A method and system for correcting SOC accuracy of electric vehicle battery based on iteration method

Abstract

The present invention discloses a method and system for correcting the SOC accuracy of an electric vehicle battery based on an iteration method, which relates to the field of lithium battery technology, including: establishing an equivalent circuit model of a lithium-ion battery, obtaining the open circuit voltage at different states of charge and each model parameter in the equivalent circuit model through a pulse charge and discharge experiment; determining the functional relationship between the open circuit voltage and the state of charge, and constructing a SOC-OCV relationship table between the open circuit voltage OCV and different state of charge SOC values; updating the coefficients in the equivalent circuit model based on the open circuit voltage OCV and its corresponding SOC value; determining the relationship between each model parameter in the updated equivalent circuit model and the state of charge, and establishing a state space equation; using an extended Kalman filter algorithm to iteratively calculate the SOC value of the state space equation to determine the SOC value of the lithium-ion battery. The present invention can perform real-time precision correction on the SOC, improve the SOC accuracy, and ensure vehicle performance and safety.

Description

Technical Field

[0001] The present invention relates to the technical field of lithium batteries, and more specifically to an iterative method and system for correcting the SOC accuracy of an electric vehicle battery. Background Art

[0002] Due to the advantages of high energy density and relatively stable performance, lithium batteries have become the main power source for electric vehicles in the future. However, the quality of lithium batteries is not easy to control when they are mass-produced. There are slight differences in the power of battery cells when they leave the factory. Moreover, due to factors such as operating environment and aging, the inconsistency between batteries will become more obvious, and the battery efficiency and life will also deteriorate. In addition, overcharging or over-discharging may cause safety problems such as fire in serious cases.

[0003] SOC, or State of Charge, refers to the state of charge of the battery, also known as the remaining power. After long-term use of electric bicycles, due to battery aging, the internal active lithium decreases, the activity of positive and negative electrode materials decays, the amount of electrolyte decreases, the nuclear and mass transfer impedances increase, and the battery OCV curve and polarization curve will undergo irreversible changes. The SOC algorithm in the BMS generally uses OCV as the calibration curve, combined with the current time integral curve and the change in the internal resistance of the battery system for partial correction. However, after the battery ages, the calibration curve is inaccurate and the battery ages abnormally, resulting in a decrease in the SOC calculation accuracy of the BMS. The judgment that the charging current needs to be reduced at high SOC to prevent lithium precipitation, the high SOC and large charging current accelerate battery aging, and the low SOC needs to reduce the discharge current to prevent the battery from over-discharging. The problems are out of control, further exacerbating the battery life decay aging and increasing the safety risks of electric vehicles. Therefore, for the battery system of electric bicycles in use, it is necessary not only to perform periodic detection of the SOC accuracy, but also to perform accuracy correction and improvement on the system with a large number of SOC errors.

[0004] Therefore, how to perform real-time precision correction on SOC, improve SOC accuracy, and ensure vehicle performance and safety is a technical problem that technical personnel in this field urgently need to solve. Summary of the invention

[0005] In view of this, the present invention provides an electric vehicle battery SOC accuracy correction method and system based on an iteration method, which can achieve real-time accuracy correction of SOC, improve SOC accuracy, and ensure vehicle performance and safety.

[0006] In order to achieve the above object, the present invention provides the following technical solutions:

[0007] A method for correcting the SOC accuracy of an electric vehicle battery based on an iteration method comprises the following steps:

[0008] Establish an equivalent circuit model of lithium-ion batteries, and obtain the open circuit voltage at different charge states and various model parameters in the equivalent circuit model through pulse charge and discharge experiments;

[0009] Determine the functional relationship between open circuit voltage and state of charge, and construct a SOC-OCV relationship table between open circuit voltage OCV and different state of charge SOC values;

[0010] Based on the open circuit voltage OCV and its corresponding SOC value, the coefficients in the equivalent circuit model are updated;

[0011] Determine the relationship between each model parameter and the state of charge in the updated equivalent circuit model, and establish a state space equation;

[0012] The SOC value of the state space equation is iteratively calculated using an extended Kalman filter algorithm to determine the SOC value of the lithium-ion battery.

[0013] The technical effect achieved by the above technical solution is: updating the coefficients in the equivalent circuit model and using the extended Kalman filter for iterative calculation. Compared with the prior art using a fixed battery model, it avoids the problem of a large difference between the battery SOC and the actual value due to the large error of the battery model itself, thereby improving the accuracy of the SOC.

