Power battery charging control method and system

Abstract

The invention belongs to the technical field of battery charging management and control, and particularly relates to a power battery charging management and control method and system.The method comprises the steps that after a battery is connected with a charger, a battery management system obtains the current state of the battery, and target charging current is determined according to the battery state; the battery management system sends a charging instruction to the charger based on the obtained target charging current; the charger adjusts the charging current to the target current according to the received charging instruction, and charges the battery with the adjusted charging current; in the charging process, the battery management system monitors the state of the battery in real time; the battery management system judges whether a preset charging cut-off condition is met or not according to the state of the battery; when the battery management system judges that the charging cut-off condition is met, a charging end instruction is sent to the charger; or after the battery management system receives a charging stopping message sent by the charger, a charging ending instruction is sent to the charger. The charging time is shortened and the charging efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of battery charging control, and specifically relates to a power battery charging control method and system. Background Art

[0002] With the increasing global awareness of environmental protection and the rapid development of science and technology, electric vehicles (EVs) and renewable energy storage systems (RESS) are becoming more popular at an unprecedented rate, becoming an important force in promoting green travel and achieving energy transformation. In this context, power batteries, as the core components of these systems, have a performance and safety and reliability that are directly related to the efficiency of the entire system and the trust of users. Power batteries must not only have basic properties such as high energy density and long cycle life, but must also be able to maintain stable performance under various working conditions, especially in the critical link of charging.

[0003] Traditional charging methods, whether constant current charging or constant voltage charging, have certain limitations. They often ignore the dynamic changes of the battery during the charging process, which directly affect the charging efficiency and safety of the battery. Charging with fixed charging parameters may not only cause battery overcharging, increase the risk of thermal runaway and short circuit, but also prolong the charging time due to low charging efficiency, affecting the user experience. Summary of the invention

[0004] In order to solve the problem that traditional charging control methods may cause battery overcharging, increase the risk of thermal runaway and short circuit, and may also prolong the charging time due to low charging efficiency, the present invention provides a power battery charging control method and system.

[0005] In a first aspect, the technical solution of the present invention provides a power battery charging control method, the method is applied to a control system, the control system includes a battery management system and a charger; the battery management system is used to manage the battery, the method includes: After the battery is connected to the charger, the battery management system obtains the current status of the battery and determines the target charging current based on the battery status; The battery management system sends a charging instruction to the charger based on the acquired target charging current; The charger adjusts the charging current to the target current according to the received charging instruction, and charges the battery with the adjusted charging current; During the charging process, the battery management system monitors the battery status in real time; The battery management system determines whether the preset charging cut-off condition is reached based on the battery status; When the battery management system determines that the charging termination condition is met, it sends a charging end instruction to the charger; or, when the battery management system receives a message from the charger to terminate charging, it sends a charging end instruction to the charger, and the charger stops current output in response to the charging end instruction.

[0006] As a preferred embodiment of the technical solution of the present invention, the battery management system obtains the current state of the battery, and before the step of determining the target charging current according to the battery state, the step includes: The battery management system divides the battery charging interval into stages with different strategies, and each strategy has a different number of stages; The particle swarm algorithm is used to calculate the optimal charging current in each stage; Compare the charging time and charged power under each division strategy to obtain the optimal strategy; and generate a relationship table between the charging interval and the corresponding optimal charging current under the optimal strategy.

[0007] As a preferred embodiment of the technical solution of the present invention, the step of using a particle swarm algorithm to calculate the optimal charging current in each stage includes: According to the specified maximum charging current and the SOC interval of the battery, by dividing the SOC interval into stages, m groups of current sequences are generated, and the current sequences constitute an initial current population; Set the fitness function and use the particle swarm optimization algorithm to optimize the parameters; After reaching the optimal point or the set number of iterations, the optimal charging current for each stage is output.

[0008] As a preferred embodiment of the technical solution of the present invention, the steps of setting a fitness function and using a multi-objective particle swarm optimization algorithm to perform parameter optimization include: Initialize the particle population, where the velocity is zero, the number of individuals is m, and the position of the i-th particle is The velocity of the ith particle is ; Set the fitness function to evaluate the fitness of each particle in the population; Update the position and velocity of each particle; Compare the fitness value of the current particle swarm with the fitness value of the previous particle swarm to judge the convergence.

