Battery pulse repairing method and related equipment

Abstract

The invention relates to the technical field of battery management, and particularly discloses a battery pulse repair method and related equipment, and the method comprises the steps: S1, obtaining a repair task instruction issued by a remote management terminal; s2, evaluating whether the current environment meets the condition of executing the repair task instruction according to the site environment data, and if yes, executing the step S3; s3, calculating and outputting a pulse parameter to be applied at the current moment based on a local control algorithm module, and performing pulse repair on the to-be-repaired battery pack based on the pulse parameter; s4, recording process data and a repair result of pulse repair, and associating the task ID; s5, when a communication link with the remote management terminal is unblocked, process data and a repair result are uploaded to the remote management terminal in a subpackage mode based on the task ID; according to the method, the self-adaptive dynamic repair of the battery is realized, the pertinence and effectiveness of pulse repair are improved, and the remote management terminal is ensured to obtain complete repair process and result data.

Description

Technical Field

[0001] This application relates to the technical field of battery management. Specifically, it relates to a battery pulse repair method and related equipment. Background Art

[0002] In the context of centralized electric bicycle charging stations and large-scale operation of shared electric bicycles, the health management of battery packs faces multiple technical challenges. The urban site environment shows significant heterogeneity: underground sites have long-term problems of low temperature and high humidity, open-air sites face extreme temperature fluctuations, and indoor sites are affected by electromagnetic interference. This environmental difference leads to the initial state of the battery pack returning to the site showing multi-dimensional discreteness, including differences in remaining power, monomer voltage drift, uneven internal resistance distribution, and hidden damage (such as low-temperature crystallization and mechanical stress damage) caused by different usage scenarios.

[0003] The existing remote management terminal is the core of the battery management system. It collects battery data through the Internet of Things, uses data analysis algorithms to evaluate the battery health status, identifies the battery packs that need pulse repair, analyzes the types of health problems, and generates customized pulse repair plans, and then sends instructions to the site automatic repair equipment through the Internet of Things. However, the repair process of the battery pack shows strong dynamic characteristics. The response of parameters such as battery temperature and internal resistance under the action of pulses has non-linear time-varying characteristics, and the static parameter sequence relying on the remote management terminal cannot adapt to this dynamic change, resulting in problems such as insufficient repair.

[0004] More severely, the massive state data (including voltage / current / temperature time series and pulse response characteristics) generated during the repair process cannot be reliably transmitted back during communication interruption, resulting in the management terminal being difficult to build a complete battery health file, forming a data island, and affecting the management terminal's evaluation of the repair effect and the optimization of future strategies.

[0005] In response to the above problems, there is currently no effective technical solution. Summary of the Invention

[0006] The purpose of this application is to provide a battery pulse repair method and related equipment to achieve the adaptive dynamic repair of the battery, improve the pertinence and effectiveness of pulse repair, and ensure that the data generated during the repair process can be uploaded to the remote management terminal.

[0007] In a first aspect, this application provides a battery pulse repair method, which is applied in a charging station. The method includes the following steps: S1. Obtain the repair task instruction issued by the remote management terminal. The repair task instruction includes a task ID, a macroscopic repair target, and a repair strategy; S2. Collect site environmental data based on local sensors, and evaluate whether the current environment meets the conditions for executing the repair task instruction according to the site environmental data. If it meets the conditions, execute step S3; S3. According to the macroscopic repair target and the repair strategy, combined with the battery dynamic parameters of the battery pack to be repaired collected in real time by local sensors, calculate and output the pulse parameters to be applied at the current moment based on the local control algorithm module, so as to perform pulse repair on the battery pack to be repaired based on the pulse parameters; S4. Record the process data and repair results of the pulse repair, and associate the task ID; S5. When the communication link with the remote management terminal is unobstructed, upload the process data and repair results in packets to the remote management terminal based on the task ID.

[0008] The battery pulse repair method of the present application outputs the current optimal pulse parameters according to the macroscopic repair target and the repair strategy combined with the real-time collected battery dynamic parameters to repair the battery pack to be repaired in a reliable environment, realizing the adaptive dynamic repair of the battery, significantly improving the pertinence and effectiveness of the pulse repair. Secondly, the method also records the process data and repair results and uploads them when the communication is unobstructed, ensuring that the remote management terminal can obtain the complete repair process and result data, which is conducive to accurate repair effect evaluation and future strategy optimization.

[0009] In the battery pulse repair method described above, step S2 includes: Collect the battery initial state data and site environmental data of the battery pack to be repaired based on local sensors, and evaluate whether the current environment and battery state meet the conditions for executing the repair task instruction according to the battery initial state data and the site environmental data. If it meets the conditions, execute step S3; otherwise, delay or reject the execution of step S3, and record the reason.

[0010] By adding condition evaluation and judgment before the repair starts, the method of the present application can avoid repairing under unfavorable conditions.

[0011] In the battery pulse repair method described above, during the execution of the pulse repair in step S3, the method further includes the steps of: SA. Collect and monitor whether the key battery parameters exceed the preset safety threshold based on local sensors. If they exceed, trigger the safety protection action.

[0012] In the battery pulse repair method described above, the setting process of the safety threshold includes: SA1. Obtain the battery type; SA2. Infer the repair stage according to the current pulse parameters; SA3. Extract the safety threshold from a pre - constructed safety threshold library according to the battery type and the repair stage.