[0014] Optionally, the equivalent circuit model of the lithium-ion battery is an improved second-order RC equivalent circuit model based on different ambient temperatures;

[0015] The circuit structure of the improved second-order RC equivalent circuit model includes a voltage source, an ohmic resistor, a first RC loop and a second RC loop connected in series; in the first RC loop, a first polarization resistor is connected in parallel with a first polarization capacitor; in the second RC loop, a second polarization resistor is connected in parallel with a second polarization capacitor;

[0016] The model parameters in the equivalent circuit model are the ohmic resistance, the first polarization resistance, the first polarization capacitance, the second polarization resistance and the second polarization capacitance.

[0017] The technical effect achieved by the above technical solution is: an improved second-order RC equivalent circuit model based on different ambient temperatures is established, which can realize accurate estimation of SOC under different ambient temperatures.

[0018] Optionally, the pulse charge and discharge experiment specifically includes the following steps:

[0019] The lithium-ion battery is fully charged and then discharged after being left at rest for a long time. When the battery state of charge (SOC) drops by 10%, the voltage across the battery obtained after standing for 60 minutes is the open circuit voltage (OCV) of the battery under the state of charge (SOC). The OCV-SOC measurement of the discharge process is completed, and the OCV-SOC measurement of the charging process is performed based on the discharge process.

[0020] After obtaining the OCV under different battery states of charge (SOC), MATLAB was used to fit the OCV-SOC curve to obtain the quantitative functional relationship between open circuit voltage and state of charge.

[0021] Optionally, the method further includes:

[0022] The final SOC value of the lithium-ion battery is substituted into the updated equivalent circuit model function, the simulation voltage of the lithium-ion battery is calculated, and the simulation voltage is compared with the measured open circuit voltage to verify whether the initial values ​​of each model parameter in the equivalent circuit model are accurate.

[0023] Optionally, the method further includes:

[0024] Based on the obtained open circuit voltage at the current moment and each model parameter in the equivalent circuit model, the terminal voltage at the current moment is calculated;

[0025] Measure the terminal voltage at the current moment and obtain the error of the terminal voltage of the lithium-ion battery;

[0026] Determine whether the error of the lithium-ion battery terminal voltage exceeds a preset error threshold. If so, update the next moment to the current moment according to a preset iteration time interval and recalculate the updated SOC value at the current moment and the error of the lithium-ion battery terminal voltage until the error of the lithium-ion battery terminal voltage is less than the preset error threshold.

[0027] The technical effect achieved by the above technical solution is: by comparing the obtained lithium-ion battery terminal voltage error with the preset error threshold, the accuracy of SOC estimation can be further ensured and the estimation precision can be improved.

[0028] Optionally, the extended Kalman filter algorithm specifically includes the following steps:

[0029] Establish the state equation and output equation of the lithium-ion battery discretization, and perform ampere-hour integration on the measured current value;

[0030] Based on the electric quantity value obtained by integrating the ampere-hour, the predicted value of the open circuit voltage is calculated;

[0031] Using the prediction covariance of the previous iteration cycle, calculate the prediction covariance and Kalman gain of this iteration;

[0032] The SOC value is calculated based on the predicted value of the open circuit voltage, the Kalman gain and the measured voltage value;

[0033] Based on the Kalman gain and the prediction covariance of this iteration, the prediction covariance of the next iteration cycle is calculated, and the next round of loop iteration is started until the preset number of loop iterations is reached.

[0034] The present invention also discloses an electric vehicle battery SOC accuracy correction system based on an iteration method, comprising: a first establishment module, an acquisition module, a determination module, an update module, a second establishment module and a calculation module, and each structure is connected in sequence;

[0035] The first building module is used to build an equivalent circuit model of a lithium-ion battery;

[0036] An acquisition module is used to obtain the open circuit voltage at different charge states and various model parameters in the equivalent circuit model through pulse charge and discharge experiments;

[0037] A determination module is used to determine the functional relationship between the open circuit voltage and the state of charge, and to construct a SOC-OCV relationship table between the open circuit voltage OCV and different state of charge SOC values;

[0038] An updating module, which updates coefficients in an equivalent circuit model based on an open circuit voltage OCV and a corresponding SOC value;

[0039] The second establishment module is used to determine the relationship between each model parameter and the state of charge in the updated equivalent circuit model and establish a state space equation;

[0040] The calculation module is used to iteratively calculate the SOC value of the state space equation through an extended Kalman filter algorithm to determine the SOC value of the lithium-ion battery.