[0009] As a preferred embodiment of the technical solution of the present invention, the steps of comparing the charging time and the charged power under each division strategy to obtain the optimal strategy; and generating a relationship table between the charging interval and the corresponding optimal charging current under the optimal strategy include: Obtain the charging time and charged power under each partitioning strategy; Calculate the average charging power under each partitioning strategy, and delete the partitioning strategy with the smallest average charging power; Calculate the average charging time under each of the remaining partitioning strategies, and delete the partitioning strategy with the longest average charging time; Calculate the difference in average charged power in adjacent stages of the current remaining partitioning strategies, and select the partitioning strategy with the smallest average charged power among the two partitioning strategies with the smallest difference as the optimal strategy; Generate a relationship table between the charging interval and the corresponding optimal charging current under the optimal strategy.

[0010] As a preferred embodiment of the technical solution of the present invention, the battery management system obtains the current state of the battery, and the step of determining the target charging current according to the battery state includes: The battery management system obtains the current state of the battery; the state includes the battery SOC; Determine the current battery charging range under the optimal sub-strategy based on the acquired SOC; According to the charging interval, a corresponding optimal charging current is obtained from an optimal charging current relationship table as a target charging current.

[0011] As a preferred embodiment of the technical solution of the present invention, during the charging process, the battery management system monitors the status of the battery in real time and includes: According to the battery status, it is determined that the battery is currently in the last stage of charging; If yes, the steps are executed: the battery management system determines whether a preset charging cut-off condition is reached according to the battery status; If not, when it is determined according to the battery status that the battery needs to enter the next stage, the steps are performed: determining the charging interval of the current battery under the optimal sub-strategy according to the acquired SOC.

[0012] As a preferred embodiment of the technical solution of the present invention, the battery status also includes battery voltage, battery temperature and charging time; the step of the battery management system judging whether a preset charging cut-off condition is reached according to the battery status includes: When the battery voltage reaches the cut-off voltage, the battery temperature reaches the preset temperature, or the charging time reaches the preset maximum charging time, the charging cut-off condition is met; otherwise, the charging cut-off condition is not met. This is to prevent the battery from overcharging, which can cause the battery to overheat, swell, and be damaged. For example, for lithium-ion batteries, when the voltage of a single battery reaches 4.2V or 4.25V (the specific value may vary depending on the battery type and BMS design), the constant current or constant voltage charging state will be terminated immediately.

[0013] High temperature can cause battery degradation, so the BMS will limit or terminate charging to keep the battery temperature within the allowable range. For example, during constant current charging, when the battery temperature reaches 60°C, the constant current charging state should be terminated immediately. This helps protect the battery from high temperature damage and prolongs its service life.

[0014] To ensure safe battery charging, in addition to setting the maximum voltage, maximum temperature, and minimum charging current, the maximum charging time should also be set. In certain situations (such as when temperature and voltage detection fails), the maximum charging time can serve as an additional safety measure.

[0015] As a preferred embodiment of the technical solution of the present invention, the battery management system obtains the current state of the battery, and before the step of determining the target charging current according to the battery state, the step includes: The battery management system obtains the record of battery deep discharge; Determine whether the number of deep discharges of the battery has reached the set number; If yes, output a prompt message; and output a constant current charging or constant voltage charging instruction to the charger; If not, execute the following steps: The battery management system obtains the current state of the battery and determines the target charging current according to the battery state.

[0016] Some BMS can adjust the termination conditions based on the battery's health status and usage history. For example, if the battery has been used for a long time or has experienced multiple deep discharges, the BMS may control the charging process more strictly to prevent further degradation of the battery.

[0017] In a second aspect, the technical solution of the present invention provides a power battery charging control system, including a battery management system and a charger; after the battery is connected to the charger, the battery management system obtains the current state of the battery and determines the target charging current according to the battery state; the battery management system sends a charging instruction to the charger based on the obtained target charging current; during the charging process, the battery management system monitors the state of the battery in real time; the battery management system determines whether a preset charging cut-off condition is met according to the state of the battery; when the battery management system determines that the charging cut-off condition is met, it sends a charging end instruction to the charger; or, when the battery management system receives a message sent by the charger to terminate charging, it sends a charging end instruction to the charger; The charger adjusts the charging current to the target current according to the received charging instruction, and charges the battery with the adjusted charging current; the charger stops the current output in response to the charging end instruction.

[0018] As a preferred embodiment of the technical solution of the present invention, the battery management system divides the battery charging interval into stages according to different strategies, and each strategy has a different number of stages; a particle swarm algorithm is used to calculate the optimal charging current for each stage; the charging time and the charged power under each division strategy are compared to obtain the optimal strategy; and a relationship table between the charging interval and the corresponding optimal charging current under the optimal strategy is generated.