[0013] The battery pulse repair method described above, wherein step SA2 includes: According to the current pulse parameters, combined with the preset mapping relationship between the battery repair stage and the pulse parameters, determine the repair stage to which the current pulse parameters belong.

[0014] The battery pulse repair method described above, wherein the process data includes the pulse parameter sequence during the pulse repair process and the change curve of the key battery parameters among the battery dynamic parameters; the repair result includes the repair duration and the battery health assessment results before and after the pulse repair.

[0015] The battery pulse repair method described above, wherein step S3 includes: S31. According to the macroscopic repair target and the repair strategy, call the adaptive mapping relationship model in the local control algorithm module, and the adaptive mapping relationship model is used to map the pairing relationship between the battery dynamic parameters and the pulse parameters; S32. Repeat the following steps until the pulse repair of the battery pack to be repaired is completed: S321. Based on the local sensor, monitor and obtain the battery dynamic parameters of the battery pack to be repaired in real - time; S322. Based on the adaptive mapping relationship model, calculate the reference pulse parameters to be applied currently according to the battery dynamic parameters; S323. Perform pulse repair on the battery pack to be repaired based on the pulse parameters smoothly adjusted according to the reference pulse parameters.

[0016] The battery pulse repair method described above, wherein step S31 includes: S311'. Obtain the current battery quality assessment result according to the macroscopic repair target, and the current battery quality assessment result is sent by the remote management terminal or generated by the local assessment module, and is the quality result of the repair index associated with the macroscopic repair target; S312'. According to the macroscopic repair target and the repair strategy, combined with the interval where the current battery quality assessment result is located, select the corresponding adaptive mapping relationship model from the preset adaptive mapping relationship model library.

[0017] In a second aspect, the present application also provides an electronic device, including a processor and a memory, where the memory stores computer - readable instructions, and when the computer - readable instructions are executed by the processor, the steps in the method provided in the first aspect above are run.

[0018] In a third aspect, the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it runs the steps in the method provided in the first aspect as described above.

[0019] As can be seen from the above, the present application provides a battery pulse repair method and related devices. Among them, the battery pulse repair method of the present application outputs the current optimal pulse parameters according to the macroscopic repair target and repair strategy combined with the real-time collected battery dynamic parameters to repair the battery pack to be repaired under the condition of reliable environment, realizing the adaptive dynamic repair of the battery, significantly improving the pertinence and effectiveness of the pulse repair. Secondly, the method also records the process data and repair results and uploads them when the communication is smooth, ensuring that the remote management terminal can obtain the complete repair process and result data, which is conducive to accurate repair effect evaluation and future strategy optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a flowchart of the battery pulse repair method provided by some embodiments of the present application.

[0021] Figure 2 It is a schematic structural diagram of the battery pulse repair method provided by some other embodiments of the present application.

[0022] Figure 3 It is a schematic structural diagram of the electronic device provided by the embodiment of the present application.

[0023] Reference numerals: 201, processor; 202, memory; 203, communication bus. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0024] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and illustrated herein can be arranged and designed in various different configurations. Therefore, the detailed description of the embodiments of the present application provided in the drawings below is not intended to limit the scope of the present application claimed, but merely represents the selected embodiments of the present application. All other embodiments obtained by those skilled in the art based on the embodiments of the present application without creative efforts belong to the scope of protection of the present application.

[0025] It should be noted that: similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of the present application, the terms "first", "second", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0026] In a first aspect, please refer to Figure 1 and Figure 2 . Some embodiments of the present application provide a battery pulse repair method, which is applied in a charging station. The method includes the following steps: S1. Obtain a repair task instruction sent by a remote management terminal. The repair task instruction includes a task ID, a macroscopic repair target, and a repair strategy; S2. Collect site environment data based on local sensors, and evaluate whether the current environment meets the conditions for executing the repair task instruction according to the site environment data. If it meets, execute step S3; S3. According to the macroscopic repair target and the repair strategy, combined with the battery dynamic parameters of the battery pack to be repaired collected in real time by local sensors, calculate and output the pulse parameters to be applied at the current moment based on the local control algorithm module, so as to perform pulse repair on the battery pack to be repaired based on the pulse parameters; S4. Record the process data and repair results of the pulse repair, and associate the task ID; S5. When the communication link with the remote management terminal is unobstructed, upload the process data and repair results to the remote management terminal in packets based on the task ID.

[0027] Specifically, in step S1, the method of the present application receives a repair task instruction sent by a remote management terminal. The instruction carries the unique identifier (task ID) of the task, the macroscopic repair target to be achieved, and the selected repair strategy. This enables the repair tasks to be uniformly scheduled and managed by the remote management terminal. The task ID facilitates subsequent data traceability and association, and the macroscopic repair target and repair strategy provide directions and constraints for local execution.

[0028] More specifically, in step S2, the method of the present application collects the site environment data of the charging station through locally deployed sensors. The site environment data may include environmental temperature and humidity. Step S2 also evaluates whether the current environment meets the conditions for executing the repair task instruction according to the site environment data. This takes into account the complexity of the charging station environment, avoids repairing the battery in an adverse environment, and ensures the repair effect and safety.

