Battery cell dynamic adjustment method, apparatus and device, and storage medium

Abstract

According to the battery monomer dynamic adjustment method, device and equipment and the storage medium, target operation state parameters corresponding to multiple battery monomers are periodically collected, historical operation data are fused according to the target operation state parameters, the abnormal levels of the multiple battery monomers in the current monitoring period are determined, and then the dynamic adjustment of the multiple battery monomers in the current monitoring period is achieved according to comprehensive operation indexes. And dynamically adjusting the charge-discharge rate, the current or the connection state of the target battery monomer. Target operation state parameters and historical operation data of a plurality of battery monomers are fused, and a pre-constructed battery monomer comprehensive operation health state evaluation model is combined to analyze a target battery monomer of which the state needs to be adjusted and an abnormal level of the target battery monomer; and state adjustment is carried out on the target single battery in combination with the abnormal level, so that the single battery is ensured to work in an efficient and safe state, and the overall performance of the energy storage system is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless energy storage, and particularly relates to a method, device, equipment and storage medium for dynamically adjusting battery monomers. Background Art

[0002] With the wide application of renewable energy globally, energy storage systems have become an essential part of modern power grids and electric vehicles. Common energy storage systems usually consist of multiple battery monomers, and these battery monomers need to be managed and balanced in terms of energy to prevent overcharging, over-discharging or unbalanced discharging of the battery due to performance differences between battery monomers. Traditional energy storage systems are limited to simple status monitoring and data transmission, lacking real-time optimization and control of the comprehensive status of battery monomers, resulting in the inability to efficiently control the overall performance of the energy storage system and posing safety hazards. Summary of the Invention

[0003] In view of this, embodiments of the present invention provide a method, device, equipment and storage medium for dynamically adjusting battery monomers. By fusing the target operating state parameters and historical operating data of multiple battery monomers, and combining with a pre-constructed comprehensive operating health status evaluation model of battery monomers, the target battery monomers that need to be adjusted in status and the comprehensive operating indicators of the target battery monomers are analyzed, and the status of the target battery monomers is adjusted in combination with the comprehensive operating indicators to ensure that the battery monomers work in an efficient and safe state, thereby improving the overall performance of the energy storage system.

[0004] The first aspect of the embodiments of the present invention provides a method for dynamically adjusting battery monomers, which is applied to an energy storage system. The energy storage system includes multiple battery monomers and a central processing system. The method for dynamically adjusting battery monomers is executed by the central processing system and includes: Periodically collect the corresponding target operating state parameters for the multiple battery monomers; Input the target operating state parameters and fuse the historical operating data of the battery monomers into a pre-constructed comprehensive operating health status evaluation model of battery monomers for analysis to determine the target battery monomers and the abnormal level of the target battery monomers in the current monitoring period; the target battery monomers are the battery monomers that need to adjust their operating status; Dynamically adjust the operating status of the target battery monomers according to the abnormal level.

[0005] In one embodiment, the target operating state parameters include battery temperature, state of charge, voltage and current; the historical operating data includes historical temperature change rate and state of charge change rate.

[0006] In one embodiment, the step of inputting the target operating state parameters and fusing the historical operating data of the battery monomers includes: Based on the historical temperature change rate and the state of charge change rate, missing values and significantly unrealistic operating state parameters in the target operating state parameters are removed, and the remaining operating state parameters are normalized.

[0007] In one embodiment, the pre-constructed comprehensive operating health state evaluation model of the battery cell includes a multi-dimensional threshold condition model, a logical judgment model, and a logical decision-making module; Inputting the target operating state parameters and fusing the historical operating data of the battery cell into the pre-constructed comprehensive operating health state evaluation model of the battery cell for analysis, to determine the target battery cell and the abnormal level of the target battery cell in the current monitoring period, includes: Inputting the normalized data into the multi-dimensional threshold condition model for analysis to obtain the first comprehensive operating index of each battery cell; Inputting the normalized data into the logical judgment model to obtain the second comprehensive operating index of each battery cell; Inputting the first comprehensive operating index and the second comprehensive operating index into the logical decision-making module for analysis to obtain the target battery cell and the abnormal level of the target battery cell in the current monitoring period.

[0008] In one embodiment, the inputting the normalized data into the multi-dimensional threshold condition model for analysis to obtain the first comprehensive operating index of each battery cell, includes: Inputting the normalized data into the multi-dimensional threshold condition model, and the multi-dimensional threshold condition model analyzes the normalized data based on a multi-level threshold system to obtain the first comprehensive operating index of each battery cell.

