Battery overcharge aging detection method and device, electronic equipment and medium

Abstract

The invention discloses a battery overcharge aging detection method and device, electronic equipment and a medium, relates to the field of power electronics, and considers that the capacity and the ohmic internal resistance of a battery in the charging and discharging process change continuously, the ohmic internal resistance of the battery is iterated in real time by using a particle swarm algorithm in the scheme. The most accurate current ohmic internal resistance in the ohmic internal resistance iterated by the particle swarm algorithm is determined according to the current end voltage and the current end current detected in real time in the unit constant-current charging and discharging period; the change rate of the capacity peak value of the battery and the relative change rate of the internal resistance capacity are obviously different from those in a normal aging condition, so that the change rate of the capacity peak value of the battery and the relative change rate of the internal resistance capacity need to be determined, and the overcharge aging degree of the battery is further determined. According to the scheme, the overcharge aging degree of the battery can be accurately determined without disassembling the battery.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of power electronics, in particular to a battery overcharge aging detection method and device, electronic equipment and medium. BACKGROUND

[0002] Because the ohmic internal resistance and capacity of the battery change constantly during the charging and discharging process, the battery management system (BMS) of the vehicle collects the parameters of the battery and estimates the state of the battery, which will all produce errors, so the battery may appear slight overcharging during the actual charging process. Overcharging will cause the capacity and performance of the battery to decline, and if the overcharged battery is serious, it may even cause thermal runaway. Currently, to detect whether the battery is overcharged, the battery needs to be disassembled and the internal structure of the battery is observed by electron microscopy. This method is destructive and the battery is easily damaged during disassembly. SUMMARY

[0003] The purpose of the present application is to provide a battery overcharge aging detection method and device, electronic equipment and medium. Considering that the capacity and ohmic internal resistance of the battery change constantly during the charging and discharging process, the present application uses a particle swarm algorithm to iteratively determine the ohmic internal resistance of the battery in real time, and determines the most accurate current ohmic internal resistance from the ohmic internal resistance iteratively determined by the particle swarm algorithm according to the current terminal voltage and current detected in real time during the unit constant current charging and discharging cycle. In addition, because when the battery is overcharged, the capacity peak size change rate and internal resistance capacity relative change rate of the battery will be significantly different from the size when the battery is normally aged, the capacity peak size change rate and internal resistance capacity relative change rate of the battery also need to be determined, and then the overcharge aging degree of the battery is determined. The present application can accurately determine the overcharge aging degree of the battery without disassembling the battery.

[0004] To solve the above technical problems, the present application provides a battery overcharge aging detection method, comprising:

[0005] determining the initial ohmic internal resistance, initial terminal voltage, initial terminal current, initial capacity, current capacity, current terminal voltage and current terminal current of the battery during the unit constant current charging and discharging cycle;

[0006] determining the current ohmic internal resistance of the battery according to the current terminal voltage, current terminal current and particle swarm algorithm;

[0007] determining the internal resistance capacity relative change rate of the battery during the unit constant current charging and discharging cycle based on the initial ohmic internal resistance of the battery, the current ohmic internal resistance, the initial capacity and the current capacity;

[0008] determine a capacity peak size change rate of the battery in the unit constant current charge and discharge cycle based on the initial terminal voltage, the initial terminal current, the current terminal voltage and the current terminal current;

[0009] determine the overcharge aging degree of the battery according to the internal resistance capacity relative change rate and the capacity peak size change rate.

[0010] Optionally, the current ohmic internal resistance of the battery is determined according to the current terminal voltage, the current terminal current and the particle swarm algorithm, including:

[0011] establish an equivalent second-order RC circuit model of the battery, the equivalent second-order RC circuit model including: an equivalent open circuit voltage of the battery, an equivalent ohmic internal resistance of the battery, an equivalent first polarization internal resistance of the battery, an equivalent second polarization internal resistance of the battery, an equivalent first polarization capacitance of the battery and an equivalent second polarization capacitance of the battery, the equivalent open circuit voltage being connected in series with the equivalent ohmic internal resistance, the equivalent first polarization internal resistance and the equivalent second polarization internal resistance in sequence, the equivalent first polarization internal resistance being connected in parallel with the equivalent first polarization capacitance, and the equivalent second polarization internal resistance being connected in parallel with the equivalent second polarization capacitance;

[0012] determine a plurality of groups of initial particles according to the equivalent second-order RC circuit model and the particle swarm algorithm, each group of the initial particles corresponding to the equivalent open circuit voltage of the equivalent open circuit voltage, the equivalent ohmic internal resistance, the equivalent first polarization internal resistance, the equivalent second polarization internal resistance, the equivalent first polarization capacitance and the equivalent second polarization capacitance;

[0013] determine an initial inertia coefficient of each group of the initial particles;

[0014] determine an optimal particle of each group of the initial particles in an iteration process based on the initial inertia coefficient and each group of the initial particles, the optimal particle representing a target particle at which a difference between an equivalent terminal voltage corresponding to each group of the initial particles in the iteration process and a current terminal voltage is smallest;

[0015] determine the current ohmic internal resistance of the battery as the equivalent ohmic internal resistance corresponding to the optimal particle.

[0016] Optionally, the determination of the optimal particle of each group of the initial particles in the iteration process based on the initial inertia coefficient and each group of the initial particles includes:

[0017] determine whether there is an equivalent terminal voltage corresponding to each group of the initial particles, which has a difference from the current terminal voltage smaller than a preset threshold value;

[0018] If there is an equivalent terminal voltage corresponding to the current terminal voltage in the equivalent terminal voltages corresponding to the initial particles of each group, the initial particle corresponding to the equivalent terminal voltage with the smallest difference from the current terminal voltage is taken as the optimal particle.

[0019] If there is no equivalent terminal voltage corresponding to the current terminal voltage in the equivalent terminal voltages corresponding to the initial particles of each group, the initial particles of each group are determined according to the initial inertia coefficient and the initial particles of each group.

[0020] It is judged whether there is an equivalent terminal voltage corresponding to the current terminal voltage in the equivalent terminal voltages corresponding to the initial particles of each group.

[0021] If there is an equivalent terminal voltage corresponding to the current terminal voltage in the equivalent terminal voltages corresponding to the initial particles of each group, the initial particle corresponding to the equivalent terminal voltage with the smallest difference from the current terminal voltage is taken as the optimal particle.

[0022] If there is no equivalent terminal voltage corresponding to the current terminal voltage in the equivalent terminal voltages corresponding to the initial particles of each group, the initial inertia coefficient is updated according to the number of iterations of the initial particles of each group, and new iteration particles are determined according to the updated initial inertia coefficient and the iteration particles of each group, until there is an equivalent terminal voltage corresponding to the current terminal voltage in the equivalent terminal voltages corresponding to the new iteration particles of each group, and the new iteration particle corresponding to the equivalent terminal voltage with the smallest difference from the current terminal voltage is taken as the optimal particle.

