Lithium ion battery pack operation management method and system based on multi-parameter evaluation, medium and program product

Abstract

The invention relates to the technical field of lithium ion battery operation safety evaluation, relates to the technical field of battery safety, and aims to reasonably match working battery groups required in an actual application scene through reasonable grouping, prolong the service life of batteries through grouping operation, and avoid single battery modules adjacent in physical position as much as possible during grouping. According to the lithium battery pack, rapid heat rising and concentration during operation of the working battery pack are avoided, a buffer area exists in the lithium battery pack as much as possible during operation, the buffer area is beneficial to heat dissipation and serves as a preparation pack of the next-stage working battery pack, and through real-time monitoring of temperature / voltage abnormity of the battery module pack and monitoring of the adjacent battery pack, the energy consumption of the lithium battery pack is reduced. And dynamically adjusting the working priority. The system has the advantages that it is ensured that the system responds to the load requirement through the optimal battery module combination, the output capacity is maximized on the premise that safety is ensured, and the reliability and safety are improved when products with the high power and the high energy storage capacity are used for meeting the small electricity consumption scene.

Description

Technical Field

[0001] The present application relates to the field of lithium battery packs, and in particular to an operation and management method of a lithium battery pack. Background Art

[0002] At present, due to the popularity of new energy and outdoor activities, the operation and management of battery packs has become a Energy storage products are a key technical point of differentiation. Different energy storage products are selected to meet varying needs in different power usage scenarios. When using higher-power, higher-capacity products to meet smaller power usage scenarios, optimizing operational management solutions becomes a crucial benchmark for product performance. Currently, most conventional approaches, such as those mentioned in CN117318211A, focus on managing charging and discharging rather than overall battery pack operation.

[0003] In related technologies, selective charging and discharging is used: for abnormal cells (such as low voltage), only specific cells are charged and discharged for maintenance through switch control (such as K0-Kn, KA1 / KB1, etc.), reducing the overall maintenance time. When the entire group is charged and discharged, the discharge energy of the high-voltage cells is used to charge the low-voltage cells, reducing energy consumption. The intelligent control and feedback BMS management unit is linked to the charge and discharge management unit through the CAN bus to dynamically adjust the switch status and charge and discharge parameters, combined with the display storage unit to monitor data in real time, calibrate the SOC status, and support customized charge and discharge strategies. However, in this scenario, it cannot solve the problem of using products with higher power and higher energy storage to meet small power consumption scenarios and achieve a more reasonable and reliable effect. Summary of the Invention

[0004] The purpose of this application is to provide a lithium-ion battery pack operation management method, system, medium and program product based on multi-parameter evaluation to improve the rationality and safety of battery pack operation.

[0005] In the first aspect, the lithium-ion battery pack operation management method based on multi-parameter evaluation provided by the present application adopts the following technical solutions: Obtain temperature data, voltage data, SOC data, and SOH data of each single battery module in the target lithium battery pack within a preset operating time; Building a comprehensive evaluation model for battery operating capability based on the SOC data, the SOH data, and the temperature data of each battery module to obtain operating capability parameters of each battery module; Grouping and positioning the working battery modules according to the operating capacity parameters of each single battery; Preset the job combination priority queue of the working battery module group according to the average battery operating capacity parameters and the required working voltage data of each working battery module group; Based on the job combination priority queue of the working battery module group and the positioning of the working battery module group, monitoring the average operating capacity parameters of the battery module groups surrounding the working battery module group currently operating and the priority queues in which the battery module groups are located; Based on the operating data of the surrounding battery module groups, a battery module group influence coefficient is obtained, and the operation combination priority of the working battery module group is dynamically adjusted according to the battery module influence coefficient.

[0006] By adopting the above technical solution, the load can be evenly distributed based on the SOC / SOH-temperature comprehensive evaluation model, and the high-risk working group can be dynamically downgraded through the thermal-electric coupling influence coefficient of the adjacent modules. At the same time, combined with physical positioning and priority queue scheduling, it is ensured that the system responds to load demands with the optimal battery module combination, maximizes output capacity while ensuring safety, and improves the reliability and safety of using higher-power and higher-energy storage products to meet small-scale power consumption scenarios.

