Online operation and maintenance management method for storage battery pack

Abstract

The invention discloses an online operation and maintenance management method for a storage battery pack, and relates to the technical field of operation and maintenance management, and the method comprises the following steps: S1, collecting the initial data of a battery of the storage battery pack, and constructing a dynamic performance model; s2, carrying out real-time prediction on the operation state of the battery of the storage battery pack; s3, dynamically adjusting a charging and discharging strategy of the storage battery pack; s4, predicting the residual life of the storage battery pack; s5, carrying out operation and maintenance work; and S6, designing a decommissioning and replacement management mechanism of the storage battery pack. According to the online operation and maintenance management method for the storage battery pack, the operation and maintenance task is intelligently scheduled based on the model prediction result, and the influence of temperature, load and environmental factors on the battery performance is introduced, so that the operation of the battery pack under different load and environmental conditions can be predicted and optimized more accurately. Through accurate residual life prediction and fault early warning, the service life of the battery pack can be remarkably prolonged, the fault occurrence rate is reduced, and maintenance scheduling is optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of operation and maintenance management, and in particular to an online operation and maintenance management method for a battery pack. Background Art

[0002] With the growing demand for battery packs in electric vehicles, energy storage systems, drones and other fields, how to ensure the efficient and safe operation of battery packs has become an important issue in modern energy management. The operation and maintenance management of battery packs not only includes real-time monitoring of the battery pack status, but also requires accurate assessment of its health status, life prediction and fault warning to maximize service life and reduce maintenance costs. Traditional battery pack operation and maintenance methods mostly rely on simple time- or voltage-based health assessments, but lack comprehensive analysis of multi-dimensional factors such as battery pack health status, operating environment and load changes. These existing methods usually ignore the synergistic effect of each single cell in the battery pack, and in the actual operation and maintenance process, it is difficult to accurately predict the battery pack life and fault warning, which affects the safety, stability and operational efficiency of the battery pack. Summary of the invention

[0003] In view of the deficiencies in the prior art, the present invention provides an online operation and maintenance management method for a battery pack to solve the problems raised in the above background technology.

[0004] To achieve the above object, the present invention provides the following technical solutions: In a first aspect, an embodiment of the present invention provides a method for online operation and maintenance management of a battery pack, comprising the following steps: S1. Before the battery pack is put into use, the initial data of the battery pack cells are collected, and a dynamic performance model is constructed based on the electrochemical characteristics of the battery; S2. Based on the dynamic performance model, the operating status of the battery pack is predicted in real time through continuous data monitoring; S3, dynamically adjusting the charging and discharging strategy of the battery pack based on the real-time prediction results; S4. After optimizing the charging and discharging strategy, predict the remaining life of the battery pack; S5. Performing operation and maintenance work on the battery pack using the optimized charging and discharging strategy; S6. During the operation and maintenance process, design a battery pack retirement and replacement management mechanism.

[0005] To further optimize the technical solution, in the steps S1 and S2, in the dynamic performance model, the performance of the battery pack is set to be affected by the following variables: Battery cell voltage ; Battery temperature ; Battery charge and discharge status ; Battery health status ; Load changes ; The dynamic performance model is used to describe the change of voltage, temperature, and health status of battery cells over time during the charging and discharging process, including: The relationship between battery cell voltage and charge and discharge status; The relationship between battery health status and usage time; Effect of temperature on battery performance.

[0006] To further optimize the technical solution, the dynamic performance model describes the relationship between the battery cell voltage and the charge and discharge state, including: For A battery cell, its voltage The change over time is expressed as: ; in, is the initial voltage of the battery, i.e. the theoretical full-charge voltage; and is the degradation factor related to the battery type and health status; It is the charging state of the battery cell, which changes with the charging and discharging process; is the influence coefficient of temperature on battery voltage; It is the temperature of the battery cell, which changes with the charging and discharging process and the ambient temperature factors; is an exponential decay term.

[0007] To further optimize the technical solution, the dynamic performance model describes the relationship between the battery health status and the usage time, including: Battery health status It is represented by the following equation: ; in, is the initial health state of the battery; It is a decay factor related to battery materials and usage conditions; is the coefficient of influence of battery load on health status; It is the load intensity, which indicates the intensity of the load that the battery bears.