[0019] As a preferred embodiment of the technical solution of the present invention, the battery management system generates m groups of current sequences by dividing the SOC interval into stages according to the specified maximum charging current and the SOC interval of the battery, and the current sequences constitute the initial current population; sets the fitness function and uses the particle swarm optimization algorithm to optimize the parameters; and outputs the optimal charging current for each stage after reaching the optimal point or the set number of iterations.

[0020] As a preferred embodiment of the technical solution of the present invention, the battery management system obtains the charging time and charging power under each partitioning strategy; calculates the average charging power under each partitioning strategy, and deletes the partitioning strategy with the smallest average charging power; calculates the average charging time under each partitioning strategy in the remaining partitioning strategies, and deletes the partitioning strategy with the longest average charging time; calculates the difference in the average charging power of adjacent stages in the current remaining partitioning strategies, and selects the partitioning strategy with the smallest average charging power among the two partitioning strategies with the smallest difference as the optimal strategy; Generate a relationship table between the charging interval and the corresponding optimal charging current under the optimal strategy.

[0021] As a preferred embodiment of the technical solution of the present invention, the battery management system obtains the current state of the battery; the state includes the battery SOC; the charging interval of the current battery under the optimization strategy is determined according to the obtained SOC; and the corresponding optimal charging current is obtained in the optimal charging current relationship table according to the charging interval as the target charging current.

[0022] As a preferred embodiment of the technical solution of the present invention, the battery management system obtains the record of deep discharge of the battery; determines whether the number of deep discharges of the battery reaches the set number; if so, outputs a prompt message; and outputs a constant current charging or constant voltage charging instruction to the charger; Some BMS can adjust the termination conditions based on the battery's health status and usage history. For example, if the battery has been used for a long time or has experienced multiple deep discharges, the BMS may control the charging process more strictly to prevent further degradation of the battery.

[0023] It can be seen from the above technical solutions that the present invention has the following advantages: by monitoring the battery status in real time and determining the target charging current according to the battery status, the charging capacity of the battery can be maximized, the charging time can be shortened, and the charging efficiency can be improved. During the charging process, the battery management system monitors the battery status in real time and determines whether the preset charging cut-off condition is reached according to the battery status. This can effectively avoid safety hazards such as battery overheating and overcharging, and protect the safety of the battery.

[0024] The method of the present invention allows the battery management system to adopt different charging strategies according to the different states of the battery, and calculates the optimal charging current through the particle swarm algorithm. This enhances the flexibility of the system, enabling it to adapt to different types of batteries and different charging requirements. By accurately controlling the charging process, the method of the present invention can provide users with more stable and reliable charging services. At the same time, due to the shortened charging time and improved charging efficiency, the user experience will also be significantly improved. Optimizing the charging process of power batteries can not only improve the utilization rate of the battery, but also reduce energy waste. This is of great significance for promoting the development of electric vehicles and renewable energy storage systems.

[0025] Such a control system can not only effectively prevent battery overcharging and reduce the risk of thermal runaway, but also significantly improve charging efficiency and shorten charging time, thereby extending the battery life and reducing maintenance costs. In addition, the system can continuously optimize charging strategies based on individual battery differences and historical charging data, provide more personalized charging services, and further enhance user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0027] Figure 1 is a schematic flow chart of a method according to an embodiment of the present invention.

[0028] Figure 2 is a schematic block diagram of a system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0030] like Figure 1 As shown, an embodiment of the present invention provides a power battery charging control method, the method is applied to a control system, the control system includes a battery management system and a charger; the battery management system is used to manage the battery, the method includes: Step 1: After the battery is connected to the charger, the battery management system obtains the current status of the battery and determines the target charging current based on the battery status; Step 2: The battery management system sends a charging instruction to the charger based on the acquired target charging current; Step 3: The charger adjusts the charging current to the target current according to the received charging instruction, and charges the battery with the adjusted charging current; Step 4: During the charging process, the battery management system monitors the battery status in real time; Step 5: The battery management system determines whether the preset charging cut-off condition is reached according to the battery status; Step 6: When the battery management system determines that the charging termination condition is met, it sends a charging end instruction to the charger; or, when the battery management system receives a message from the charger to terminate charging, it sends a charging end instruction to the charger, and the charger stops current output in response to the charging end instruction.