[0009] In one embodiment, the logical judgment model is a group pair space model constructed based on preset logical rules; Inputting the normalized data into the logical judgment model to obtain the second comprehensive operating index of each battery cell, includes: Inputting the normalized data into the group pair space model, and the group pair space model analyzes based on the preset logical rules and judgment combinations to obtain the second comprehensive operating index of each battery cell.

[0010] In one embodiment, the inputting the first comprehensive operating index and the second comprehensive operating index into the logical decision-making module for analysis to obtain the target battery cell and the abnormal level of the target battery cell in the current monitoring period, includes: Input the first comprehensive operation index and the second comprehensive operation index into the logical decision-making module. The logical decision-making module analyzes the first comprehensive operation index and the second comprehensive operation index through a predefined decision matrix to obtain the comprehensive operation scores of each battery cell. Identify the target battery cell and the abnormal level of the target battery cell based on the comprehensive operation scores. Make real-time operation and maintenance decisions for the target battery based on this abnormal level.

[0011] In the second aspect of the embodiments of the present application, a battery cell dynamic adjustment device is provided, including: An acquisition module, configured to periodically acquire the corresponding target operation state parameters for the multiple battery cells; A determination module, configured to input the target operation state parameters and fuse the historical operation data of the battery cell into a pre-constructed battery cell comprehensive operation health state evaluation model for analysis, and determine the target battery cell and the abnormal level of the target battery cell in the current monitoring period; the target battery cell is the battery cell that needs to adjust its operation state; An adjustment module, configured to dynamically adjust the operation state of the target battery cell according to the abnormal level.

[0012] In an embodiment, the target operation state parameters include battery temperature, state of charge, voltage, and current; the historical operation data includes historical temperature change rate and state of charge change rate.

[0013] In an embodiment, the determination module is specifically configured to, based on the historical temperature change rate and the state of charge change rate, remove the operation state parameters with missing values and obvious non-conformities to the actual situation in the target operation state parameters, and perform normalization processing on the remaining operation state parameters.

[0014] In an embodiment, the pre-constructed battery cell comprehensive operation health state evaluation model includes a multi-dimensional threshold condition model, a logical judgment model, and a logical decision-making module; the determination unit includes: A first obtaining subunit, configured to input the data after normalization processing into the multi-dimensional threshold condition model for analysis, and obtain the first comprehensive operation index of each battery cell; A second obtaining subunit, configured to input the normalized data into the logical judgment model, and obtain the second comprehensive operation index of each battery cell; A third obtaining subunit, configured to input the first comprehensive operation index and the second comprehensive operation into the logical decision-making module for analysis, and obtain the target battery cell and the abnormal level of the target battery cell in the current monitoring period.

[0015] In an embodiment, the first obtaining subunit is specifically configured to: The normalized data is input into the multi-dimensional threshold condition model, and the multi-dimensional threshold condition model analyzes the normalized data based on a multi-level threshold system to obtain a first comprehensive operation index of each battery cell.

[0016] In one embodiment, the logic judgment model is a pair space model constructed based on preset logic rules; the second obtaining subunit is specifically used to: The normalized data is input into the dual space model, and the dual space model performs analysis based on the preset logic rules and judgment combination to obtain a second comprehensive operation index of each battery cell.

[0017] In one embodiment, the third obtaining subunit is specifically used for: The first comprehensive operation index and the second comprehensive operation index are input into the logic decision module, and the logic decision module analyzes the first comprehensive operation index and the second comprehensive operation index through a predefined decision matrix to obtain a comprehensive operation score of each battery cell; based on the comprehensive operation score, the target battery cell and the abnormal level of the target battery cell are identified. Based on the abnormal level, a real-time operation and maintenance decision is made for the target battery.

[0018] The third aspect of an embodiment of the present application provides a battery cell dynamic adjustment device, including: a processor, a memory, and a computer program stored in the memory and executable on the processor; when the processor executes the computer program, the steps of the battery cell dynamic adjustment method described in the first aspect above are implemented.

[0019] A fourth aspect of an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the battery cell dynamic adjustment method described in the first aspect above are implemented.