[0007] In some embodiments of the first aspect, grouping and positioning the working battery modules according to the operating capability parameters of the individual single batteries specifically includes: According to the single battery operation capability parameter, an average single battery operation capability parameter is obtained, and the working battery modules are grouped in combination with a grouping parameter standard.

[0008] By adopting the above technical solution, batteries with similar performance can be divided into the same group, such as those with similar power, health, and temperature, to avoid the entire group running out of power prematurely or having unstable voltage due to a few poor batteries in the group.

[0009] In some embodiments of the first aspect, based on the average battery operating capacity parameters and required operating voltage data of each working battery module group, a job combination priority queue of the working battery module group is preset, specifically including: Obtaining an average battery operating capacity parameter of each working battery module group based on the operating capacity parameters of each single battery cell and the number of single batteries included in the working battery module group; According to the necessary working voltage data and the voltage data of each single battery module, the number of single battery working cells required during operation is obtained; based on the number of single battery working cells and the average battery operating capacity parameters of each working battery module group, the working combination priority of the working battery module group is set.

[0010] By adopting this technical solution, the number of battery packs to be activated is adjusted based on the voltage required by the current operation. Battery packs with high capacity that can meet the work requirements are prioritized, avoiding unstable power supply or the waste of resources caused by too many battery packs operating at the same time. The corresponding working battery packs are replaced according to different operation requirements and operation stages, effectively allocating battery pack usage.

[0011] In some embodiments of the first aspect, based on the job combination priority queue of the working battery module group and the positioning of the working battery module group, monitoring the average operating capacity parameters of the battery module groups surrounding the working battery module group currently operating and the priority queues in which the battery module groups are located specifically includes: Based on the positioning of the working battery module group, obtaining the operating capability parameters of the battery module groups surrounding the currently operating working battery module and the priority queues of the battery module groups; Based on the job combination priority queue of the working battery module group, the battery module group in the next job combination priority queue in the battery module group around the working battery module of the current job is located, and the operating capacity parameter changes of the battery module group in the next job combination priority queue are monitored.

[0012] By adopting the above technical solution, the battery module status around the current working battery pack, such as temperature, voltage, capacity, etc., is monitored, and abnormalities in adjacent areas (such as local overheating or performance degradation) are discovered in a timely manner to avoid the spread of thermal runaway or voltage collapse caused by failures of surrounding battery packs. It also ensures that when it is necessary to switch the working group of surrounding battery packs, it is in a ready state and the performance meets the standards.

[0013] In some embodiments of the first aspect, after the step of monitoring the change in the operating capability parameter of the battery module group in the next job combination priority queue, the step further includes: When the operating capability parameter of the battery module group of the next job combination priority queue is less than the operating capability parameter required by its priority queue, the job combination priority of the corresponding battery module group is re-rated.

[0014] By adopting the above technical solution, when it is detected that the performance of the next-priority battery pack does not meet the requirements (such as the SOC is too low or the temperature exceeds the standard), its priority is immediately downgraded or removed from the queue to prevent power outages or safety risks caused by unavailable groups when switching battery working groups. This ensures that the priority queue always reflects the latest status of the battery pack and avoids operational errors caused by data lags.

[0015] In some embodiments of the first aspect, based on the operating data of the surrounding battery module groups, a battery module group influence coefficient is obtained, and the operation combination priority of the working battery module group is dynamically adjusted according to the battery module influence coefficient, specifically including: Obtaining a temperature change, a distance change, a voltage change, and a change in an operating capability parameter of a surrounding battery module group to obtain an influence coefficient of the battery module group; Based on the battery module group influence coefficient, the unit time change of the battery module group operating capability parameter is obtained, and according to the unit time change of the battery module group operating capability parameter, the operation combination priority of the working battery module group is dynamically adjusted.

[0016] By employing the above technical solution, a model is constructed to model how the operating capacity parameters of a battery workgroup change with temperature, distance, and operating time. If a battery workgroup's operating capacity is affected by other operational factors such as heat diffusion in surrounding modules, it is removed from the high-priority queue in advance and replaced with a battery pack with slower degradation, maintaining the stability of the entire battery pack.

[0017] In some embodiments of the first aspect, the step of dynamically adjusting the operation combination priority of the working battery module group specifically includes: Based on the job combination priority and battery module group influence coefficient of each working battery module group, the changing relationship between the battery module group operating capacity parameters and working hours is simulated to set the re-rating time; When the working time of the current working battery module group reaches the re-rating time, the operation combination priority of the working battery module group is set based on the current battery module group operation capability parameter.

