SOC correction method and SOC correction apparatus for charging termination stage of battery

Abstract

Provided in the present application are a SOC correction method and SOC correction apparatus for a charging termination stage of a battery. The method comprises: when it is determined, by means of a battery management system and a charging current of a battery, that the battery is currently in a charging state, and the temperature of the battery is within a preset temperature range, acquiring a terminal voltage of the battery; on the basis of the terminal voltage and a starting correction voltage threshold value of a charging termination stage, determining a current charging stage of the battery; and when the current charging stage of the battery is the charging termination stage, on the basis of the terminal voltage, acquiring a target SOC value corresponding to the battery, and on the basis of an error between an actual SOC value and the target SOC value of the battery, using a fuzzy self-tuning PID control algorithm to correct the actual SOC value, so as to obtain a corrected SOC value of the battery. By means of the method and apparatus, a fuzzy self-tuning PID control algorithm is used to correct an overestimated SOC point in advance, such that the overestimated SOC point smoothly approaches a target SOC value, thereby realizing accurate SOC estimation.

Description

SOC correction method and device at the end of battery charging

[0001] Cross-reference to Related Applications

[0002] The present application claims priority to the Chinese patent application No. 2024111634343, filed on August 23, 2024, and entitled "SOC correction method and device at the end of battery charging", the content of which is incorporated herein by reference in its entirety. TECHNICAL FIELD

[0003] The present application relates to the technical field of batteries, in particular to a SOC correction method and device at the end of battery charging. BACKGROUND

[0004] Lithium iron phosphate batteries are widely used in energy storage fields such as photovoltaic, electric vehicles and communication base stations due to their safety, long life and high temperature resistance. Real-time estimation of the state of charge (SOC) of lithium iron phosphate batteries is strongly related to battery charging and discharging management and electric vehicle energy management. Accurate SOC estimation is of great significance for prolonging battery life, optimizing energy and safety management, and preventing overcharging and overdischarging of power batteries. However, for vehicle lithium iron phosphate batteries, there are fewer measurable parameters and many factors to consider, such as high dynamic load, self-discharge, aging and hysteresis characteristics. At the same time, the working process of lithium batteries is affected by the nonlinearity between various physical quantities, electro-thermal coupling and uncertain external disturbances, making it difficult to accurately estimate the battery SOC.

[0005] Currently, the main estimation methods include open-circuit voltage method, ampere-hour integral method, model-based observer method and data-driven estimation algorithm. Among the many SOC estimation algorithms, the ampere-hour integral method based on no model is simple in structure and easy to implement, and is widely used in battery management systems (BMS). However, the ampere-hour integral method is an open-loop algorithm that relies heavily on the initial value of SOC. Due to the accuracy of the sensor itself and the limited time interval, there is a cumulative error in the ampere-hour integral process. This algorithm cannot eliminate errors in the process, and the effect of SOC estimation using only the ampere-hour integral method is not good.

[0006] SUMMARY

[0007] Therefore, the purpose of the present application is to provide a SOC correction method and device at the end of battery charging.

[0008] In a first aspect, an optional embodiment of the present application provides a SOC correction method at the end of battery charging, which comprises:

[0009] acquire the terminal voltage of the battery when it is judged by the battery management system and the charging current of the battery that the battery is currently in a charging state and the temperature of the battery is within a preset temperature range;

[0010] judge the charging stage in which the battery currently is according to the terminal voltage and a charging-end-starting correction voltage threshold value; wherein the charging stage includes a non-charging end, a pseudo-charging end and a charging end;

[0011] when the charging stage in which the battery currently is is the charging end, acquire the SOC target value corresponding to the battery based on the terminal voltage, and correct the SOC actual value of the battery based on the error between the SOC actual value and the SOC target value by using a fuzzy self-tuning PID control algorithm to obtain the SOC correction value of the battery.

[0012] In a second aspect, another optional embodiment of the present application further provides a SOC correction device for a charging end of a battery, which comprises:

[0013] a terminal voltage acquisition module, configured to acquire the terminal voltage of the battery when it is judged by the battery management system and the charging current of the battery that the battery is currently in a charging state and the temperature of the battery is within a preset temperature range;

[0014] a charging stage judgment module, configured to judge the charging stage in which the battery currently is according to the terminal voltage and a charging-end-starting correction voltage threshold value; wherein the charging stage includes a non-charging end, a pseudo-charging end and a charging end;

[0015] a charging-end SOC correction module, configured to acquire the SOC target value corresponding to the battery based on the terminal voltage when the charging stage in which the battery currently is is the charging end, and correct the SOC actual value of the battery based on the error between the SOC actual value and the SOC target value by using a fuzzy self-tuning PID control algorithm to obtain the SOC correction value of the battery.

[0016] In a third aspect, another optional embodiment of the present application further provides an electronic device, which comprises a processor, a memory and a bus, the memory stores machine readable instructions executable by the processor, when the electronic device is running, the processor and the memory communicate through the bus, and the machine readable instructions are executed by the processor to perform the steps of the SOC correction method for a charging end of a battery as described above.

[0017] In a fourth aspect, another optional embodiment of the present application further provides a computer readable storage medium, which stores a computer program. The computer program is run in a processor to perform the steps of the SOC correction method for a battery charging end as described above.

[0018] The SOC correction method for a battery charging end and the SOC charging device provided by the embodiments of the present application can determine whether the battery enters the end correction by comparing the real-time detected terminal voltage with the start correction voltage threshold of the charging end. If the battery is at the charging end, the SOC target value is obtained through the measurable terminal voltage. The SOC point that is too high is corrected in advance based on the error between the actual SOC value and the SOC target value by using the fuzzy self-tuning PID control algorithm. The error between the actual SOC value and the SOC target value is continuously reduced so as to smoothly approach the SOC target value, thereby realizing accurate estimation of the SOC.

