Multi-target cooperative charging and discharging method and system for energy storage battery

Abstract

This application relates to the field of charge and discharge technology, and provides a method and system for multi-objective coordinated charge and discharge of energy storage batteries. The method includes acquiring battery operating parameters and calculating state of charge (SOC) and state of health (SOH) values; generating a safe voltage boundary value based on the SOC, SOH, and operating parameters; determining a power limiting coefficient based on the safe voltage boundary value, SOC, and operating parameters; generating a globally limited reference current value based on the power limiting coefficient; determining a target execution current amplitude based on the globally limited reference current value, SOH, and SOC; generating an optimal current timing curve containing a expected trajectory based on the target execution current amplitude; collecting actual operating data and comparing it with the expected trajectory to obtain a deviation; adjusting control parameters based on the deviation and the optimal current timing curve; and generating a final control command. This method helps reduce the battery aging rate.

Description

Technical Field

[0001] This application relates to the field of charging and discharging technology, and in particular to a multi-target coordinated charging and discharging method and system for energy storage batteries. Background Technology

[0002] With the large-scale grid connection of renewable energy and the improvement of the electricity market mechanism, energy storage systems are increasingly widely used in grid peak shaving, frequency regulation and industrial and commercial energy management, becoming a key supporting link in building a new power system.

[0003] However, existing energy storage battery charge and discharge control strategies have significant shortcomings in dealing with the inconsistency of individual cells within the battery pack. They typically employ fixed thresholds or post-event equalization mechanisms, lacking the ability to dynamically adjust power distribution based on the electrochemical state of individual cells during real-time charging and discharging. This results in the overall usable capacity of the battery pack being limited by the worst-performing cells and is prone to local overcharging and over-discharging, thereby accelerating battery aging. Summary of the Invention

[0004] The main objective of this application is to provide a multi-objective coordinated charging and discharging method and system for energy storage batteries, which aims to solve the technical problems raised in the background art.

[0005] In a first aspect, this application provides a multi-target coordinated charging and discharging method for energy storage batteries, comprising: Discrete temperature measurement point data is acquired, and continuous three-dimensional temperature field distribution data is generated based on the discrete temperature measurement point data. A dynamic thermal feature vector is then generated based on the continuous three-dimensional temperature field distribution data. A virtual partition boundary coordinate set is generated based on the dynamic thermal feature vector, and a partition heat load demand sequence is generated based on the virtual partition boundary coordinate set and the dynamic thermal feature vector. A corrected total partition heat load demand sequence is generated based on the partition heat load demand sequence, and an optimal cooling medium allocation parameter set is generated based on the corrected total partition heat load demand sequence. A drive control command is generated based on the optimal cooling medium allocation parameter set, and the drive control command is sent to the actuator.

[0006] Secondly, this application also provides a multi-target coordinated charging and discharging device for energy storage batteries, comprising: The system comprises three modules: an acquisition module for acquiring discrete temperature measurement point data, generating continuous three-dimensional temperature field distribution data based on the discrete temperature measurement point data, and generating a dynamic thermal feature vector based on the continuous three-dimensional temperature field distribution data; a first generation module for generating a set of virtual partition boundary coordinates based on the dynamic thermal feature vector, and generating a partition heat load demand sequence based on the set of virtual partition boundary coordinates and the dynamic thermal feature vector; a second generation module for generating a corrected total partition heat load demand sequence based on the partition heat load demand sequence, and generating an optimal cooling medium allocation parameter set based on the corrected total partition heat load demand sequence; and a third generation module for generating drive control commands based on the optimal cooling medium allocation parameter set, and sending the drive control commands to the actuators.

[0007] This application provides a multi-target coordinated charging and discharging method and system for energy storage batteries. The method, on the one hand, dynamically generates an upper limit for safe charging voltage and a lower limit for safe discharging voltage by real-time acquisition of the terminal voltage, surface temperature, and current flowing through individual cells and calculation of the state of charge (SOC) and state of health (SOH) values. This provides precise physical safety boundaries for the charging and discharging process to avoid local overcharging and over-discharging. On the other hand, it identifies the target limiting module with the lowest SOC or highest surface temperature and calculates a power limiting coefficient to generate a globally limited reference current value. This solves the problem of the overall usable capacity of the battery pack being limited by the worst-performing individual cell and achieves dynamic power balance allocation. Furthermore, it obtains the deviation by comparing actual operating data with the expected trajectory and adjusts control parameters accordingly to generate a final control command adapted to the real-time state. This eliminates the accelerated battery aging phenomenon caused by fixed thresholds or post-event equalization mechanisms and improves system operational safety. Attached Figure Description