[0041] Optionally, the equivalent circuit model of the lithium-ion battery is an improved second-order RC equivalent circuit model based on different ambient temperatures;

[0042] The circuit structure of the improved second-order RC equivalent circuit model includes a voltage source, an ohmic resistor, a first RC loop and a second RC loop connected in series; in the first RC loop, a first polarization resistor is connected in parallel with a first polarization capacitor; in the second RC loop, a second polarization resistor is connected in parallel with a second polarization capacitor;

[0043] The model parameters in the equivalent circuit model are the ohmic resistance, the first polarization resistance, the first polarization capacitance, the second polarization resistance and the second polarization capacitance.

[0044] It can be seen from the above technical solutions that, compared with the prior art, the present invention discloses a method and system for correcting the SOC accuracy of an electric vehicle battery based on an iteration method. Compared with the prior art that uses a fixed battery model, the present invention updates the coefficients in the equivalent circuit model and uses an extended Kalman filter for iterative calculation to avoid the problem of a large difference between the battery SOC and the actual value due to the large error of the battery model itself, thereby improving the estimation accuracy of the SOC; secondly, an improved second-order RC equivalent circuit model based on different ambient temperatures is also established, which can realize accurate estimation of the SOC at different ambient temperatures and ensure vehicle performance and safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0046] Figure 1 It is a flow chart of the SOC accuracy correction method of electric vehicle battery based on iteration method;

[0047] Figure 2 This is the structural diagram of the electric vehicle battery SOC accuracy correction system based on the iteration method. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] Example 1

[0050] Electric vehicles require safe and efficient batteries as a power source. Accurately predicting the battery's SOC plays a vital role in achieving the best performance and range of electric vehicles. However, the state of charge of lithium-ion batteries cannot be measured directly, and is affected by many factors such as charge and discharge rate, battery aging, and battery internal resistance, making it difficult to accurately and quickly measure SOC.

[0051] To this end, the embodiment of the present invention discloses a method for correcting the SOC accuracy of an electric vehicle battery based on an iteration method, such as Figure 1 As shown, the following steps are included:

[0052] Establish an equivalent circuit model of lithium-ion batteries, and obtain the open circuit voltage at different charge states and various model parameters in the equivalent circuit model through pulse charge and discharge experiments;

[0053] Determine the functional relationship between open circuit voltage and state of charge, and construct a SOC-OCV relationship table between open circuit voltage OCV and different state of charge SOC values;

[0054] Based on the open circuit voltage OCV and its corresponding SOC value, the coefficients in the equivalent circuit model are updated;

[0055] Determine the relationship between each model parameter and the state of charge in the updated equivalent circuit model, and establish a state space equation;

[0056] The SOC value of the state space equation is iteratively calculated using an extended Kalman filter algorithm to determine the SOC value of the lithium-ion battery.

[0057] Compared with the prior art that uses a fixed battery model, this embodiment updates the coefficients in the equivalent circuit model and uses an extended Kalman filter for iterative calculation, thereby avoiding the problem of a large difference between the battery SOC and the actual value due to the large error of the battery model itself, thereby improving the accuracy of the SOC.

[0058] The ambient temperature will affect the chemical reaction of the lithium battery, causing the battery capacity and OCV-SOC curve to change at different ambient temperatures, resulting in a large SOC estimation error. Therefore, in this embodiment, the established equivalent circuit model of the lithium-ion battery can be designed as an improved second-order RC equivalent circuit model based on different ambient temperatures;

[0059] The circuit structure of the improved second-order RC equivalent circuit model includes a voltage source, an ohmic resistor, a first RC loop and a second RC loop connected in series; in the first RC loop, the first polarization resistor is connected in parallel with the first polarization capacitor; in the second RC loop, the second polarization resistor is connected in parallel with the second polarization capacitor; and the model parameters in the equivalent circuit model are the ohmic resistor, the first polarization resistor, the first polarization capacitor, the second polarization resistor and the second polarization capacitor.