[0029] More specifically, during the execution of the pulse repair process, step S3 continuously monitors the battery dynamic parameters of the battery pack in real time through local sensors. These parameters reflect the real-time response of the battery under the action of the pulse. The battery dynamic parameters may include data such as the change rate of the battery temperature, the real-time numerical change of the internal resistance, the fluctuation of the monomer voltage, and the response characteristics to the applied current pulse. Then, based on these real-time dynamic parameters, step S3 combines the macroscopic repair target and repair strategy sent remotely, and dynamically calculates and adjusts the pulse parameters to be applied at the current moment (such as the amplitude, width, frequency, duty cycle, etc. of the pulse) locally using the control algorithm module. This local control method based on real-time dynamic feedback can accurately adapt to the non-linear time-varying response of the battery under the action of the pulse, overcomes the defect that the remote static parameters in the background art cannot adapt to the dynamic changes, and significantly improves the pertinence and effectiveness of the pulse repair.

[0030] More specifically, step S4 records the process data and repair results of the pulse repair and associates them with the task ID. During the repair process, the process data such as the battery dynamic parameters collected in real time and the applied pulse parameters, as well as the final repair results (such as the repair duration and the battery health assessment before and after the repair) are recorded locally. By associating the task ID, it is ensured that these data correspond to a specific repair task, providing a basis for subsequent data management and transmission.

[0031] More specifically, when the communication link with the remote management terminal is unobstructed, step S5 uploads the process data and repair results to the remote management terminal in packets based on the task ID, which solves the problem of unreliable communication. The data is not forced to be uploaded in real time in case of possible communication interruption, but is uploaded in packets in a manner associated with the task ID when the communication link is confirmed to be unobstructed. This mechanism ensures that even in an environment with unstable communication, the repair data can be reliably saved and completely transmitted back to the remote management terminal when conditions permit, avoiding data loss, enabling the remote management terminal to build a complete battery health file, conduct accurate repair effect evaluation, and optimize future strategies.

[0032] More specifically, the battery pulse repair method according to the embodiments of the present application solves the problems that the battery pulse repair parameters cannot be dynamically adjusted according to the battery state and the repair data transmission is unreliable. First, the remote management terminal generates a repair task instruction including a task ID, a macroscopic repair target, and a repair strategy based on the remote diagnosis of the battery pack, and sends it to the local repair device at the charging station through the communication network. The local repair device receives and parses the instruction. Before the repair execution, the local sensor collects the site environment data to determine whether the current environment state is suitable for performing the battery repair. Then, when the environment is suitable for battery repair, the local sensor collects the dynamic response parameters of the battery pack under the action of the pulse in real time and continuously. These dynamic parameters directly reflect the current internal state of the battery and its response to the repair pulse. The local control algorithm module uses these real-time dynamic parameters as inputs, combines the macroscopic repair target and repair strategy set remotely, performs real-time calculation and adjustment, and outputs the current optimal pulse parameters. Thus, the applied pulse parameters can be adaptively adjusted according to the actual dynamic changes of the battery, avoiding the problems of insufficient or excessive repair caused by using a static parameter sequence, and improving the effectiveness of the repair. During the repair process, step S4 is responsible for locally storing the process data of the battery repair and the final repair result, and associating them with the task ID to ensure the integrity of the data. Even if a communication interruption occurs during the repair process, the data will not be lost. Step S5 solves the problem of reliable data backhaul. When it is detected that the communication link with the remote management terminal is unobstructed, the locally stored repair data will be packetized according to the task ID and actively uploaded to the remote management terminal to ensure that the remote management terminal can obtain the complete repair process and result data for building a battery health file and optimizing future repair strategies.

[0033] The battery pulse repair method according to the embodiments of the present application repairs the battery pack to be repaired by outputting the current optimal pulse parameters according to the macroscopic repair target and repair strategy in combination with the real-time collected battery dynamic parameters under reliable environmental conditions, realizing the adaptive dynamic repair of the battery, significantly improving the pertinence and effectiveness of the pulse repair. Secondly, the method also records the process data and the repair result and uploads them when the communication is unobstructed, ensuring that the remote management terminal can obtain the complete repair process and result data for accurate repair effect evaluation and future strategy optimization.

[0034] It should be noted that the local sensor may include common sensors such as a temperature sensor, a humidity sensor, a voltage acquisition module, an internal resistance test module, and a coulomb meter for collecting and obtaining corresponding data.

[0035] In some preferred embodiments, step S2 includes: Collect the initial battery state data and site environment data of the battery pack to be repaired based on local sensors, and evaluate whether the current environment and battery state meet the conditions for executing the repair task instruction according to the initial battery state data and site environment data. If they meet, execute step S3; otherwise, delay the execution of step S3 or reject the execution of step S3 and record the reason.

[0036] Specifically, the above steps are used to evaluate the current environmental conditions and the initial state of the battery pack to be repaired before starting the actual pulse repair. The process is mainly based on the initial battery state data and site environment data collected by local sensors to determine whether these conditions are suitable for executing the repair task instruction issued by the remote management terminal. If the evaluation result shows that the current conditions meet the requirements for executing the repair task, the method continues to execute the subsequent pulse parameter calculation and repair steps. If the evaluation result shows that the current conditions do not meet the requirements, the method will not immediately execute the subsequent repair steps, but instead choose to delay the execution or reject the execution of the subsequent repair steps and record the reason for non-execution. By adding condition evaluation and judgment before the repair starts, the method of the present application can avoid performing repairs under adverse conditions.

[0037] More specifically, the initial battery state data may include data such as the current temperature, single-cell voltage, overall internal resistance, and remaining charge.

