Battery state of charge estimation methods, apparatus, computer equipment and storage media

Abstract

This invention relates to the field of battery management technology, and discloses a method, apparatus, computer device, and storage medium for estimating the state of charge (SOC) of a battery. The method involves acquiring the battery's current, voltage, and temperature; determining the battery's DC internal resistance based on the temperature; determining the battery's Joule heat based on the current and DC internal resistance; determining the battery's equivalent internal temperature based on the Joule heat; and estimating the battery's SOC based on the current, voltage, and equivalent internal temperature. The SOC estimation method provided by this invention calculates the battery's heat and determines the corresponding real-time equivalent internal temperature based on the relationship between the equivalent internal temperature and the heat. This method is not limited by the battery's structure and materials, improves the stability of the real-time internal temperature, and has wider applicability. Furthermore, by substituting the equivalent internal temperature into a preset model to estimate the battery's SOC, the accuracy of the SOC estimation is improved.

Description

Technical Field

[0001] This invention relates to the field of battery management technology, and in particular to a method, apparatus, computer device, and storage medium for estimating the state of charge of a battery. Background Technology

[0002] As one of the three core components of an electric vehicle, the performance of the power battery system directly affects the overall vehicle performance. Among these components, the State of Charge (SOC) is a crucial performance indicator. SOC reflects the battery's remaining capacity. It cannot be directly measured; rather, it must be estimated using a series of battery parameters. SOC estimation is a core function of the battery management system. Lithium-ion battery SOC estimation typically employs an equivalent circuit model. Model parameters are identified based on current, terminal voltage, and temperature feedback from the data acquisition unit to obtain an accurate SOC. While the acquired current and terminal voltage data are generally consistent with the actual battery values, the temperature sensor is located outside the cell. Current flowing through the cell generates heat, and the heat transfer to the sensor results in a delay and loss, leading to a difference between the measured temperature and the actual internal temperature of the cell.

[0003] Existing technologies establish a rigorous thermal conduction model to determine the correlation between cell temperature and the measured temperature. Based on the measured temperature, the real-time cell temperature is obtained, and the battery's state of charge (SOC) is estimated using an equivalent circuit model. However, modeling a thermal conduction model requires numerous complex thermal conduction parameters, and modifications to the cell structure and battery materials can significantly impact these temperature parameters. Using the real-time internal temperature of the cell obtained from the thermal conduction model to estimate the battery's SOC is limited by battery structure and materials, resulting in unstable real-time internal temperature results that cannot meet the needs of rapid battery technology iteration. Furthermore, it affects the accuracy of SOC estimation, hindering battery management. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, apparatus, computer device, and storage medium for estimating the state of charge of a battery to address the aforementioned technical problems, thereby resolving the issues of the inability to obtain stable real-time internal temperature results and the low accuracy of battery state of charge estimation.

[0005] A method for estimating the state of charge of a battery, comprising:

[0006] Obtain the battery's current, voltage, and temperature;

[0007] The DC internal resistance of the battery is determined based on the temperature.

[0008] The Joule heat of the battery is determined based on the current and the DC internal resistance;

[0009] The equivalent internal temperature of the battery is determined based on the Joule heating.

[0010] The state of charge of the battery is estimated based on the current, the voltage, and the equivalent internal temperature.

[0011] A battery state of charge estimation device, comprising:

[0012] The data acquisition module is used to acquire the battery's current, voltage, and temperature.

[0013] A DC internal resistance determination module is used to determine the DC internal resistance of the battery based on the temperature.

[0014] A Joule heating determination module is used to determine the Joule heating of the battery based on the current and the DC internal resistance;

[0015] An equivalent internal temperature determination module is used to determine the equivalent internal temperature of the battery based on the Joule heating.

[0016] A battery state of charge estimation module is used to estimate the battery state of charge based on the current, the voltage, and the equivalent internal temperature.

[0017] A computer device includes a memory, a processor, and computer-readable instructions stored in the memory and executable on the processor, wherein the processor implements the above-described battery state-of-charge estimation method when executing the computer-readable instructions.

[0018] One or more readable storage media storing computer-readable instructions, which, when executed by one or more processors, cause the one or more processors to perform the battery state-of-charge estimation method described above.