[0031] In some embodiments, the battery management system obtains the current state of the battery, and before the step of determining the target charging current according to the battery state includes: S01: The battery management system divides the battery charging interval into stages with different strategies, and each strategy has a different number of stages; S02: Particle swarm algorithm is used to calculate the optimal charging current in each stage; S03: Compare the charging time and the charged power under each division strategy to obtain the optimal strategy; and generate a relationship table between the charging interval and the corresponding optimal charging current under the optimal strategy.

[0032] The battery management system (BMS) first divides the battery's charging range from a low power state (such as SOC 20%) to a high power state (such as SOC 80% or 95%) into multiple stages based on the battery's chemical characteristics, historical charging data, and the charging goals set by the user (such as fast charging, normal charging, or protecting battery life).

[0033] The number of stages can be different under different strategies. For example, strategy A may simply divide the charging process into two stages (fast charging stage and constant voltage charging stage), while strategy B may be more detailed and divided into five stages (pre-charging, fast charging, gentle charging, constant voltage charging and floating charging) to more finely control the charging process.

[0034] For each stage under each strategy, the BMS uses a particle swarm algorithm (PSO) for optimization calculations. PSO is an optimization algorithm based on swarm intelligence that simulates the foraging behavior of bird flocks to find the optimal solution to the problem. In each stage, a set of particles is defined, each particle represents a possible charging current value. The position (i.e., charging current value) and speed (i.e., the adjustment direction of the charging current) of the particles are updated iteratively to minimize the objective function (such as charging time, battery temperature rise, charging efficiency, etc.). After multiple iterations, the algorithm converges to the optimal solution, that is, the optimal charging current for each stage.

[0035] BMS calculates the total charging time and charged power under each division strategy, as well as other possible performance indicators (such as battery temperature, charging efficiency, etc.). By comprehensively comparing these indicators, BMS selects the optimal charging strategy, which is a strategy that can charge more power in a shorter time while keeping the battery temperature within a safe range and with higher charging efficiency. Based on the selected optimal strategy, BMS generates a relationship table between the charging range and the corresponding optimal charging current. This table lists in detail each stage from low power to high power, as well as the optimal charging current that should be used in each stage.

[0036] Improve charging efficiency and safety: By precisely controlling the charging current, BMS can dynamically adjust the charging strategy according to the real-time status of the battery, avoiding overcharging and undercharging, thereby improving charging efficiency and battery safety. By optimizing the charging process, the battery cycle stress is reduced, which helps to extend the battery life and reduce the user's maintenance costs. According to the charging goals set by the user, BMS can provide more personalized charging services, such as fast charging or charging modes that protect battery life, which improves user satisfaction. BMS can learn the charging history and characteristics of the battery and continuously optimize the charging strategy to make it more intelligent and adaptive to different battery states and charging environments.

[0037] Specifically, the steps of using the particle swarm algorithm to calculate the optimal charging current in each stage include: S021: According to the specified maximum charging current and the SOC interval of the battery, the SOC interval is divided into stages to generate m groups of current sequences, wherein the current sequences constitute an initial current population; According to the current state of the battery (such as SOC, i.e., the remaining power percentage) and the target state of charge, the SOC interval is divided into multiple stages. For example, the SOC interval from 20% to 80% can be divided into 4 stages, each corresponding to a certain SOC range (such as 20%-40%, 40%-60%, 60%-80%). o For each stage, a sequence of possible charging current values ​​within the stage is generated based on the specified maximum charging current and the chemical characteristics of the battery (such as the maximum acceptable charging rate, battery temperature, etc.). This sequence will be used as the initial population in the particle swarm algorithm. Assuming that n charging current values ​​are generated in each stage, a total of m groups of current sequences will be generated for m stages, each containing n current values.

[0038] S022: Set the fitness function and use the particle swarm optimization algorithm to optimize the parameters; In this step, the particle population is initialized, where the velocity is zero, the number of individuals is m, and the position of the i-th particle is The velocity of the ith particle is ; Set the fitness function to evaluate the fitness of each particle in the population; update the position and velocity of each particle; compare the fitness value of the current particle swarm with the fitness value of the previous particle swarm to judge the convergence.

[0039] In the particle swarm algorithm, each particle represents a potential solution. Therefore, each particle can be initialized as a vector containing m charging current values, where each value corresponds to the optimal charging current candidate for a stage. The position and velocity of the particle also need to be initialized. The position represents the combination of the current charging current value, and the velocity represents the direction and magnitude of the charging current value adjustment.