[0038] Specifically, after receiving the repair task instruction issued by the remote management terminal, the local system first collects the site environment data based on local sensors, such as the environmental temperature and humidity. At the same time, it collects the initial battery state data of the battery pack to be repaired, such as the current temperature, single-cell voltage, overall internal resistance, and remaining charge. Before performing the actual pulse repair steps, use the collected initial battery state data and site environment data to evaluate whether the current environment and battery state meet the requirements for executing this repair task instruction. The evaluation process is carried out according to preset rules or algorithms, which take into account environmental factors (such as whether the temperature is within the appropriate range) and battery state factors (such as whether the initial internal resistance is too high). If the evaluation result determines that the current conditions are suitable for repair, the system is allowed to continue executing the subsequent pulse parameter calculation and pulse repair operations. If the evaluation result determines that the current conditions are not suitable, for example, the environmental temperature is too low or the initial state of the battery is abnormal, the system will not immediately perform the repair, but will choose to re-evaluate after a certain delay according to the evaluation result, or directly reject the execution of this repair task and record the reason for non-execution. Thus, it avoids ineffective or potentially harmful repair attempts under unsuitable conditions and improves the effectiveness and safety of the repair process.

[0039] In some preferred embodiments, step S2 includes: S21. Determine the applicable range of health level and the applicable range of environment level based on the macroscopic repair goal and repair strategy; S22. Calculate and obtain the battery health level based on the initial battery state data, and calculate and obtain the environmental adaptability level based on the site environment data; S23. Determine whether the battery health level is within the applicable range of health level. If so, execute step S24; otherwise, reject the execution of step S3. S24. Determine whether the environmental adaptability level is within the applicable range of environment level. If so, execute step S3; otherwise, after a preset delay, return to step S22 based on the re - collected site environment data.

[0040] Specifically, in the above - mentioned processing steps, the macroscopic repair goal and repair strategy are used to set the applicable ranges of battery health level and environmental conditions, providing a judgment basis for subsequent evaluations. Among them, the initial battery state data and site environment data are used to calculate the current health level of the battery pack to be repaired and the environmental adaptability level of the site environment. The battery health level is compared with the applicable range of health level to decide whether to continue evaluating environmental conditions or directly reject the repair. The environmental adaptability level is compared with the applicable range of environment level to decide whether to immediately execute the repair, re - evaluate after a delay, or reject the repair.

[0041] More specifically, after receiving the repair task instruction, step S21 determines the range of battery health levels and the range of site environmental adaptability levels suitable for executing the task according to the macroscopic repair goal and repair strategy in the instruction. Then, step S23 determines whether the calculated battery health level falls within the preset applicable range of health level. If it is not within the range, it is considered that the battery state is not suitable for the current repair task, and the subsequent pulse repair steps are rejected, and the reason for rejection is recorded. If the battery health level is within the applicable range, it is further determined whether the calculated environmental adaptability level falls within the preset applicable range of environment level. If the environmental adaptability level is not within the range, the pulse repair is not immediately executed. Instead, after waiting for a preset period of time, the site environment data is re - collected, and the process returns to the step of recalculating the environmental adaptability level for re - evaluation. If the environmental adaptability level is within the applicable range, it is considered that both the current environment and battery state meet the conditions for executing the repair task, and the pulse repair step is started. Through this series of judgments, it is ensured that the pulse repair is carried out under suitable battery states and environmental conditions, avoiding ineffective operations and improving the repair efficiency.

[0042] In some preferred embodiments, as Figure 2 shown, during the execution of the pulse repair in step S3, the method further includes the step: SA. Based on the local sensor, collect and monitor whether the key battery parameters exceed the preset safety threshold. If so, trigger the safety protection action.

[0043] Specifically, the key battery parameters may include one or more of battery temperature, cell voltage, total voltage, and total current. The preset safety threshold defines the safe operating range of the battery under different conditions. The safety threshold can be set according to the battery type and the current repair stage.

[0044] More specifically, during the pulse repair process, the battery parameters show dynamic changes. The response under the pulse has non-linear time-varying characteristics, and there is a risk that the key battery parameters exceed the safety range, which may cause battery damage or safety risks. To solve this problem, a safety monitoring step is executed in parallel during the pulse repair process. Step SA compares the collected key battery parameters with the corresponding safety thresholds to determine whether the battery state is within the safe range. If any of the key battery parameters exceeds the corresponding safety threshold, it indicates that the battery may be in a dangerous state. At this time, the system will immediately trigger a safety protection action. The safety protection action may include stopping the pulse repair, reducing the pulse intensity, or disconnecting the circuit connection, etc., aiming to prevent the battery from being damaged or causing a safety accident due to overheating, overvoltage, overcurrent, etc. Real-time collection and monitoring of the key battery parameters provide dynamic safety guarantee data; the preset safety threshold defines the boundary of safe operation; triggering the safety protection action when exceeding the threshold provides an immediate risk response mechanism. These technical features work together to ensure the safe progress of the pulse repair process and avoid potential dangers.

[0045] In some preferred embodiments, the safety threshold is set based on the battery type and the repair stage.

[0046] Specifically, the safety threshold is set based on the battery type to ensure that the threshold matches the different battery chemical characteristics. The safety threshold is set based on the repair stage to make the threshold adapt to the electrical characteristics of different periods of the pulse repair process. The method of the present application improves the adaptability of safety monitoring by combining the battery type and the repair stage to set the safety threshold.