[0019] The aforementioned battery state of charge (SOC) estimation method, apparatus, computer equipment, and storage medium acquire the battery's current, voltage, and temperature; determine the battery's DC internal resistance based on the temperature; determine the battery's Joule heat based on the current and DC internal resistance; determine the battery's equivalent internal temperature based on the Joule heat; and process the current, voltage, and equivalent internal temperature using a preset SOC estimation model to generate the battery's SOC. The battery SOC estimation method provided by this invention calculates the battery's heat and determines the corresponding real-time equivalent internal temperature based on the relationship between the equivalent internal temperature and the heat. This method is not limited by the battery's structure and materials, improving the stability of the real-time internal temperature results and broadening its applicability. Furthermore, by substituting the equivalent internal temperature into a preset model to estimate the battery's SOC, the accuracy of the SOC estimation is improved. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart illustrating a battery state of charge estimation method according to an embodiment of the present invention;

[0022] Figure 2 This is a comparison of estimation errors of the battery state of charge estimation method in one embodiment of the present invention;

[0023] Figure 3 This is a schematic diagram of a battery state of charge estimation device in one embodiment of the present invention;

[0024] Figure 4 This is a schematic diagram of a computer device according to an embodiment of the present invention. Detailed Implementation

[0025] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] In one embodiment, such as Figure 1 As shown, a method for estimating the state of charge of a battery is provided, including the following steps S10-S50.

[0027] S10: Obtain the battery's current, voltage, and temperature.

[0028] Understandably, a battery management system includes various current acquisition devices for measuring current and terminal voltage acquisition devices for measuring terminal voltage. The battery's current and voltage are real-time data obtained by these acquisition devices, and the acquired current and terminal voltage data are consistent with the actual values ​​of the battery cells. The battery temperature is real-time temperature data obtained by external sensors. Because the current flowing through the cell generates heat, causing the temperature to rise, there is some heat loss during heat conduction from the inside of the cell to the external sensors. Therefore, there is a difference between the battery temperature and the actual internal temperature of the cell.

[0029] S20. Determine the DC internal resistance of the battery based on the temperature.

[0030] Understandably, battery internal resistance is an important indicator of battery performance, generally categorized into DC internal resistance and AC internal resistance. DC internal resistance refers to the ratio of the battery's voltage change to the corresponding discharge current change under operating conditions. For individual cells, AC internal resistance, commonly known as ohmic internal resistance, is generally used to evaluate battery characteristics. However, for large battery pack applications, such as the power battery systems of electric vehicles, DC internal resistance is typically used to evaluate battery characteristics. The actual operating temperature range of electric vehicle power batteries is relatively wide, and the battery internal resistance varies under different temperatures and operating conditions. While the DC internal resistance decreases with increasing temperature, the relationship between battery temperature and DC internal resistance is not linear. This embodiment pre-establishes internal resistance-temperature relationship data, which allows the determination of the DC internal resistance corresponding to a given temperature.

[0031] S30. Determine the Joule heat of the battery based on the current and the DC internal resistance.

[0032] Understandably, heat is generated when an electric current passes through a conductor; this is known as the thermal effect of electric current. Joule's law is a quantitative law explaining how conduction current converts electrical energy into heat energy. The heat generated by an electric current passing through a conductor is directly proportional to the square of the current, the resistance of the conductor, and the duration of the current flow. In this embodiment, the Joule heat of the battery can be determined per unit time using the current and the DC internal resistance.

[0033] S40. Determine the equivalent internal temperature of the battery based on the Joule heating.

[0034] Understandably, since heat is generated every moment as current flows through the cell, the accumulated heat raises the internal temperature of the cell. Therefore, a functional relationship between the internal temperature of the cell and Joule heat can be established, and the heat-temperature correlation parameter can be determined. Under actual operating conditions, the Joule heat at the current moment is calculated cumulatively, and the internal temperature of the cell corresponding to the Joule heat, i.e., the equivalent internal temperature of the battery, is obtained based on the heat-temperature correlation parameter.

[0035] S50. Estimate the state of charge of the battery based on the current, the voltage and the equivalent internal temperature.

[0036] Understandably, methods for estimating the state of charge (SOC) of a battery include the ampere-hour integration method, discharge test method, open-circuit voltage method, equivalent circuit model method, and neural network method. This embodiment uses an equivalent circuit model as the preset SOC estimation model. Based on the battery equivalent circuit model, the system's state equations and measurement equations are established. The battery's current, voltage, and equivalent internal temperature are input into the equivalent circuit model to identify the model parameters. Then, the Kalman filter algorithm is applied to estimate the battery's SOC.