[0008] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0009] Figure 1 A schematic flowchart of a multi-target coordinated charging and discharging method for energy storage batteries provided in an embodiment of this application; Figure 2 This is a schematic diagram of the structure of a multi-target coordinated charging and discharging system for energy storage batteries provided in an embodiment of this application. Detailed Implementation

[0010] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0011] The flowchart shown in the attached diagram is for illustrative purposes only and does not necessarily include all content and operations / steps, nor does it necessarily have to be performed in the described order. For example, some operations / steps can be broken down, combined, or partially merged, so the actual execution order may change depending on the actual situation.

[0012] This application provides a method and system for multi-target coordinated charging and discharging of energy storage batteries.

[0013] The following detailed description of some embodiments of this application is provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0014] Please refer to Figure 1 , Figure 1 This is a schematic flowchart illustrating a multi-objective coordinated charging and discharging method for energy storage batteries, provided as an embodiment of this application. Figure 1 As shown, the multi-target coordinated charging and discharging method for energy storage batteries includes steps S1 to S4.

[0015] S1. Obtain battery operating parameters and calculate the state of charge (SOC) and state of health (SOH) values. Generate a safe voltage boundary value based on the SOC, SOH, and operating parameters. Specifically, collect the terminal voltage, surface temperature, and current of a single battery cell. Derive the SOC value by using the cumulative amount of current over time and the correspondence between the terminal voltage and the current. Simultaneously, derive the SOH value based on the drift characteristics of internal resistance increasing with usage frequency and the decay trend of capacity retention. Substitute the derived SOC, SOH, and collected surface temperature values ​​into a preset electrochemical polarization mapping relationship and iteratively calculate the maximum charging polarization voltage threshold and the maximum discharging polarization voltage threshold under the current operating conditions. Superimpose the maximum charging polarization voltage threshold and the terminal voltage value to obtain the upper limit of the safe charging voltage. Perform a difference calculation between the maximum discharging polarization voltage threshold and the terminal voltage value to obtain the lower limit of the safe discharging voltage. Output the set of the upper limit of the safe charging voltage and the lower limit of the safe discharging voltage as the safe voltage boundary value.

[0016] S2. Determine the power limitation coefficient based on the safety voltage boundary value, the state of charge (SOC) value, and the operating parameters, and generate a globally limited reference current value based on the power limitation coefficient. Specifically, iterate through the real-time individual cell voltage and temperature values ​​of all series-connected modules in the battery pack, identify the target limitation module with the lowest SOC value or the highest surface temperature, calculate the deviation between the SOC value of the target limitation module and the average SOC value of all cells, and the temperature difference between the surface temperature of the target limitation module and the average temperature of all cells. Calculate the power limitation coefficient corresponding to the target limitation module using the deviation, temperature difference, and safety voltage boundary value through a preset piecewise linear mapping rule. Multiply the power limitation coefficient by the theoretical reference current value corresponding to the total system power demand to obtain a corrected current value. Compare the corrected current values ​​corresponding to all modules and select the minimum value as the globally limited reference current value for output.

[0017] S3. Determine the target execution current amplitude based on the global constrained reference current value, the health state value, and the state of charge value. Generate an optimal current timing curve containing the expected trajectory based on the target execution current amplitude. Specifically, calculate the aging compensation factor based on the decay ratio of the health state value relative to the nominal capacity of the new battery state. Determine the applicable segmented charging mode based on the numerical range of the state of charge value. Multiply the global constrained reference current value and the aging compensation factor to obtain the target execution current amplitude. Set the target execution current amplitude as the base current amplitude under the segmented charging mode. Within a fixed future time window, select the current curve that meets the power limit coefficient constraint and conforms to the segmented charging mode as the optimal current timing curve, with the constraints of minimizing the temperature rise rate and maximizing the energy throughput. Record the expected power change trajectory and expected temperature change trajectory corresponding to the optimal current timing curve.

[0018] S4. Collect actual operating data and compare it with the expected trajectory to obtain the deviation. Adjust the control parameters according to the deviation and the optimal current timing curve to generate the final control command.