[0047] More specifically, during the repair process, the method of the present application determines the repair stage to which the current pulse parameters belong according to the current pulse parameters in combination with the preset mapping relationship between the battery repair stage and the pulse parameters. Subsequently, the corresponding safety threshold is extracted from the pre-constructed safety threshold library. Thus, the setting of the safety threshold can accurately match the battery characteristics and the repair process, ensuring the safety of the battery during the pulse repair process.

[0048] In some preferred embodiments, the process of setting the safety threshold includes: SA1. Obtain the battery type; SA2. Infer the repair stage according to the current pulse parameters; SA3. Extract the safety threshold from a pre-built safety threshold library according to the battery type and the repair stage.

[0049] Specifically, step SA1 of obtaining the type of the battery to be repaired is the basic information for setting the safety threshold. Different types of batteries have different safety characteristics and parameter ranges. Step SA2 infers the current repair stage based on the currently applied pulse parameters. Pulse parameters are usually adjusted during the repair process according to the repair strategy and the battery state. Different combinations of pulse parameters or variation rules correspond to different stages of the repair process. By analyzing the current pulse parameters, it can be determined which stage the repair process has reached, such as the initial activation stage, the capacity recovery stage, or the performance optimization stage. Step SA3 combines the battery type obtained in SA1 and the repair stage inferred in SA2 to search for and extract the corresponding safety threshold from a pre-built safety threshold library. This safety threshold library stores the safety thresholds to be adopted for different battery types at different repair stages. For example, for a certain type of lithium-ion battery, the temperature safety threshold may be set to a lower value during the initial activation stage, while the voltage safety threshold may be set to a higher value during the capacity recovery stage. Through the above steps, the safety threshold can be adjusted according to the battery type and the dynamic stage of the repair. Thus, the safety monitoring threshold can be dynamically adjusted according to the actual progress of the repair, the safety monitoring is more accurate, and potential safety risks can be identified more effectively at different repair stages, thereby triggering corresponding safety protection actions and improving the safety of the repair process.

[0050] In some preferred embodiments, step SA2 includes: Determine the repair stage to which the current pulse parameter belongs according to the current pulse parameter in combination with the preset mapping relationship between the battery repair stage and the pulse parameter.

[0051] Specifically, the above processing method pre-establishes a mapping relationship associating different sets of pulse parameters with specific battery repair stages to identify the repair stage corresponding to the current pulse parameter according to the current pulse parameter, so as to accurately determine the repair stage, providing basic information for extracting the safety threshold according to the battery type and the repair stage later, ensuring that the setting of the safety threshold matches the current repair state, and improving the accuracy of the safety threshold setting.

[0052] In some preferred embodiments, the key battery parameters include battery temperature, single-cell voltage, total voltage, and total current.

[0053] Specifically, among these key battery parameters, the battery temperature is a direct indicator reflecting the internal thermal state of the battery. An abnormal increase in it is a precursor to thermal runaway. The cell voltage reflects the working state of each battery cell in the battery pack, the total voltage reflects the overall voltage level of the entire battery pack, and the total current reflects the magnitude of the charge and discharge current of the battery pack. Therefore, monitoring the battery temperature can detect overheating risks in a timely manner, monitoring the cell voltage can identify problems such as overcharging, over-discharging, or cell imbalance, which may lead to a decline in battery performance or even safety accidents. Monitoring the total voltage can determine whether the battery pack is within the normal voltage range, and monitoring the total current can prevent overcurrent from damaging the battery. Thus, determining these parameters as key parameters ensures comprehensive monitoring of the core safety state of the battery during the pulse repair process, ensuring that the battery always operates within a safe range during the pulse repair process and effectively reducing safety risks caused by repair operations or abnormal conditions of the battery itself.

[0054] In some preferred embodiments, the battery dynamic parameters include the battery temperature change rate, internal resistance change data, cell voltage fluctuation, and current response characteristics during the repair process.

[0055] Specifically, the battery temperature change rate reflects the thermal effect rate of the battery under the action of pulses. The internal resistance change data monitors the real-time improvement or deterioration trend of the internal state of the battery. The cell voltage fluctuation reveals the dynamic performance of the consistency or abnormality of the cells inside the battery pack. The current response characteristics reflect the instantaneous response characteristics of the battery to the pulsed current, such as the response time or waveform distortion. These parameters are collected in real time by local sensors and provide dynamic feedback information on the battery during the repair process for the local control algorithm.

[0056] More specifically, in view of the strong dynamic characteristics and non-linear time-varying response during the battery pack repair process, this solution uses the battery temperature change rate, internal resistance change data, cell voltage fluctuation, and current response characteristics during the repair process as inputs to the local control algorithm. The local control algorithm module calculates and outputs the pulse parameters to be applied at the current moment based on these real-time dynamic parameters. For example, when the battery temperature change rate is too high, the algorithm can adjust the pulse parameters to reduce the thermal effect; when the internal resistance change data shows an improving trend, the algorithm can optimize the pulse parameters to accelerate the repair process; when the cell voltage fluctuation increases, the algorithm can adjust the pulse parameters to improve cell consistency; when the current response characteristics are abnormal, the algorithm can trigger adjustments or pauses. Thus, the pulse parameters calculated based on these dynamic parameters can adapt to the actual state of the battery during the repair process in real time, overcome the limitations of relying on static parameter sequences, improve the effectiveness and adaptability of pulse repair, and solve problems such as insufficient repair.