[0019] In order to make the above objectives, features and advantages of the present application more apparent, the following will specifically describe preferred embodiments in combination with the attached drawings, and make a detailed description as follows. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as a limitation to the scope. For those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0021] Fig. 1 is a flow chart of a SOC correction method for a battery charging end provided by an optional embodiment of the present application;

[0022] Fig. 2 is a voltage and current curve diagram of a lithium iron phosphate battery during charging provided by an optional embodiment of the present application;

[0023] Fig. 3 is a structure diagram of a fuzzy self-tuning PID controller provided by an optional embodiment of the present application;

[0024] Fig. 4(A) is a distribution curve of a system error e membership function provided by an optional embodiment of the present application;

[0025] Fig. 4(B) is a distribution curve of a system error change rate ec membership function provided by an optional embodiment of the present application;

[0026] Fig. 4(C) is a distribution curve of a membership function of ΔKp provided by an optional embodiment of the present application;

[0027] Fig. 5 is a flow chart of an SOC correction algorithm at the end of battery charging according to an optional embodiment of the present application;

[0028] Fig. 6 is a structural schematic diagram of an SOC correction device at the end of battery charging according to an optional embodiment of the present application;

[0029] Fig. 7 is a structural schematic diagram of an electronic device according to an optional embodiment of the present application. DETAILED DESCRIPTION

[0030] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application and not all embodiments. The components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments of the present application, every other embodiment obtained by a person skilled in the art without creative work belongs to the scope of protection of the present application.

[0031] Firstly, the application scenarios applicable to the present application are introduced. The present application can be applied to the field of battery technology.

[0032] Lithium iron phosphate batteries are widely used in energy storage fields such as photovoltaic, electric vehicles and communication base stations due to their safety, long life and high temperature resistance. The real-time estimation of the state of charge (SOC) of lithium iron phosphate batteries is strongly related to battery charging and discharging management and electric vehicle energy management. Accurate SOC estimation is of great significance for prolonging the service life of the battery, optimizing energy management and safety management, and preventing overcharging and overdischarging of the power battery. However, for vehicle lithium iron phosphate batteries, there are fewer measurable parameters and many factors to be considered, such as high dynamic load, self-discharge, aging and hysteresis characteristics. At the same time, the lithium battery working process is affected by the nonlinearity between various physical quantities, electro-thermal coupling and uncertain external disturbances, which makes it difficult to accurately estimate the battery SOC.

[0033] It is found through research that at present, mainstream estimation methods include open-circuit voltage method, ampere-hour integral method, model-based observer method and data-driven estimation algorithm. Among the many SOC estimation algorithms, the ampere-hour integral method based on a model-free structure is simple and easy to implement, and is widely used in battery management systems (BMS). However, the ampere-hour integral method is an open-loop algorithm that depends heavily on the initial value of SOC. Due to the precision of the sensor itself and the limited time interval, the ampere-hour integral process has cumulative errors. This algorithm cannot eliminate errors during the process, and the effect of SOC estimation using only the ampere-hour integral method is poor.

[0034] Based on this, the SOC correction method at the end of battery charging provided by the embodiments of the present application uses a fuzzy self-tuning PID control algorithm to correct the virtual high SOC point in advance when the battery is at the end of charging, continuously reduces the error between the actual value of SOC and the target value of SOC, and makes it smoothly approach the target value of SOC, so as to realize accurate estimation of SOC.

[0035] Please refer to FIG. 1, which is a flowchart of a SOC correction method at the end of battery charging provided by an optional embodiment of the present application. As shown in FIG. 1, the SOC correction method provided by an optional embodiment of the present application includes:

[0036] S101, when it is judged through the charging current of the battery management system and the battery that the battery is currently in a charging state, and the temperature of the battery is within a preset temperature range, the terminal voltage of the battery is obtained.

[0037] For the above step S101, in specific implementation, first, it is judged through the battery management system and the current charging current of the battery whether the battery is currently in a charging state. If it is in a charging state, the temperature of the battery is obtained. When the temperature of the battery is within a preset temperature range, the terminal voltage of the battery is obtained, and the subsequent judgment is entered. Specifically, whether the battery is currently in a charging state can be judged according to the state of the battery management system and the charging current of the battery. If the condition is met, and the temperature of the battery is also within a preset temperature range, the subsequent SOC correction stage is entered.

[0038] S102, the charging stage in which the battery currently is is judged according to the terminal voltage and the charging end start correction voltage threshold.

[0039] Here, specifically, the charging stage includes a non-charging end, a pseudo-charging end and a charging end. As an example, the charging end start correction voltage threshold can be the terminal voltage corresponding to the true SOC value of 95% at the charging end start correction point. The charging end start correction voltage threshold can be determined based on requirements, which is not limited in the present application.

[0040] For the step S102, in a specific implementation, the end voltage of the battery and the preset charging end start correction voltage threshold are used to determine the charging stage of the current battery. According to an optional embodiment provided by the present application, the entire charging process of the battery is divided into three charging stages, i.e., a non-charging end stage, a pseudo-charging end stage and a charging end stage.

[0041] As an optional embodiment, for the step S102, the determination of the charging stage of the current battery according to the end voltage and the charging end start correction voltage threshold comprises:

[0042] In step 1021, when the end voltage does not reach the charging end start correction voltage threshold and the actual SOC value is less than or equal to the SOC threshold, it is considered that the current battery is in the non-charging end stage.

[0043] In step 1022, when the end voltage does not reach the charging end start correction voltage threshold and the actual SOC value is greater than the SOC threshold, it is considered that the current battery is in the pseudo-charging end stage.

[0044] In step 1023, when the end voltage reaches the charging end start correction voltage threshold, it is considered that the current battery is in the charging end stage.

[0045] Here, as an example, the SOC threshold can be 95% of the true SOC value corresponding to the charging end start correction point, which is not limited in the present application.

[0046] For the steps 1021-1023, in a specific implementation, when the end voltage of the battery does not reach the charging end start correction voltage threshold and the actual SOC value is less than or equal to the SOC threshold, it is considered that the current battery is in the non-charging end stage. When the end voltage does not reach the charging end start correction voltage threshold and the actual SOC value is greater than the SOC threshold, it is considered that the current battery is in the pseudo-charging end stage. When the end voltage reaches the charging end start correction voltage threshold, it is considered that the current battery is in the charging end stage.

[0047] According to the SOC correction method provided by the present application, when the battery is in the non-charging end stage, no SOC correction operation is performed, and the normal ampere-hour integration is maintained, and the integration rate is 1.