[0008] To further optimize the technical solution, the dynamic performance model describes the effect of temperature on battery performance, including: The temperature of the battery affects the rate of its internal electrochemical reaction, and a temperature correction term is introduced to output the impact of temperature changes on battery performance: ; in, is the temperature coefficient, which indicates the effect of temperature changes on the battery voltage; It is the reference temperature, which is the normal temperature of 25℃.

[0009] To further optimize the technical solution, in step S2, based on the dynamic performance model, the real-time data continuously monitored is used to perform abnormal prediction and risk assessment, and the voltage, temperature, and battery charge and discharge status of the battery are monitored in real time and compared with the normal range; When it is detected that the voltage change trend of a battery cell is abnormal, the temperature is too high, or the health status declines too quickly, the model will issue a warning signal.

[0010] To further optimize the technical solution, in step S4, the remaining life of the battery pack is predicted, including: After adopting the charging and discharging strategy, real-time data of each battery cell in the battery pack is collected, including the battery's health status, charging status, temperature, and battery pack load. Through real-time monitoring, the data is dynamically updated, and the remaining life of the battery pack is predicted through the nonlinear regression relationship of multiple variables.

[0011] The technical solution is further optimized by performing maintenance scheduling based on the prediction of the remaining life of the battery pack, including giving priority to replacing severely degraded battery cells, globally optimizing maintenance timing, and dynamically adjusting load and charging and discharging strategies.

[0012] Further optimizing the technical solution, in step S5, the operation and maintenance work includes real-time status simulation and remote debugging; Real-time status simulation: Simulate the behavior of the battery pack under different working conditions in real time to help operation and maintenance personnel understand the cause of the fault. Through the system interface, operation and maintenance personnel can view the simulated data of the battery pack under different scenarios and perform diagnosis and troubleshooting based on the fault characteristics. Remote debugging: Operation and maintenance personnel can directly adjust the control parameters of the battery pack through the cloud platform, optimize the charging and discharging strategies, and perform debugging and optimization without interfering with the normal operation of the battery pack.

[0013] To further optimize the technical solution, in step S6, the retirement and replacement management mechanism includes: Decommissioning plans are made based on the predicted remaining life and health status, taking into account the economic value, environmental impact and recycling of the battery pack; In the retirement plan, new replacement batteries are used and retired batteries are recycled to optimize the battery pack disposal process.

[0014] In a second aspect, an embodiment of the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program instructions are executed by the processor, the steps of a battery pack online operation and maintenance management method as described in the first aspect of the present invention are implemented.

[0015] In a third aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, the steps of a battery pack online operation and maintenance management method as described in the first aspect of the present invention are implemented.

[0016] Compared with the prior art, the present invention provides a battery pack online operation and maintenance management method, which has the following beneficial effects: This online operation and maintenance management method for battery packs combines dynamic performance modeling, health status assessment, and life prediction technology to comprehensively collect the operating data of the single cells in the battery pack to monitor the health status and operation of the battery pack in real time, and intelligently schedules the operation and maintenance tasks based on the model prediction results. The effects of temperature, load, and environmental factors on battery performance are introduced, so that the operation of the battery pack under different load and environmental conditions can be more accurately predicted and optimized. Through accurate remaining life prediction and fault warning, the present invention can significantly extend the service life of the battery pack, reduce the occurrence of faults, optimize maintenance scheduling, and effectively improve the safety, stability, and overall efficiency of the battery pack, and has important practical application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 A schematic diagram of a flow chart of an online operation and maintenance management method for a battery pack proposed by the present invention; Figure 2 A schematic diagram of the composition of a dynamic performance model in an online operation and maintenance management method for a battery pack proposed by the present invention; Figure 3 A schematic diagram of a method for battery pack maintenance scheduling in a battery pack online operation and maintenance management method proposed by the present invention. DETAILED DESCRIPTION

[0019] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0020] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0021] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0022] Embodiment 1: Reference Figure 1 to Figure 3 , which is the first embodiment of the present invention, provides a battery pack online operation and maintenance management method, comprising the following steps: S1. Before the battery pack is put into use, the initial data of the battery pack cells are collected, and a dynamic performance model is constructed in combination with the electrochemical characteristics of the cells.