[0057] More specifically, the battery temperature change rate can be obtained by continuously collecting the battery temperature during the repair process and calculating the ratio of the temperature difference between adjacent time points to the time interval. The internal resistance change data can be obtained by measuring the voltage and current responses of the battery under the action of a specific pulse or test signal, calculating the internal resistance value, and recording its change sequence over time. The monomer voltage fluctuation can be measured by calculating the maximum difference or standard deviation of the monomer voltage by real-time monitoring the voltage of each monomer in the battery pack. The current response characteristics can be analyzed by collecting the current waveform during the pulse current application and analyzing characteristic parameters such as its rising edge, falling edge, plateau time, or distortion degree.

[0058] In some preferred embodiments, the process data includes the pulse parameter sequence during the pulse repair process and the change curve of the battery key parameters among the battery dynamic parameters; the repair result includes the repair duration and the battery health assessment results before and after the pulse repair.

[0059] Specifically, recording these data provides detailed information on the repair process, including the applied stimuli and the real-time response of the battery. Uploading these data enables the remote management terminal to obtain complete repair event information for evaluation and optimization.

[0060] More specifically, the recorded process data includes the time series of each set of pulse parameters (e.g., pulse voltage, pulse width, pulse frequency, duty cycle, etc.) calculated and applied by the local control algorithm module during the repair process. At the same time, the real-time numerical values or change curves of the key battery parameters among the battery dynamic parameters collected in real-time by the local sensor are also recorded, forming a time-synchronized data stream corresponding to the pulse parameter sequence. The change curves of these dynamic parameters reflect the instantaneous and cumulative responses of the battery under specific pulse stimuli. After the repair is completed, the local device records the duration of the entire pulse repair operation as the repair duration. In addition, before and after the pulse repair operation, a health assessment of the battery pack is performed, such as measuring the overall internal resistance, evaluating the capacity, or conducting other diagnostic tests, and the health assessment results before and after the repair are recorded. All these recorded data, including the pulse parameter sequence, the dynamic parameter change curve, the repair duration, and the health assessment results before and after the repair, are associated with the received task ID. The local device continuously monitors the communication link status with the remote management terminal. Once it detects that the communication link is unobstructed, the local device organizes the stored process data and repair results associated with the completed task according to the task ID and uploads them in sub-packages to the remote management terminal. By uploading these comprehensive and specific data, the remote management terminal can understand in detail the execution details of each repair task, the specific reactions of the battery during the repair process, and the final achieved repair effect. The combination of the pulse parameter sequence and the dynamic parameter change curve enables the remote terminal to analyze the impact of different pulse strategies on the battery dynamic behavior. The repair duration and the health assessment results directly quantify the efficiency and effectiveness of the repair. These data together construct a complete battery health profile and provide a basis for the remote management terminal to conduct strategy analysis, optimization, and adjustment based on the actual repair data, solving the problem of difficult remote assessment and strategy optimization caused by unclear or incomplete data.

[0061] In some preferred embodiments, the macroscopic repair objectives are at least classified into the percentage reduction of internal resistance, the target capacity recovery rate, and the upper limit of the repair duration; the repair strategies are at least classified into the polarization suppression strategy and the dendrite dissolution strategy.

[0062] Specifically, the macroscopic repair objectives are specifically defined as indicators such as the percentage reduction of internal resistance, the target capacity recovery rate, and the upper limit of the repair duration, setting quantifiable endpoints or limits for the repair task. The repair strategies are specifically defined as methods such as the polarization suppression strategy and the dendrite dissolution strategy, providing the technical directions for the local control algorithm to perform the repair. These classifications and definitions make the instruction content issued by the remote management terminal structured, enabling the local system to accurately identify the repair objectives and the basic technical paths to be adopted.

[0063] More specifically, the percentage reduction in internal resistance sets a quantitative target for internal resistance improvement. The target capacity recovery rate sets a quantitative target for capacity increase. The upper limit of the repair duration sets a time limit for the repair process. The polarization suppression strategy guides the system to adopt pulse waveforms and parameters suitable for reducing battery polarization. The dendrite dissolution strategy guides the system to adopt pulse waveforms and parameters suitable for dissolving dendrites.

[0064] More specifically, when the remote management terminal issues a repair task instruction containing a task ID, a macroscopic repair target, and a repair strategy, the local system receives and parses the instruction. Based on the macroscopic repair target (e.g., the percentage reduction in internal resistance) and the repair strategy (e.g., the polarization suppression strategy) clearly specified in the instruction, the local control algorithm module can accurately understand the intention of the remote instruction. The local control algorithm module combines the dynamically acquired battery parameters collected in real time and, based on the understanding of the macroscopic target and the repair strategy, calculates the pulse parameters to be applied at the current moment. For example, if the macroscopic target is to reduce the internal resistance and the strategy is polarization suppression, the algorithm will first adjust the pulse parameters to optimize the effect of internal resistance reduction and adopt a pulse waveform that is conducive to suppressing polarization. This specific definition of the target and strategy improves the execution accuracy of the local system for the instruction, enabling the local control algorithm to more effectively adjust the pulse parameters according to the dynamically changing battery state, thereby enhancing the pertinence and effectiveness of the dynamic pulse repair process.