[0048] S103, when the battery is currently in the charging stage at the end of the charging, the SOC target value corresponding to the battery is obtained based on the terminal voltage, and the SOC actual value of the battery is corrected based on the error between the SOC target value and the SOC actual value, using a fuzzy self-tuning PID control algorithm to obtain the SOC correction value of the battery.

[0049] For the above step S103, when the battery is currently in the charging stage at the end of the charging, the SOC target value corresponding to the battery is obtained based on the terminal voltage, and the SOC actual value of the battery is corrected based on the error between the SOC target value and the SOC actual value, using a fuzzy self-tuning PID control algorithm to obtain the SOC correction value of the battery.

[0050] As an optional embodiment, for the above step S103, the SOC target value corresponding to the battery is obtained based on the terminal voltage, including:

[0051] A: Obtain a plurality of historical terminal voltages of the battery during charging.

[0052] For the above step A, in the implementation, a plurality of historical terminal voltages of the battery during charging are obtained.

[0053] B: When it is judged that the terminal voltage of the battery shows a monotonic increasing trend based on the historical terminal voltage and the terminal voltage, the SOC target value corresponding to the temperature, current rate and terminal voltage of the battery is obtained from the SOC mapping relationship table.

[0054] C: When it is judged that the terminal voltage of the battery shows a monotonic decreasing trend based on the historical terminal voltage and the terminal voltage, the SOC value corresponding to the current rate switching time of the battery is taken as the SOC initial value of the variable rate ampere-hour integral method at the next time, and the SOC target value is determined using the variable rate ampere-hour integral method and the SOC initial value.

[0055] It should be noted that the SOC mapping relationship table refers to a data table constructed in advance for storing the corresponding relationship between temperature, current rate, voltage and SOC at the end of charging.

[0056] Here, in the fast charging process, as the SOC gradually increases, the constant current charging current obtained based on the fast charging map table gradually decreases, and in the short time after the current switching, the terminal voltage presents a gradually decreasing trend, and thereafter, with the accumulation of the charging capacity, the terminal voltage presents a gradually increasing trend. Please refer to FIG. 2, which is a voltage and current curve diagram of a lithium iron phosphate battery during charging according to an optional embodiment of the application. In the charging state, when the current rate decreases, the terminal voltage will appear a short-term downward trend, and the SOC is in an upward trend. In this stage, the terminal voltage and the SOC do not have a one-to-one correspondence, and cannot be obtained by offline table lookup. In the voltage decreasing stage, the variable-rate ampere-hour integration method is used to obtain the SOC target value of the terminal voltage decreasing part, and the variable-rate ampere-hour integration takes the charging rate as the input, wherein a smaller integration rate (0≤IntgRate<0.8) is adopted for a large current rate, and a real integration rate (0.8≤IntgRate≤1) is as close as possible for a small rate; in the terminal voltage increasing stage, the terminal voltage increasing part SOC target value can be obtained by querying the charging end temperature-current rate-voltage-SOC table (offline calibration value).

[0057] In the entire charging process of the battery, for the charging end, at a certain temperature and a certain charging rate, the terminal voltage of the battery has a corresponding relationship with the SOC, and the SOC target value can be obtained by the terminal voltage in different charging stages. For the above steps B-step C, in the specific implementation, when it is judged based on the historical terminal voltage and the terminal voltage that the terminal voltage of the battery presents a monotonically increasing trend, the SOC target value corresponding to the temperature, the current rate and the terminal voltage of the battery is obtained from the SOC mapping relationship table. Specifically, under normal conditions at the charging end, the SOC target value is obtained by table lookup: when the charging end correction condition is met and the terminal voltage presents a monotonically increasing trend, the SOC target value under the corresponding temperature and current rate can be obtained by the charging end temperature-current rate-voltage-SOC table. When it is judged based on the historical terminal voltage and the terminal voltage that the terminal voltage of the battery presents a monotonically decreasing trend, the SOC value of the battery at the current rate switching time is taken as the SOC initial value of the variable-rate ampere-hour integration method at the next time, and the variable-rate ampere-hour integration method and the SOC initial value are used to determine the SOC target value. Specifically, under abnormal conditions at the charging end, the SOC target value is obtained by inheritance: when the charging rate is switched, the terminal voltage presents a monotonically decreasing trend and maintains for a certain time, and table lookup cannot be performed. However, since the SOC target value at the previous time is obtained by table lookup, it has a certain credibility, and the table lookup value corresponding to the current rate switching time is taken as the SOC initial value of the variable-rate ampere-hour integration method at the next time, and the variable-rate ampere-hour integration method is used to obtain the SOC target value in the subsequent terminal voltage decreasing segment.

[0058] According to the SOC correction method provided in the application, in the SOC correction stage at the end of charging, the SOC ampere-hour integral system of the power battery is taken as the research object, and a fuzzy self-tuning PID control algorithm is designed. Please refer to FIG. 3, which is a structure diagram of a fuzzy self-tuning PID controller according to an optional embodiment of the application. The fuzzy self-tuning PID controller has the characteristics of high PID control precision, flexibility and adaptability of fuzzy control. Since the SOC tracking of the power battery does not require an accurate mathematical model, the specific parameters of the controller are adjusted by using the experience method on the basis of considering the stability, response speed, overshoot and steady-state accuracy of the output, so as to meet the design requirements of the SOC tracking controller.

[0059] As an optional embodiment, for the step S103, the SOC actual value is corrected by using the fuzzy self-tuning PID control algorithm based on the error between the SOC actual value and the SOC target value, so as to obtain the SOC correction value of the battery, which comprises the following steps:

[0060] I: determining the SOC error value according to the SOC actual value and the SOC target value.

[0061] For the step I, in the specific implementation, the SOC error value is determined according to the SOC actual value and the SOC target value. Specifically, the difference between the SOC actual value and the SOC target value is taken as the SOC error value, and the expression is e(k)=SOCCalibrat(k)-SOCtarget(k).

[0062] Wherein, SOCCalibrat(k) represents the SOC actual value, SOCtarget(k) represents the SOC target value, and e(k) is the SOC error value.

[0063] II: when the absolute value of the SOC error value is less than or equal to the preset error threshold, determining the error change rate based on the SOC error value, and taking the SOC error value and the error change rate as the input parameters of the fuzzy self-tuning PID control algorithm.

