Convert the mapping relationship between the terminal battery voltage and the battery state of charge from a rectangular coordinate system to a polar coordinate system; The rectangular coordinate system includes a first axis and a second axis that are perpendicular to each other. The first axis is used to represent the battery terminal voltage; the second axis is used to represent the battery state of charge, and the rectangular coordinate system (0, the battery upper limit voltage) is used as the polar coordinate origin.

6. The polar coordinate-based SOC correction method according to claim 5, characterized in that: Calculate the polar diameter and polar angle of each sampling point in polar coordinates, specifically: Wherein, ri is the polar radius of the mapping relationship between the actual collected battery terminal voltage and the battery state of charge at the i-th sampling point converted into polar coordinates, θi is the polar angle of the mapping relationship between the actual collected battery terminal voltage and the battery state of charge at the i-th sampling point converted into polar coordinates, SOCi is the battery state of charge corresponding to the i-th sampling point, and Ui is the actual collected battery terminal voltage at the i-th sampling point; Among them, r set i is the mapping relationship between the estimated battery terminal voltage and the battery state of charge corresponding to the i-th sampling point converted to the polar coordinates, θ set i is the polar angle converted from the mapping relationship between the estimated battery terminal voltage and the battery state of charge corresponding to the i-th sampling point to the polar coordinates, and Uesti is the estimated battery terminal voltage.

7. The polar coordinate-based SOC correction method according to claim 6, characterized in that: The calculation method of the optimal battery state of charge at the preset time is: Set the minimum RMS deviation of the voltage pole angle and pole diameter at the objective function terminal Loss. The expression of Loss is as follows: Solve the SOCx that minimizes Loss, then SOCx is the optimal battery state of charge at the preset time; Wherein, k1 is the first weight coefficient, and k2 is the second weight coefficient.

8. The polar coordinate-based SOC correction method according to claim 7, characterized in that: The calculation method of the first battery state of charge is: Wherein, Q is the current maximum available capacity of the battery; SOCt is the first battery state of charge, indicating the target battery state of charge at the current time t; I is the battery current; t0 is the preset time; and t is the current time.

9. The SOC correction method based on polar coordinates according to claim 8, characterized in that: The preset time is the time of the first sampling point.

10. A SOC correction system based on polar coordinates, characterized in that: include: A terminal voltage estimation model establishment module (1) is used to establish a terminal voltage estimation model, wherein the terminal voltage estimation model is used to characterize the mapping relationship between the battery terminal voltage and the battery state of charge, battery current, battery temperature, battery health status, and operating time; A data acquisition module (2) is used to collect the battery terminal voltage, battery current, battery temperature and sampling point time of the battery at N sampling points, and calculate the battery state of charge corresponding to each sampling point by using the ampere-hour integration method, and simultaneously obtain the battery health status corresponding to each sampling point; A terminal voltage estimation module (3) estimates the battery terminal voltage corresponding to each sampling point through the terminal voltage estimation model based on the battery current, battery temperature, sampling point time, battery state of charge and battery health status corresponding to each sampling point; A polar coordinate conversion module (4) is used to convert the mapping relationship between the actual collected battery terminal voltage and the battery state of charge, and the mapping relationship between the estimated battery terminal voltage and the battery state of charge into a polar coordinate system, and calculate the polar diameter and polar angle of each sampling point in the polar coordinate system; An optimal SOC solving module (5) is used to solve the optimal battery state of charge at a preset time by using the polar diameter and polar angle under polar coordinates; A target SOC calculation module (6) is used to calculate a first battery state of charge by an ampere-hour integration method based on the optimal battery state of charge at the preset moment; An SOC correction module (7) is used to correct the second battery state of charge based on the first battery state of charge.

11. A vehicle, characterized in that: The polar coordinate-based SOC correction system according to claim 10 is adopted.

12. An electronic device, characterized in that: The electronic device includes a processor and a memory, wherein at least one computer program is stored in the memory. When the at least one computer program is loaded and executed by the processor, the steps of the polar coordinate-based SOC correction method according to any one of claims 1 to 9 can be executed.

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