[0065] In some preferred embodiments, step S3 includes: S31. According to the macroscopic repair target and the repair strategy, call the adaptive mapping relationship model in the local control algorithm module. The adaptive mapping relationship model is used to map the pairing relationship between the battery dynamic parameters and the pulse parameters; S32. Repeat the following steps until the pulse repair of the battery pack to be repaired is completed: S321. Based on the local sensor, monitor and obtain the battery dynamic parameters of the battery pack to be repaired in real time; S322. Based on the adaptive mapping relationship model, calculate the reference pulse parameters to be applied currently according to the battery dynamic parameters; S323. Perform pulse repair on the battery pack to be repaired based on the pulse parameters smoothly adjusted according to the reference pulse parameters.

[0066] Specifically, the local control algorithm module deploys multiple adaptive mapping relationship models for combined use with different macroscopic repair targets and repair strategies. Step S31 involves selecting or calling an adaptive mapping relationship model according to the macroscopic repair target and the repair strategy. This model establishes the corresponding relationship between the battery dynamic parameters and the pulse parameters, and its adaptive characteristic enables it to be adjusted according to the actual dynamic state of the battery.

[0067] More specifically, step S32 is a loop that is repeatedly executed until the repair is completed. The completion of the repair means that at least one condition in the macro repair goal is achieved, such as reaching the upper limit of the repair duration.

[0068] More specifically, the adaptive mapping relationship model is used to calculate the reference pulse parameters to be applied at the current moment according to the current battery state, including pulse amplitude, pulse frequency, pulse duty cycle, and pulse waveform.

[0069] More specifically, step S321 obtains the dynamic parameters of the battery in real time through a local sensor, providing the real state information of the battery at the current moment. Step S322 inputs the dynamically obtained battery parameters into the adaptive mapping relationship model, and the model calculates the reference pulse parameters that should theoretically be applied at this moment according to the current state. Step S323 does not directly apply the reference pulse parameters, but smooths and adjusts them before application, thereby avoiding sudden changes in pulse parameters and enhancing the stability and safety of the repair process. Thus, the method of the present application can continuously and adaptively adjust the applied pulse parameters according to the real-time dynamic response of the battery during the repair process, thereby more precisely controlling the repair process, improving the repair effect, and overcoming the limitations of static or non-feedback algorithms in dealing with dynamic systems.

[0070] In some preferred embodiments, the adaptive mapping relationship model is a non-linear regression model with battery dynamic parameters as input and reference pulse parameters as output; the pulse parameters in step S323 are obtained by smoothing and adjusting based on the reference pulse parameters and the moving average filtering algorithm.

[0071] Specifically, the adaptive mapping relationship model is defined as a non-linear regression model that receives battery dynamic parameters as input, calculates, and outputs reference pulse parameters. This model structure can capture the complex non-linear relationship between battery dynamic parameters and the required pulse parameters. The calculated reference pulse parameters are used to determine the actual applied pulse parameters, and the moving average filtering algorithm is applied in the determination process. The moving average filtering algorithm processes the continuously calculated reference pulse parameters to generate smoothed pulse parameters. Thus, the changing trend of the applied pulse parameters is more stable, avoiding instantaneous fluctuations. In this way, the applied pulse parameters can respond to the dynamic changes of the battery state while maintaining the necessary stability, improving the reliability and safety of the repair process.

[0072] In some preferred embodiments, the adaptive mapping relationship model is a combined model including a pulse amplitude calculation model, a pulse frequency calculation model, a pulse duty cycle calculation model, and a pulse waveform selection model. Among them, the pulse amplitude calculation model, the pulse frequency calculation model, and the pulse duty cycle calculation model are all non-linear regression models, and the pulse waveform selection model is a classification model.

[0073] In some preferred embodiments, step S31 includes: S311. According to the macroscopic repair target and the repair strategy, select the corresponding adaptive mapping relationship model from a preset adaptive mapping relationship model library, where each model in the adaptive mapping relationship model library corresponds to a different combination of macroscopic repair target and repair strategy.

[0074] Specifically, the macroscopic repair target and the repair strategy are key information in the repair task instruction sent by the remote management terminal, which define the purpose and method of this repair. By associating different models with different combinations of macroscopic repair target and repair strategy, it can be ensured that when performing pulse repair, the adaptive mapping relationship model used is optimized for the current battery state and repair requirements. Thus, by selecting the most suitable model for the current task, the response accuracy of the model to the change of battery dynamic parameters is improved, making the calculated reference pulse parameters more accurate, and thereby optimizing the pulse repair process.

[0075] In some other embodiments, step S31 includes: S311'. Obtain the current battery quality assessment result according to the macroscopic repair target. The current battery quality assessment result is sent by the remote management terminal or generated by the local assessment module, and is the quality result of the repair index associated with the macroscopic repair target; S312'. According to the macroscopic repair target and the repair strategy, and in combination with the current battery quality assessment result, select the corresponding adaptive mapping relationship model from a preset adaptive mapping relationship model library.

[0076] Specifically, in step S311', the current battery quality assessment result is associated with the macroscopic repair target, reflecting the current state or problem degree of the battery in the indicators related to the macroscopic repair target. This result can be generated and sent by the remote management terminal based on historical data and analysis, or calculated and generated by the local assessment module in real time according to the initial battery state data and site environment data collected locally.