[0037] This embodiment acquires the battery's current, voltage, and temperature; determines the battery's DC internal resistance based on the temperature; determines the battery's Joule heat based on the current and DC internal resistance; determines the battery's equivalent internal temperature based on the Joule heat; and estimates the battery's state of charge (SOC) based on the current, voltage, and equivalent internal temperature. The battery SOC estimation method provided by this invention calculates the battery's heat and determines the corresponding real-time equivalent internal temperature based on the relationship between the equivalent internal temperature and the heat. This method is not limited by the battery's structure and materials, improving the stability of the real-time internal temperature results and broadening its applicability. Furthermore, by substituting the equivalent internal temperature into a preset model to estimate the battery SOC, the accuracy of the SOC estimation is improved.

[0038] Optionally, step S20, namely determining the DC internal resistance of the battery based on the temperature, includes:

[0039] S201. Obtain internal resistance-temperature relationship data;

[0040] S202. Find the DC internal resistance corresponding to the temperature from the internal resistance-temperature relationship data.

[0041] Understandably, the DC internal resistance of a lithium-ion battery decreases during charging and discharging as temperature rises. However, the relationship between temperature increase and internal resistance decrease is not a simple linear one. Internal resistance-temperature relationship data is established by pre-statistically analyzing the DC internal resistance at different temperatures. This data shows the correspondence between the battery's DC internal resistance and the measured battery temperature. The internal resistance-temperature relationship data can be in tabular or coordinate graph form, allowing users to find the corresponding DC internal resistance based on the battery's temperature from the internal resistance-temperature relationship data.

[0042] The internal resistance-temperature relationship data in this embodiment facilitates quick lookup, determines the DC internal resistance corresponding to the battery temperature, improves the accuracy of DC internal resistance, and is beneficial for subsequent Joule heat calculations.

[0043] Optionally, step S201, i.e., before obtaining the internal resistance-temperature relationship data, includes:

[0044] S2011. Obtain DC internal resistance data at multiple temperatures; the DC internal resistance data includes the DC internal resistance at multiple state-of-charge points at each temperature;

[0045] S2012. Calculate the average internal resistance at the corresponding temperature based on the DC internal resistance at multiple state-of-charge points at each temperature.

[0046] S2013. Generate the internal resistance-temperature relationship data based on the average internal resistance.

[0047] Understandably, the state of charge (SOC) of a battery reflects its remaining capacity, numerically defined as the ratio of remaining capacity to the battery's total capacity, usually expressed as a percentage. The SOC ranges from 0% to 100%, with SOC = 0 indicating a fully discharged battery and SOC = 100% indicating a fully charged battery. Calculating the DC internal resistance requires establishing the battery's current-voltage characteristic curves at 0-100% SOC. This involves alternately charging and discharging the battery at different SOCs using a fixed current rate to calculate the DC internal resistance. The magnitude of the charging and discharging current is commonly expressed as a current ratio. For example, when a 100Ah battery is discharged at 20A, its discharge current ratio is 0.2C, where C represents the battery's nominal capacity. In this embodiment, when the battery temperature is at a specified temperature, the current multiplier is fixed at 0.5C. The DC internal resistance of 11 state of charge points (SOC) = [0, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100%) is measured and the average value is calculated. Based on the average internal resistance, internal resistance-temperature relationship data is generated. That is, at a specified temperature T = [-40, -20, -10, 0, 25, 40, 80], the DC internal resistance DCIR = [10, 10, 8, 5, 2, 1.5, 1] ​​is obtained. The internal resistance and temperature have a one-to-one correspondence.

[0048] This embodiment establishes internal resistance-temperature relationship data by measuring the DC internal resistance of the battery at a specified temperature. The influence of changes in the state of charge on the internal resistance is eliminated by averaging the internal resistance at multiple state of charge points, ensuring the accuracy of the calculation. The internal resistance-temperature relationship data achieves a one-to-one correspondence between DC internal resistance and temperature.

[0049] Optionally, step S30, namely determining the Joule heat of the battery based on the current and the DC internal resistance, includes:

[0050] S301. Obtain the thermal model parameters corresponding to the current operating conditions of the battery;

[0051] S302. The current, the DC internal resistance, and the thermal model parameters are processed using a thermal model to generate the Joule heat of the battery; the thermal model includes:

[0052] Q = F factor *Q delay +(1-F factor )*I 2 *DCIR

[0053] Where Q represents the Joule heat at the current moment;

[0054] F factor Indicates the parameters of the thermal model;

[0055] Q delayThis indicates the Joule temperature at the previous moment;

[0056] I represents electric current;

[0057] DCIR represents DC internal resistance.