[0023] In this embodiment, the battery pack status estimation is updated in real time, potential abnormalities of the battery pack are diagnosed at an early stage, and personalized health assessment and prediction can be performed on battery packs of different models and different usage environments.

[0024] S2. Based on the dynamic performance model, the operating status of the battery pack is predicted in real time through continuous data monitoring.

[0025] Based on the monitored data, trend analysis is performed to identify possible anomalies in the battery pack in advance, such as battery cell voltage deviation, temperature anomaly, abnormal number of charge and discharge cycles, etc. By comparing with historical data and model predictions, the risk level of the anomaly is assessed and early warning is issued.

[0026] In this embodiment, in the dynamic performance model, it is assumed that the performance of the battery pack is affected by the following variables: Battery cell voltage ; Battery temperature ; Battery charge and discharge status ; Battery health status ; Load changes .

[0027] The dynamic performance model is used to describe the change of voltage, temperature, and health status of battery cells over time during the charging and discharging process, including: The relationship between battery cell voltage and charge and discharge status; The relationship between battery health status and usage time; Effect of temperature on battery performance.

[0028] Furthermore, in the dynamic performance model, the relationship between the battery cell voltage and the charge and discharge state is described, including: For A battery cell, its voltage The change over time is expressed as: Formula (1); in, is the initial voltage of the battery, i.e. the theoretical full-charge voltage; and is the degradation factor related to the battery type and health status; It is the charging state of the battery cell, which changes with the charging and discharging process; is the influence coefficient of temperature on battery voltage; It is the temperature of the battery cell, which changes with the charging and discharging process and the ambient temperature factors; is an exponential decay term.

[0029] This formula describes the decay process of battery cell voltage, especially in the charge and discharge cycle, the battery voltage is not only affected by SOC (state of charge), but also by temperature changes and battery health decay. The decay term is expressed by the exponential decay term It simulates the performance degradation of the battery during long-term use.

[0030] Furthermore, in the dynamic performance model, the relationship between the battery health status and the usage time is described, including: Battery health status It is represented by the following equation: ; in, is the initial health state of the battery (usually 1); It is a decay factor related to battery materials and usage conditions (such as ambient temperature); is the coefficient of influence of battery load on health status; It is the load intensity, which indicates the intensity of the load that the battery bears.

[0031] This equation shows that the health of the battery declines over time, and the greater the load intensity and the longer the duration, the faster the battery health declines. This is because high loads increase the intensity of chemical reactions inside the battery, accelerate material aging, and reduce battery life.

[0032] Furthermore, in the dynamic performance model, the effect of temperature on battery performance is described, including: The temperature of the battery affects the rate of its internal electrochemical reaction, and a temperature correction term is introduced to output the impact of temperature changes on battery performance: Formula (2); in, is the temperature coefficient, which indicates the effect of temperature changes on the battery voltage; It is the reference temperature, which is the normal temperature of 25℃.

[0033] This item shows that increased temperature will cause the battery voltage to increase and may also accelerate health degradation, so it needs to be considered in actual operation and maintenance.

[0034] In the same battery cell In general, when considering the effect of temperature on voltage, formula (1) and formula (2) reflect different levels of influence: Formula (1) mainly describes the battery voltage Changes over time, affected by the state of charge ,temperature , and recession effects This formula already includes the linear effect of temperature on voltage (via Item), which is used to calculate the basic value of the battery voltage.

[0035] Formula (2) introduces the temperature coefficient , based on the reference temperature The battery voltage is further corrected to reflect the nonlinear effect of temperature deviation on the voltage. This correction method is suitable for use under certain extreme temperature changes to adjust the accuracy of the battery voltage.

[0036] In practical applications, it is not possible to simply select formula (1) or formula (2) as the final result. Instead, it is necessary to make a judgment based on the temperature change range and usage scenario: Normal temperature change scenario: When the temperature change range is small (such as ), formula (1) can accurately describe the voltage change. No additional temperature correction is required.

[0037] Extreme temperature change scenario: When the temperature deviates significantly from the reference temperature (such as or ), you need to use formula (2) to calculate the voltage of formula (1) Corrections are made to reflect the impact of temperature nonlinear effects on voltage.