[0023] Optionally, before the initial particle corresponding to the equivalent terminal voltage with the smallest difference from the current terminal voltage is taken as the optimal particle, the method further comprises:

[0024] It is judged whether the equivalent open-circuit voltage, the equivalent ohmic internal resistance, the equivalent first polarization internal resistance, the equivalent second polarization internal resistance, the equivalent first polarization capacitance and the equivalent second polarization capacitance corresponding to the initial particle corresponding to the equivalent terminal voltage with the smallest difference from the current terminal voltage are all positive numbers.

[0025] If the equivalent open-circuit voltage, the equivalent ohmic internal resistance, the equivalent first polarization internal resistance, the equivalent second polarization internal resistance, the equivalent first polarization capacitance and the equivalent second polarization capacitance corresponding to the initial particle corresponding to the equivalent terminal voltage with the smallest difference from the current terminal voltage are all positive numbers, the step of taking the initial particle corresponding to the equivalent terminal voltage with the smallest difference from the current terminal voltage as the optimal particle is triggered.

[0026] If the equivalent open circuit voltage, the equivalent ohmic internal resistance, the equivalent first polarization internal resistance, the equivalent second polarization internal resistance, the equivalent first polarization capacitance and the equivalent second polarization capacitance corresponding to the initial particle corresponding to the equivalent terminal voltage with the smallest difference value from the current terminal voltage are not all positive numbers, the step of determining the iteration after particles corresponding to each group of initial particles according to the initial inertia coefficient and each group of initial particles is triggered.

[0027] Optionally, before the new iteration after particle corresponding to the equivalent terminal voltage with the smallest difference value from the current terminal voltage is taken as the optimal particle, the step of:

[0028] determining whether the equivalent open circuit voltage, the equivalent ohmic internal resistance, the equivalent first polarization internal resistance, the equivalent second polarization internal resistance, the equivalent first polarization capacitance and the equivalent second polarization capacitance corresponding to the new iteration after particle corresponding to the equivalent terminal voltage with the smallest difference value from the current terminal voltage are all positive numbers is further included.

[0029] If the equivalent open circuit voltage, the equivalent ohmic internal resistance, the equivalent first polarization internal resistance, the equivalent second polarization internal resistance, the equivalent first polarization capacitance and the equivalent second polarization capacitance corresponding to the new iteration after particle corresponding to the equivalent terminal voltage with the smallest difference value from the current terminal voltage are all positive numbers, the step of taking the new iteration after particle corresponding to the equivalent terminal voltage with the smallest difference value from the current terminal voltage as the optimal particle is triggered.

[0030] If the equivalent open circuit voltage, the equivalent ohmic internal resistance, the equivalent first polarization internal resistance, the equivalent second polarization internal resistance, the equivalent first polarization capacitance and the equivalent second polarization capacitance corresponding to the new iteration after particle corresponding to the equivalent terminal voltage with the smallest difference value from the current terminal voltage are not all positive numbers, the new iteration after each group of iteration after particles is iterated, and when there is an equivalent terminal voltage with a difference value smaller than a preset threshold from the current terminal voltage in the equivalent terminal voltage corresponding to the new iteration after each group of iteration after particles, if the equivalent open circuit voltage, the equivalent ohmic internal resistance, the equivalent first polarization internal resistance, the equivalent second polarization internal resistance, the equivalent first polarization capacitance and the equivalent second polarization capacitance corresponding to the iteration after new iteration after particle corresponding to the equivalent terminal voltage with the smallest difference value from the current terminal voltage are all positive numbers, the iteration after new iteration after particle corresponding to the equivalent terminal voltage with the smallest difference value from the current terminal voltage is taken as the optimal particle.

[0031] Optionally, the determination of the overcharge aging degree of the battery according to the internal resistance capacity relative change rate and the capacity peak value size change rate comprises:

[0032] determining a fuzzy membership function;

[0033] According to the membership function, the internal resistance capacity relative change rate and the capacity peak size change rate are fuzzily converted into corresponding first fuzzy language variable and second fuzzy language variable;

[0034] According to the membership function, the first fuzzy language variable and the second fuzzy language variable, the overcharge aging degree of the battery is determined.

[0035] Optionally, the overcharge aging degree of the battery is determined according to the membership function, the first fuzzy language variable and the second fuzzy language variable, comprising:

[0036] Based on the first fuzzy language variable, the second fuzzy language variable and a preset fuzzy logic diagnosis rule, a fuzzy logic output variable corresponding to the first fuzzy language variable and the second fuzzy language variable is determined;

[0037] According to the membership function, the fuzzy logic output variable and a barycenter method defuzzification operation formula, the percentage of the overcharge aging degree of the battery is determined.

[0038] The barycenter method defuzzification operation formula is: ;

[0039] represents the percentage of the overcharge aging degree of the battery after defuzzification at time t, represents the i-th fuzzy logic output variable, and n represents the number of the fuzzy logic output variables, represents the weight of the i-th fuzzy logic output variable in all fuzzy logic output variables.

[0040] To solve the above technical problems, the application further provides a battery overcharge aging detection device, comprising:

[0041] A first determination module is configured to determine an initial ohmic internal resistance, an initial terminal voltage, an initial terminal current, an initial capacity, a current capacity, a current terminal voltage and a current terminal current of a battery in a unit constant current charge and discharge cycle.

[0042] A second determination module is configured to determine a current ohmic internal resistance of the battery according to the current terminal voltage, the current terminal current and a particle swarm algorithm.

[0043] A third determination module is configured to determine an internal resistance capacity relative change rate of the battery in the unit constant current charge and discharge cycle based on the initial ohmic internal resistance of the battery, the current ohmic internal resistance, the initial capacity and the current capacity.

[0044] a fourth determining module, configured to determine a capacity peak value size change rate of the battery in the unit constant current charge and discharge cycle based on the initial terminal voltage, the initial terminal current, the current terminal voltage and the current terminal current;

[0045] a fifth determining module, configured to determine an overcharge aging degree of the battery according to the internal resistance capacity relative change rate and the capacity peak value size change rate.

[0046] To solve the above technical problems, the application further provides an electronic device, comprising:

[0047] a memory, configured to store a computer program;

[0048] a processor, configured to implement the steps of the battery overcharge aging detection method when the computer program is executed.

[0049] To solve the above technical problems, the application further provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the battery overcharge aging detection method.

[0050] The application aims to provide a battery overcharge aging detection method, device, electronic device and medium, which considers that the capacity and ohmic internal resistance of the battery change constantly during the charge and discharge process, so the ohmic internal resistance of the battery is iterated in real time by using a particle swarm algorithm, and the most accurate current ohmic internal resistance in the ohmic internal resistance iterated by the particle swarm algorithm is determined according to the current terminal voltage and the current terminal current detected in real time in the unit constant current charge and discharge cycle, in addition, because the capacity peak value size change rate and the internal resistance capacity relative change rate of the battery are obviously different from the size in the normal aging condition when the battery is in the overcharge aging condition, the capacity peak value size change rate and the internal resistance capacity relative change rate of the battery need to be determined, and then the overcharge aging degree of the battery is determined, and the overcharge aging degree of the battery can be accurately determined without disassembling the battery. BRIEF DESCRIPTION OF DRAWINGS

[0051] In order to more clearly illustrate the technical solutions of the embodiments of the application or the prior art, the following will briefly introduce the drawings needed in the embodiments or the prior art description. Obviously, the drawings in the following description only constitute the embodiments of the application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of the provided drawings.