[0064] Here, ε is defined as the preset error threshold.

[0065] For the step II, in the specific implementation, when the SOC error value is less than or equal to the preset error threshold, i.e. |e|≤ε, the error change rate is determined based on the SOC error value, the integral element is introduced to eliminate the steady-state error of the system and improve the control precision, and the SOC error value and the error change rate are taken as the input parameters of the fuzzy self-tuning PID control algorithm.

[0066] III: obtaining the correction coefficient of the fuzzy self-tuning PID control algorithm by fuzzy processing, fuzzy reasoning and de-fuzzy processing of the input parameter through the fuzzy self-tuning PID control algorithm.

[0067] For the above steps, in specific implementation, the input parameter is fuzzy processed, fuzzy reasoned and de-fuzzy processed by the fuzzy self-tuning PID control algorithm to obtain the correction coefficient of the fuzzy self-tuning PID control algorithm.

[0068] The PID controller runs on a hardware system and is a kind of sampling control, which calculates the control amount according to the error information of the target value (SOCtarget) and the actual output (SOCCalibrat) at the sampling time, and its discrete PID expression is:

[0069] In the above formula, the discrete PID control is a linear controller, which calculates the control amount by linear combination of the three correction links of proportional control, integral control and differential control, and the functions of the correction links are as follows:

[0070] Proportional coefficient Kp: reflects the error signal proportionally, and the controller produces control action immediately to reduce the error once there is error, but the Kp value cannot eliminate the steady-state error of the system. The greater the Kp, the faster the system response speed and the higher the regulation accuracy, but it is easy to produce overshoot; the smaller the Kp, the slower the system response speed and the lower the regulation accuracy.

[0071] Integral coefficient Ki: used to eliminate the steady-state error of the system and improve the error-free degree of the system, but too strong integral action will increase the system overshoot and even cause the system to oscillate. Due to the particularity of SOC correction, it is not allowed to have a large overshoot, because the SOC calculated by ampere-hour integral in the charging process cannot be reduced, and if the SOC overshoot is too large, the purpose of SOC correction will be lost.

[0072] Differential coefficient Kd: reflects the change trend of the error signal and can introduce an effective early correction signal in the system before the error signal becomes too large, which is used to improve the dynamic characteristics of the system, reduce the overshoot, overcome the oscillation and improve the stability of the system. The greater the Kd, the earlier the response process is braked, thereby prolonging the regulation time.

[0073] The SOC tracking process of the power battery is strongly related to the user experience, and the SOC tracking rate needs to be strictly controlled, and the SOC should not be tracked too fast, and the SOC should not be kept at a high level for a long time, that is, the parameters of the above PID correction links need to be adjusted to control the dynamic response speed of the tracking system. The fuzzy self-tuning PID control algorithm is an adaptive PID control algorithm. By analyzing the relationship between the three PID parameters and the control error e and the error change rate ec, the three PID parameters are self-adaptively tuned according to the fuzzy principle to meet the different requirements of different e and ec for the control parameters, so that the SOC tracking process at the end of charging has good dynamic and static performance, and the basic principles of tuning are as follows:

[0074] When the error |e| is large, a larger Kp value should be selected to make the system have good fast tracking performance, and at the same time, the integral control effect should be limited to prevent integral saturation and avoid large overshoot in the system response, and a smaller Ki should be selected, and under normal circumstances Ki=0; the selection of Kd is moderate.

[0075] When the error |e| is medium, a smaller Kp value and Ki value should be selected to make the system response have smaller overshoot; at this time, the value of Kd has a greater impact on the system, if the error |e| and the error change rate |ec| are opposite in sign at this time, a smaller Kd value should be selected, otherwise a moderate Kd value should be selected to prevent the error from continuing to be large.

[0076] When the error |e| is small, larger Kp and Ki values should be selected to make the system have good stability, and smaller Kd values should be selected to avoid oscillation of the system output near the target value.

[0077] When the error change rate |ec| is large, a smaller Kp value should be selected to ensure the response speed and stability accuracy of the system and prevent large overshoot; when the error change rate |ec| is medium, the values of Kp and Ki should be increased to speed up the response speed of the system and have better steady-state performance, and a smaller Kd value should be selected; when the error change rate |ec| is small, larger Kp and Ki values and appropriate Kd values should be selected to ensure that the system has a faster response speed.

[0078] If the error and the error change rate are opposite in sign, a smaller Kd or zero Kd should be selected; otherwise, if the error and the error change rate are the same in sign at this time, a larger Kd should be selected to prevent the error from continuing to be large.

[0079] Here, specifically, for the above step III, the fuzzy self-tuning PID control algorithm design process is as follows:

[0080] Step 1: Determine the parameters of the fuzzy control interface: for the fuzzy self-tuning PID control algorithm, a 2-input 2-output control method is adopted, in which the input parameters are selected as the SOC error value e and the error change rate ec, and the output parameters are the correction parameters ΔKp and ΔKd of the fuzzy self-tuning PID control algorithm.

[0081] Step 2: Determine the fuzzy domain: the domain of the SOC error value e on the fuzzy set is [-150 1500], and the language variable fuzzy subsets are {NB, NM, NS, ZO, PS, PM, PB}, with the domain values divided into "negative big" (NB), "negative medium" (NM), "negative small" (NS), "zero" (ZO), "positive small" (PS), "positive medium" (PM), and "positive big" (PB), i.e. e = 100 * [-15 -10 -50 1015]. The domain of the error change rate ec on the fuzzy set is [-30 30], and the language variable fuzzy subsets are {NB, NS, ZO, PS, PB}, with the domain values divided into "negative big" (NB), "negative small" (NS), "zero" (ZO), "positive small" (PS), and "positive big" (PB), i.e. ec = 6 * [-5 -20 25]. The domain of the output PID correction parameter ΔKp on the fuzzy set is [-0.025 0.025], and the language variable fuzzy subsets are {NB, NM, NS, ZO, PS, PM, PB}, ΔKp = [-0.025 -0.020 -0.010 0 0.010 0.020 0.025]. The domain of the output PID positive parameter ΔKd on the fuzzy set is [-2.5 2.5], and the language variable fuzzy subsets are {NB, NM, NS, ZO, PS, PM, PB}, ΔKd = [-2.5 -2 -1 0 1 2 2.5].