[0038] In the operation and maintenance system, the basic voltage value of the battery cell is first calculated according to formula (1).

[0039] Check the current temperature Is it within the reference range?

[0040] If it is within the reference range, directly use the result of formula (1).

[0041] If it is outside the reference range, use formula (2) to correct the result of formula (1).

[0042] This processing method can more accurately reflect the complex changes in battery voltage with temperature and avoid estimation errors caused by excessive temperature fluctuations.

[0043] Based on the dynamic performance model, the real-time data continuously monitored is used to predict abnormalities and assess risks. The battery voltage, temperature, and battery charge and discharge status indicators are monitored in real time and compared with the normal range. When it is detected that the voltage change trend of a battery cell is abnormal, the temperature is too high, or the health status declines too quickly, the model will issue a warning signal.

[0044] The model, when used in step S1, includes: By collecting the initial data of the battery pack (such as voltage, temperature, charging state, etc.), the parameters in the model are trained and optimized using machine learning methods to obtain personalized parameters for each battery cell (such as These initial parameters provide the basis for subsequent diagnosis and prediction of the system.

[0045] During the initial operation stage, the system will collect real-time voltage, current, temperature, SOC and other data of each cell in the battery pack.

[0046] Use these data to fit the decay coefficient of each battery cell (such as and etc.), build a preliminary dynamic performance model.

[0047] The initially established model can perform health assessment and detect the current state of the battery pack.

[0048] On this basis, the system will gradually adjust and optimize the model parameters according to the performance of the battery pack under different working conditions, so that the model can more accurately reflect the health status and performance degradation of the battery pack.

[0049] The model, when used in step S2, includes: Based on the established dynamic performance model, the system uses the monitored real-time data to predict anomalies and assess risks. For example, the system will monitor the battery voltage, temperature, SOC and other indicators in real time and compare them with the normal range predicted by the model. When the system detects that the voltage change trend of a battery cell is abnormal, the temperature is too high, or the health status declines too quickly, the model will issue a warning signal.

[0050] In this process, the role of the model is mainly reflected in: Risk assessment: Based on real-time data, assess the risk level of the battery pack in its current state. , , The changing trend of the battery cells can be used to evaluate the possible failure types of the battery cells (such as overheating, over-discharge, excessive degradation, etc.).

[0051] Abnormal prediction: Through model prediction, potential failure points of battery cells can be identified in advance. For example, when the voltage of a battery cell drops too fast or the temperature rises abnormally, the model will issue an alarm in advance to prompt the operation and maintenance personnel to check or adjust the charging and discharging strategy.

[0052] Through the above dynamic performance model, we can accurately simulate the state changes of the battery pack, and then perform health assessment, abnormality prediction and risk assessment. This model can not only be used for preliminary performance modeling and diagnosis, but also for real-time abnormality prediction and risk assessment to ensure the efficient and safe operation of the battery pack.

[0053] S3. Based on the real-time prediction results, dynamically adjust the charging and discharging strategy of the battery pack.

[0054] In this embodiment, the charging and discharging strategy of the battery pack is dynamically adjusted according to the risk and abnormal prediction results identified in step S2. For example, when the system detects that a battery cell is overheated, the system will automatically adjust the charging current, reduce the load, or balance the health of the battery through periodic equalization charging. In some extreme cases, such as severe overtemperature, the system will adjust the workload of the battery pack and reduce the load by dispatching other backup battery packs to reduce the risk of battery damage.

[0055] In addition, the charging and discharging strategies are optimized and adjusted according to the operating status of the battery pack and external environmental factors (such as temperature, humidity, etc.) to maximize the service life of the battery pack and improve the adaptability and stability of the battery pack in high-load environments.

[0056] S4. After optimizing the charging and discharging strategy, predict the remaining life of the battery pack.

[0057] In this embodiment, the remaining life of the battery pack is predicted, including: After adopting the charging and discharging strategy, real-time data of each battery cell in the battery pack is collected, including the battery's health status, charging status, temperature, and battery pack load. Through real-time monitoring, the data is dynamically updated, and the remaining life of the battery pack is predicted through the nonlinear regression relationship of multiple variables.