[0052] Figure 1 A process flow chart of a battery overcharge aging detection method provided by the application;

[0053] Figure 2An IC curve schematic diagram in a battery charging state is provided for the application.

[0054] Figure 3 An equivalent second-order RC circuit model structure schematic diagram is provided for the application.

[0055] Figure 4 A particle swarm algorithm flow chart is provided for the application.

[0056] Figure 5 A fuzzy diagnosis flow chart is provided for the application.

[0057] Figure 6 An internal resistance capacity relative change rate and membership function corresponding relationship schematic diagram is provided for the application.

[0058] Figure 7 A battery overcharge aging detection device structure schematic diagram is provided for the application.

[0059] Figure 8 An electronic device structure schematic diagram is provided for the application. DETAILED DESCRIPTION

[0060] The core of the application is to provide a battery overcharge aging detection method, device, electronic equipment and medium, considering that the capacity and ohmic internal resistance of the battery change constantly during charging and discharging, so the present scheme uses the particle swarm algorithm to iteratively determine the ohmic internal resistance of the battery in real time, and determines the most accurate current ohmic internal resistance in the ohmic internal resistance iteratively determined by the particle swarm algorithm according to the current terminal voltage and current detected in real time in a unit constant current charging and discharging cycle. In addition, because when the battery is overcharged and aged, the capacity peak size change rate and the internal resistance capacity relative change rate of the battery will be obviously different from the size when it is normally aged, the capacity peak size change rate and the internal resistance capacity relative change rate of the battery need to be determined, and then the overcharge aging degree of the battery is determined. The present scheme can accurately determine the overcharge aging degree of the battery without disassembling the battery.

[0061] To make the objectives, 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 some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0062] Please refer to Figure 1 , Figure 1 A process flow chart of a battery overcharge aging detection method is provided for the application. The battery overcharge aging detection method comprises:

[0063] S11: determining initial ohmic internal resistance, initial terminal voltage, initial terminal current, initial capacity, current capacity, current terminal voltage and current terminal current of the battery in a unit constant current charge and discharge cycle;

[0064] S12: determining current ohmic internal resistance of the battery according to the current terminal voltage, the current terminal current and the particle swarm algorithm;

[0065] S13: determining internal resistance capacity relative change rate of the battery in the unit constant current charge and discharge cycle based on the initial ohmic internal resistance, the current ohmic internal resistance, the initial capacity and the current capacity of the battery;

[0066] S14: determining capacity peak value size change rate of the battery in the unit constant current charge and discharge cycle based on the initial terminal voltage, the initial terminal current, the current terminal voltage and the current terminal current;

[0067] S15: determining overcharge aging degree of the battery according to the internal resistance capacity relative change rate and the capacity peak value size change rate.

[0068] In the application, considering that the ohmic internal resistance and capacity of the battery change constantly in the charge and discharge process, and when the battery has overcharge aging, the capacity peak value size change rate and the internal resistance capacity relative change rate of the battery are obviously different from those in the normal aging, the capacity peak value size change rate and the internal resistance capacity relative change rate of the battery need to be determined, the internal resistance capacity relative change rate needs to be determined by the internal resistance change rate of the battery, i.e. the change amount of the current ohmic internal resistance and the initial ohmic internal resistance, and the capacity change rate of the battery, i.e. the change amount ratio of the current capacity and the initial capacity, so the accurate current ohmic internal resistance needs to be determined first, because the current ohmic internal resistance corresponds to the terminal voltage and the terminal current of the battery, and the particle swarm algorithm can iterate different ohmic internal resistances and compare them with the current terminal voltage and the current terminal current of the battery, so that the accurate current ohmic internal resistance can be selected, and the accurate internal resistance capacity relative change rate can be determined, in addition, because the capacity size change rate of the battery is only related to the current change amount of the battery in the unit constant current charge and discharge cycle, and the capacity peak value size change rate of the battery is related to the current change rate and the terminal voltage change rate of the battery in the unit constant current charge and discharge cycle, so the capacity peak value size change rate of the battery can be determined according to the current change rate and the terminal voltage change rate corresponding to the current ohmic internal resistance determined by the particle swarm algorithm, and finally the overcharge aging degree of the battery can be determined according to the capacity peak value size change rate and the internal resistance capacity relative change rate of the battery, the overcharge aging degree of the battery can be accurately determined without disassembling the battery.

[0069] The embodiment provides a battery overcharge aging detection method, considering that the capacity and ohmic internal resistance of the battery change continuously in the charging and discharging process, so the scheme uses a particle swarm algorithm to iteratively determine the ohmic internal resistance of the battery in real time, and determines the most accurate current ohmic internal resistance in the ohmic internal resistance iteratively determined by the particle swarm algorithm according to the current terminal voltage and the current terminal current detected in a unit constant current charging and discharging cycle. In addition, because when the battery is in an overcharge aging state, the capacity peak size change rate and the internal resistance capacity relative change rate of the battery are obviously different from the size in a normal aging state, the capacity peak size change rate and the internal resistance capacity relative change rate of the battery need to be determined, and then the overcharge aging degree of the battery is determined. The scheme can accurately determine the overcharge aging degree of the battery without disassembling the battery.

[0070] On the basis of the above embodiment:

[0071] As an optional embodiment, the current ohmic internal resistance of the battery is determined according to the current terminal voltage, the current terminal current and the particle swarm algorithm, and the method comprises the steps of:

[0072] An equivalent second-order RC circuit model of the battery is established, and the equivalent second-order RC circuit model comprises: an equivalent open circuit power supply of the battery, an equivalent ohmic internal resistance of the battery, an equivalent first polarization internal resistance of the battery, an equivalent second polarization internal resistance of the battery, an equivalent first polarization capacitance of the battery and an equivalent second polarization capacitance of the battery. The equivalent open circuit power supply is connected in series with the equivalent ohmic internal resistance, the equivalent first polarization internal resistance and the equivalent second polarization internal resistance in sequence, the equivalent first polarization internal resistance is connected in parallel with the equivalent first polarization capacitance, and the equivalent second polarization internal resistance is connected in parallel with the equivalent second polarization capacitance.

[0073] A plurality of groups of initial particles are determined according to the equivalent second-order RC circuit model and the particle swarm algorithm, and each group of initial particles corresponds to the equivalent open circuit voltage of the equivalent open circuit power supply, the equivalent ohmic internal resistance, the equivalent first polarization internal resistance, the equivalent second polarization internal resistance, the equivalent first polarization capacitance and the equivalent second polarization capacitance.

[0074] An initial inertia coefficient of each group of initial particles is determined.

[0075] Based on the initial inertia coefficient and each group of initial particles, an optimal particle of each group of initial particles in an iteration process is determined, and the optimal particle represents a target particle in which a difference between an equivalent terminal voltage corresponding to each group of initial particles in the iteration process and a current terminal voltage corresponding to each group of initial particles is the smallest.