[0082] Step 3: Determine the fuzzy membership function: in this application, the negative big (NB) fuzzy vector of the input and output quantities adopts the Z-type membership function (zmf), the positive big (PB) fuzzy vector of the input and output quantities adopts the s-type membership function (smf), and the rest adopts the triangular membership function (trimf). Please refer to FIG. 4(A), FIG. 4(B), and FIG. 4(C), FIG. 4(A) is a system error e membership function distribution curve provided by an optional embodiment of the application, FIG. 4(B) is a system error change rate ec membership function distribution curve provided by an optional embodiment of the application, and FIG. 4(C) is a ΔKp membership function distribution curve provided by an optional embodiment of the application, wherein the membership functions of ΔKp and ΔKd are the same, only the numerical values of the domains are different.

[0083] On the basis of expert experience, according to the setting basic principle between PID three parameters and control error e and error change rate ec, through simulation experiment adjustment, the fuzzy control rule table is summarized. Please refer to Table 1 and Table 2, Table 1 is a fuzzy control rule table of ΔKp provided by one optional embodiment of the application, and Table 2 is a fuzzy control rule table of ΔKd provided by one optional embodiment of the application.

[0084] Table 1 Fuzzy control rule table of ΔKp

[0085] Table 2 Fuzzy control rule table of ΔKd

[0086] Here, it should be noted that when the error change rate |ec| is small, Kd should not be selected too large at this time, otherwise the system is sensitive to disturbance and the oscillation is intensified; the above Table 1 and Table 2 are one of examples of the fuzzy control rule table provided by the application, and in fact, the fuzzy control rule table is not limited to the above examples.

[0087] Based on the fuzzy rule table of step 3, the fuzzy reasoning is carried out, the fuzzy matrix reasoning of PID parameters is designed by using if-then conditional statement, a fuzzy set of output space is mapped to a determined point, and the practical application purpose is achieved. The relationship is expressed by the following 35 relationships:

[0088] 1). If (e is NB) and (ec is NB) then (ΔKp is PB) (ΔKd is PS);

[0089] 2). If (e is NM) and (ec is NB) then (ΔKp is NM) (ΔKd is ZO);

[0090] …

[0091] 35). If (e is PB) and (ec is PB) then (ΔKp is PB) (ΔKd is PB).

[0092] Step 4: De-fuzzification: the output obtained through fuzzy reasoning is a fuzzy set, in actual use, a determined PID parameter is used to control the SOC tracking process, and this requires de-fuzzification processing. In the application, the "median method" is adopted, that is, the horizontal coordinate of the 1 / 2 area of the area surrounded by the fuzzy membership function curve and the fuzzy coordinate is taken as the decision value.

[0093] From this, the accurate amount {e, ec} of fuzzy control can be obtained, and the self-tuning control amount parameter can be expressed as:

[0094] In the formula, and are the initial values of the parameters.

[0095] Thus, in the operation process of the fuzzy self-tuning PID control algorithm, the SOC error value e and the error change rate ec are detected in real time, and are quantified to the corresponding argument domain, and the response value of each parameter is inferred from the fuzzy rule table, so as to complete the online tuning of the three parameters of PID.

[0096] IV: Adjusting the ampere-hour integral rate of the ampere-hour integral method by using the fuzzy self-tuning PID control algorithm and the correction coefficient, obtaining a first target ampere-hour integral rate, and correcting the SOC actual value by using the ampere-hour integral method and the first target ampere-hour integral rate to obtain the SOC correction value.

[0097] For the above step IV, when the correction coefficient of the fuzzy self-tuning PID control algorithm is determined, the first target ampere-hour integral rate is obtained by adjusting the ampere-hour integral rate of the ampere-hour integral method by using the fuzzy self-tuning PID control algorithm and the correction coefficient, and the SOC correction value is obtained by correcting the SOC actual value by using the ampere-hour integral method and the first target ampere-hour integral rate. Here, the method of correcting the SOC by using the ampere-hour integral method is described in detail in the prior art, and will not be repeated here. Thus, according to the SOC correction method provided in the present application, when the power battery is at the end of charging, the SOC target value is first obtained based on the SOC lookup table method or the inheritance method, the real-time SOC error value and the SOC error change rate are obtained, the fuzzy self-tuning PID control algorithm (FATPID-Fuzzy Adaptive Tuning PID Control Algorithm) is used to obtain the ampere-hour integral rate, the error feedback amount is introduced, and the closed-loop algorithm is introduced to the open-loop ampere-hour integral method at the end of charging, so as to greatly improve the estimation accuracy of the SOC.

[0098] As an optional embodiment, for the above step S103, the SOC actual value of the battery is corrected by using the fuzzy self-tuning PID control algorithm based on the error between the SOC actual value and the SOC target value, to obtain the SOC correction value of the battery, and the method further comprises:

[0099] When the absolute value of the SOC error value is greater than the preset error threshold, the integral action in the fuzzy self-tuning PID control algorithm is cancelled, the PD control is used to correct the SOC actual value, and the SOC correction value is obtained.

[0100] For the above steps, in specific implementation, when the absolute value of the SOC error value is greater than the preset error threshold, i.e., |e(k)|>ε, the integral action in the fuzzy self-tuning PID control algorithm is cancelled, and the PD control is used to correct the SOC actual value to obtain the SOC correction value. In this way, the integral separation type PID controller is used in the present application, when the SOC error value is greater than the preset error threshold, the integral link is cancelled to prevent the system stability from being reduced due to the integral link, and to avoid the SOC estimated value from generating a too large overshoot. The differential control can effectively reflect the change trend of the system input signal, so that an early correction signal is obtained through the controller to increase the damping degree of the system, so as to improve the stability of the SOC convergence process.

[0101] As an optional embodiment, when the current charging stage of the battery is the pseudo end of charging, the SOC actual value is corrected by the following steps:

[0102] A second target ampere-hour integral rate is determined in a preset integral rate range, and the SOC actual value is corrected by using the ampere-hour integral method and the second target ampere-hour integral rate to obtain the SOC correction value.