[0019] Specifically, during the control cycle, the actual operating current value, actual state of charge value, and actual temperature value are collected. The quantity deviation between the actual state of charge value and the expected quantity change trajectory is calculated, and the temperature deviation between the actual temperature value and the expected temperature change trajectory is calculated. If the quantity deviation or temperature deviation exceeds the preset fault tolerance threshold and the current is in pulse charging mode, the ratio of the on-time to off-time of the pulse current is adjusted according to the direction of the quantity deviation to update the pulse duty cycle. If the current is in constant current mode or constant voltage mode, the target execution current amplitude is linearly fine-tuned according to the temperature deviation to obtain the adjusted current value. The final control command is generated based on the updated pulse duty cycle or the adjusted current value.

[0020] The method provided in this embodiment, on the one hand, dynamically generates an upper limit for safe charging voltage and a lower limit for safe discharging voltage by real-time acquisition of the terminal voltage, surface temperature, and current flowing through individual cells and calculation of state of charge and state of health values, thereby providing precise physical safety boundaries for the charging and discharging process to avoid local overcharging and over-discharging; on the other hand, by identifying the target limiting module with the lowest state of charge value or the highest surface temperature and calculating the power limiting coefficient, a globally limited reference current value is generated, thereby solving the problem that the overall usable capacity of the battery pack is limited by the worst-performing individual cell and achieving dynamic power balance distribution; furthermore, by collecting actual operating data and comparing it with the expected trajectory to obtain the deviation and adjusting the control parameters accordingly, a final control command adapted to the real-time state is generated, thereby eliminating the accelerated battery aging phenomenon caused by fixed thresholds or post-event equalization mechanisms and improving the system's operational safety.

[0021] In some embodiments, the step of acquiring battery operating parameters and calculating state of charge (SOC) and state of health (SQH) values, and generating a safe voltage boundary value based on the SOC, SQH, and operating parameters, includes: S11. Collect the terminal voltage, surface temperature and current flowing through the individual battery cells, and calculate the state of charge value and the health value.

[0022] Specifically, high-precision sensors are used to read in real time the terminal voltage values ​​at both ends of a single cell, the surface temperature values ​​of the battery casing, and the current values ​​flowing through the battery. The read current values ​​are integrated over time and combined with the open-circuit voltage correction coefficient to derive the state of charge (SOC) value. At the same time, the linear drift characteristics of internal resistance with the number of cycles and the decay curve of capacity retention over time are analyzed to derive the state of health (SQH) value. The derived SOCH and SQH values ​​are used as the basis for subsequent calculations.

[0023] S12. Determine the polarization voltage threshold based on the state of charge (SOC), the state of health (SCH), and the surface temperature. Specifically, the calculated SOC, SCH, and the collected surface temperature are input into a pre-stored battery electrochemical characteristic mapping relationship. The mapping relationship is used to simulate the electrochemical reaction kinetics of the battery under different aging conditions and temperature conditions. The maximum charging polarization voltage and the maximum discharging polarization voltage that the battery can withstand under the current operating conditions are solved through iterative calculations. The maximum charging polarization voltage and the maximum discharging polarization voltage are then determined as the polarization voltage threshold.

[0024] S13. Generate a safe charging voltage upper limit and a safe discharging voltage lower limit based on the polarization voltage threshold and the terminal voltage, as the safe voltage boundary values. Specifically, add the maximum charging polarization voltage value in the determined polarization voltage threshold to the real-time acquired terminal voltage value to obtain the safe charging voltage upper limit; subtract the maximum discharging polarization voltage value in the polarization voltage threshold from the real-time acquired terminal voltage value to obtain the safe discharging voltage lower limit; combine the calculated safe charging voltage upper limit and safe discharging voltage lower limit into a set and mark it as the safe voltage boundary value, which is used to limit the voltage range of subsequent charging and discharging operations.

[0025] The method provided in this embodiment, on the one hand, accurately grasps the current energy reserve state and aging degree of the battery by real-time acquisition of terminal voltage, surface temperature, and flowing current, and calculates the state of charge value and state of health value, thereby providing a reliable data basis for state estimation; on the other hand, it determines the polarization voltage threshold based on the state of charge value, state of health value, and surface temperature, thereby quantifying the electrochemical polarization limit of the battery under the current operating conditions, and thus avoiding the acceleration of internal side reactions due to excessive polarization; furthermore, it generates an upper limit value for safe charging voltage and a lower limit value for safe discharging voltage based on the polarization voltage threshold and terminal voltage, thereby constructing a dynamically changing safe voltage boundary value, and thus preventing the battery from reaching the critical point of electrochemical stability during charging and discharging.