[0076] The equivalent ohmic internal resistance corresponding to the optimal particle is taken as the current ohmic internal resistance of the battery.

[0077] In the present invention, considering that the internal resistance of the battery includes ohmic internal resistance and polarization internal resistance, in order to accurately determine the ohmic internal resistance of the battery, this scheme chooses to establish an equivalent second-order circuit model and determine several groups of initial particles through the particle swarm algorithm. Each group of initial particles corresponds to equivalent parameters in the equivalent second-order circuit model. The initial inertia parameters of each group of initial particles are determined for subsequent iterative updates to determine the optimal particles of each group of initial particles in the iterative process. For example: if the equivalent ohmic internal resistance in a group of initial particles is 3 ohms, then the value of the equivalent ohmic internal resistance after the first iteration should be 3 ohms + initial inertia coefficient × preset constant, and the optimal particle determined should be the target particle when the difference between the equivalent terminal voltage corresponding to each group of initial particles and the corresponding current terminal voltage is the smallest during the iterative process. In this way, the equivalent ohmic internal resistance corresponding to the optimal particle can be used as the current ohmic internal resistance of the battery. That is, considering that the ohmic internal resistance of the battery is in a changing state during the charging and discharging process, but the terminal voltage of the battery during the charging and discharging process can be detected in real time, this scheme selects a group of particles that are closest to the real-time measured terminal voltage during the charging and discharging process through an iterative particle method, and uses the corresponding equivalent ohmic internal resistance as the current ohmic internal resistance of the battery, thereby accurately measuring the ohmic internal resistance of the battery and ensuring the integrity of the scheme.

[0078] As an optional embodiment, determining the optimal particle of each group of initial particles in the iterative process based on the initial inertia coefficient and each group of initial particles includes:

[0079] Determine whether there is an equivalent terminal voltage corresponding to each group of initial particles, the difference between which and the current terminal voltage is less than a preset threshold;

[0080] If there is an equivalent terminal voltage corresponding to each group of initial particles whose difference with the current terminal voltage is less than a preset threshold, the initial particle corresponding to the equivalent terminal voltage with the smallest difference with the current terminal voltage is selected as the optimal particle;

[0081] If there is no equivalent terminal voltage corresponding to each group of initial particles whose difference with the current terminal voltage is less than a preset threshold, then the iterated particles corresponding to each group of initial particles are determined according to the initial inertia coefficient and each group of initial particles;

[0082] Determine whether there is an equivalent terminal voltage corresponding to the particle after each group of iterations whose difference with the current terminal voltage is less than a preset threshold;

[0083] If there is an equivalent terminal voltage corresponding to each group of iterated particles whose difference with the current terminal voltage is less than a preset threshold, the iterated particle corresponding to the equivalent terminal voltage with the smallest difference with the current terminal voltage is selected as the optimal particle;

[0084] If there is no equivalent terminal voltage corresponding to the current terminal voltage in the equivalent terminal voltages corresponding to the particles after iteration of each group, the initial inertia coefficient is updated according to the iteration number of the initial particles of each group, and the new particles after iteration are determined according to the updated initial inertia coefficient and the particles after iteration of each group, until there is an equivalent terminal voltage corresponding to the current terminal voltage in the equivalent terminal voltages corresponding to the new particles after iteration of each group, and the new particle after iteration corresponding to the equivalent terminal voltage with the smallest difference from the current terminal voltage is taken as the optimal particle.

[0085] In the present application, considering that the working process of the particle swarm algorithm is to continuously iterate particles, for example, if the equivalent ohmic internal resistance of the initial particles in each group is 3 ohms, the value of the equivalent ohmic internal resistance after the first iteration should be 3 ohms + initial inertia coefficient x preset constant, and the optimal particle should be the target particle with the smallest difference between the equivalent terminal voltage corresponding to each group of initial particles and the corresponding current terminal voltage in the iteration process, wherein the initial inertia coefficient changes with the change of the iteration number, so that the parameters of the particles are updated by the initial inertia coefficient, and then it is determined whether the updated particles meet the end condition, if the condition is met, the optimal particle is determined, and the process of determining the optimal particle of each group of initial particles in the iteration process is actually to first determine whether there is an equivalent terminal voltage corresponding to the current terminal voltage in the equivalent terminal voltages corresponding to each group of initial particles, if there is, it is proved that the initial particle corresponding to the equivalent terminal voltage with the smallest difference from the current terminal voltage is the optimal particle, otherwise, the inertia coefficient is updated according to the iteration number of the particles, and the particles after iteration are determined again, and the judgment is performed again until there is an equivalent terminal voltage corresponding to the current terminal voltage in the equivalent terminal voltages corresponding to the new particles after iteration of each group, and the new particle after iteration corresponding to the equivalent terminal voltage with the smallest difference from the current terminal voltage is taken as the optimal particle, thereby improving the reliability of the optimal particle determination process.

[0086] As an optional embodiment, before taking the initial particle corresponding to the equivalent terminal voltage with the smallest difference from the current terminal voltage as the optimal particle, the following steps are further included:

[0087] It is determined whether the equivalent open circuit voltage, the equivalent ohmic internal resistance, the equivalent first polarization internal resistance, the equivalent second polarization internal resistance, the equivalent first polarization capacitance and the equivalent second polarization capacitance corresponding to the initial particle corresponding to the equivalent terminal voltage with the smallest difference from the current terminal voltage are all positive numbers;

[0088] if the equivalent open circuit voltage, the equivalent ohmic internal resistance, the equivalent first polarization internal resistance, the equivalent second polarization internal resistance, the equivalent first polarization capacitance and the equivalent second polarization capacitance corresponding to the initial particle corresponding to the equivalent terminal voltage with the smallest difference value from the current terminal voltage are all positive numbers, a step of triggering the initial particle corresponding to the equivalent terminal voltage with the smallest difference value from the current terminal voltage as the optimal particle is triggered;

[0089] if the equivalent open circuit voltage, the equivalent ohmic internal resistance, the equivalent first polarization internal resistance, the equivalent second polarization internal resistance, the equivalent first polarization capacitance and the equivalent second polarization capacitance corresponding to the initial particle corresponding to the equivalent terminal voltage with the smallest difference value from the current terminal voltage are not all positive numbers, a step of determining the iteration after particle corresponding to each group of initial particles according to the initial inertia coefficient and each group of initial particles is triggered.

[0090] In the application, although it is judged that there is an equivalent terminal voltage with a difference value less than a preset threshold in the equivalent terminal voltage corresponding to each group of initial particles, that is, there is an equivalent terminal voltage approximately equal to the current terminal voltage in each group of initial particles, because the equivalent open circuit voltage, the equivalent ohmic internal resistance, the equivalent first polarization internal resistance, the equivalent second polarization internal resistance, the equivalent first polarization capacitance and the equivalent second polarization capacitance of the initial particle corresponding to the battery, after meeting the optimal particle determination condition, it is also necessary to ensure that each equivalent parameter is positive, so that the optimal particle determined is correct, otherwise, as long as one parameter in the equivalent open circuit voltage, the equivalent ohmic internal resistance, the equivalent first polarization internal resistance, the equivalent second polarization internal resistance, the equivalent first polarization capacitance and the equivalent second polarization capacitance of the initial particle corresponding to the battery is not positive, it is proved that this group of initial particles is wrong, and it is necessary to continue to iterate and update, so as to avoid the error of battery overcharge aging detection result caused by the error of equivalent parameters, and improve the accuracy and reliability of the scheme.