[0040] The fitness function is used to evaluate the quality of each particle. In the battery charging optimization problem, the fitness function can be based on multiple indicators, such as charging time, battery temperature, charging efficiency, etc.

[0041] For example, the fitness function can be defined as: Fitness = w1 * (1 / ChargingTime) + w2 * (1 / BatteryTemperature) + w3 * ChargingEfficiency, where w1, w2, and w3 are weight coefficients used to balance the importance of different indicators. According to the fitness function, calculate the fitness value of each particle. Update the personal best position (pBest) and global best position (gBest) of each particle. The personal best position is the best position found by the particle during the iteration process, and the global best position is the best position found in the population. According to the update rule, adjust the speed and position of the particle. This usually involves the calculation of the current position, speed, personal best position, and global best position of the particle. Repeat the above process until the set number of iterations is reached or a certain stopping condition is met (such as the fitness value no longer increases significantly).

[0042] Here, the update formula is as follows:

[0043]

[0044] v n ( k ) is the n The velocity vector of the particle, x n ( k ) is the n The position vector of a particle, w ( k ) is the inertia weight, is the self-perception learning factor, is the social cognitive learning factor, r 1 and r 2 is a random value in the range [0, 1], It is the best performing particle in the current group;

[0045]

[0046]

[0047] Among them, y(k) is the actual running state of the kth iteration, y*(k) is the set running state of the kth iteration, is the maximum value in the running state, It is the minimum value of the running status.

[0048] S023: After reaching the optimal point or reaching the set number of iterations, the optimal charging current of each stage is output.

[0049] The algorithm stops when the particle swarm algorithm reaches the optimal point (i.e., the fitness value of the global optimal position is no longer significantly improved) or reaches the set number of iterations. The optimal charging current value for each stage is extracted from the global optimal position. These values ​​form part of the optimal charging strategy. The optimal charging current value for each stage is output to the BMS system for use in the actual charging process. At the same time, these values ​​can also be saved in the database for subsequent analysis and optimization. Through the above implementation process, the particle swarm algorithm can effectively find the optimal charging current value for each stage, thereby optimizing the battery charging process.

[0050] In some embodiments, the steps of comparing the charging time and the charged power under each division strategy to obtain the optimal strategy; and generating a relationship table between the charging interval and the corresponding optimal charging current under the optimal strategy include: S031: Obtain the charging time and charging power under each partitioning strategy; For each battery charging interval division strategy, the total charging time and total charged power under the strategy are recorded and obtained through actual charging tests or simulated charging processes.

[0051] S032: Preliminary screening - deleting the partitioning strategy with the smallest average charged power; Calculate the average charge power under each partitioning strategy (total charge power divided by the number of stages divided into the charging interval). Compare the average charge power of all partitioning strategies and delete the partitioning strategy with the smallest average charge power, because this means that the strategy charges the least power in the same time and has low efficiency.

[0052] S033: Further screening - deleting the partitioning strategy with the longest average charging time; For the remaining partitioning strategies, calculate the average charging time under each strategy (total charging time divided by the number of stages divided into charging intervals, but here it is more common to directly compare the total charging time because the number of stages is different). Compare the average charging time of the remaining strategies (or directly compare the total charging time), and delete the partitioning strategy with the longest average charging time (or the longest total time in direct comparison), because long-term charging may increase the thermal stress and aging rate of the battery.

[0053] S034: Fine screening – selecting the best strategy; For the remaining partitioning strategies, the difference in average charge between adjacent stages is calculated. This helps evaluate the smoothness of the strategy during the charging process. The smaller the difference, the smoother the charging process and the better the protection of the battery. Among the two partitioning strategies with the smallest difference, the strategy with the smaller average charge is selected as the optimal strategy. This is because, when the charging smoothness is similar, choosing a strategy with a slightly smaller charge may mean that the strategy does a better job in protecting battery life and reducing thermal stress, especially when the battery is close to full charge, and the smaller charging current helps reduce battery degradation.

[0054] S035: Generate a charging relationship table under the optimal strategy; According to the selected optimal strategy, each charging interval (stage) and the corresponding optimal charging current value are recorded in detail to generate a relationship table between the charging interval and the optimal charging current. This table will serve as the basis for the BMS system to control the charging current during the actual charging process.