[0058] Understandably, the current operating condition of the battery refers to the current temperature conditions of the battery, and the thermal model parameter F. factor This is used to adjust the heat transfer time coefficient. In calculating the Joule heat of the battery per unit time, the default time setting is 1, therefore the time parameter is not considered in the thermal model. The Joule heat of the battery includes the heat I generated by the current passing through the cell at the current moment. 2 *DCIR also includes the heat Q accumulated by the current passing through the cell at the previous moment. delay The actual Joule heat of the battery at the current moment is obtained by summing up the parameters of the thermal model. The Joule heat Q1 at the first moment is calculated by only including the heat I generated by the current passing through the cell at the first moment. 2 *DCIR, i.e., Q delay The initial value of Q0 is zero; the Joule heat Q2 at the second moment is calculated including the heat I generated by the current passing through the cell at the second moment. 2 *DCIR and the Joule heat Q1 at the first moment.

[0059] This embodiment generates Joule heat of the battery by setting thermal model parameters in the thermal model, accumulating the heat at the current moment and the heat transferred at the previous moment, thus achieving accurate calculation of Joule heat.

[0060] Optionally, step S40, namely determining the equivalent internal temperature of the battery based on the Joule heating, includes:

[0061] S401. Obtain the heat temperature correlation parameters corresponding to the current operating condition;

[0062] S402. Process the thermal temperature correlation parameters and the Joule heat using an equivalent temperature model to generate the equivalent internal temperature of the battery; the equivalent temperature model includes:

[0063] EIDT = Q / Q factor

[0064] Where EIDT represents the equivalent internal temperature corresponding to the Joule heat at the current moment;

[0065] Q factor This represents the parameters related to heat and temperature.

[0066] Understandably, current flowing through the battery cell generates heat, and the accumulated heat raises the internal temperature of the cell. This means there is a positive correlation between Joule heating and the battery's equivalent internal temperature. The heat-temperature correlation parameter Q... factorThis parameter represents the functional relationship between Joule heat and equivalent internal temperature, converting the equivalent internal temperature into a thermodynamic temperature expression, with units of J / K. For mass-produced batteries of the same type, the battery characteristics are identical, therefore corresponding to the same thermal-temperature correlation parameter.

[0067] This embodiment sets heat-temperature correlation parameters based on the equivalent temperature model, realizing the effect of obtaining the internal temperature of the battery cell from the measured external temperature of the battery cell based on Joule thermal equivalence, that is, realizing the conversion between battery temperature and equivalent internal temperature.

[0068] Optionally, step S40, namely determining the equivalent internal temperature of the battery based on the Joule heating, further includes:

[0069] S403. Obtain the heating influence factor and the heat temperature correlation parameter corresponding to the current operating condition;

[0070] S404. The equivalent internal temperature of the battery is generated by processing the heating influence factor, the heat-temperature correlation parameter, and the Joule heat through a heating equivalent temperature model; the heating equivalent temperature model includes:

[0071] EIDT heated =Q / Q factor +heat factor

[0072] Among them, EIDT heated This represents the equivalent internal temperature corresponding to the Joule heat at the current moment under the heating strategy;

[0073] Q factor This represents the heat-temperature correlation parameter;

[0074] heat factor This indicates the heating effect factor.

[0075] Understandably, temperature has a significant impact on battery performance. At low temperatures, the viscosity of the battery electrolyte increases and the conductivity decreases, leading to a decline in battery performance. Therefore, when using power batteries in low-temperature conditions, heating strategies are needed to improve battery performance. Battery heating methods are divided into external heating and internal heating. External heating transfers externally generated heat to the battery through convection, conduction, etc., such as preheating with a heating film on the side of the battery. Internal heating, on the other hand, generates heat directly inside the battery, such as current-induced preheating. Under the battery operating conditions where heating strategies are in effect, the equivalent internal temperature of the battery is affected not only by Joule heating but also by the temperature difference corresponding to the heating strategy. Different heating strategies have different effects on the equivalent internal temperature, and the heating influence factor is used to indicate the temperature difference corresponding to the heating strategy.

[0076] This embodiment takes into account the impact of the temperature difference generated by the heating strategy on the equivalent internal temperature, and sets a heating influence factor to realize the conversion between battery temperature and equivalent internal temperature under the heating strategy.

[0077] Optionally, step S403, namely obtaining the heating influence factor, includes:

[0078] S4031. Obtain time-temperature relationship data for the heating strategy;

[0079] S4032. Find the heating temperature corresponding to the current moment from the time-temperature relationship data, and use it as the heating influence factor.