[0018] By adopting this technical solution, we can predict the workload of battery packs in advance and pre-determine the priority allocation of the working battery module groups. This avoids the irrationality of fixed-cycle switching between working battery groups. Based on battery degradation and environmental changes, we dynamically adjust the continuous operation time of the working group, forcing a switch to the backup group to prevent long-term overload and aging of a single battery module group. This triggers priority reassessment in advance, replacing fixed switching nodes to quickly respond to risks and maximize battery utilization.

[0019] In a second aspect, an embodiment of the present application provides a lithium-ion battery pack operation and management system based on multi-parameter evaluation. The lithium-ion battery pack operation and management system based on multi-parameter evaluation includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and one or more processors call the computer instructions to enable the system to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0020] In a third aspect, an embodiment of the present application provides a computer-readable storage medium comprising instructions, which, when executed on a system, enables the system to execute the method described in the first aspect and any possible implementation of the first aspect.

[0021] In a fourth aspect, an embodiment of the present application provides a computer program product, characterized in that when the computer program product is run on a system, the system executes the method described in any possible implementation manner in the first aspect.

[0022] In summary, this application includes at least one of the following beneficial technical effects: 1. It can evenly distribute loads based on a comprehensive SOC / SOH-temperature assessment model, dynamically downgrade high-risk workgroups through the thermal-electrical coupling influence coefficient of adjacent modules, and combine physical positioning with priority queue scheduling to ensure that the system responds to load demands with the optimal battery module combination, maximizing output capacity while ensuring safety. This improves the reliability and safety of using higher-power and higher-energy storage products to meet small power consumption scenarios. 2. Based on the voltage required for the current operation, the number of battery packs to be activated should be adjusted. Prioritize battery packs with high capacity that can meet the work requirements to avoid unstable power supply or waste of resources caused by too many battery packs working at the same time. Replace the corresponding working battery pack according to different operation requirements and operation stages, and reasonably allocate the use of battery packs; 3. Build a model to measure how battery workgroup operating parameters change with temperature, distance, and operating time. If a battery workgroup's operating parameters are affected by other operational factors, such as heat diffusion from surrounding modules, the workgroup will be removed from the high-priority queue and replaced with a battery pack with slower degradation to maintain the stability of the entire battery pack. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is a flow chart of a lithium-ion battery pack operation management method based on multi-parameter evaluation in an embodiment of the present application; Figure 2 This is a schematic diagram of a process for dynamically adjusting the operating priority of a lithium-ion battery pack based on multi-parameter evaluation in an embodiment of the present application; Figure 3 This is a schematic diagram of the physical position distribution of the working battery module group during operation in an embodiment of the present application; Figure 4 This is a schematic diagram of the physical device structure of a lithium-ion battery pack operation management system based on multi-parameter evaluation provided in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The terms used in the following examples of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification and appended claims of this application, the singular expressions "a," "an," "said," "above," "the," and "this" are intended to include plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in this application refers to any or all possible combinations comprising one or more of the listed items.

[0025] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood to imply or suggest relative importance or implicitly indicate the number of the technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of this application, unless otherwise specified, "plurality" means two or more.

[0026] The following uses an embodiment and combines Figure 1 , a lithium-ion battery pack operation management method based on multi-parameter evaluation in an embodiment of the present application is described: Reference Figure 1 and Figure 3 , is a flow chart of a lithium-ion battery pack operation management method based on multi-parameter evaluation in an embodiment of the present application.

[0027] S101, obtaining temperature data, voltage data, SOC data, and SOH data of each single battery module in a target lithium battery pack within a preset operating time; This step collects operating parameters, such as temperature and voltage, for each cell module in a lithium-ion battery pack. This is monitored in real time using thermocouples or infrared temperature sensors attached to the cell surface, while voltage is measured using an ADC module. The collected data is then read periodically. Kalman filtering is then used to derive the SOC data for the cell module, and the SOH data is derived based on voltage and current changes. The operating parameters of the cell module provide a solid foundation for subsequent evaluation of the battery's overall performance.