[0055] In some embodiments, the battery management system obtains the current state of the battery, and the step of determining the target charging current according to the battery state includes: Step 11: The battery management system obtains the current state of the battery; the state includes the battery SOC; The battery management system (BMS) collects the current status data of the battery in real time through built-in sensors or externally connected sensor networks. These data include but are not limited to the battery's voltage, current, temperature, and remaining capacity (State of Charge, SOC for short). The BMS preprocesses the collected raw data, including data cleaning, denoising, calibration, etc., to ensure the accuracy and reliability of the data. In particular, the calculation of SOC may involve complex algorithms, such as coulomb counting method, open circuit voltage method, etc., to accurately estimate the remaining capacity of the battery.

[0056] Step 12: Determine the charging interval of the current battery under the optimal sub-strategy according to the acquired SOC; BMS uses preset battery optimization strategies, which may be based on factors such as battery chemistry, capacity, usage history, user preferences, etc. Each strategy defines different charging interval divisions, which reflect the charging characteristics and requirements of the battery at different SOCs. BMS compares the current battery SOC with the charging interval in the optimization strategy to determine the current charging interval of the battery. This step is the basis for the subsequent selection of the optimal charging current.

[0057] Step 13: Obtain the corresponding optimal charging current from the optimal charging current relationship table according to the charging interval as the target charging current.

[0058] Optimal charging current relationship table: The BMS stores an optimal charging current relationship table, which lists the optimal charging current values ​​corresponding to each charging interval according to the optimization strategy. These optimal values ​​may be pre-calculated through optimization techniques such as particle swarm algorithms and genetic algorithms, aiming to balance multiple performance indicators such as charging speed, battery life, and charging efficiency. Once the current battery charging interval is determined, the BMS will look up the optimal charging current value corresponding to the interval in the optimal charging current relationship table. This value will be set as the current target charging current to guide the subsequent charging process.

[0059] In the actual charging process, the BMS may also need to fine-tune the target charging current according to the real-time status of the battery (such as temperature and voltage changes) to ensure the safety and efficiency of the charging process. These adjustments may be based on preset control logic or more complex real-time optimization algorithms, which will not be described here.

[0060] In some embodiments, during the charging process, the battery management system monitors the status of the battery in real time and includes: According to the battery status, it is determined that the battery is currently in the last stage of charging; If yes, the steps are executed: the battery management system determines whether a preset charging cut-off condition is reached according to the battery status; If not, when it is determined according to the battery status that the battery needs to enter the next stage, the steps are performed: determining the charging interval of the current battery under the optimal sub-strategy according to the acquired SOC.

[0061] In some embodiments, the battery status also includes battery voltage, battery temperature and charging time; the steps of the battery management system determining whether a preset charging cut-off condition is reached according to the battery status include: When the battery voltage reaches the cut-off voltage, the battery temperature reaches the preset temperature, or the charging time reaches the preset maximum charging time, the charging cut-off condition is met; otherwise, the charging cut-off condition is not met. This is to prevent the battery from overcharging, which can cause the battery to overheat, swell, and be damaged. For example, for lithium-ion batteries, when the voltage of a single battery reaches 4.2V or 4.25V (the specific value may vary depending on the battery type and BMS design), the constant current or constant voltage charging state will be terminated immediately.

[0062] High temperature can cause battery degradation, so the BMS will limit or terminate charging to keep the battery temperature within the allowable range. For example, during constant current charging, when the battery temperature reaches 60°C, the constant current charging state should be terminated immediately. This helps protect the battery from high temperature damage and prolongs its service life.

[0063] To ensure safe battery charging, in addition to setting the maximum voltage, maximum temperature, and minimum charging current, the maximum charging time should also be set. In certain situations (such as when temperature and voltage detection fails), the maximum charging time can serve as an additional safety measure.

[0064] In some embodiments, the battery management system obtains the current state of the battery, and before the step of determining the target charging current according to the battery state includes: The battery management system obtains the record of battery deep discharge; Determine whether the number of deep discharges of the battery has reached the set number; If yes, output a prompt message; and output a constant current charging or constant voltage charging instruction to the charger; If not, execute the following steps: The battery management system obtains the current state of the battery and determines the target charging current according to the battery state.

[0065] Some BMS can adjust the termination conditions based on the battery's health status and usage history. For example, if the battery has been used for a long time or has experienced multiple deep discharges, the BMS may control the charging process more strictly to prevent further degradation of the battery.