[0020] The beneficial effects of the embodiments of the present application are as follows: a method, device, equipment and storage medium for dynamic adjustment of battery cells are provided, which periodically collects the corresponding target operating state parameters of multiple battery cells, and fuses the historical operating data according to the target operating state parameters to determine the abnormal level of multiple battery cells in the current monitoring cycle, and then dynamically adjusts the charge and discharge rate, current or connection state of the target battery cell according to the abnormal level. The purpose is to fuse the target operating state parameters and historical operating data of multiple battery cells, and analyze the target battery cells that need to be adjusted and the abnormal level of the target battery cells in combination with the pre-built battery cell comprehensive operating health status assessment model, and adjust the state of the target battery cells in combination with the abnormal level to ensure that the battery cells work in an efficient and safe state, thereby improving the overall performance of the energy storage system. Brief Description of the Drawings

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0022] Figure 1 It is a schematic flowchart of the implementation of the battery cell dynamic adjustment method provided by an embodiment of the present application; Figure 2 It is a schematic diagram of the battery cell dynamic adjustment device provided by an embodiment of the present application; Figure 3 It is a schematic diagram of the battery cell dynamic adjustment equipment provided by an embodiment of the present application. Detailed Embodiments

[0023] The following will describe in detail the embodiments of the technical solutions of the present application in conjunction with the drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present application, so they are only examples and cannot be used to limit the protection scope of the present application.

[0024] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above description of the drawings are intended to cover non-exclusive inclusion.

[0025] In the description of the embodiments of this application, technical terms such as "first" and "second" are only used to distinguish different objects and cannot be understood as indicating or implying relative importance or implicitly indicating the quantity, specific order or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "a plurality" means more than two unless otherwise specifically defined.

[0026] Referring to "embodiments" herein means that the specific features, structures or characteristics described in connection with the embodiments can be included in at least one embodiment of this application. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0027] In the description of the embodiments of the present application, the term "and / or" is merely a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after.

[0028] In the description of the embodiments of the present application, the term "multiple frames" refers to two or more (including two).

[0029] In the description of the embodiments of the present application, the orientation or positional relationship indicated by technical terms such as "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc. is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the embodiments of the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation to the embodiments of the present application.

[0030] The embodiments of the present invention provide a method, device, equipment and storage medium for dynamically adjusting battery cells. By fusing the target operating state parameters and historical operation data of multiple battery cells, and combining the pre-constructed comprehensive operating health state evaluation model of battery cells, the target battery cells that need to be adjusted in state and the comprehensive operating indicators of the target battery cells are analyzed, and the state of the target battery cells is adjusted in combination with the comprehensive operating indicators to ensure that the battery cells work in an efficient and safe state, thereby improving the overall performance of the energy storage system.

[0031] Please refer to Figure 1 , Figure 1 which is a schematic flowchart of the implementation of the method for dynamically adjusting battery cells provided by an embodiment of the present application. The method for dynamically adjusting battery cells is applied to an energy storage system, which includes multiple battery cells and a central processing system. The method for dynamically adjusting battery cells is implemented by the central processing system, and the central processing system can be integrated in the cloud or a local server. It can be seen that Figure 1 the method for dynamically adjusting battery cells provided by the embodiments of the present application includes: S101: Periodically collect the corresponding target operating state parameters for multiple battery cells.

[0032] The target operating state parameters include battery temperature, state of charge, voltage, and current.

[0033] In this embodiment, each battery cell is equipped with a temperature sensor (such as an NTC), a voltage / current detection circuit (such as a Hall sensor), and an SOC estimation module (such as a coulomb meter). The central processing system periodically sends a data synchronization acquisition task to a data acquisition unit such as a DAU. The DAU uses a multi-channel ADC to synchronously acquire the detection signals of each temperature sensor, voltage / current detection circuit, and SOC estimation module, and obtains the target operating state parameters corresponding to multiple battery cells.

[0034] S102: Incorporate the target operating state parameters and fuse them with the historical operating data of the battery cell, and input them into a pre-constructed comprehensive operating health status evaluation model of the battery cell for analysis to determine the target battery cell and the anomaly level of the target battery cell in the current monitoring period.

[0035] Among them, the target battery cell is the battery cell that needs to adjust its operating state.

[0036] The historical operating data includes the historical temperature change rate and the state of charge change rate in multiple different historical acquisition periods.