[0080] Understandably, a heating strategy includes heating time and the corresponding heating power. The heating power can be constant or change over time. When a heating strategy is implemented on a battery, the heat generated by the accumulated heating power over time is transferred to the battery, causing its internal temperature to rise. The temperature difference resulting from the heating strategy is called the heating temperature. Time-temperature relationship data is established by pre-statistically analyzing the heating temperatures at different times corresponding to the heating strategy. This data can be in tabular or coordinate graph form, facilitating the retrieval of the heating temperature corresponding to the current moment from the time-temperature relationship data based on the duration of the heating strategy's effect, serving as a heating influencing factor.

[0081] This embodiment determines the heating temperature at the current moment by using the time-temperature relationship data of the heating strategy, and determines the heating influencing factors in real time. This enables rapid matching of heating influencing factors, and the influence of the heating strategy is offset by the heating influencing factors, thus ensuring the accuracy of the equivalent internal temperature.

[0082] In one specific embodiment, before the power battery is officially applied to a vehicle, it needs to undergo testing under specified operating conditions. This embodiment sets and corrects initial values ​​for the thermal-temperature correlation parameters, the thermal-temperature correlation parameters, and the heating influence factor based on test data corresponding to different types of batteries. The specified operating conditions are the operating temperature conditions set according to specified test standards, such as -20℃, 0℃, and 25℃ in the New European Driving Cycle (NEDC) test, or -20℃, 0℃, and 25℃ in the Worldwide Harmonized Light Vehicles Test Cycle (WLTC) test. Since the equivalent internal temperature is higher than the battery test temperature, the battery test temperature is obtained from the test data and a differential curve of the battery test temperature is plotted. Initial values ​​for the thermal model parameters are set based on the battery test temperature differential curve to ensure that the peak half-width at half-maximum (HWHM) of the equivalent internal temperature curve under various test conditions is 1 to 1.5 times that of the battery test temperature differential curve, preferably 1.2 times. Initial values ​​for the thermal-temperature correlation parameters are set to ensure that the peak value of the equivalent internal test temperature curve under the NEDC test condition of -20℃ is 10℃. The initial value for the heating influence factor is set to 0℃.

[0083] Initial values ​​of thermal model parameters, thermal-temperature correlation parameters, and heating influence factors are obtained to establish an initial thermal model, an initial equivalent temperature model, and an initial heating equivalent temperature model. The first current, first voltage, and first temperature of the battery under specified operating conditions are obtained, and the first DC internal resistance of the battery is determined based on the first temperature. The first Joule heat of the battery is determined by processing the first current, first DC internal resistance, and initial values ​​of the thermal model parameters using the initial thermal model. If no heating strategy exists, the first Joule heat and initial values ​​of the thermal-temperature correlation parameters are processed using the initial equivalent temperature model to determine the first equivalent internal temperature of the battery. If a heating strategy exists, the first Joule heat, initial values ​​of the thermal-temperature correlation parameters, and initial values ​​of the heating influence factor are processed using the initial heating equivalent temperature model to determine the first equivalent internal temperature of the battery. The first current, first voltage, and first equivalent internal temperature are processed using a preset battery state of charge estimation model to obtain the first battery state of charge result. The battery state of charge under specified operating conditions is calculated using the ampere-hour integration method, which serves as the second battery state of charge result. The error between the first and second battery state of charge (SOC) results is obtained, using the second SOC result as the baseline. The error is calculated by subtracting the difference between the ratio of the first and second SOC results and 1. This error is compared to a preset threshold, which can be configured as needed (default is 5%). A smaller preset threshold results in a closer approximate equivalent internal temperature to the actual internal temperature of the battery cell, leading to a more accurate SOC estimation. If the error exceeds the preset threshold, the initial values ​​of the thermal model parameters, thermal-temperature correlation parameters, and heating influence factors are corrected. The equivalent internal temperature is then recalculated and substituted into the preset SOC estimation model to obtain the third battery SOC result, ensuring that the error between the third and second SOC results is less than the preset threshold. The corrected thermal model parameters, thermal-temperature correlation parameters, and heating influence factors are then obtained, and a thermal model, an equivalent temperature model, and a heating equivalent temperature model are established.