[0028] S102: constructing a comprehensive evaluation model for battery operating capability based on the SOC data, the SOH data, and the temperature data of each battery module to obtain operating capability parameters of each battery module; This step is to apply the trained model to the SOC data, SOH data, and temperature data of the single battery module per unit time, etc., to measure the comprehensive performance of each single battery module in the lithium battery pack, which serves as data support for subsequent management methods. Specifically, it may include but is not limited to: SOC change rate, SOH decay rate, temperature gradient, historical data, and the establishment of single battery operating capacity parameters. It still needs to be based on the change gradient of the corresponding performance parameters of the single battery module. The following performance parameters need to be calculated for the change gradient: SOC change rate: reflects the charge and discharge rate of the battery.

[0029] SOH decay rate: reflects changes in the battery's health status.

[0030] Temperature gradient: reflects the rate of temperature change of the battery.

[0031] Historical data: such as the mean, variance, and other statistical characteristics of SOC, SOH, and temperature over a period of time.

[0032] S103, grouping and positioning the working battery modules according to the operating capability parameters of the individual single batteries; This step groups the batteries based on the single-battery operating capacity parameters obtained in the previous step. The batteries are divided into several groups based on their operating capacity. The single-battery operating modules are grouped based on the preset grouping values ​​for the strength of the single-battery operating capacity. When grouping, the working battery groups operating in the same group prioritize single-battery modules with non-adjacent physical locations. For example, if the preferred physical location is (0,1), then (0,0), (0,2), and (1,1) will be marked as non-preferred single-battery modules in the same group.

[0033] S104, presetting a job combination priority queue for each working battery module group based on the average battery operating capacity parameters and required working voltage data of each working battery module group; This step calculates the average battery operating capacity parameter of each working group based on the operating capacity parameters of all single batteries in each working group. Based on the voltage required for the actual scenario and the voltage provided by each working battery module group, the required number of working battery module groups is determined, and then the working battery module group combination with priority is determined. For example, if the required voltage is 100V, and the current working battery module group has a combination of 30V, 20V, 40V, and 10V, the combination with the average battery operating capacity parameter that meets the requirements of the first working stage is selected for the operation. The remaining working battery module groups are then combined and prioritized. Working battery module groups can only be switched when the subsequent working stage changes.

[0034] S105: Based on the job combination priority queue of the working battery module group and the location of the working battery module group, monitor the average operating capacity parameters of the battery module groups surrounding the working battery module group currently operating and the priority queues of the battery module groups; This step involves the management system collecting real-time operating data from each battery module group, including parameters such as voltage, current, temperature, and SOC, and calculating its operating capacity parameters based on this collected data. Secondly, based on the positioning information of the active battery module group (such as spatial coordinates or logical topological location), the priority queues of the surrounding battery module groups are determined, and the real-time operating capacity parameters and priority information of the surrounding battery module groups are obtained.

[0035] S106. Obtaining a battery module group influence coefficient based on the operating data of the surrounding battery module groups, and dynamically adjusting the operation combination priority of the working battery module group according to the battery module influence coefficient; This step locates the battery module groups around the working battery module group based on the physical position of the current working battery module group, and then records the specific parameters of the battery module group per unit time, such as how much the temperature rise of the working battery module group will increase per unit time, and how the operating capacity parameters of the battery module group itself will fluctuate. At the same time, it also records the relevant influencing parameters such as the influence of distance on the battery module group when the distance from the working battery module group is different, and then weights the influence coefficient of the battery module group according to the size of the influence. Subsequently, the battery module group influence parameters are used to predict how long the working battery module group needs to switch after working and how often the operation priority of other battery module groups needs to be reset.

[0036] The implementation principle of the embodiment of the present application is: through reasonable grouping to reasonably match the working battery grouping required in the actual application scenario, the group operation extends the service life of the battery, and at the same time, avoid single battery modules with adjacent physical positions as much as possible when grouping, avoid the rapid increase and concentration of heat when the working battery pack is running, and try to have a buffer zone in the lithium battery pack during operation. This buffer zone is beneficial to dissipating heat and serves as a reserve group for the next level of working battery pack. By real-time monitoring of temperature / voltage anomalies of the battery module group and monitoring with adjacent battery groups, the probability of thermal runaway is reduced, and high-adaptability battery packs are called first to reduce ineffective internal consumption.