[0091] As an optional embodiment, before the new iteration after particle corresponding to the equivalent terminal voltage with the smallest difference value from the current terminal voltage is taken as the optimal particle, it further includes:

[0092] determining whether the equivalent open circuit voltage, the equivalent ohmic internal resistance, the equivalent first polarization internal resistance, the equivalent second polarization internal resistance, the equivalent first polarization capacitance and the equivalent second polarization capacitance corresponding to the new iteration after particle corresponding to the equivalent terminal voltage with the smallest difference value from the current terminal voltage are all positive numbers;

[0093] if the equivalent open circuit voltage, the equivalent ohmic internal resistance, the equivalent first polarization internal resistance, the equivalent second polarization internal resistance, the equivalent first polarization capacitance and the equivalent second polarization capacitance corresponding to the new iteration after particle corresponding to the equivalent terminal voltage with the smallest difference value from the current terminal voltage are all positive numbers, a step of triggering the new iteration after particle corresponding to the equivalent terminal voltage with the smallest difference value from the current terminal voltage as the optimal particle is triggered;

[0094] If the equivalent open-circuit voltage, the equivalent ohmic internal resistance, the equivalent first polarization internal resistance, the equivalent second polarization internal resistance, the equivalent first polarization capacitance and the equivalent second polarization capacitance corresponding to the new iteration particle corresponding to the equivalent terminal voltage with the smallest difference from the current terminal voltage are all positive numbers, the new iteration particles are iterated, until there is an equivalent terminal voltage with a difference from the current terminal voltage less than a preset threshold in the equivalent terminal voltage corresponding to the new iteration particles, and if the equivalent open-circuit voltage, the equivalent ohmic internal resistance, the equivalent first polarization internal resistance, the equivalent second polarization internal resistance, the equivalent first polarization capacitance and the equivalent second polarization capacitance corresponding to the new iteration particle corresponding to the equivalent terminal voltage with the smallest difference from the current terminal voltage are all positive numbers, the new iteration particle corresponding to the equivalent terminal voltage with the smallest difference from the current terminal voltage is taken as the optimal particle.

[0095] In the present application, although it is judged that there is an equivalent terminal voltage with a difference from the current terminal voltage less than a preset threshold in the equivalent terminal voltage corresponding to the new iteration particles, that is, there is an equivalent terminal voltage approximately equal to the current terminal voltage in the new iteration particles, because the new iteration particles correspond to the equivalent open-circuit voltage, the equivalent ohmic internal resistance, the equivalent first polarization internal resistance, the equivalent second polarization internal resistance, the equivalent first polarization capacitance and the equivalent second polarization capacitance of the battery, after meeting the optimal particle determination condition, it is also necessary to ensure that each equivalent parameter is positive, so that the optimal particle determined is correct, otherwise, as long as one parameter in the equivalent open-circuit voltage, the equivalent ohmic internal resistance, the equivalent first polarization internal resistance, the equivalent second polarization internal resistance, the equivalent first polarization capacitance and the equivalent second polarization capacitance corresponding to the new iteration particles is not a positive number, it is proved that the new iteration particles are wrong, and it is necessary to continue iteration and update, avoiding the error of battery overcharge aging detection result caused by the error of equivalent parameters, and improving the accuracy and reliability of the scheme.

[0096] As an optional embodiment, the overcharge aging degree of the battery is determined according to the internal resistance capacity relative change rate and the capacity peak value size change rate, comprising:

[0097] determining the fuzzy membership function;

[0098] relatively fuzzifying the internal resistance capacity relative change rate and the capacity peak value size change rate into corresponding first fuzzy language variables and second fuzzy language variables according to the membership function;

[0099] determining the overcharge aging degree of the battery according to the membership function, the first fuzzy language variable and the second fuzzy language variable.

[0100] In the application, it is considered that there is a corresponding relationship between the internal resistance capacity relative change rate and the capacity peak size change rate and the failure mode of the battery, in addition, it is considered that the fuzzy logic is a way to deal with uncertainty and ambiguity, which can greatly improve the accuracy and efficiency of fault diagnosis through the establishment of fuzzy rules, fuzzy pattern matching and abnormal behavior analysis, therefore, the fuzzy logic diagnosis method is adopted to determine the fuzzy membership function corresponding to the fuzzy diagnosis rule, the membership function represents the corresponding relationship between the fuzzy language variable and the overcharge aging degree, then the internal resistance capacity relative change rate and the capacity peak size change rate are relatively fuzzed into the corresponding first fuzzy language variable and the second fuzzy language variable according to the membership function, finally, the overcharge aging degree of the battery can be determined according to the membership function, the first fuzzy language variable and the second fuzzy language variable, which ensures the integrity of the overcharge aging degree determination process.

[0101] As an optional embodiment, the overcharge aging degree of the battery is determined according to the membership function, the first fuzzy language variable and the second fuzzy language variable, which comprises:

[0102] determining the fuzzy logic output variable corresponding to the first fuzzy language variable and the second fuzzy language variable based on the first fuzzy language variable, the second fuzzy language variable and the preset fuzzy logic diagnosis rule;

[0103] determining the percentage of the overcharge aging degree of the battery according to the membership function, the fuzzy logic output variable and the barycentric method defuzzification operation formula;

[0104] wherein, the barycentric method defuzzification operation formula is: ;

[0105] represents the percentage of the overcharge aging degree of the battery after defuzzification at time t, represents the i th fuzzy logic output variable, and n represents the number of fuzzy logic output variables, represents the weight of the i th fuzzy logic output variable in all fuzzy logic output variables.

[0106] In the application, the specific process of determining the overcharge aging degree of the battery according to the membership function, the first fuzzy language variable and the second fuzzy language variable is to determine the fuzzy logic output variable corresponding to the first fuzzy language variable and the second fuzzy language variable under the preset fuzzy diagnosis rule, and the fuzzy logic output variable corresponds to the normal aging, overcharge warning and overcharge attenuation of the battery, then the membership function and the fuzzy logic output variable are substituted into the barycentric method defuzzification operation formula to determine the percentage of the overcharge aging degree of the battery, that is, the percentage of the overcharge aging degree of the battery corresponding to the internal resistance capacity relative change rate and the capacity peak size change rate is solved by the barycentric method defuzzification operation, which ensures the integrity of the scheme.