[0066] like Figure 2 As shown, an embodiment of the present invention provides a power battery charging control system, including a battery management system and a charger; after the battery is connected to the charger, the battery management system obtains the current state of the battery and determines the target charging current according to the battery state; the battery management system sends a charging instruction to the charger based on the obtained target charging current; during the charging process, the battery management system monitors the state of the battery in real time; the battery management system determines whether a preset charging cut-off condition is met according to the state of the battery; when the battery management system determines that the charging cut-off condition is met, it sends a charging end instruction to the charger; or, when the battery management system receives a message sent by the charger to terminate charging, it sends a charging end instruction to the charger; The charger adjusts the charging current to the target current according to the received charging instruction, and charges the battery with the adjusted charging current; the charger stops the current output in response to the charging end instruction.

[0067] In some embodiments, the battery management system divides the battery charging interval into stages according to different strategies, and each strategy has a different number of stages; a particle swarm algorithm is used to calculate the optimal charging current for each stage; the charging time and the charged power under each division strategy are compared to obtain the optimal strategy; and a relationship table between the charging interval and the corresponding optimal charging current under the optimal strategy is generated.

[0068] In some embodiments, the battery management system generates m groups of current sequences by dividing the SOC interval into stages according to the specified maximum charging current and the SOC interval of the battery, and the current sequences constitute an initial current population; sets a fitness function and uses a particle swarm optimization algorithm to optimize parameters; and outputs the optimal charging current for each stage after reaching the optimal point or the set number of iterations.

[0069] In some embodiments, the battery management system obtains the charging time and charging power under each partitioning strategy; calculates the average charging power under each partitioning strategy, and deletes the partitioning strategy with the smallest average charging power; calculates the average charging time under each partitioning strategy in the remaining partitioning strategies, and deletes the partitioning strategy with the longest average charging time; calculates the difference in the average charging power of adjacent stages in the current remaining partitioning strategies, and selects the partitioning strategy with the smallest average charging power among the two partitioning strategies with the smallest difference as the optimal strategy; Generate a relationship table between the charging interval and the corresponding optimal charging current under the optimal strategy.

[0070] In some embodiments, a battery management system obtains a current state of a battery; the state includes a battery SOC; a charging interval of the current battery under an optimization strategy is determined based on the obtained SOC; and a corresponding optimal charging current is obtained from an optimal charging current relationship table based on the charging interval as a target charging current.

[0071] In some embodiments, the battery management system obtains a record of deep discharge of the battery; determines whether the number of deep discharges of the battery reaches a set number; if so, outputs a prompt message; and outputs a constant current charging or constant voltage charging instruction to the charger; Some BMS can adjust the termination conditions based on the battery's health status and usage history. For example, if the battery has been used for a long time or has experienced multiple deep discharges, the BMS may control the charging process more strictly to prevent further degradation of the battery.

[0072] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0073] An embodiment of a power battery charging control system provided in an embodiment of the present invention belongs to the same inventive concept as the power battery charging control method of the above-mentioned embodiments. For details not described in detail in the embodiment of the power battery charging control system, reference can be made to the embodiment of the above-mentioned power battery charging control method.

[0074] Although the present invention has been described in detail with reference to the accompanying drawings and in combination with the preferred embodiments, the present invention is not limited thereto. Without departing from the spirit and essence of the present invention, a person of ordinary skill in the art may make various equivalent modifications or substitutions to the embodiments of the present invention, and these modifications or substitutions shall be within the scope of the present invention. Any person of ordinary skill in the art may easily think of changes or substitutions within the technical scope disclosed by the present invention, and these shall be within the scope of protection of the present invention.

Claims

1. A power battery charging control method, characterized in that: The method is applied to a management and control system, the management and control system includes a battery management system and a charger; the battery management system is used to manage batteries, and the method includes: After the battery is connected to the charger, the battery management system obtains the current status of the battery and determines the target charging current based on the battery status; The battery management system sends a charging instruction to the charger based on the acquired target charging current; The charger adjusts the charging current to the target current according to the received charging instruction, and charges the battery with the adjusted charging current; During the charging process, the battery management system monitors the battery status in real time; The battery management system determines whether the preset charging cut-off condition is reached based on the battery status; When the battery management system determines that the charging termination condition is met, it sends a charging end instruction to the charger; or, when the battery management system receives a message from the charger to terminate charging, it sends a charging end instruction to the charger, and the charger stops current output in response to the charging end instruction.