[0037] The following uses an embodiment and combines Figure 2 , a method for dynamically adjusting the operating priority of a lithium-ion battery pack based on multi-parameter evaluation in an embodiment of the present application is described: Reference Figure 2 and Figure 3 , is a schematic diagram of a process for dynamically adjusting the operating priority of a lithium-ion battery pack based on multi-parameter evaluation in an embodiment of the present application.

[0038] S1031 . Obtain an average single-battery operating capability parameter based on the single-battery operating capability parameter, and group the working battery modules in accordance with a grouping parameter standard.

[0039] This step groups the batteries based on the single-battery operating capacity parameters obtained in the previous step. The batteries are divided into several groups based on their operating capacity. The division criteria are to take the average of all single-battery operating capacity parameters and preset grouping values ​​based on the strength of the single-battery operating capacity. For example, those 20% above the average are classified as strong groups, those below 20% are classified as weak groups, and the rest are classified as intermediate groups. When grouping, working battery groups operating in the same group prioritize single-battery modules with non-adjacent physical locations. For example, assuming the preferred physical location is (0,1), then (0,0), (0,2), and (1,1) will be marked as non-preferred single-battery modules in the same group.

[0040] S1041. Obtain an average battery operating capacity parameter of each working battery module group according to the operating capacity parameter of each single battery cell and the number of single batteries included in the working battery module group.

[0041] This step is to traverse the operating capacity parameters of all single batteries in each preset working battery module group, and add up the sum to obtain the total capacity value. Assuming that each group contains 4 single batteries, the operating capacity parameters of the 4 single batteries are accumulated and then averaged to obtain the average capacity parameter of the group.

[0042] S1042. Obtain the number of working single batteries required for operation based on the necessary working voltage data and the voltage data of each single battery module; and set the working combination priority of the working battery module group based on the number of working single batteries and the average battery operating capacity parameters of each working battery module group.

[0043] This step calculates the number of cells required for operation based on the system's real-time voltage requirement (e.g., 48V for a specific operating voltage) and the average cell voltage (e.g., 2V). The system prioritizes the number of working battery modules with higher average operating capacity parameters, ensuring that after combining several working battery modules, the number of working batteries in each module exceeds the number of cells required for operation. Prioritize working battery module modules with a number close to the required number of cells. Candidate modules are sorted in descending order by their average capacity parameters and assigned a corresponding call priority.

[0044] S1051. Based on the positioning of the working battery module group, obtain the operating capacity parameters of the battery module groups surrounding the currently operating working battery module and the priority queue of the battery module group.

[0045] This step is to define the proximity range based on the physical positioning of the working battery module group, such as the coordinate (1,1), and set the battery module groups whose coordinate distance does not exceed the preset value as the surrounding battery module groups, or the battery module groups that are directly electrically connected as the surrounding battery module groups. The group of the surrounding battery module groups is queried through the BMS database, and their average operating capacity parameters and their current position in the priority queue are obtained in real time. The data of the surrounding battery module groups is updated in the preset time period or when certain parameters mutate to monitor whether there are any abnormalities.

[0046] S1052. Based on the job combination priority queue of the working battery module group, locate the battery module group in the next job combination priority queue among the battery module groups surrounding the working battery module of the current job, and monitor the changes in the operating capacity parameters of the battery module group in the next job combination priority queue.

[0047] This step is to determine the next-priority battery module group of the current working battery module group from the preset priority queue, and combine it with the physical positioning database to screen out the battery module candidate group with the next priority around the current working group, and read the average capacity parameters, temperature, voltage and other data of the candidate group through the BMS system.

[0048] S1053: When the operating capacity parameter of the battery module group of the next job combination priority queue is less than the operating capacity parameter required by its priority queue, the job combination priority of the corresponding battery module group is re-classified.

[0049] This step is based on obtaining the operating capacity parameters of the next priority group and comparing them with the operating capacity parameters of other battery module groups in the job combination priority queue. For example, when the current working battery module group is running, the system monitors that the average operating capacity parameter of the next priority group in the surrounding battery module groups has dropped from 0.82 to 0.72 due to temperature increase, and at the same time, there is an operating capacity parameter higher than 0.72 in the job combination priority queue, which automatically triggers the re-evaluation of the job combination priority queue.

[0050] S1061. Obtain the temperature change, distance change, voltage change, and battery module group operating capability parameter change of the surrounding battery module groups to obtain a battery module group influence coefficient.