[0037] Incorporating the target operating state parameters and fusing them with the historical operating data of the battery cell includes: based on the historical temperature change rate and the state of charge change rate, removing the operating state parameters with missing values and those that are significantly inconsistent with the actual situation in the target operating state parameters, and normalizing the remaining operating state parameters.

[0038] Specifically, identify the missing values in the target operating state parameters (such as voltage, current, temperature, state of charge), and delete the corresponding missing values; determine the temperature change rate threshold in the historical operating data based on the temperature change rate, and remove the temperature values in the target operating state parameters that exceed the corresponding temperature change rate threshold as the values of the operating state parameters that are significantly inconsistent with the actual situation; determine the reasonable range of the state of charge based on the state of charge change rate, and remove the state of charge that does not fall within the reasonable range of the state of charge; normalize the remaining data. Through the above technical solutions, the accuracy and integrity of the data are ensured, which can more reliably reflect the performance of the battery cell and provide high-quality data input for subsequent analysis.

[0039] The pre-constructed comprehensive operating health status evaluation model of the battery cell includes a multi-dimensional threshold condition model, a logical judgment model, and a logical decision-making module.

[0040] Input the normalized data into the pre-constructed comprehensive operation health state evaluation model of a single battery cell for analysis to determine the target battery cell and the anomaly level of the target battery cell in the current monitoring period, including: input the normalized data into the multi-dimensional threshold condition model for analysis to obtain the first comprehensive operation index of each battery cell; input the normalized data into the logical judgment model to obtain the second comprehensive operation index of each battery cell; input the first comprehensive operation index and the second comprehensive operation into the logical decision-making module for analysis to obtain the target battery cell and the anomaly level of the target battery cell in the current monitoring period.

[0041] In this embodiment, the multi-dimensional threshold condition model is a condition model based on a multi-level threshold system. Input the normalized data into the multi-dimensional threshold condition model for analysis to obtain the first comprehensive operation index of each battery cell, including: input the normalized data into the multi-dimensional threshold condition model, and the multi-dimensional threshold condition model analyzes the normalized data based on the multi-level threshold system to obtain the first comprehensive operation index of each battery cell.

[0042] Specifically, the multi-dimensional threshold condition model provided in the embodiment of the present application includes a three-level threshold system condition model. The three-level threshold system condition model presets three levels of thresholds, namely safety, warning, and alarm, for each target operation state parameter. When the value of a target operation state parameter is within the corresponding threshold, it outputs the first comprehensive operation index corresponding to the state. For example, when the temperature is less than 1.2, it corresponds to the safety threshold; when the temperature is greater than or equal to 1.2 and less than 1.8, it corresponds to the warning threshold; when the temperature is greater than or equal to 1.8, it corresponds to the alarm threshold. Similarly, when the voltage is less than 0.7, it corresponds to the safety threshold; when the voltage is greater than or equal to 0.7 and less than 1.3, it corresponds to the warning threshold; when the voltage is greater than or equal to 1.3, it corresponds to the alarm threshold, etc. The state corresponding to each operation state parameter (temperature, SOC, voltage, and current) is represented by a binary code. For example, 00: represents safety, 01 represents warning, and 11 represents alarm. The first comprehensive operation index is generated by an 8-bit binary word. For example: the first comprehensive operation index can be expressed as: temperature 01 + SOC 00 + voltage 11 + current 01 → 01001101.

[0043] Exemplarily, the normalized data is input into the multidimensional threshold condition model, and the multidimensional threshold condition model analyzes the normalized data based on the multi-level threshold system to obtain the first comprehensive operation index of each battery cell, including: inputting the normalized data into the multidimensional threshold condition model, analyzing the normalized data based on the multi-level threshold system, if the value corresponding to the data crosses from the safe area to the early warning or alarm area, it needs to be continuously observed that it is consistent within a preset sampling period, such as 3 sampling periods, then the first comprehensive operation index of the corresponding state is generated; or if the value corresponding to the data falls back from the alarm or early warning area, the first comprehensive operation index of the corresponding state is immediately generated. Through this multidimensional threshold condition model, not only can the instantaneous fluctuation misjudgment be avoided, but also it can ensure that it remains in a safe state.

[0044] The logic judgment model is a pair space model constructed based on preset logic rules. The normalized data is input into the logic judgment model to obtain the second comprehensive operating index of each battery cell, including: The normalized data is input into the dual space model, and the dual space model performs analysis based on preset logic rules and judgment combinations to obtain the second comprehensive operating index of each battery cell.