[0084] This embodiment calculates and compares the battery's state of charge (SOC) under the same specified operating condition using a preset battery SOC estimation model and the ampere-hour integration method. Based on the comparison results, the initial values ​​of the thermal model parameters, thermal-temperature correlation parameters, and heating influence factors are corrected to obtain thermal model parameters, thermal-temperature correlation parameters, and heating influence factors that are more applicable and accurate. An equivalent internal temperature conversion is achieved through a set of parameters (thermal model parameters, thermal-temperature correlation parameters, and heating influence factors). For different types of battery packs, simple parameter matching can be performed using test operating condition data to quickly obtain the corresponding set of parameters, which is not limited by the battery's structure and material parameters, thus broadening its applicability.

[0085] To further illustrate the accuracy of the battery state-of-charge (POC) estimation method of the present invention, the POC of the same lithium-ion battery was estimated using different methods. Specifically, the POC calculated using the ampere-hour integration method was labeled as reference sample data; the POC calculated using the POC estimation method of the present invention was labeled as embodiment sample data; and the POC estimated using the internal cell temperature obtained from the thermal conduction model and substituted into the equivalent circuit model was labeled as comparative sample data. Reference sample data, embodiment sample data, and comparative sample data were obtained under the same operating temperature. The estimation error of the embodiment sample data compared to the reference sample data was calculated as the embodiment error; the estimation error of the comparative sample data compared to the reference sample data was calculated as the comparative error; the embodiment error and the comparative error were compared to determine the estimation accuracy. Figure 2 As shown in the comparison chart of estimation errors, when the battery operating temperatures are [-20, -10, 0, 10, 25, 45], the corresponding comparative errors are [4.8, 4.0, 1.9, 1.6, 0.8, 1.1], and the corresponding example errors are [4.0, 3.5, 1.6, 1.2, 0.7, 0.8]. The example error is significantly smaller than the comparative error. Therefore, the battery state-of-charge estimation method of this invention yields a lower error and higher estimation accuracy, indirectly indicating that the equivalent internal temperature obtained by this invention is closer to the actual temperature of the battery cell. Thus, the battery state-of-charge estimation method of this invention has significant advantages and broad application prospects.

[0086] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0087] In one embodiment, a battery state of charge (SOC) estimation device is provided, which corresponds one-to-one with the battery SOC estimation method described in the above embodiments. For example... Figure 3 As shown, the battery state of charge estimation device includes a data acquisition module 10, a DC internal resistance determination module 20, a Joule heat determination module 30, an equivalent internal temperature determination module 40, and a battery state of charge estimation module 50. Detailed descriptions of each functional module are as follows:

[0088] The data acquisition module 10 is used to acquire the battery's current, voltage, and temperature;

[0089] DC internal resistance determination module 20 is used to determine the DC internal resistance of the battery based on the temperature;

[0090] The Joule heating determination module 30 is used to determine the Joule heating of the battery based on the current and the DC internal resistance.

[0091] Equivalent internal temperature determination module 40 is used to determine the equivalent internal temperature of the battery based on the Joule heating.

[0092] The battery state of charge estimation module 50 is used to estimate the battery state of charge based on the current, the voltage and the equivalent internal temperature.

[0093] Optionally, the DC internal resistance determination module 20 includes:

[0094] The relationship data acquisition unit is used to acquire internal resistance-temperature relationship data;

[0095] A DC internal resistance lookup unit is used to find the DC internal resistance corresponding to the temperature from the internal resistance-temperature relationship data.

[0096] Optionally, the DC internal resistance determination module 20 also includes:

[0097] A DC internal resistance data acquisition unit is used to acquire DC internal resistance data at multiple temperatures; the DC internal resistance data includes the DC internal resistance at multiple state-of-charge points at each temperature;

[0098] The internal resistance average value calculation unit is used to calculate the average internal resistance value at the corresponding temperature based on the DC internal resistance of multiple state-of-charge points at each temperature.

[0099] The relationship data generation unit is used to generate the internal resistance-temperature relationship data based on the average internal resistance.

[0100] Optionally, the Joule heating determination module 30 includes:

[0101] A thermal model parameter acquisition unit is used to acquire thermal model parameters corresponding to the current operating conditions of the battery.

[0102] A thermal model processing unit is used to process the current, the DC internal resistance, and the thermal model parameters through a thermal model to generate the Joule heat of the battery; the thermal model includes:

[0103] Q = F factor *Q delay +(1-F factor )*I 2 *DCIR

[0104] Where Q represents the Joule heat at the current moment;

[0105] F factor Indicates the parameters of the thermal model;

[0106] Qdelay This indicates the Joule temperature at the previous moment;

[0107] I represents electric current;

[0108] DCIR represents DC internal resistance.