[0107] It should be noted that the specific technical solutions of the present application are as follows:

[0108] 1. Perform corresponding charge and discharge tests on the battery to be tested to obtain relevant data during the charge and discharge process;

[0109] 2. Analyze the data to obtain corresponding characteristic parameters;

[0110] 3. Build a second-order RC equivalent circuit model and perform online parameter identification (particle iteration using the particle swarm algorithm), and obtain corresponding characteristic parameters through the battery management system during normal operation of the energy storage system;

[0111] 4. Based on the fault characteristic quantities corresponding to the optimal particles and the fuzzy logic algorithm, establish a battery overcharge aging fault diagnosis model for the energy storage system;

[0112] 5. Preprocess the real-time data in the energy storage system, then fuzzy process the preprocessed data, and use a triangular membership function as the membership function of the input parameters of the overcharge aging fault diagnosis model for the energy storage system battery;

[0113] 6. Establish fuzzy rules, use the Mamdani model to establish IF-THEN fuzzy rules, and according to experimental data and analysis, develop a fuzzy logic diagnosis system rule base for the fault mode of lithium batteries;

[0114] 7. Defuzzification, use the gravity method to perform defuzzification operation to obtain the prediction result of the overcharge aging degree.

[0115] It should also be noted that the formula for calculating the relative change rate of internal resistance and capacity is: wherein, and represent the initial internal resistance and initial capacity of the battery, and represent the current internal resistance and current capacity of the battery, represents the internal resistance change amount, represents the capacity change amount.

[0116] It should also be noted that the principle of the IC curve of the battery is that the IC curve of the battery is obtained by taking the first derivative of the voltage-capacity (V-Q) curve under constant current charge and discharge operation. When there is a phase balance in the charge and discharge process of the battery, a peak value will appear on the IC curve. The flatter the voltage platform of the battery, the larger the peak value of dQ / dV. For example, Figure 2As shown, under the influence of overcharge condition, the peaks of curves I, III and IV all have obvious changes, in which the peak value of I peak decreases faster under overcharge cycle than under normal aging, and its relative position also has obvious shift; the peak value of III peak also decreases faster, and even after 30 cycles, III peak reversely grows.

[0117] It should also be noted that the structure of the equivalent second-order RC circuit model is as shown in Figure 3 , wherein, represents the equivalent open-circuit voltage of the battery, represents the equivalent ohmic internal resistance, and respectively represent the equivalent first polarization internal resistance and the equivalent second polarization internal resistance, and respectively represent the equivalent first polarization capacitance and the equivalent second polarization capacitance, and respectively represent the terminal voltage of the equivalent first polarization capacitance and the terminal voltage of the equivalent second polarization capacitance.

[0118] ;

[0119] , wherein, represents the current terminal voltage, represents the current terminal current, represents the initial terminal voltage of the equivalent first polarization capacitance in a unit constant-current charge-discharge cycle, represents the initial terminal voltage of the equivalent second polarization capacitance in a unit constant-current charge-discharge cycle, represents the current terminal voltage of the equivalent first polarization capacitance in a unit constant-current charge-discharge cycle, represents the current terminal voltage of the equivalent second polarization capacitance in a unit constant-current charge-discharge cycle, and respectively represent the time constant corresponding to the equivalent first polarization capacitance and the equivalent second polarization capacitance; represents the initial terminal current of the battery in a unit constant-current charge-discharge cycle.

[0120] It should also be noted that the online parameter identification method in the present application selects the particle swarm algorithm to complete the online parameter identification of the model. Compared with other intelligent algorithms, the particle swarm algorithm is simple and easy to implement, the program is simpler, the calculation convergence speed is fast, it also has memory function and the limitation to search space is relatively small. The updating formula of the inertia coefficient is: ; wherein ω0 represents a given initial inertia coefficient, represents a control factor of exponential function decay rate, k is the iteration number, and C is a preset constant, The updated inertia coefficient is represented. According to the characteristics of the exponential function, the decay rate of the early stage is greater than that of the later stage, so a larger initial ω is given, which can ensure its strong global search ability, and the smaller ω level after decay in the later iteration stage helps the local search ability to optimize. In addition, the specific process of the particle swarm algorithm is as shown in Figure 4 .

[0121] It should be noted that the specific steps of the battery overcharge fuzzy diagnosis system are as follows:

[0122] (1) Select the Mamdani model for design, determine the input fault characteristic parameters, select the triangular membership function as the membership function for the fuzzy process, in actual application, both triangular membership function and other membership functions can be selected, which is determined by actual needs, and the present application does not make special limitation. In addition, according to the data and analysis obtained from various test experiments, combined with the expert knowledge of the actual battery, the appropriate fuzzy rules and fuzzy diagnosis matrix are established;

[0123] (2) Input the external characteristic data of the battery to be diagnosed, obtain the fault characteristic quantity input fuzzy diagnosis system through the parameter identification of the battery model and the calculation of the incremental capacity, and perform fuzzy operation through the diagnosis rules in the knowledge base;

[0124] (3) According to the fuzzy logic output variable, the probability value of the occurrence of overcharge aging is obtained by defuzzification, as shown in Figure 5 .

[0125] It should be noted that when the triangular membership function is used as the membership function of the input parameter, the first input fault characteristic quantity, the relative change rate of internal resistance capacity, is determined, and its domain is defined in the closed interval [2, 12], the input relative change rate of internal resistance capacity is fuzzy to five fuzzy language variables, which are small (S), relatively small (RS), medium (M), relatively large (RL) and large (L). The corresponding relationship between the relative change rate of internal resistance capacity and the membership function is shown in Figure 6 In addition, the rule base of the lithium battery overcharge fault diagnosis system is shown in Table 1.

[0126] Table 1

[0127]

[0128] In combination with the analysis of overcharge aging in the experiment, the expert experience method is used to analyze the corresponding relationship between the fault characteristic quantity and the fault mode, and the rule base of the fuzzy logic diagnosis system of the fault mode of the battery is formulated. After the first fuzzy language variable and the second fuzzy language variable corresponding to the relative change rate of the internal resistance and the capacity and the size change rate of the capacity peak value are determined, the fuzzy logic output variable corresponding to the first fuzzy language variable and the second fuzzy language variable is determined according to the fuzzy logic diagnosis rule. The barycentric method is used for defuzzification operation on the fuzzy logic output variable, and the percentage of the overcharge aging degree of the battery can be obtained.

[0129] Please refer to Figure 7 , Figure 7 A structural schematic diagram of a battery overcharge aging detection device provided by the present application. The battery overcharge aging detection device comprises:

[0130] The first determining module 11 is configured to determine the initial ohmic internal resistance, the initial terminal voltage, the initial terminal current, the initial capacity, the current capacity, the current terminal voltage and the current terminal current of the battery in a unit constant current charging and discharging cycle.

[0131] The second determining module 12 is configured to determine the current ohmic internal resistance of the battery according to the current terminal voltage, the current terminal current and the particle swarm algorithm.

[0132] The third determining module 13 is configured to determine the relative change rate of the internal resistance and the capacity of the battery in the unit constant current charging and discharging cycle based on the initial ohmic internal resistance, the current ohmic internal resistance, the initial capacity and the current capacity of the battery.

[0133] The fourth determining module 14 is configured to determine the size change rate of the capacity peak value of the battery in the unit constant current charging and discharging cycle based on the initial terminal voltage, the initial terminal current, the current terminal voltage and the current terminal current.