[0077] More specifically, then, step S312' compares the obtained current battery quality assessment result with multiple classification intervals preset corresponding to the macroscopic repair target and the repair strategy, and selects an adaptive mapping relationship model according to the interval in which the result falls. The adaptive mapping relationship model library is deployed in the local control algorithm module, which contains multiple models, and each model corresponds to a different combination of macroscopic repair target, repair strategy, and current battery quality assessment result classification interval. This way of selecting a model based on the specific quality state of the battery enables the selected model to more accurately reflect the actual repair requirements of the battery, improves the pertinence and effectiveness of pulse parameter adjustment, thereby enhancing the repair effect, and solving the problem of insufficient repair or low efficiency caused by selecting a model only based on macroscopic information.

[0078] For a second aspect, please refer to Figure 3 , some embodiments of the present application further provide a schematic structural diagram of an electronic device. The present application provides an electronic device, including: a processor 201 and a memory 202. The processor 201 and the memory 202 are interconnected and communicate with each other through a communication bus 203 and / or other forms of connection mechanisms (not marked). The memory 202 stores computer-readable instructions executable by the processor 201. When the electronic device runs, the processor 201 executes the computer-readable instructions to execute the methods in any optional implementation manner of the above embodiments.

[0079] For a third aspect, embodiments of the present application provide a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it executes the methods in any optional implementation manner of the above embodiments. Among them, the computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM for short), electrically erasable programmable read-only memory (EEPROM for short), erasable programmable read-only memory (EPROM for short), programmable read-only memory (PROM for short), read-only memory (ROM for short), magnetic memory, flash memory, a magnetic disk or an optical disc.

[0080] In addition, the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0081] Furthermore, in each embodiment of the present application, the functional modules can be integrated together to form an independent part, or each module can exist alone, or two or more modules can be integrated to form an independent part.

[0082] In this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations.

[0083] The above are only the embodiments of the present application and are not intended to limit the protection scope of the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application.

Claims

1. A battery pulse repair method, which is applied in a charging station, is characterized in that, The method includes the following steps: S1. Obtain a repair task instruction issued by a remote management terminal, where the repair task instruction includes a task ID, a macro repair target, and a repair strategy; S2. Collect site environment data based on local sensors, and evaluate whether the current environment meets the conditions for executing the repair task instruction according to the site environment data. If it meets the conditions, execute step S3; S3. Based on the macro repair target and the repair strategy, combine the battery dynamic parameters of the battery pack to be repaired collected in real time by local sensors, and calculate and output the pulse parameters to be applied at the current moment based on a local control algorithm module, so as to perform pulse repair on the battery pack to be repaired based on the pulse parameters; S4. Record the process data and repair results of the pulse repair, and associate the task ID; S5. When the communication link with the remote management terminal is unobstructed, upload the process data and repair results to the remote management terminal in packets based on the task ID.

2. The battery pulse repair method according to claim 1, wherein Step S2 includes: Collect the initial battery state data of the battery pack to be repaired and site environment data based on local sensors, and evaluate whether the current environment and battery state meet the conditions for executing the repair task instruction according to the initial battery state data and the site environment data. If it meets the conditions, execute step S3. Otherwise, delay or reject the execution of step S3, and record the reason.

3. The battery pulse repair method according to claim 1, characterized in that, During the execution of the pulse repair in step S3, the method further includes the steps of: SA. Collect and monitor whether the key battery parameters exceed a preset safety threshold based on local sensors. If they exceed, trigger a safety protection action.

4. The battery pulse repair method according to claim 3, wherein The setting process of the safety threshold includes: SA1. Obtain the battery type; SA2. Infer the repair stage based on the current pulse parameters; SA3. Extract the safety threshold from a pre-constructed safety threshold library according to the battery type and the repair stage.

5. The battery pulse repair method according to claim 4, characterized in that, Step SA2 includes: Determine the repair stage to which the current pulse parameters belong according to the current pulse parameters and in combination with the mapping relationship between the preset battery repair stage and the pulse parameters.

6. The battery pulse repair method according to claim 1, wherein The process data includes the pulse parameter sequence during the pulse repair process and the change curve of the key battery parameters in the battery dynamic parameters; the repair results include the repair duration and the battery health assessment results before and after the pulse repair.

7. The battery pulse repair method according to claim 1, wherein Step S3 includes: S31. According to the macro repair target and the repair strategy, call the adaptive mapping relationship model in the local control algorithm module, where the adaptive mapping relationship model is used to map the pairing relationship between the battery dynamic parameters and the pulse parameters; S32. Repeat the following steps until the pulse repair of the battery pack to be repaired is completed: S321. Monitor and obtain the battery dynamic parameters of the battery pack to be repaired in real time based on local sensors; S322. Based on the adaptive mapping relationship model, calculate the reference pulse parameters to be applied currently according to the battery dynamic parameters; S323. Perform pulse repair on the battery pack to be repaired based on the pulse parameters smoothly adjusted according to the reference pulse parameters.

8. The battery pulse repair method according to claim 7, characterized in that Step S31 includes: S311': Obtain the current battery quality assessment result according to the macro repair target. The current battery quality assessment result is sent by a remote management terminal or generated by a local assessment module, and is the quality result of a repair index associated with the macro repair target; S312': According to the macro repair target and the repair strategy, and in combination with the interval where the current battery quality assessment result is located, select a corresponding adaptive mapping relationship model from a preset adaptive mapping relationship model library.

9. An electronic device, characterized in that, It includes a processor and a memory. The memory stores computer-readable instructions. When the computer-readable instructions are executed by the processor, the steps in the method according to any one of claims 1-8 are run.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps in the method according to any one of claims 1-8 are run.

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