[0058] in, The battery health status is obtained through the previous dynamic performance model evaluation, which reflects the degree of degradation of the battery cells; The charging status will change with each charge and discharge cycle, and the system will monitor the battery charge in real time; The load is affected by the external load demand, which is usually related to the actual load used by the battery pack; Temperature is one of the key factors affecting battery performance and life. The system monitors the temperature of each battery cell.

[0059] If the health status of a battery cell declines, its impact on the life of the entire battery pack will be calculated, which will in turn affect the prediction of the remaining life. When the temperature is too high or the load is at a high intensity for a long time, it will be predicted that the remaining life of the battery pack will decrease in advance. In this way, the battery pack can be intelligently scheduled for maintenance, replacement or calibration to ensure the efficient operation and safety of the battery pack throughout its life cycle.

[0060] Furthermore, the maintenance scheduling based on the prediction of the remaining life of the battery pack includes giving priority to replacing severely degraded battery cells, globally optimizing the maintenance timing, and dynamically adjusting the load and charging and discharging strategies.

[0061] Furthermore, Prioritize replacement of severely degraded battery cells: If the health status of a battery cell has dropped significantly and the battery has a greater impact on the performance of the entire battery pack, the system will prioritize replacing the battery.

[0062] Globally optimized maintenance timing: The overall health status of the battery pack is comprehensively considered to predict the life of the entire battery pack, not just the life of a single battery. Therefore, the system will arrange maintenance or replacement in advance when the overall life of the battery pack is about to expire, avoiding sudden failure of the entire battery pack during use.

[0063] Dynamically adjust the load and charge and discharge strategies: When the model predicts that the remaining life of the battery pack is short, the system may adjust the charge and discharge strategy to reduce the load on the battery pack and reduce the temperature change of the battery, thereby delaying further decline in life.

[0064] S5. Perform operation and maintenance work on the battery pack that adopts the optimized charging and discharging strategy.

[0065] In this embodiment, the operation and maintenance work includes real-time status simulation and remote debugging; Real-time status simulation: Simulate the behavior of the battery pack under different working conditions in real time to help operation and maintenance personnel understand the cause of the fault. Through the system interface, operation and maintenance personnel can view the simulated data of the battery pack under different scenarios and perform diagnosis and troubleshooting based on the fault characteristics. Remote debugging: Operation and maintenance personnel can directly adjust the control parameters of the battery pack through the cloud platform, optimize the charging and discharging strategies, and perform debugging and optimization without interfering with the normal operation of the battery pack.

[0066] S6. During the operation and maintenance process, design a battery pack retirement and replacement management mechanism.

[0067] In this embodiment, when the battery pack reaches a certain service life or its performance declines to a certain extent, the system will start the retirement and replacement management mechanism. Through multi-dimensional evaluation of the battery pack, the system not only makes retirement plans based on its remaining life and health status, but also considers factors such as the economic value, environmental impact and recycling of the battery pack. During the retirement stage, the system will recommend the use of new replacement batteries and select them based on the current market's technological progress and product needs to ensure that the new battery pack can be seamlessly replaced and meet future operation and maintenance needs.

[0068] The system will also recycle resources during the decommissioning process, optimize the battery pack processing flow, reduce environmental pollution, and recycle and reuse valuable components in the battery as much as possible.

[0069] Embodiment 2: This embodiment also provides a computer device, which is applicable to a battery pack online operation and maintenance management method, including a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement a battery pack online operation and maintenance management method as proposed in the above embodiment.

[0070] This embodiment further provides a storage medium on which a computer program is stored. When the program is executed by a processor, an online operation and maintenance management method for a battery pack as proposed in the above embodiment is implemented.

[0071] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covered on the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0072] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0073] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0074] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk case (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0075] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit with a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit with a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0076] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A battery pack online operation and maintenance management method, characterized in that: The following steps are involved: S1. Before the battery pack is put into use, the initial data of the battery pack cells are collected, and a dynamic performance model is constructed based on the electrochemical characteristics of the battery; S2. Based on the dynamic performance model, the operating status of the battery pack is predicted in real time through continuous data monitoring; S3, dynamically adjusting the charging and discharging strategy of the battery pack based on the real-time prediction results; S4. After optimizing the charging and discharging strategy, predict the remaining life of the battery pack; S5. Performing operation and maintenance work on the battery pack using the optimized charging and discharging strategy; S6. During the operation and maintenance process, design a battery pack retirement and replacement management mechanism.