[0051] Real-time monitoring of the temperature change, distance change, voltage fluctuation, and operating capacity parameter change of the surrounding battery module groups. After normalizing these changes, the relationship between the battery module influence coefficients is obtained, that is, the different influences of each change are weighted separately. S1062. Based on the battery module group influence coefficient, obtain the unit time change of the battery module group operating capacity parameter, simulate the change relationship between the battery module group operating capacity parameter and the working time, and set the re-rating time.

[0052] Based on the relationship between the battery module influence coefficient and the change in each data per unit time, the operating capacity parameters and duration of the battery module group are simulated. The attenuation rate of the operating capacity parameters per unit time is calculated through linear regression or exponential smoothing algorithm, and an attenuation model of the operating capacity parameters is constructed. Then, the re-rating time is set according to the operating capacity parameters required for this priority and the current operating capacity parameters.

[0053] S1063: When the working time of the current working battery module group reaches the re-rating time, the operation combination priority of the working battery module group is set based on the current battery module group operation capability parameter.

[0054] When the continuous working time of the current working battery module group reaches the preset re-rating time, the latest average operating capacity parameter of the group is obtained and compared with the average operating capacity parameter of the next priority working group in the priority queue, and the working priority of the battery module group is reset.

[0055] Reference Figure 3 , which is a schematic diagram of the physical position distribution of the working battery module group during operation in an embodiment of the present application, wherein the dotted box represents the current working battery module group, which is composed of a plurality of battery modules distributed at different battery group positions.

[0056] The following describes the system in the embodiment of the present invention from the perspective of hardware processing. Figure 4 , which is a schematic diagram of the physical device structure of a lithium-ion battery pack operation management system based on multi-parameter evaluation provided in an embodiment of the present application.

[0057] It should be noted that Figure 4 The structure of the system shown is only an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0058] like Figure 4As shown, the system includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes, such as the methods described in the above embodiments, based on programs stored in a read-only memory (ROM) 302 or programs loaded from a storage unit 308 into a random access memory (RAM) 303. RAM 303 also stores various programs and data required for system operation. CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to bus 304.

[0059] The following components are connected to the I / O interface 305: an input section 306 including a camera, infrared sensor, and the like; an output section 307 including a liquid crystal display (LCD) and speakers; a storage section 308 including a hard disk and the like; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card or a modem. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. Removable media 311, such as a magnetic disk, optical disk, magneto-optical disk, or semiconductor memory, is installed in the drive 310 as needed, so that computer programs read from the media can be installed in the storage section 308 as needed.

[0060] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for executing the methods illustrated in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via the communication section 309 and / or installed from removable media 311. When executed by the central processing unit (CPU) 301, the computer program performs the various functions defined in the present invention.

[0061] It should be noted that the computer-readable medium described in the embodiments of the present invention may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present invention, a computer-readable signal medium may include a data signal transmitted in baseband or as part of a carrier wave, which carries a computer-readable computer program. Such a propagated data signal may take any of a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof.

[0062] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of the systems, methods, and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram may represent a module, program segment, or portion of code, which contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the boxes may occur in an order different from that marked in the accompanying drawings. For example, two boxes shown in succession may actually be executed substantially in parallel, or they may sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, as well as combinations of boxes in the block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified functions or operations, or may be implemented using a combination of dedicated hardware and computer instructions.

[0063] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the system described in the above embodiments, or may exist independently and not incorporated into the system. The storage medium carries one or more computer programs, and when executed by a processor of a system, the system implements the methods provided in the above embodiments.

[0064] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0065] As used in the above embodiments, the term “when…” may be interpreted as “if…” or “after…” or “in response to determining…” or “in response to detecting…”, depending on the context. Similarly, the phrases “upon determining…” or “if (stated condition or event) is detected” may be interpreted as “if determining…” or “in response to determining…” or “upon detecting (stated condition or event)” or “in response to detecting (stated condition or event)”, depending on the context.

[0066] In the above embodiments, all or part of the embodiments can be implemented using software, hardware, firmware, or any combination thereof. When implemented using software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., a floppy disk, hard disk, magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive).