[0045] Specifically, the construction process of the dual space model includes: mapping normalized data into Boolean propositions, such as: P001: temperature ∈ [0.2, 0.8] (normal range); P002: SOC change rate ≤ 0.1 / min; P003: voltage fluctuation standard deviation < 0.05; combining Boolean propositions through logical operations (such as AND / OR / NOT) to form the health status judgment rules of battery cells, output binary judgment results, and map them into continuous probability values to be compatible with probabilistic distribution. For example: emergency failure = (P001==0) OR (P002==0) temperature or SOC abnormality; aging warning = (P003==0) AND (P004==1) voltage abnormality but normal temperature. Further, the output of the logical operation combined with the Boolean proposition is mapped into a continuous probability value to facilitate the association analysis between the logic decision module and the first comprehensive operation indicator.

[0046] Exemplarily, the normalized data is input into the logical judgment model to obtain the second comprehensive operation index of each battery cell, including: inputting the normalized data into the pair space model, and the pair space model maps the normalized data into Boolean propositions, calculates the truth values (0 or 1) of each Boolean proposition through preset logical operations, and obtains the second comprehensive operation index of each battery cell according to the judgment rules (for example, 0.1 represents normal and 0.9 represents failure). Specifically, in this embodiment, the mapping is dynamically adjusted according to the importance of the operation state parameters. For example, for the output corresponding to the key judgment rule such as overheating, the corresponding mapping rule is: map 0 to a low value close to 0 (such as 0.05), representing the probability of normal, which can be understood as "low risk but not absolutely certain"; map 1 to a high value close to 1 (such as 0.95), representing the probability of abnormality, which can be understood as "high confidence abnormality". Another example is the secondary judgment rule (such as slight aging), and the corresponding mapping rule is: map 0 to a high value close to 0 (such as 0.3), which can be understood as "low risk"; map 1 to a low value close to 1 (such as 0.7), which can be understood as "abnormal".

[0047] The logical judgment model in this embodiment is the pair space model of logical judgment, which is actually a combination of a series of logical rules and judgments, and is used to judge whether the battery cell is healthy according to the circular state parameters of multiple battery cells. These logical rules can be mathematically represented by logical expressions and Boolean algebra, which is convenient for understanding and calculation. In practical applications, the construction of the logical expression and the value of the parameters need to be determined according to the diagnostic requirements of the operation parameters of the specific battery cell.

[0048] The first comprehensive operation index and the second comprehensive operation index are input into the logical decision module for analysis to obtain the target battery cell and the abnormal level of the target battery cell in the current monitoring period, including: inputting the first comprehensive operation index and the second comprehensive operation index into the logical decision module, and the logical decision module analyzes the first comprehensive operation index and the second comprehensive operation index through a predefined decision matrix, and identifies the target battery cell and the abnormal level of the target battery cell in the current monitoring period from all battery cells according to the analysis results.

[0049] Specifically, the first comprehensive operation index (the threshold system code represented by an 8-bit binary word) is used to provide discrete state classification (such as safety / warning / alarm); the second comprehensive operation index (the probability representing the state of the battery cell output by the pair model) is used to supplement the confidence of logical reasoning. The first comprehensive operation index and the second comprehensive operation index are input into the logical decision module, and the logical decision module performs fusion analysis based on the predefined decision matrix to obtain the comprehensive operation score of each battery cell; the target battery cell and the abnormal level of the target battery cell are identified based on the comprehensive operation score. Real-time operation and maintenance decisions are made on the target battery based on this abnormal level.

[0050] For example, assume that an energy storage system includes 4 battery cells (Batt1 - Batt4), and the monitoring period is 60 ms. The first comprehensive operation index (threshold system code) is an 8 - bit binary status word (each 2 bits represents an index status) output in real - time by a three - level threshold model, which are respectively represented as: The first comprehensive operation index of battery cell Batt1 is 00 01 00 11, representing voltage warning and current alarm; The first comprehensive operation index of battery cell Batt2 is 00 00 01 00, representing SOC alarm; The first comprehensive operation index of battery cell Batt3 is 11 01 00 00, representing temperature alarm and voltage warning; The first comprehensive operation index of battery cell Batt4 is 00 00 00 00, representing all normal.