2. A battery pack online operation and maintenance management method according to claim 1, characterized in that: In the steps S1 and S2, in the dynamic performance model, the performance of the battery pack is assumed to be affected by the following variables: Battery cell voltage ; Battery temperature ; Battery charge and discharge status ; Battery health status ; Load changes ; The dynamic performance model is used to describe the change of voltage, temperature, and health status of battery cells over time during the charging and discharging process, including: The relationship between battery cell voltage and charge and discharge status; The relationship between battery health status and usage time; Effect of temperature on battery performance.

3. A battery pack online operation and maintenance management method according to claim 2, characterized in that: The dynamic performance model describes the relationship between the battery cell voltage and the charge and discharge state, including: For A battery cell, its voltage The change over time is expressed as: ； in, is the initial voltage of the battery, i.e. the theoretical full-charge voltage; and is the degradation factor related to the battery type and health status; It is the charging state of the battery cell, which changes with the charging and discharging process; is the influence coefficient of temperature on battery voltage; It is the temperature of the battery cell, which changes with the charging and discharging process and the ambient temperature factors; is an exponential decay term.

4. A battery pack online operation and maintenance management method according to claim 2, characterized in that: The dynamic performance model describes the relationship between the battery health status and the usage time, including: Battery health status It is represented by the following equation: ； in, is the initial health state of the battery; It is a decay factor related to battery materials and usage conditions; is the coefficient of influence of battery load on health status; It is the load intensity, which indicates the intensity of the load that the battery bears.

5. The method for online operation and maintenance of a battery pack according to claim 2, characterized in that: The dynamic performance model describes the effect of temperature on battery performance, including: The temperature of the battery affects the rate of its internal electrochemical reaction, and a temperature correction term is introduced to output the impact of temperature changes on battery performance: ； in, is the temperature coefficient, which indicates the effect of temperature changes on the battery voltage; It is the reference temperature, which is the normal temperature of 25℃.

6. A battery pack online operation and maintenance management method according to claim 1, characterized in that: In step S2, based on the dynamic performance model, the real-time data continuously monitored is used to perform abnormal prediction and risk assessment, and the battery voltage, temperature, and battery charge and discharge status indicators are monitored in real time and compared with the normal range; When it is detected that the voltage change trend of a battery cell is abnormal, the temperature is too high, or the health status declines too quickly, the model will issue a warning signal.

7. The method for online operation and maintenance of a battery pack according to claim 1, characterized in that: In step S4, the remaining life of the battery pack is predicted, including: After adopting the charging and discharging strategy, real-time data of each battery cell in the battery pack is collected, including the battery's health status, charging status, temperature, and battery pack load. Through real-time monitoring, the data is dynamically updated, and the remaining life of the battery pack is predicted through the nonlinear regression relationship of multiple variables.

8. A battery pack online operation and maintenance management method according to claim 7, characterized in that: The maintenance scheduling based on the prediction of the remaining life of the battery pack includes giving priority to replacing severely degraded battery cells, globally optimizing the maintenance timing, and dynamically adjusting the load and charging and discharging strategies.

9. The method for online operation and maintenance of a battery pack according to claim 1, characterized in that: In step S5, the operation and maintenance work includes real-time status simulation and remote debugging; Real-time status simulation: Simulate the behavior of the battery pack under different working conditions in real time to help operation and maintenance personnel understand the cause of the fault. Through the system interface, operation and maintenance personnel can view the simulated data of the battery pack under different scenarios and perform diagnosis and troubleshooting based on the fault characteristics. Remote debugging: Operation and maintenance personnel can directly adjust the control parameters of the battery pack through the cloud platform, optimize the charging and discharging strategies, and perform debugging and optimization without interfering with the normal operation of the battery pack.

10. The method for online operation and maintenance of a battery pack according to claim 1, characterized in that: In step S6, the retirement and replacement management mechanism includes: Decommissioning plans are made based on the predicted remaining life and health status, taking into account the economic value, environmental impact and recycling of the battery pack; In the retirement plan, new replacement batteries are used and retired batteries are recycled to optimize the battery pack disposal process.

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