[0067] Those skilled in the art will appreciate that all or part of the process steps in the above-described method embodiments can be implemented by a computer program instructing the relevant hardware. The program can be stored in a computer-readable storage medium, and when executed, the program can include the process steps in the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

[0068] The examples of this specific embodiment are all preferred embodiments of this application and are not intended to limit the scope of protection of this application. Identical components are represented by the same reference numerals. Therefore, any equivalent changes made based on the structure, shape, and principle of this application should be included in the scope of protection of this application.

Claims

1. A lithium-ion battery pack operation management method based on multi-parameter evaluation, characterized in that: include: Obtain temperature data, voltage data, SOC data, and SOH data of each single battery module in the target lithium battery pack within a preset operating time; Building a comprehensive evaluation model for battery operating capability based on the SOC data, the SOH data, and the temperature data of each battery module to obtain operating capability parameters of each battery module; Grouping and positioning the working battery modules according to the operating capacity parameters of each single battery; Preset the job combination priority queue of the working battery module group according to the average battery operating capacity parameters and the required working voltage data of each working battery module group; Based on the job combination priority queue of the working battery module group and the positioning of the working battery module group, monitoring the average operating capacity parameters of the battery module groups surrounding the working battery module group currently operating and the priority queues in which the battery module groups are located; Based on the operating data of the surrounding battery module groups, a battery module group influence coefficient is obtained, and the operation combination priority of the working battery module group is dynamically adjusted according to the battery module influence coefficient.

2. The method of claim 1 , wherein the grouping and positioning of the working battery modules is performed according to the operating capacity parameters of the individual single batteries, comprising: According to the single battery operation capability parameter, an average single battery operation capability parameter is obtained, and the working battery modules are grouped in combination with a grouping parameter standard.

3. According to claim 1, the operation combination priority queue of the working battery module group is preset according to the average battery operating capacity parameters and the required working voltage data of each working battery module group, specifically comprising: Obtaining an average battery operating capacity parameter of each working battery module group based on the operating capacity parameters of each single battery cell and the number of single batteries included in the working battery module group; According to the necessary working voltage data and the voltage data of each single battery module, the number of single battery working cells required during operation is obtained; based on the number of single battery working cells and the average battery operating capacity parameters of each working battery module group, the working combination priority of the working battery module group is set.

4. According to claim 1, based on the job combination priority queue of the working battery module group and the positioning of the working battery module group, monitoring the average operating capacity parameters of the battery module groups surrounding the working battery module group of the current job and the priority queues in which the battery module groups are located specifically includes: Based on the positioning of the working battery module group, obtaining the operating capability parameters of the battery module groups surrounding the currently operating working battery module and the priority queues of the battery module groups; Based on the job combination priority queue of the working battery module group, the battery module group in the next job combination priority queue in the battery module group around the working battery module of the current job is located, and the operating capacity parameter changes of the battery module group in the next job combination priority queue are monitored.

5. After the step of monitoring the change of the operating capability parameters of the battery module group of the next job combination priority queue according to claim 4, the method further comprises: When the operating capability parameter of the battery module group of the next job combination priority queue is less than the operating capability parameter required by its priority queue, the job combination priority of the corresponding battery module group is re-rated.

6. The method according to claim 1 , wherein the method comprises obtaining a battery module group influence coefficient based on the operating data of the surrounding battery module groups, and dynamically adjusting the operation combination priority of the working battery module group according to the battery module influence coefficient, specifically comprising: Obtaining a temperature change, a distance change, a voltage change, and a change in an operating capability parameter of a surrounding battery module group to obtain an influence coefficient of the battery module group; Based on the battery module group influence coefficient, the unit time change of the battery module group operating capability parameter is obtained, and according to the unit time change of the battery module group operating capability parameter, the operation combination priority of the working battery module group is dynamically adjusted.

7. The step of dynamically adjusting the operation combination priority of the working battery module group according to claim 6 specifically comprises: Based on the job combination priority and battery module group influence coefficient of each working battery module group, the changing relationship between the battery module group operating capacity parameters and working hours is simulated to set the re-rating time; When the working time of the current working battery module group reaches the re-rating time, the operation combination priority of the working battery module group is set based on the current battery module group operation capability parameter.

8. A lithium-ion battery pack operation management system based on multi-parameter evaluation, characterized in that: The system comprises: One or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to cause the system to execute the method according to any one of claims 1 to 7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on a system, the system is caused to perform the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product is run on a system, the system is caused to perform the method according to any one of claims 1 to 7.

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