2. The power battery charging control method according to claim 1, characterized in that: The battery management system obtains the current state of the battery and determines the target charging current according to the battery state, including: The battery management system divides the battery charging interval into stages with different strategies, and each strategy has a different number of stages; The particle swarm algorithm is used to calculate the optimal charging current in each stage; Compare the charging time and charged power under each division strategy to obtain the optimal strategy; and generate a relationship table between the charging interval and the corresponding optimal charging current under the optimal strategy.

3. The power battery charging control method according to claim 2, characterized in that: The steps of using particle swarm algorithm to calculate the optimal charging current in each stage include: According to the specified maximum charging current and the SOC interval of the battery, by dividing the SOC interval into stages, m groups of current sequences are generated, and the current sequences constitute an initial current population; Set the fitness function and use the particle swarm optimization algorithm to optimize the parameters; After reaching the optimal point or the set number of iterations, the optimal charging current for each stage is output.

4. The power battery charging control method according to claim 3, characterized in that: The steps of setting the fitness function and using the multi-objective particle swarm optimization algorithm for parameter optimization include: Initialize the particle population, where the velocity is zero, the number of individuals is m, and the position of the i-th particle is The velocity of the ith particle is ; Set the fitness function to evaluate the fitness of each particle in the population; Update the position and velocity of each particle; Compare the fitness value of the current particle swarm with the fitness value of the previous particle swarm to judge the convergence.

5. The power battery charging control method according to claim 4, characterized in that: The steps of comparing the charging time and the charged power under each division strategy to obtain the optimal strategy; and generating a relationship table between the charging interval and the corresponding optimal charging current under the optimal strategy include: Obtain the charging time and charged power under each partitioning strategy; Calculate the average charging power under each partitioning strategy, and delete the partitioning strategy with the smallest average charging power; Calculate the average charging time under each of the remaining partitioning strategies, and delete the partitioning strategy with the longest average charging time; Calculate the difference in average charged power in adjacent stages of the current remaining partitioning strategies, and select the partitioning strategy with the smallest average charged power among the two partitioning strategies with the smallest difference as the optimal strategy; Generate a relationship table between the charging interval and the corresponding optimal charging current under the optimal strategy.

6. The power battery charging control method according to claim 5, characterized in that: The battery management system obtains the current state of the battery and determines the target charging current according to the battery state. The steps include: The battery management system obtains the current state of the battery; the state includes the battery SOC; Determine the current battery charging range under the optimal sub-strategy based on the acquired SOC; According to the charging interval, a corresponding optimal charging current is obtained from an optimal charging current relationship table as a target charging current.

7. The power battery charging control method according to claim 6, characterized in that: During the charging process, the battery management system monitors the status of the battery in real time, including: According to the battery status, it is determined that the battery is currently in the last stage of charging; If yes, the steps are executed: the battery management system determines whether a preset charging cut-off condition is reached according to the battery status; If not, when it is determined according to the battery status that the battery needs to enter the next stage, the steps are performed: determining the charging interval of the current battery under the optimal sub-strategy according to the acquired SOC.

8. The power battery charging control method according to claim 7, characterized in that: The battery status also includes battery voltage, battery temperature and charging time; The steps of the battery management system determining whether a preset charging cut-off condition is reached according to the battery status include: When the battery voltage reaches the cut-off voltage, the battery temperature reaches the preset temperature, or the charging time reaches the preset maximum charging time, the charging cut-off condition is met; Otherwise, the charging cut-off condition is not met.

9. The power battery charging control method according to claim 8, characterized in that: The battery management system obtains the current state of the battery and determines the target charging current according to the battery state, including: The battery management system obtains the record of battery deep discharge; Determine whether the number of deep discharges of the battery has reached the set number; If yes, output a prompt message; and output a constant current charging or constant voltage charging instruction to the charger; If not, execute the following steps: The battery management system obtains the current state of the battery and determines the target charging current according to the battery state.

10. A power battery charging control system, characterized in that: It includes a battery management system and a charger. After the battery is connected to the charger, the battery management system obtains the current state of the battery and determines the target charging current according to the battery state. The battery management system sends a charging instruction to the charger based on the obtained target charging current. During the charging process, the battery management system monitors the battery state in real time. The battery management system determines whether the preset charging cut-off condition is reached based on the battery status; When the battery management system determines that the charging termination condition is met, it sends a charging termination instruction to the charger; or, when the battery management system receives a message from the charger to terminate charging, it sends a charging termination instruction to the charger; The charger adjusts the charging current to the target current according to the received charging instruction, and charges the battery with the adjusted charging current; the charger stops the current output in response to the charging end instruction.

Images