[0026] In some embodiments, determining a power limiting factor based on the safety voltage boundary value, the state of charge value, and the operating parameters, and generating a globally limited reference current value based on the power limiting factor, includes: S21. Identify the target limiting module with the lowest state of charge (SOC) value or the highest surface temperature, and calculate the deviation and temperature difference between the target limiting module and the average SOC value. Specifically, iterate through the real-time individual cell voltage and temperature values ​​of all series-connected modules in the battery pack, compare the SOC values ​​of each module to find the module with the lowest value, compare the surface temperatures of each module to find the module with the highest value, and determine the module with the lowest SOC value or the highest surface temperature as the target limiting module. Calculate the difference between the SOC value of the target limiting module and the average SOC value of all individual cells to obtain the deviation, and calculate the difference between the surface temperature of the target limiting module and the average temperature of all individual cells to obtain the temperature difference.

[0027] S22. Determine the power limiting coefficient corresponding to the target limiting module based on the deviation, the temperature difference, and the safety voltage boundary value. Specifically, using the calculated deviation, temperature difference, and previously generated safety voltage boundary value, perform table lookup or logical judgment operations through a preset piecewise linear mapping rule to evaluate the degree of power output capability loss of the target limiting module relative to the ideal state module. Quantize the evaluation result into a value less than or equal to one and determine it as the power limiting coefficient. This coefficient characterizes the proportion of current allowed to pass through the target limiting module at the current moment.

[0028] S23. Multiply the power limitation coefficient by the theoretical reference current value to obtain the corrected current value, and select the minimum value among all corrected current values ​​as the global limited reference current value. Specifically, multiply the determined power limitation coefficient by the theoretical reference current value corresponding to the total system power demand to obtain the corrected current value corresponding to the module. Perform the above operation on all modules to obtain a set of corrected current values. Compare the set of corrected current values ​​and select the minimum value among them. The selected minimum value is determined as the global limited reference current value of the entire battery pack in the current control cycle to ensure that the total current will not cause any single cell to exceed the safe range. The method provided in this embodiment, on the one hand, accurately locates the performance bottleneck in the battery pack by identifying the target limiting module with the lowest state of charge or the highest surface temperature and calculating the deviation and temperature difference, thereby providing a basis for differentiated power allocation; on the other hand, it determines the power limiting coefficient based on the deviation, temperature difference, and safe voltage boundary value, thereby quantifying the real-time power carrying capacity of each module and realizing fine control based on the state of individual cells; furthermore, it multiplies the power limiting coefficient by the theoretical reference current value to obtain the corrected current value and selects the minimum value as the global limited reference current value, thereby eliminating the bottleneck effect and ensuring that the battery pack operates within the safe current range and maximizes the usable capacity.

[0029] In some embodiments, determining the power limiting coefficient corresponding to the target limiting module based on the deviation, the temperature difference, and the safety voltage boundary value includes: S221. The deviation is compared with a preset state-of-charge deviation threshold to obtain a first ratio, and the temperature difference is compared with a preset temperature difference threshold to obtain a second ratio. Specifically, the calculated deviation is divided by the preset state-of-charge deviation threshold to obtain the first ratio, and the calculated temperature difference is divided by the preset temperature difference threshold to obtain the second ratio. The division operation converts the deviation and temperature difference, which have different dimensions, into dimensionless proportional values ​​for subsequent unified comparison and processing.

[0030] S212. Select the larger of the first ratio and the second ratio as the initial limit ratio, and determine whether the first difference between the upper limit of the safe charging voltage and the real-time terminal voltage of the target limiting module is less than a preset voltage margin. Specifically, compare the magnitudes of the first ratio and the second ratio, select the larger ratio as the initial limit ratio, calculate the difference between the upper limit of the safe charging voltage and the real-time terminal voltage of the target limiting module to obtain the first difference, and determine whether the first difference is less than a preset voltage margin value to determine the distance between the target limiting module and the safe voltage boundary.