[0103] When the battery is at the pseudo end of charging, the SOC target value is directly taken as the SOC actual value, the SOC target value cannot reflect the true SOC attribute, at this time the SOC actual value deviation is zero, and it is ensured that the SOC correction is not performed at the non-end of charging. For the above steps, in specific implementation, a second target ampere-hour integral rate is determined in a preset integral rate range, and the SOC actual value is corrected by using the ampere-hour integral method and the second target ampere-hour integral rate to obtain the SOC correction value. Here, the preset integral rate range can be set to 0.1≤IntgRate<0.5, which is not limited in the present application. Specifically, when the battery is at the pseudo end of charging, the real-time detected terminal voltage does not reach the charging end start correction voltage threshold, and the SOC actual value is greater than the SOC threshold, at this time the SOC target value cannot be obtained based on the terminal voltage, and the SOC correction cannot be performed based on the real-time SOC error, at this time the real-time SOC estimated value is in a false high state, the second target ampere-hour integral rate is determined from the preset integral rate range (0.1≤IntgRate<0.5), and the end correction is intervened in advance to avoid the SOC from being kept at the full charging SOC value for a long time.

[0104] As an optional embodiment, the SOC correction method provided by the present application further comprises:

[0105] When it is detected that the battery is in a full charging state, the SOC actual value is corrected to a SOC full charging value.

[0106] For the above steps, in the specific implementation, when it is detected that the battery reaches the full charging state, full charging correction is performed, and the current SOC actual value is directly corrected to the SOC full charging value.

[0107] Referring to FIG. 5, FIG. 5 is a flow chart of a SOC correction algorithm at the end of charging of a lithium iron phosphate battery according to an optional embodiment of the present application. As shown in FIG. 5, in the charging process, different SOC target values and different correction methods correspond to different charging states of the battery. As shown in FIG. 5, the complete SOC correction method is introduced according to the flow:

[0108] (1) The current temperature is judged. If the temperature meets the requirements, the corresponding end-of-charging SOC terminal voltage is queried. Otherwise, no end-of-charging correction is performed.

[0109] (2) The charging current and the BMS system state are judged to determine whether the battery is currently in a charging state. If the conditions are met, the charging state flag is set, and the subsequent stage is entered for judgment. Otherwise, no end-of-charging correction is performed.

[0110] (3) It is judged whether the charging rate meets the pre-set upper and lower limits of the charging rate. If the conditions are met, the charging rate limit flag is set, and the subsequent stage is entered for judgment. Otherwise, no end-of-charging correction is performed. (In the end-of-charging of a large rate, the actual SOC is high due to the influence of polarization. At this time, the battery charging current needs to be limited to run under the condition of a large rate. At the same time, in the charging process, a small rate of the charging current will be considered as the end of charging. Therefore, this algorithm also limits the battery charging condition under a very low rate.)

[0111] (4) It is judged whether the terminal voltage meets the pre-set starting correction voltage threshold condition. If the conditions are not met, the SOC end-of-charging correction range flag is not set, and the current SOC estimated value is greater than 95%. Then, the pseudo-end-of-charging SOC correction is entered to correct in advance at a small integral rate (0

[0112] (5) It is judged whether the terminal voltage meets the pre-set starting correction voltage threshold condition. If the conditions are met, the SOC end-of-charging correction range flag is set (the charging is terminated, and the SOC end-of-charging correction range flag is reset, which records the whole process of the end-of-charging correction.). Then, the end-of-charging SOC correction is entered, and the subsequent judgment is performed. Otherwise, the pseudo-end-of-charging SOC correction is maintained or no correction is performed.

[0113] (6) judging whether the terminal voltage meets the preset starting correction voltage threshold condition, if the condition is met, the terminal voltage correction threshold flag is set, and the SOCtarget is obtained by table lookup at this time; if the condition is not met, the terminal voltage correction threshold flag is reset, and the SOCtarget is inherited at this time;

[0114] (7) judging the terminal voltage drop flag to be set when the voltage drops (the terminal voltage drop segment can be judged in time through the current ratio switching and the smoothed filtered terminal voltage drop difference information), and then the SOCtarget is obtained based on the variable rate ampere-hour integral method. (In the terminal voltage drop segment, since the terminal voltage CV and the SOC do not have a one-to-one correspondence, the target SOC_target in this segment is calculated by the current through the variable rate ampere-hour integral method, and the initial SOC uses the table lookup target SOC_target at the time before the current switching as the reference);

[0115] (8) judging the actual terminal voltage to be greater than the ratio termination terminal voltage threshold, and then the termination correction flag is set, and the SOCtarget is obtained based on the variable rate ampere-hour integral method; otherwise, the SOCtarget is obtained by table lookup; (since the large ratio, the SOCtarget is seriously high at the end, in order to reserve the correction time, the large ratio and the large voltage limit the SOC growth speed);

[0116] (9) when the temperature, the charging ratio, the terminal voltage and the terminal voltage change trend meet the conditions, that is, the temperature condition is met, the charging ratio is within the allowed upper and lower limits, the terminal voltage is greater than the terminal voltage threshold of the 95% SOC at the end, and the terminal voltage is in an increasing trend, at this time, the SOC charging end table lookup correction flag is set, and then the SOCtarget is obtained based on the SOC charging end voltage table; if any of the above conditions is not met, the SOC charging end table lookup correction flag is reset, and then no correction is performed;

[0117] (10) obtaining the SOCtarget based on the above steps 1-9, and then using the fuzzy self-tuning PID control algorithm to perform the SOC charging end correction based on the error information of the current SOC estimated value and the SOCtarget; finally, when the detection system reaches the full charging state, the current SOC is directly corrected to the full charging SOC value.

[0118] An optional embodiment of the SOC correction method at the battery charging end provided in the application compares the real-time detected terminal voltage with the charging end starting correction voltage threshold to judge whether the battery enters the end correction, if the battery is at the charging end, the SOC target value is obtained through the measurable terminal voltage, the fuzzy self-tuning PID control algorithm is used to correct the high SOC point in advance based on the error between the SOC actual value and the SOC target value, the error between the SOC actual value and the SOC target value is continuously reduced, and the error is smoothly close to the SOC target value, so as to realize the accurate estimation of the SOC.