[0060] Next, the nonlinear function of the battery capacity with respect to the ambient temperature, the nonlinear function of the open-circuit voltage at ambient temperature with respect to the state of charge and ambient temperature, and the model parameter values ​​in the improved second-order RC equivalent circuit model are obtained; based on this, they are converted into discrete state space equations, and then according to the parameter values ​​of the battery capacity and the state of charge, the extended Kalman filter algorithm is used to perform online estimation of the state of charge, thereby realizing online estimation of the state of charge at different ambient temperatures and improving the estimation accuracy.

[0061] In addition, in another embodiment, the equivalent circuit model of the lithium-ion battery can also adopt the Thevenin equivalent circuit model, also known as the first-order RC model, which includes a voltage source and an RC parallel circuit. The loop composed of the polarization internal resistance Rs and the polarization capacitance Cs is used to simulate the dynamic process of the battery. The model takes into account the relationship between the electromotive force and the SOC and the dynamic process of the battery, and can more accurately simulate the battery charging and discharging process.

[0062] Furthermore, the pulse charge and discharge experiment specifically includes the following steps:

[0063] The lithium-ion battery is fully charged and then discharged after being left at rest for a long time. When the battery state of charge (SOC) drops by 10%, the voltage across the battery obtained after standing for 60 minutes is the open circuit voltage (OCV) of the battery under the state of charge (SOC). The OCV-SOC measurement of the discharge process is completed, and the OCV-SOC measurement of the charging process is performed based on the discharge process.

[0064] After obtaining the OCV under different battery states of charge (SOC), MATLAB was used to fit the OCV-SOC curve to obtain the quantitative functional relationship between open circuit voltage and state of charge.

[0065] The battery charge and discharge modes include constant current charging, constant voltage charging, constant current discharging, constant resistance discharging, mixed charge and discharge and step mode. In one of the cases, the lithium-ion battery is installed on the test instrument, placed in a (25±1)℃ test environment, and the following program is set: stand for 10 minutes; charge to 4.2V at a constant current of 1.0C, then charge at a constant voltage until the current drops to 0.05C, and then stop charging; stand for 5 minutes; then discharge to 3.0V at a constant current of 1.0C; repeat the above charge and discharge steps 5 to 10 times.

[0066] In a specific embodiment, the experimental conditions of the pulse charge and discharge experiment are: the pulse current amplitude is 1C, the pulse period is 420 seconds, the discharge time is 300 seconds, and the ambient temperature is controlled at 29°C.

[0067] Furthermore, the method further comprises:

[0068] The final SOC value of the lithium-ion battery is substituted into the updated equivalent circuit model function, the simulation voltage of the lithium-ion battery is calculated, and the simulation voltage is compared with the measured open circuit voltage to verify whether the initial values ​​of each model parameter in the equivalent circuit model are accurate.

[0069] Furthermore, the method further comprises:

[0070] Based on the obtained open circuit voltage at the current moment and each model parameter in the equivalent circuit model, the terminal voltage at the current moment is calculated;

[0071] Measure the terminal voltage at the current moment and obtain the error of the terminal voltage of the lithium-ion battery;

[0072] It is determined whether the error of the lithium-ion battery terminal voltage exceeds a preset error threshold. If it exceeds, the next moment is updated to the current moment according to a preset iteration time interval and the updated SOC value and the error of the lithium-ion battery terminal voltage at the current moment are recalculated until the error of the lithium-ion battery terminal voltage is less than the preset error threshold. In this embodiment, the obtained lithium-ion battery terminal voltage error is compared with the preset error threshold, which can further ensure the accuracy of SOC estimation and improve the estimation precision.

[0073] Furthermore, the extended Kalman filter algorithm specifically includes the following steps:

[0074] Establish the state equation and output equation of the lithium-ion battery discretization, and perform ampere-hour integration on the measured current value;

[0075] Based on the electric quantity value obtained by integrating the ampere-hour, the predicted value of the open circuit voltage is calculated;

[0076] Using the prediction covariance of the previous iteration cycle, calculate the prediction covariance and Kalman gain of this iteration;

[0077] The SOC value is calculated based on the predicted value of the open circuit voltage, the Kalman gain and the measured voltage value;

[0078] Based on the Kalman gain and the prediction covariance of this iteration, the prediction covariance of the next iteration cycle is calculated, and the next round of loop iteration is started until the preset number of loop iterations is reached.