[0134] The fifth determining module 15 is configured to determine the overcharge aging degree of the battery according to the relative change rate of the internal resistance and the capacity and the size change rate of the capacity peak value.

[0135] The battery overcharge aging detection device provided by the present embodiment corresponds to the above method, and has the same beneficial effects as the above method. Therefore, the embodiments of the battery overcharge aging detection device are described in the description of the embodiments of the method, and will not be described here.

[0136] Please refer to Figure 8 , Figure 8 A structural schematic diagram of an electronic device provided by the present application. The electronic device comprises:

[0137] The memory 20 is configured to store a computer program.

[0138] The processor 21 is configured to implement the steps of the battery overcharge aging detection method when executing the computer program.

[0139] The electronic device provided by the embodiment can include, but is not limited to, a smart phone, a tablet computer, a notebook computer, a desktop computer, and the like.

[0140] The processor 21 can include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like. The processor 21 can be implemented in at least one of a hardware form of a digital signal processor (DSP), a field-programmable gate array (FPGA), a programmable logic array (PLA). The processor 21 can also include a main processor and a coprocessor. The main processor is a processor for processing data in an awake state, also known as a central processing unit (CPU). The coprocessor is a low-power processor for processing data in a standby state. In some embodiments, the processor 21 can be integrated with a graphics processor (GPU) for rendering and drawing content required to be displayed by the display screen. In some embodiments, the processor 21 can further include an artificial intelligence (AI) processor for processing machine learning-related computing operations.

[0141] The memory 20 can include one or more computer-readable storage media, which can be non-transitory. The memory 20 can also include a high-speed random access memory, and a nonvolatile memory such as one or more disk storage devices, flash storage devices. In the embodiment, the memory 20 is at least used to store the following computer program 201, wherein the computer program is loaded and executed by the processor 21, and can implement the related steps of the battery overcharge aging detection method disclosed in any of the preceding embodiments. In addition, the resources stored by the memory 20 can also include an operating system 202 and data 203, and the storage mode can be temporary storage or permanent storage. The operating system 202 can include Windows, Unix, Linux, and the like. The data 203 can include, but is not limited to, a battery overcharge aging detection method, and the like.

[0142] In some embodiments, the electronic device can further include a display screen 22, an input / output interface 23, a communication interface 24, a power supply 25, and a communication bus 26.

[0143] Those skilled in the art can understand that, Figure 8The structure shown in the figures does not constitute a limitation on the electronic device, which can include more or fewer components than shown.

[0144] The embodiment aims to provide an electronic device, wherein the memory 20 is used to store a computer program, and the processor 21 is used to execute the computer program to realize the steps of the battery overcharge aging detection method, so that the detection process is more efficient and accurate.

[0145] The embodiment also provides a corresponding embodiment of a computer readable storage medium, and the computer readable storage medium stores a computer program.

[0146] It can be understood that if the method in the above embodiment is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and executes all or part of the steps of the method of each embodiment of the present application. The foregoing 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.

[0147] The computer readable storage medium provided by the embodiment corresponds to the above method, and has the same beneficial effects as the above method. Therefore, the embodiments of the computer readable storage medium part are described in the description of the embodiments of the method part, and will not be described here.

[0148] It should be noted that in the present specification, the relationship terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between the entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of another identical element in the process, method, article or device including the element.

[0149] The foregoing description of the disclosed embodiments enables a person skilled in the art to make or use the application. Modifications of these embodiments will occur to persons of skill in the art, and that the appended claims are intended to cover all such modifications that do not depart from the true spirit and scope of the application. Therefore, the application is not limited to the embodiments shown but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A battery overcharge aging detection method, characterized in that: include: Determine the initial ohmic internal resistance, initial terminal voltage, initial terminal current, initial capacity, current capacity, current terminal voltage and current terminal current of the battery during a unit constant current charge and discharge cycle; Determining the current ohmic internal resistance of the battery according to the current terminal voltage, the current terminal current, and a particle swarm algorithm; Determining a relative change rate of the internal resistance and capacity of the battery during the unit constant-current charge and discharge cycle based on the initial ohmic internal resistance of the battery, the current ohmic internal resistance, the initial capacity, and the current capacity; Determining a capacity peak value change rate of the battery within the unit constant current charge and discharge cycle based on the initial terminal voltage, the initial terminal current, the current terminal voltage, and the current terminal current; The overcharge aging degree of the battery is determined according to the relative change rate of the internal resistance capacity and the change rate of the capacity peak value.

2. The battery overcharge aging detection method according to claim 1, characterized in that: The determining the current ohmic internal resistance of the battery according to the current terminal voltage, the current terminal current, and a particle swarm algorithm includes: Establishing an equivalent second-order RC circuit model of the battery, the equivalent second-order RC circuit model including: an equivalent open-circuit power supply of the battery, an equivalent ohmic internal resistance of the battery, an equivalent first polarization internal resistance of the battery, an equivalent second polarization internal resistance of the battery, an equivalent first polarization capacitor of the battery, and an equivalent second polarization capacitor of the battery, wherein the equivalent open-circuit power supply is sequentially connected in series with the equivalent ohmic internal resistance, the equivalent first polarization internal resistance, and the equivalent second polarization internal resistance, the equivalent first polarization internal resistance is connected in parallel with the equivalent first polarization capacitor, and the equivalent second polarization internal resistance is connected in parallel with the equivalent second polarization capacitor; Determine a plurality of groups of initial particles according to the equivalent second-order RC circuit model and the particle swarm algorithm, wherein each group of initial particles corresponds to the equivalent open-circuit voltage of the equivalent open-circuit power supply, the equivalent ohmic internal resistance, the equivalent first polarization internal resistance, the equivalent second polarization internal resistance, the equivalent first polarization capacitance, and the equivalent second polarization capacitance; determining the initial inertia coefficient of each group of the initial particles; Determining the optimal particle of each group of the initial particles in the iteration process based on the initial inertia coefficient and each group of the initial particles, wherein the optimal particle represents the target particle when the difference between the equivalent terminal voltage corresponding to each group of the initial particles and the corresponding current terminal voltage is minimized during the iteration process; The equivalent ohmic internal resistance corresponding to the optimal particle is used as the current ohmic internal resistance of the battery.