[0109] Optionally, the equivalent internal temperature determination module 40 includes:

[0110] A heat-temperature correlation parameter acquisition unit is used to acquire heat-temperature correlation parameters corresponding to the current operating condition;

[0111] An equivalent temperature model processing unit is used to process the thermal temperature correlation parameters and the Joule heat through an equivalent temperature model to generate the equivalent internal temperature of the battery; the equivalent temperature model includes:

[0112] EIDT = Q / Q factor

[0113] Where EIDT represents the equivalent internal temperature corresponding to the Joule heat at the current moment;

[0114] Q factor This represents the parameters related to heat and temperature.

[0115] Optionally, the equivalent internal temperature determination module 40 also includes:

[0116] The heating influence factor acquisition unit is used to acquire the heating influence factor and the heat temperature correlation parameter corresponding to the current operating condition.

[0117] A heating equivalent temperature model processing unit is used to process the heating influence factor, the heat-temperature correlation parameter, and the Joule heat through a heating equivalent temperature model to generate the equivalent internal temperature of the battery; the heating equivalent temperature model includes:

[0118] EIDT heated =Q / Q factor +heat factor

[0119] Among them, EIDT heated This represents the equivalent internal temperature corresponding to the Joule heat at the current moment under the heating strategy;

[0120] Q factor This represents the heat-temperature correlation parameter;

[0121] heat factor This indicates the heating effect factor.

[0122] Optionally, the equivalent internal temperature determination module 40 also includes:

[0123] The heating strategy data acquisition unit is used to acquire time-temperature relationship data of the heating strategy;

[0124] The heating influence factor determination unit is used to find the heating temperature corresponding to the current moment from the time-temperature relationship data, and use it as the heating influence factor.

[0125] Specific limitations regarding the battery state-of-charge estimation device can be found in the limitations of the battery state-of-charge estimation method described above, and will not be repeated here. Each module in the aforementioned battery state-of-charge estimation device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0126] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 4 As shown, the computer device includes a processor, memory, network interface, display screen, and input device connected via a system bus. The processor provides computing and control capabilities. The memory includes a readable storage medium and internal memory. The non-volatile storage medium stores an operating system and computer-readable instructions. The internal memory provides an environment for the operation of the operating system and computer-readable instructions in the readable storage medium. The network interface is used to communicate with an external server via a network connection. When the computer-readable instructions are executed by the processor, they implement a battery state-of-charge estimation method. The readable storage medium provided in this embodiment includes both non-volatile and volatile readable storage media.

[0127] In one embodiment, a computer device is provided, including a memory, a processor, and computer-readable instructions stored in the memory and executable on the processor, wherein the processor performs the following steps when executing the computer-readable instructions:

[0128] Obtain the battery's current, voltage, and temperature;

[0129] The DC internal resistance of the battery is determined based on the temperature.

[0130] The Joule heat of the battery is determined based on the current and the DC internal resistance;

[0131] The equivalent internal temperature of the battery is determined based on the Joule heating.

[0132] The state of charge of the battery is estimated based on the current, the voltage, and the equivalent internal temperature.

[0133] In one embodiment, one or more computer-readable storage media storing computer-readable instructions are provided. The readable storage media provided in this embodiment include non-volatile readable storage media and volatile readable storage media. The readable storage media stores computer-readable instructions, which, when executed by one or more processors, perform the following steps:

[0134] Obtain the battery's current, voltage, and temperature;

[0135] The DC internal resistance of the battery is determined based on the temperature.

[0136] The Joule heat of the battery is determined based on the current and the DC internal resistance;

[0137] The equivalent internal temperature of the battery is determined based on the Joule heating.

[0138] The state of charge of the battery is estimated based on the current, the voltage, and the equivalent internal temperature.

[0139] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by instructing related hardware with computer-readable instructions. These computer-readable instructions can be stored in a non-volatile readable storage medium or a volatile readable storage medium. When executed, these computer-readable instructions can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0140] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0141] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for estimating the state of charge of a battery, characterized in that, include: Obtain the battery's current, voltage, and temperature; The DC internal resistance of the battery is determined based on the temperature. The Joule heat of the battery is determined based on the current and the DC internal resistance; The equivalent internal temperature of the battery is determined based on the Joule heating. The state of charge of the battery is estimated based on the current, the voltage, and the equivalent internal temperature. The step of determining the Joule heat of the battery based on the current and the DC internal resistance includes: The thermal model parameters corresponding to the current operating condition of the battery are obtained. These thermal model parameters are used to adjust the heat transfer time coefficient. The thermal model parameters are obtained by correcting the initial values ​​of the thermal model parameters. The initial values ​​of the thermal model parameters are set according to the battery test temperature differential curve to ensure that the peak half-width of the equivalent internal temperature curve under various test conditions is 1 to 1.5 times the peak half-width of the battery test temperature differential curve. The battery test temperature differential curve is plotted by obtaining the battery test temperature from the test data. The Joule heat of the battery is generated by processing the current, the DC internal resistance, and the thermal model parameters using a thermal model.