[0079] The traditional extended Kalman filter algorithm uses fixed model parameters for SOC estimation. At the end of battery discharge, battery polarization will cause the battery model parameters to change. If the traditional extended Kalman algorithm is used to estimate SOC, the tail error will become larger. In addition to the aforementioned method of updating the coefficients in the equivalent circuit model, the forgetting factor least squares method can also be used to estimate the battery model parameters, and then the estimated model parameters are locally weighted regressed with the battery voltage and current. The model parameters corresponding to each set of voltage and current are calculated using the fitted function to reduce the impact of model parameter changes.

[0080] Example 2

[0081] This embodiment discloses an electric vehicle battery SOC accuracy correction system based on an iteration method, such as Figure 2 As shown, it includes: a first establishing module, an acquiring module, a determining module, an updating module, a second establishing module and a calculating module, and each structure is connected in sequence;

[0082] The first building module is used to build an equivalent circuit model of a lithium-ion battery;

[0083] An acquisition module is used to obtain the open circuit voltage at different charge states and various model parameters in the equivalent circuit model through pulse charge and discharge experiments;

[0084] A determination module is used to determine the functional relationship between the open circuit voltage and the state of charge, and to construct a SOC-OCV relationship table between the open circuit voltage OCV and different state of charge SOC values;

[0085] An updating module, which updates coefficients in an equivalent circuit model based on an open circuit voltage OCV and a corresponding SOC value;

[0086] The second establishment module is used to determine the relationship between each model parameter and the state of charge in the updated equivalent circuit model and establish a state space equation;

[0087] The calculation module is used to iteratively calculate the SOC value of the state space equation through an extended Kalman filter algorithm to determine the SOC value of the lithium-ion battery.

[0088] Furthermore, the equivalent circuit model of the lithium-ion battery is an improved second-order RC equivalent circuit model based on different ambient temperatures;

[0089] The circuit structure of the improved second-order RC equivalent circuit model includes a voltage source, an ohmic resistor, a first RC loop and a second RC loop connected in series; in the first RC loop, a first polarization resistor is connected in parallel with a first polarization capacitor; in the second RC loop, a second polarization resistor is connected in parallel with a second polarization capacitor;

[0090] The model parameters in the equivalent circuit model are the ohmic resistance, the first polarization resistance, the first polarization capacitance, the second polarization resistance and the second polarization capacitance.

[0091] In the prior art, the battery system of an electric bicycle not only needs to perform periodic detection of the SOC accuracy, but also needs to perform accuracy correction and improvement on the system with a large number of SOC errors. The present invention avoids the problem of a large difference between the battery SOC and the actual value due to the large error of the battery model itself, thereby improving the estimation accuracy of the SOC. Secondly, an improved second-order RC equivalent circuit model based on different ambient temperatures is established, which can realize accurate estimation of the SOC under different ambient temperatures and ensure vehicle performance and safety.

[0092] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0093] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for correcting the SOC accuracy of an electric vehicle battery based on an iteration method, characterized in that: The following steps are involved: Establish an equivalent circuit model of lithium-ion batteries, and obtain the open circuit voltage at different charge states and various model parameters in the equivalent circuit model through pulse charge and discharge experiments; Determine the functional relationship between open circuit voltage and state of charge, and construct a SOC-OCV relationship table between open circuit voltage OCV and different state of charge SOC values; Based on the open circuit voltage OCV and its corresponding SOC value, the coefficients in the equivalent circuit model are updated; Determine the relationship between each model parameter and the state of charge in the updated equivalent circuit model, and establish a state space equation; The SOC value of the state-space equation is iteratively calculated using an extended Kalman filter algorithm to determine the SOC value of the lithium-ion battery; The equivalent circuit model of the lithium-ion battery is an improved second-order RC equivalent circuit model based on different ambient temperatures; The circuit structure of the improved second-order RC equivalent circuit model includes a voltage source, an ohmic resistor, a first RC loop and a second RC loop connected in series; in the first RC loop, a first polarization resistor is connected in parallel with a first polarization capacitor; in the second RC loop, a second polarization resistor is connected in parallel with a second polarization capacitor; The model parameters in the equivalent circuit model are ohmic resistance, first polarization resistance, first polarization capacitance, second polarization resistance and second polarization capacitance; The pulse charge and discharge experiment is specifically The following steps are involved: The lithium-ion battery is fully charged and then discharged after being left at rest for a long time. When the battery state of charge (SOC) drops by 10%, the voltage across the battery obtained after standing for 60 minutes is the open circuit voltage (OCV) of the battery under the state of charge (SOC). The OCV-SOC measurement of the discharge process is completed, and the OCV-SOC measurement of the charging process is performed based on the discharge process. After obtaining the OCV under different battery states of charge (SOC), MATLAB was used to fit the OCV-SOC curve to obtain the quantitative functional relationship between open circuit voltage and state of charge.