3. The battery overcharge aging detection method according to claim 2, characterized in that: The determining of the optimal particles of each group of the initial particles in the iterative process based on the initial inertia coefficient and each group of the initial particles includes: Determining whether there is an equivalent terminal voltage corresponding to each group of the initial particles, the difference between which and the current terminal voltage is less than a preset threshold; If there is an equivalent terminal voltage corresponding to each group of the initial particles whose difference with the current terminal voltage is less than a preset threshold, the initial particle corresponding to the equivalent terminal voltage having the smallest difference with the current terminal voltage is selected as the optimal particle; If there is no equivalent terminal voltage corresponding to each group of the initial particles whose difference with the current terminal voltage is less than a preset threshold, determining the iterated particles corresponding to each group of the initial particles according to the initial inertia coefficient and each group of the initial particles; Determining whether there is an equivalent terminal voltage corresponding to each group of the iterated particles, the difference between which and the current terminal voltage is less than a preset threshold; If there is an equivalent terminal voltage corresponding to each group of the iterated particles whose difference with the current terminal voltage is less than a preset threshold, the iterated particle corresponding to the equivalent terminal voltage having the smallest difference with the current terminal voltage is selected as the optimal particle; If no equivalent terminal voltage corresponding to each group of the iterated particles has an equivalent terminal voltage whose difference with the current terminal voltage is less than a preset threshold, the initial inertia coefficient is updated according to the number of iterations of each group of the initial particles, and a new iterated particle is determined based on the updated initial inertia coefficient and each group of the iterated particles. If no equivalent terminal voltage corresponding to each new group of the iterated particles has an equivalent terminal voltage whose difference with the current terminal voltage is less than a preset threshold, the new iterated particle corresponding to the equivalent terminal voltage with the smallest difference with the current terminal voltage is selected as the optimal particle.

4. The battery overcharge aging detection method according to claim 3, characterized in that: Before taking the initial particle corresponding to the equivalent terminal voltage having the smallest difference with the current terminal voltage as the optimal particle, the method further includes: Determine whether the equivalent open circuit voltage, equivalent ohmic internal resistance, equivalent first polarization internal resistance, equivalent second polarization internal resistance, equivalent first polarization capacitance, and equivalent second polarization capacitance corresponding to the initial particles corresponding to the equivalent terminal voltage having the smallest difference from the current terminal voltage are all positive numbers; If the equivalent open-circuit voltage, equivalent ohmic internal resistance, equivalent first polarization internal resistance, equivalent second polarization internal resistance, equivalent first polarization capacitance, and equivalent second polarization capacitance corresponding to the initial particle corresponding to the equivalent terminal voltage having the smallest difference from the current terminal voltage are all positive numbers, then triggering the step of selecting the initial particle corresponding to the equivalent terminal voltage having the smallest difference from the current terminal voltage as the optimal particle; If the equivalent open-circuit voltage, equivalent ohmic internal resistance, equivalent first polarization internal resistance, equivalent second polarization internal resistance, equivalent first polarization capacitance and equivalent second polarization capacitance corresponding to the initial particles corresponding to the equivalent terminal voltage having the smallest difference with the current terminal voltage are not all positive numbers, then a step of determining the iterative particles corresponding to each group of the initial particles according to the initial inertia coefficient and each group of the initial particles is triggered.

5. The battery overcharge aging detection method according to claim 3, characterized in that: Before taking the new iterated particle corresponding to the equivalent terminal voltage having the smallest difference with the current terminal voltage as the optimal particle, the method further includes: Determine whether the equivalent open circuit voltage, equivalent ohmic internal resistance, equivalent first polarization internal resistance, equivalent second polarization internal resistance, equivalent first polarization capacitance, and equivalent second polarization capacitance corresponding to the new iterated particle corresponding to the equivalent terminal voltage having the smallest difference from the current terminal voltage are all positive numbers; If the equivalent open-circuit voltage, equivalent ohmic internal resistance, equivalent first polarization internal resistance, equivalent second polarization internal resistance, equivalent first polarization capacitance, and equivalent second polarization capacitance corresponding to the new iterated particle corresponding to the equivalent terminal voltage having the smallest difference from the current terminal voltage are all positive numbers, then triggering the step of selecting the new iterated particle corresponding to the equivalent terminal voltage having the smallest difference from the current terminal voltage as the optimal particle; If the equivalent open-circuit voltage, equivalent ohmic internal resistance, equivalent first polarization internal resistance, equivalent second polarization internal resistance, equivalent first polarization capacitance, and equivalent second polarization capacitance corresponding to the new iterated particle corresponding to the equivalent terminal voltage with the smallest difference from the current terminal voltage are not all positive, then iterate each new group of iterated particles until an equivalent terminal voltage corresponding to each new group of iterated particles has an equivalent terminal voltage whose difference from the current terminal voltage is less than a preset threshold. If the equivalent open-circuit voltage, equivalent ohmic internal resistance, equivalent first polarization internal resistance, equivalent second polarization internal resistance, equivalent first polarization capacitance, and equivalent second polarization capacitance corresponding to the new iterated particle corresponding to the equivalent terminal voltage with the smallest difference from the current terminal voltage are all positive, then the new iterated particle corresponding to the equivalent terminal voltage with the smallest difference from the current terminal voltage is selected as the optimal particle.

6. The battery overcharge aging detection method according to any one of claims 1 to 5, characterized in that: The determining the overcharge aging degree of the battery according to the relative change rate of the internal resistance capacity and the change rate of the peak capacity includes: Determine the fuzzified membership function; According to the membership function, the internal resistance capacity relative change rate and the capacity peak value change rate are relatively fuzzified into corresponding first fuzzy linguistic variables and second fuzzy linguistic variables; The overcharge aging degree of the battery is determined according to the membership function, the first fuzzy linguistic variable, and the second fuzzy linguistic variable.

7. The battery overcharge aging detection method according to claim 6, characterized in that: The determining the overcharge aging degree of the battery according to the membership function, the first fuzzy linguistic variable, and the second fuzzy linguistic variable includes: Determining fuzzy logic output variables corresponding to the first fuzzy linguistic variable and the second fuzzy linguistic variable based on the first fuzzy linguistic variable, the second fuzzy linguistic variable, and a preset fuzzy logic diagnostic rule; Determining the percentage of the battery overcharge aging degree according to the membership function, the fuzzy logic output variable and the centroid method defuzzification operation formula; The centroid method defuzzification calculation formula is: ; represents the percentage of the battery overcharge aging degree obtained after defuzzification at time t, represents the i-th fuzzy logic output variable, n represents the number of fuzzy logic output variables, represents the weight of the i-th fuzzy logic output variable in all fuzzy logic output variables.

8. A battery overcharge aging detection device, characterized in that: include: A first determination module is used to determine the initial ohmic internal resistance, initial terminal voltage, initial terminal current, initial capacity, current capacity, current terminal voltage and current terminal current of the battery in a unit constant current charge and discharge cycle; A second determination module is configured to determine a current ohmic internal resistance of the battery according to the current terminal voltage, the current terminal current, and a particle swarm algorithm; a third determining module, configured to determine a relative change rate of the internal resistance and capacity of the battery during the unit constant-current charge and discharge cycle based on the initial ohmic internal resistance, the current ohmic internal resistance, the initial capacity, and the current capacity of the battery; a fourth determining module, configured to determine a capacity peak value change rate of the battery within the unit constant current charge and discharge cycle based on the initial terminal voltage, the initial terminal current, the current terminal voltage, and the current terminal current; A fifth determining module is configured to determine the overcharge aging degree of the battery according to the relative change rate of the internal resistance capacity and the change rate of the capacity peak value.

9. An electronic device, characterized in that: include: memory for storing computer programs; A processor, configured to implement the steps of the battery overcharge and aging detection method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the battery overcharge and aging detection method according to any one of claims 1 to 7.

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