[0031] S213. If the first difference is less than the preset voltage margin, the initial limiting ratio is multiplied by a preset derating factor to obtain an updated limiting ratio. If the first difference is greater than or equal to the preset voltage margin, the initial limiting ratio is directly determined as the updated limiting ratio. Specifically, if the judgment result is that the first difference is less than the preset voltage margin, it indicates that the target limiting module is close to the safety boundary. The initial limiting ratio is multiplied by the preset derating factor to obtain an updated limiting ratio to reduce power output. If the judgment result is that the first difference is greater than or equal to the preset voltage margin, it indicates that the target limiting module is far from the safety boundary. The initial limiting ratio is directly determined as the updated limiting ratio to maintain the current power level.

[0032] S214. The updated limiting ratio is determined as the power limiting coefficient corresponding to the target limiting module. Specifically, the updated limiting ratio obtained after the above logical judgment and calculation is directly assigned and determined as the power limiting coefficient corresponding to the target limiting module. This coefficient will serve as a key input parameter for subsequent calculation of the global limited reference current value, thereby realizing dynamic limiting of the power of the target limiting module.

[0033] The method provided in this embodiment, on the one hand, standardizes multidimensional state differences by comparing the deviation with a preset state of charge deviation threshold to obtain a first ratio and comparing the temperature difference with a preset temperature difference threshold to obtain a second ratio, thereby facilitating a unified assessment of the degree of inconsistency; on the other hand, it selects the larger value of the first ratio and the second ratio as the initial limiting ratio and judges the relationship between the voltage difference and the preset voltage margin, thereby comprehensively considering the state deviation and the voltage safety margin, and formulating a more conservative or aggressive initial limiting strategy; furthermore, it corrects the initial limiting ratio based on the comparison result of the voltage difference and the preset voltage margin to obtain an updated limiting ratio and determines it as the power limiting coefficient, thereby automatically reducing the power limit when approaching the safety boundary, thereby preventing the risk of overcharging due to voltage surges.

[0034] In some embodiments, determining the target execution current amplitude based on the global constrained reference current value, the health state value, and the state of charge value, and generating an optimal current time series curve containing the expected trajectory based on the target execution current amplitude, includes: S31. Calculate the aging compensation factor based on the health status value, and determine the segmented charging mode based on the state of charge value. Specifically, obtain the nominal capacity value in the new battery state, calculate the ratio of the health status value to the nominal capacity value to obtain the capacity decay ratio, determine the difference between the value and the capacity decay ratio as the aging compensation factor, and determine the value range of the state of charge value. If the state of charge value is in the low capacity range, determine the segmented charging mode as constant current charging mode; if the state of charge value is in the medium capacity range, determine the segmented charging mode as pulse charging mode; if the state of charge value is in the high capacity range, determine the segmented charging mode as constant voltage charging mode.

[0035] S32. Multiply the globally constrained reference current value by the aging compensation factor to obtain the target execution current amplitude. Specifically, the globally constrained reference current value generated in the previous step is multiplied by the calculated aging compensation factor. This operation scales the reference current to obtain the target execution current amplitude after considering battery aging factors. This amplitude reflects the maximum current intensity that the battery can actually safely withstand under its current healthy state.

[0036] S33. Based on the target execution current amplitude and the segmented charging mode, generate the optimal current timing curve and record the corresponding expected power change trajectory and expected temperature change trajectory. Specifically, using the target execution current amplitude as the base current value, and combining it with the determined logic rules of the segmented charging mode, plan the sequence of current changes over time within a fixed future time window to generate the optimal current timing curve that satisfies the constraints of minimizing the temperature rise rate and maximizing energy throughput. Simultaneously, calculate and record the expected power change trajectory and expected temperature change trajectory within the future time window based on this curve, serving as a reference standard for subsequent real-time control. The method provided in this embodiment, on the one hand, calculates an aging compensation factor based on the health status value and determines a segmented charging mode based on the state of charge value, thereby incorporating the battery aging degree and current charge state into the control strategy, and thus achieving adaptive switching of the charging mode; on the other hand, it multiplies the global limited reference current value with the aging compensation factor to obtain the target execution current amplitude, thereby automatically compensating for changes in current carrying capacity caused by capacity decay, and thus avoiding excessive current stress on the aging battery; furthermore, it generates an optimal current timing curve based on the target execution current amplitude and the segmented charging mode, and records the expected charge change trajectory and expected temperature change trajectory, thereby providing a forward-looking reference trajectory for real-time control, and thus improving the system's response capability and control accuracy to load fluctuations.