2. The electric vehicle battery SOC accuracy correction method based on iteration method according to claim 1 is characterized in that: The method further comprises: The final SOC value of the lithium-ion battery is substituted into the updated equivalent circuit model function, the simulation voltage of the lithium-ion battery is calculated, and the simulation voltage is compared with the measured open circuit voltage to verify whether the initial values ​​of each model parameter in the equivalent circuit model are accurate.

3. The electric vehicle battery SOC accuracy correction method based on iteration method according to claim 1 is characterized in that: The method further comprises: Based on the obtained open circuit voltage at the current moment and each model parameter in the equivalent circuit model, the terminal voltage at the current moment is calculated; Measure the terminal voltage at the current moment and obtain the error of the terminal voltage of the lithium-ion battery; Determine whether the error of the lithium-ion battery terminal voltage exceeds a preset error threshold. If so, update the next moment to the current moment according to a preset iteration time interval and recalculate the updated SOC value at the current moment and the error of the lithium-ion battery terminal voltage until the error of the lithium-ion battery terminal voltage is less than the preset error threshold.

4. The electric vehicle battery SOC accuracy correction method based on iteration method according to claim 1 is characterized in that: The extended Kalman filter algorithm specifically includes the following steps: Establish the state equation and output equation of the lithium-ion battery discretization, and perform ampere-hour integration on the measured current value; Based on the electric quantity value obtained by integrating the ampere-hour, the predicted value of the open circuit voltage is calculated; Using the prediction covariance of the previous iteration cycle, calculate the prediction covariance and Kalman gain of this iteration; The SOC value is calculated based on the predicted value of the open circuit voltage, the Kalman gain and the measured voltage value; Based on the Kalman gain and the prediction covariance of this iteration, the prediction covariance of the next iteration cycle is calculated, and the next round of loop iteration is started until the preset number of loop iterations is reached.

5. An electric vehicle battery SOC accuracy correction system based on iteration method, characterized in that: include: A first establishing module, an acquiring module, a determining module, an updating module, a second establishing module and a calculating module, and each structure is connected in sequence; The first building module is used to build an equivalent circuit model of a lithium-ion battery; An acquisition module is used to obtain the open circuit voltage at different charge states and various model parameters in the equivalent circuit model through pulse charge and discharge experiments; A determination module is used to determine the functional relationship between the open circuit voltage and the state of charge, and to construct a SOC-OCV relationship table between the open circuit voltage OCV and different state of charge SOC values; An updating module, which updates coefficients in an equivalent circuit model based on an open circuit voltage OCV and a corresponding SOC value; The second establishment module is used to determine the relationship between each model parameter and the state of charge in the updated equivalent circuit model and establish a state space equation; A calculation module, used for iteratively calculating the SOC value of the state space equation by an extended Kalman filter algorithm to determine the SOC value of the lithium-ion battery; The equivalent circuit model of the lithium-ion battery is an improved second-order RC equivalent circuit model based on different ambient temperatures; The circuit structure of the improved second-order RC equivalent circuit model includes a voltage source, an ohmic resistor, a first RC loop and a second RC loop connected in series; in the first RC loop, a first polarization resistor is connected in parallel with a first polarization capacitor; in the second RC loop, a second polarization resistor is connected in parallel with a second polarization capacitor; The model parameters in the equivalent circuit model are ohmic resistance, first polarization resistance, first polarization capacitance, second polarization resistance and second polarization capacitance; The pulse charge and discharge experiment is specifically The following steps are involved: The lithium-ion battery is fully charged and then discharged after being left at rest for a long time. When the battery state of charge (SOC) drops by 10%, the voltage across the battery obtained after standing for 60 minutes is the open circuit voltage (OCV) of the battery under the state of charge (SOC). The OCV-SOC measurement of the discharge process is completed, and the OCV-SOC measurement of the charging process is performed based on the discharge process. After obtaining the OCV under different battery states of charge (SOC), MATLAB was used to fit the OCV-SOC curve to obtain the quantitative functional relationship between open circuit voltage and state of charge.

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