[0119] Please refer to Figure 6, which is a schematic diagram of a SOC correction device at the end of a battery charging terminal according to an optional embodiment of this application. As shown in Figure 6, the SOC correction device 600 includes:

[0120] The terminal voltage acquisition module 601 is used to acquire the terminal voltage of the battery when it is determined by the battery management system and the charging current of the battery that the battery is currently in a charging state and the temperature of the battery is within a preset temperature range.

[0121] The charging stage determination module 602 is used to determine the current charging stage of the battery based on the terminal voltage and the charging end start correction voltage threshold; wherein, the charging stage includes non-charging end, pseudo-charging end, and charging end;

[0122] The charging end SOC correction module 603 is used to obtain the target SOC value of the battery based on the terminal voltage when the battery is currently in the charging end stage, and to correct the actual SOC value based on the error between the actual SOC value of the battery and the target SOC value using a fuzzy self-tuning PID control algorithm to obtain the corrected SOC value of the battery.

[0123] Furthermore, when the charging end SOC correction module 603 corrects the actual SOC value based on the error between the actual SOC value and the target SOC value of the battery using a fuzzy self-tuning PID control algorithm to obtain the corrected SOC value of the battery, the charging end SOC correction module 603 is also used for:

[0124] The SOC error value is determined based on the actual SOC value and the target SOC value;

[0125] When the absolute value of the SOC error is less than or equal to the preset error threshold, the error change rate is determined based on the SOC error, and the SOC error and the error change rate are used as input parameters of the fuzzy self-tuning PID control algorithm.

[0126] The input parameters are fuzzified, fuzzy inferred, and defuzzified by the fuzzy self-tuning PID control algorithm to obtain the correction coefficients of the fuzzy self-tuning PID control algorithm.

[0127] The fuzzy self-tuning PID control algorithm and the correction coefficient are used to adjust the ampere-hour integral rate of the ampere-hour integral method to obtain a first target ampere-hour integral rate. The actual value of the SOC is then corrected using the ampere-hour integral method and the first target ampere-hour integral rate to obtain the corrected SOC value.

[0128] Further, the charging end SOC correction module 603 is further configured to:

[0129] cancel the integral action in the fuzzy self-tuning PID control algorithm when the absolute value of the SOC error value is greater than the preset error threshold, and correct the SOC actual value by using PD control to obtain the SOC correction value.

[0130] Further, the SOC correction device 600 further comprises a pseudo charging end SOC correction module, when the battery is currently in the pseudo charging end, the pseudo charging end SOC correction module is configured to correct the SOC actual value by the following steps:

[0131] determining a second target ampere-hour integral rate in a preset integral rate range, and correcting the SOC actual value by using the ampere-hour integral method and the second target ampere-hour integral rate to obtain the SOC correction value.

[0132] Further, the charging stage judgment module 602 is further configured to:

[0133] when the terminal voltage does not reach the charging end starting correction voltage threshold, and the SOC actual value is less than or equal to the SOC threshold, it is considered that the battery is currently in the non-charging end;

[0134] when the terminal voltage does not reach the charging end starting correction voltage threshold, and the SOC actual value is greater than the SOC threshold, it is considered that the battery is currently in the pseudo charging end;

[0135] when the terminal voltage reaches the charging end starting correction voltage threshold, it is considered that the battery is currently in the charging end.

[0136] Further, the charging end SOC correction module 603 is further configured to:

[0137] obtain a plurality of historical terminal voltages of the battery in the charging process;

[0138] When it is judged that the terminal voltage of the battery is in a monotone increasing trend based on the historical terminal voltage and the terminal voltage, an SOC target value corresponding to the temperature, the current rate and the terminal voltage of the battery is obtained from an SOC mapping relationship table;

[0139] When it is judged that the terminal voltage of the battery is in a monotone decreasing trend based on the historical terminal voltage and the terminal voltage, an SOC value corresponding to the current rate switching time of the battery is taken as an SOC initial value of a variable-rate ampere-hour integration method at a next time, and the SOC target value is determined by using the variable-rate ampere-hour integration method and the SOC initial value.

[0140] Further, the SOC correction device 600 further comprises a full-charge correction module, which is configured to:

[0141] When it is detected that the battery is in a full-charge state, the SOC actual value is corrected to an SOC full-charge value.

[0142] Please refer to FIG. 7, which is a structural schematic diagram of an electronic device provided by an optional embodiment of the present application. As shown in FIG. 7, the electronic device 700 comprises a processor 710, a memory 720 and a bus 730.

[0143] The memory 720 stores machine readable instructions executable by the processor 710. When the electronic device 700 is running, the processor 710 and the memory 720 communicate with each other through the bus 730. When the machine readable instructions are executed by the processor 710, the steps of the SOC correction method at the end of battery charging can be performed, and the specific implementation manners can be referred to the method embodiments, which will not be described here again.

[0144] An optional embodiment of the present application further provides a computer readable storage medium, which stores a computer program. When the computer program is run by a processor, the steps of the SOC correction method at the end of battery charging in the method embodiments shown in FIG. 1 can be performed, and the specific implementation manners can be referred to the method embodiments, which will not be described here again.

[0145] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described system, device and unit can refer to the corresponding processes in the foregoing method embodiments, which will not be described here again.

[0146] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented in other manners. The described device embodiments are merely schematic, for example, the division of the units is only a logical function division, and there can be another division manner in actual implementation, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections between different units, or the among different units, can be indirect couplings or communication connections through some interfaces, devices or units, and can be in electrical, mechanical or other forms.

[0147] The units described as separated components can or can not be physically separated, and the components displayed as units can or can not be physical units, i.e., can be located in one place, or can be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purposes of the embodiments of the present application.

[0148] In addition, each functional unit in the embodiments of the present application can be integrated in one processing unit, or each unit can exist physically as a separate unit, or two or more units can be integrated in one unit.