[0037] In some embodiments, calculating the aging compensation factor based on the health status value and determining the segmented charging mode based on the state of charge value includes: S311. Obtain the nominal capacity value in the new battery state, calculate the ratio of the health state value to the nominal capacity value to obtain the capacity decay ratio, and determine the difference between 1 and the capacity decay ratio as the aging compensation factor. Specifically, read the stored nominal capacity value in the new battery state, divide the real-time calculated health state value by the nominal capacity value to obtain the capacity decay ratio, subtract the capacity decay ratio from the value to obtain the difference, and determine the difference as the aging compensation factor. The value of this factor decreases as the battery ages, and is used to linearly adjust the current amplitude.

[0038] S312. Determine whether the state of charge (SOC) value is less than a first preset threshold. If the SOC value is less than the first preset threshold, then the current segmented charging mode is determined to be a constant current charging mode. Specifically, the real-time calculated SOC value is compared with the preset first preset threshold value. If the SOC value is less than the first preset threshold, it is determined that the battery is in a low-charge state, and the current segmented charging mode is marked as a constant current charging mode. In this mode, fast charging is performed with a constant current.

[0039] S313. If the state of charge (SOC) value is greater than or equal to the first preset threshold and less than the second preset threshold, the current segmented charging mode is determined to be a pulse charging mode. If the SOC value is greater than or equal to the second preset threshold, the current segmented charging mode is determined to be a constant voltage charging mode. Specifically, if the SOC value is greater than or equal to the first preset threshold and simultaneously less than the second preset threshold, the battery is determined to be in a medium charge state, and the current segmented charging mode is marked as a pulse charging mode. In this mode, a pulse current is used for restorative charging. If the SOC value is greater than or equal to the second preset threshold, the battery is determined to be in a high charge state, and the current segmented charging mode is marked as a constant voltage charging mode. In this mode, a constant voltage is maintained until charging is completed. The method provided in this embodiment, on the one hand, obtains the nominal capacity value and calculates the ratio of the health status value to the nominal capacity value to obtain the capacity decay ratio, and then determines the difference between 1 and the capacity decay ratio as the aging compensation factor, thereby quantifying the impact of battery aging on current carrying capacity; on the other hand, by judging the relationship between the state of charge value and the first preset threshold, a constant current charging mode is determined in the low power stage, thereby achieving rapid energy replenishment; furthermore, by judging the relationship between the state of charge value and the first preset threshold and the second preset threshold, a pulse charging mode and a constant voltage charging mode are determined in the medium and high power stages, respectively, thereby taking into account both charging speed and battery life protection.

[0040] In some embodiments, the step of collecting actual operating data and comparing it with the expected trajectory to obtain a deviation, adjusting control parameters based on the deviation and the optimal current timing curve, and generating a final control command includes: S41. During the control cycle, collect the actual operating current, actual state of charge (SBC) value, and actual temperature value; calculate the quantity deviation between the actual SBC value and the expected quantity change trajectory; and calculate the temperature deviation between the actual temperature value and the expected temperature change trajectory. Specifically, during each control cycle, read the actual operating current value, actual SBC value, and actual temperature value in real time. Subtract the actual SBC value from the previously recorded expected quantity change trajectory value at the same moment to obtain the quantity deviation; subtract the actual temperature value from the previously recorded expected temperature change trajectory value at the same moment to obtain the temperature deviation. These are used to measure the degree of deviation between the actual operating state and the planned trajectory.

[0041] S42. If the power deviation or temperature deviation exceeds a preset fault tolerance threshold, and the current charging mode is pulse charging, the ratio of the pulse current's on-time to off-time is adjusted according to the direction of the power deviation to update the pulse duty cycle. Specifically, it is determined whether the absolute value of the power deviation or temperature deviation exceeds the preset fault tolerance threshold. If it exceeds the threshold and the current segmented charging mode is pulse charging mode, the ratio of the pulse current's on-time to off-time is increased or decreased according to the positive or negative direction of the power deviation. The pulse duty cycle is updated by adjusting this ratio to correct the deviation in power or temperature.