2. The battery state of charge estimation method as described in claim 1, characterized in that, Determining the DC internal resistance of the battery based on the temperature includes: Obtain internal resistance-temperature relationship data; Find the DC internal resistance corresponding to the temperature from the internal resistance-temperature relationship data.

3. The battery state of charge estimation method as described in claim 2, characterized in that, Before obtaining the internal resistance-temperature relationship data, the process also includes: Acquire DC internal resistance data at multiple temperatures; the DC internal resistance data includes the DC internal resistance at multiple state-of-charge points at each temperature; The average internal resistance at each temperature is calculated based on the DC internal resistance at multiple charge state points at each temperature. The internal resistance-temperature relationship data is generated based on the average internal resistance.

4. The battery state of charge estimation method as described in claim 1, characterized in that, The thermal model includes: in, This indicates the Joule temperature at the current moment; Indicates the parameters of the thermal model; This indicates the Joule temperature at the previous moment; Indicates current; This indicates the DC internal resistance.

5. The battery state of charge estimation method as described in claim 4, characterized in that, Determining the equivalent internal temperature of the battery based on the Joule heating includes: Obtain the heat-temperature correlation parameters corresponding to the current operating condition; The equivalent internal temperature of the battery is generated by processing the thermal temperature correlation parameters and the Joule heat using an equivalent temperature model; the equivalent temperature model includes: in, This represents the equivalent internal temperature corresponding to the Joule heat at the current moment. This represents the parameters related to heat and temperature.

6. The battery state of charge estimation method as described in claim 4, characterized in that, The step of determining the equivalent internal temperature of the battery based on the Joule heating further includes: Obtain the heating influence factor and the heat temperature correlation parameters corresponding to the current operating condition; The equivalent internal temperature of the battery is generated by processing the heating influence factor, the heat-temperature correlation parameter, and the Joule heat using a heating equivalent temperature model; the heating equivalent temperature model includes: in, This represents the equivalent internal temperature corresponding to the Joule heat at the current moment under the heating strategy; This represents the heat-temperature correlation parameter; This indicates the heating effect factor.

7. The battery state of charge estimation method as described in claim 6, characterized in that, The acquisition of heating influence factors includes: Acquire time-temperature relationship data for the heating strategy; The heating temperature corresponding to the current moment is found from the time-temperature relationship data and used as the heating influence factor.

8. A battery state of charge estimation device, characterized in that, include: The data acquisition module is used to acquire the battery's current, voltage, and temperature. A DC internal resistance determination module is used to determine the DC internal resistance of the battery based on the temperature. A Joule heating determination module is used to determine the Joule heating of the battery based on the current and the DC internal resistance; An equivalent internal temperature determination module is used to determine the equivalent internal temperature of the battery based on the Joule heating. A battery state of charge estimation module is used to estimate the battery state of charge based on the current, the voltage, and the equivalent internal temperature. The Joule heating determination module includes: A thermal model parameter acquisition unit is used to acquire thermal model parameters corresponding to the current operating condition of the battery. The thermal model parameters are used to adjust the heat transfer time coefficient. The thermal model parameters are obtained by correcting the initial values ​​of the thermal model parameters. The initial values ​​of the thermal model parameters are set according to the battery test temperature differential curve to ensure that the peak half-width of the equivalent internal temperature curve under various test conditions is 1 to 1.5 times the peak half-width of the battery test temperature differential curve. The battery test temperature differential curve is plotted by acquiring the battery test temperature from the test data. A thermal model processing unit is used to process the current, the DC internal resistance, and the thermal model parameters through a thermal model to generate the Joule heat of the battery.

9. A computer device comprising a memory, a processor, and computer-readable instructions stored in the memory and executable on the processor, characterized in that, When the processor executes the computer-readable instructions, it implements the battery state-of-charge estimation method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing computer-readable instructions, characterized in that, When the computer-readable instructions are executed by one or more processors, the one or more processors cause the battery state-of-charge estimation method as described in any one of claims 1 to 7.

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