[0149] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a non-volatile computer readable storage medium executable by a processor. Based on this understanding, the technical solutions of the present application or the parts of the technical solutions that make essential contributions to the prior art can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0150] Finally, it should be noted that the above-described embodiments are merely specific embodiments of the present application, which are used to illustrate the technical solutions of the present application, but not to limit the same. The protection scope of the present application is not limited thereto. Although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those skilled in the art that any skilled person in the art can still modify or easily think of changes to the technical solutions recorded in the foregoing embodiments, or make equivalent replacements to some of the technical features, within the technical scope disclosed by the present application. The modifications, changes or replacements do not make the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for correcting SOC at the end of battery charging, the method comprising: obtaining an end voltage of the battery when the battery is determined to be in a charging state by a battery management system and a charging current of the battery, and a temperature of the battery is within a preset temperature range; determining a charging stage in which the battery is currently located according to the end voltage and a charging-end-starting correction voltage threshold, wherein the charging stage comprises a non-charging-end stage, a pseudo-charging-end stage and a charging-end stage; when the battery is currently located in the charging-end stage, obtaining a target SOC value of the battery based on the end voltage, and correcting an actual SOC value of the battery based on an error between the target SOC value and the actual SOC value by using a fuzzy self-tuning PID control algorithm to obtain a corrected SOC value of the battery.

2. The SOC correction method of claim 1, wherein, The correcting of the actual SOC value by using the fuzzy self-tuning PID control algorithm based on the error between the target SOC value and the actual SOC value to obtain the corrected SOC value of the battery comprises: determining an SOC error value according to the actual SOC value and the target SOC value; when an absolute value of the SOC error value is less than or equal to a preset error threshold, determining an error change rate based on the SOC error value, and taking the SOC error value and the error change rate as input parameters of the fuzzy self-tuning PID control algorithm; obtaining a correction coefficient of the fuzzy self-tuning PID control algorithm by fuzzy processing, fuzzy reasoning and de-fuzzy processing of the input parameters; obtaining a first target ampere-hour integral rate by adjusting an ampere-hour integral rate of an ampere-hour integral method using the fuzzy self-tuning PID control algorithm and the correction coefficient, and correcting the actual SOC value using the ampere-hour integral method and the first target ampere-hour integral rate to obtain the corrected SOC value.

3. The SOC correction method of claim 2, wherein, The correcting of the actual SOC value by using the fuzzy self-tuning PID control algorithm based on the error between the target SOC value and the actual SOC value to obtain the corrected SOC value of the battery further comprises: when the absolute value of the SOC error value is greater than the preset error threshold, canceling an integral action in the fuzzy self-tuning PID control algorithm, and correcting the actual SOC value by using a PD control to obtain the corrected SOC value.

4. The SOC correction method of claim 2, wherein, The fuzzy self-tuning PID control algorithm is determined by the following steps: determining input parameters and output parameters of the fuzzy self-tuning PID control algorithm, wherein the input parameters are an SOC error value and an error change rate, and the output parameters are correction parameters of the fuzzy self-tuning PID control algorithm; determining a fuzzy domain of the input parameters and a fuzzy domain of the output parameters; determining a fuzzy membership function of the fuzzy self-tuning PID control algorithm; de-fuzzy processing of an output obtained by the fuzzy reasoning of the fuzzy self-tuning PID control algorithm is performed by using a median method.

5. The SOC correction method of claim 1, wherein, When the current charging stage of the battery is the pseudo end-of-charge, the actual SOC value is corrected by the following steps: A second target ampere-hour integration rate is determined in a preset integration rate range, so as to correct the actual SOC value by using the ampere-hour integration method and the second target ampere-hour integration rate to obtain the corrected SOC value.

6. The SOC correction method of claim 1, wherein, The current charging stage of the battery is determined according to the terminal voltage and a charging end-start correction voltage threshold, including: When the terminal voltage does not reach the charging end-start correction voltage threshold and the actual SOC value is less than or equal to an SOC threshold, it is considered that the current charging stage of the battery is the non-end-of-charge; When the terminal voltage does not reach the charging end-start correction voltage threshold and the actual SOC value is greater than the SOC threshold, it is considered that the current charging stage of the battery is the pseudo end-of-charge; When the terminal voltage reaches the charging end-start correction voltage threshold, it is considered that the current charging stage of the battery is the end-of-charge.

7. The SOC correction method of claim 1, wherein, The SOC target value corresponding to the battery is obtained based on the terminal voltage, including: A plurality of historical terminal voltages of the battery in a charging process are obtained; When it is determined based on the historical terminal voltages and the terminal voltage that the terminal voltage of the battery presents a monotone increasing trend, an SOC target value corresponding to the temperature, current rate and terminal voltage of the battery is obtained from an SOC mapping relationship table; When it is determined based on the historical terminal voltages and the terminal voltage that the terminal voltage of the battery presents a monotone decreasing trend, an SOC initial value of a variable-rate ampere-hour integration method at a next time point is taken as an SOC value corresponding to a current rate switching time point of the battery, and the SOC target value is determined by using the variable-rate ampere-hour integration method and the SOC initial value.

8. The SOC correction method of claim 1, wherein, The SOC correction method further includes: When it is detected that the battery is in a full-charge state, the actual SOC value is corrected to an SOC full-charge value. 9.A SOC correction device for an end-of-charge of a battery, the SOC correction device comprising: a terminal voltage obtaining module, configured to obtain a terminal voltage of the battery when it is determined that the battery is in a charging state by a battery management system and a charging current of the battery, and a temperature of the battery is in a preset temperature range; a charging stage determining module, configured to determine a current charging stage of the battery according to the terminal voltage and a charging end-start correction voltage threshold; wherein the charging stage includes a non-end-of-charge, a pseudo end-of-charge and an end-of-charge; an end-of-charge SOC correction module, configured to, when the current charging stage of the battery is the end-of-charge, obtain an SOC target value corresponding to the battery based on the terminal voltage, and correct an actual SOC value of the battery by using a fuzzy self-tuning PID control algorithm based on an error between the actual SOC value and the SOC target value, to obtain a corrected SOC value of the battery.

10. An electronic device comprising: A processor, a memory, and a bus, the memory storing machine readable instructions executable by the processor, when the electronic device is running, the processor and the memory communicating through the bus, the machine readable instructions being executed by the processor to perform the steps of the method for correcting the SOC at the end of battery charging according to any one of claims 1 to 8.

11. A computer readable storage medium, the computer readable storage medium storing a computer program, the computer program being executed by a processor to perform the steps of the method for correcting the SOC at the end of battery charging according to any one of claims 1 to 8.

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