[0042] S43. If the current mode is constant current or constant voltage, the target execution current amplitude is linearly fine-tuned according to the temperature deviation to obtain an adjusted current value. The final control command is generated based on the pulse duty cycle or the adjusted current value. Specifically, if the current segmented charging mode is constant current or constant voltage, the target execution current amplitude is linearly increased or decreased according to the magnitude of the temperature deviation to obtain an adjusted current value. If the current mode is pulse, the updated pulse duty cycle is used. If the current mode is constant current or constant voltage, the adjusted current value is used. The final control command is generated based on the selected parameters to drive the converter to perform actions. The method provided in this embodiment, on the one hand, collects actual operating data during the control cycle and calculates the deviation between the actual state of charge value and the expected charge change trajectory, as well as the deviation between the actual temperature value and the expected temperature change trajectory, thereby quantifying the degree of deviation between the operating state and the planned trajectory in real time, and thus providing error input for closed-loop control; on the other hand, if the deviation exceeds a preset fault tolerance threshold and the system is in pulse charging mode, the pulse duty cycle is adjusted according to the direction of the charge deviation, thereby dynamically balancing charging efficiency and temperature rise control in pulse mode, and thus suppressing state deviation; furthermore, if the system is in constant current mode or constant voltage mode, the target execution current amplitude is linearly fine-tuned according to the temperature deviation to obtain the adjusted current value and generate the final control command, thereby suppressing temperature anomalies through current fine-tuning in continuous charging mode, and thus ensuring that the battery always operates along the optimal trajectory.

[0043] Please see Figure 2 , Figure 2 This is a schematic diagram of a multi-objective coordinated charging and discharging system for an energy storage battery, provided as an embodiment of this application. Figure 2 As shown, the multi-target coordinated charging and discharging system 100 for energy storage batteries includes: The acquisition module 110 is used to acquire battery operating parameters and calculate the state of charge (SOC) and state of health (SOH) values, and generate a safe voltage boundary value based on the SOC, SOH, and operating parameters. The first generation module 120 is used to determine a power limiting coefficient based on the safe voltage boundary value, the SOC, and the operating parameters, and generate a globally limited reference current value based on the power limiting coefficient. The second generation module 130 is used to determine a target execution current amplitude based on the globally limited reference current value, the SOH value, and the SOC, and generate an optimal current timing curve containing the expected trajectory based on the target execution current amplitude. The third generation module 140 is used to collect actual operating data and compare it with the expected trajectory to obtain the deviation, adjust control parameters based on the deviation and the optimal current timing curve, and generate a final control command.

[0044] It should be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0045] It should also be understood that the term "and / or" as used in this specification and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations. It should be noted that, herein, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0046] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments. The above descriptions are merely specific implementations of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A multi-objective synergistic charging and discharging method for energy storage batteries, characterized in that, include: Obtain battery operating parameters and calculate state of charge and state of health values, and generate safe voltage boundary values ​​based on the state of charge, state of health values ​​and operating parameters; A power limiting factor is determined based on the safety voltage boundary value, the state of charge value, and the operating parameters. A global limited reference current value is generated based on the power limiting factor. A target execution current amplitude is determined based on the global limited reference current value, the health state value, and the state of charge value. An optimal current timing curve containing the expected trajectory is generated based on the target execution current amplitude. Actual operating data is collected and compared with the expected trajectory to obtain the deviation. Control parameters are adjusted based on the deviation and the optimal current timing curve to generate the final control command.

2. The multi-objective synergic charge and discharge method of the energy storage battery according to claim 1, characterized in that, The step of acquiring battery operating parameters and calculating state of charge (SOC) and state of health (SQH) values, and generating a safe voltage boundary value based on the SOC, SQH, and operating parameters, includes: The terminal voltage, surface temperature, and current flowing through a single cell are collected to calculate the state of charge (SOC) value and the state of health (SCH) value. A polarization voltage threshold is determined based on the SOC value, the SCH value, and the surface temperature. An upper limit for safe charging voltage and a lower limit for safe discharging voltage are generated based on the polarization voltage threshold and the terminal voltage, which serve as the safe voltage boundary values. 3.The multi-objective synergic charge and discharge method of the energy storage battery according to claim 1, characterized in that, The step of determining the power limitation factor based on the safety voltage boundary value, the state of charge value, and the operating parameters, and generating a globally limited reference current value based on the power limitation factor, includes: Identify the target limiting module with the lowest state of charge or the highest surface temperature, and calculate the deviation and temperature difference between the target limiting module and the average state. Determine the power limiting coefficient corresponding to the target limiting module based on the deviation, the temperature difference, and the safe voltage boundary value. Multiply the power limiting coefficient by the theoretical reference current value to obtain the corrected current value, and select the minimum value among all corrected current values ​​as the global limiting reference current value.

4. The multi-objective synergic charge and discharge method of the energy storage battery according to claim 3, characterized in that, Determining the power limiting coefficient corresponding to the target limiting module based on the deviation, the temperature difference, and the safety voltage boundary value includes: The deviation is compared with a preset state-of-charge deviation threshold to obtain a first ratio, and the temperature difference is compared with a preset temperature difference threshold to obtain a second ratio. The larger of the first ratio and the second ratio is selected as the initial limiting ratio, and it is determined whether the first difference between the upper limit of the safe charging voltage and the real-time terminal voltage of the target limiting module is less than a preset voltage margin. If the first difference is less than the preset voltage margin, the initial limiting ratio is multiplied by a preset derating factor to obtain an updated limiting ratio. If the first difference is greater than or equal to the preset voltage margin, the initial limiting ratio is directly determined as the updated limiting ratio. The updated limiting ratio is determined as the power limiting coefficient corresponding to the target limiting module.

5. The multi-objective synergic charge and discharge method of energy storage battery according to claim 1, characterized in that, The step of determining the target execution current amplitude based on the global constrained reference current value, the health state value, and the state of charge value, and generating an optimal current time series curve containing the expected trajectory based on the target execution current amplitude, includes: The aging compensation factor is calculated based on the health status value, and the segmented charging mode is determined based on the state of charge value; the target execution current amplitude is obtained by multiplying the global limited reference current value by the aging compensation factor; the optimal current timing curve is generated based on the target execution current amplitude and the segmented charging mode, and the corresponding expected power change trajectory and expected temperature change trajectory are recorded.

6. The multi-objective synergic charge and discharge method of the energy storage battery according to claim 4, characterized in that, The step of calculating the aging compensation factor based on the health status value and determining the segmented charging mode based on the state of charge value includes: Obtain the nominal capacity value of the new battery state, calculate the ratio of the health state value to the nominal capacity value to obtain the capacity decay ratio, and determine the difference between 1 and the capacity decay ratio as the aging compensation factor; determine whether the state of charge value is less than a first preset threshold. If the state of charge value is less than the first preset threshold, then determine the current segmented charging mode as a constant current charging mode; if the state of charge value is greater than or equal to the first preset threshold and less than a second preset threshold, then determine the current segmented charging mode as a pulse charging mode; if the state of charge value is greater than or equal to the second preset threshold, then determine the current segmented charging mode as a constant voltage charging mode.

7. The multi-objective synergic charge and discharge method of energy storage battery according to claim 1, characterized in that, The process involves collecting actual operating data and comparing it with the expected trajectory to obtain the deviation. Based on the deviation and the optimal current timing curve, control parameters are adjusted to generate the final control command, including: During the control cycle, the actual operating current, actual state of charge (SOC), and actual temperature are collected. The SOC deviation between the actual SOC and the expected SOC change trajectory is calculated, and the temperature deviation between the actual temperature and the expected temperature change trajectory is also calculated. If the SOC or temperature deviation exceeds a preset fault tolerance threshold and the current mode is pulse charging, the ratio of the pulse current's on-time to off-time is adjusted according to the direction of the SOC deviation to update the pulse duty cycle. If the current mode is constant current or constant voltage, the target execution current amplitude is linearly fine-tuned according to the temperature deviation to obtain an adjusted current value. The final control command is generated based on the pulse duty cycle or the adjusted current value.

8. A multi-target coordinated charging and discharging system for energy storage batteries, characterized in that, include: The acquisition module is used to acquire battery operating parameters and calculate the state of charge value and state of health value, and generate a safe voltage boundary value based on the state of charge value, the state of health value and the operating parameters; The first generation module is used to determine the power limiting coefficient based on the safety voltage boundary value, the state of charge value and the operating parameters, and generate a global limited reference current value based on the power limiting coefficient. The second generation module is used to determine the target execution current amplitude based on the global constrained reference current value, the health state value and the state of charge value, and to generate an optimal current time series curve containing the expected trajectory based on the target execution current amplitude. The third generation module is used to collect actual operating data and compare it with the expected trajectory to obtain the deviation amount, adjust the control parameters according to the deviation amount and the optimal current timing curve, and generate the final control command.

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