[0051] The second comprehensive operation index is the failure probability (0.1 - 0.9) output by the group - even space model, which is represented as: The second comprehensive operation index of battery cell Batt1 is 0.8, representing that the internal resistance anomaly triggers P003 = 1; The second comprehensive operation index of battery cell Batt2 is 0.3, representing that the SOC fluctuates but no combination rule is triggered; The second comprehensive operation index of battery cell Batt3 is 0.95, representing that the temperature exceeds the limit (P001 = 1) AND the voltage is abnormal (P002 = 1); The second comprehensive operation index of battery cell Batt4 is 0.1, representing no anomaly.

[0052] Input the first comprehensive operation index and the second comprehensive operation index of the above four battery cells into the logic decision module. The logic decision module performs fusion analysis using a pre - defined decision matrix to obtain the comprehensive operation score of each battery cell; Identify the target battery cell and the abnormal level of the target battery cell based on the comprehensive operation score. Make real - time operation and maintenance decisions for the target battery based on this abnormal level.

[0053] For example, the analysis process for battery cell Batt1: The input is: 00 01 00 11 and 0.8; The comprehensive operation score obtained after fusion analysis based on the decision matrix is 75, and the corresponding abnormal level is a serious anomaly. Another example is the analysis process for battery cell Batt3: The input is: 11 01 00 00 and 0.95; The comprehensive operation score obtained after fusion analysis based on the decision matrix is 95, and the corresponding abnormal level is an emergency fault.

[0054] Exemplarily, the pre - defined decision matrix can be represented by Table 1 below: Table 1 S103: Dynamically adjust the operation state of the target battery cell according to the abnormal level.

[0055] For example, the anomaly level of battery cell Batt1 is a severe anomaly, triggering the shutdown and maintenance process of this battery cell Batt1. Another example is that the anomaly level of battery cell Batt3 is an emergency fault, triggering this battery cell Batt2 to immediately cut off the circuit and give an alarm.

[0056] Through the above analysis, it can be seen that the battery cell dynamic regulation method provided by the embodiments of the present application, for multiple battery cells, periodically collects their corresponding target operating state parameters, and based on the target operating state parameters, fuses the historical operating data to determine the anomaly levels of the multiple battery cells in the current monitoring period. Furthermore, according to the anomaly levels, dynamically adjusts the charge and discharge rates, currents, or connection states of the target battery cells. The aim is to fuse the target operating state parameters and historical operating data of multiple battery cells, analyze the target battery cells that need to be adjusted in state and the anomaly levels of the target battery cells in combination with a pre-constructed comprehensive operating health state assessment model for battery cells, and perform state regulation on the target battery cells in combination with the anomaly levels to ensure that the battery cells work in an efficient and safe state, thereby improving the overall performance of the energy storage system.

[0057] Please refer to Figure 2 , Figure 2 which is a schematic diagram of a battery cell dynamic regulation device provided by an embodiment of the present application. Each module or unit included in the battery cell dynamic regulation device 20 provided in this embodiment is used to execute Figure 1 the respective steps in the corresponding embodiment. Specifically, please refer to Figure 1 the relevant descriptions in the corresponding embodiment. For the sake of clarity, only the parts related to this embodiment are shown. Refer to Figure 3 , the battery cell dynamic regulation device 20 includes: An acquisition module 210, configured to periodically acquire the corresponding target operating state parameters for the multiple battery cells; A determination module 220, configured to input the target operating state parameters and fuse the historical operating data of the battery cells into a pre-constructed comprehensive operating health state assessment model for battery cells for analysis, to determine the target battery cells and the anomaly levels of the target battery cells in the current monitoring period; the target battery cells are the battery cells that need to adjust their operating states; An adjustment module 230, configured to dynamically adjust the operating states of the target battery cells according to the anomaly levels.

[0058] In one embodiment, the target operating state parameters include battery temperature, state of charge, voltage, and current; the historical operating data includes historical temperature change rate and state of charge change rate.

[0059] In one embodiment, the determining module 220 is specifically configured to remove the operation state parameters with missing values and obvious non - conforming to the actual situation from the target operation state parameters based on the historical temperature change rate and the state of charge change rate, and perform normalization processing on the remaining operation state parameters.

[0060] In one embodiment, the pre - constructed comprehensive operation health state evaluation model of the battery cell includes a multi - dimensional threshold condition model, a logical judgment model, and a logical decision - making module; The determining unit includes: The first obtaining subunit is configured to input the data after normalization processing into the multi - dimensional threshold condition model for analysis, and obtain the first comprehensive operation index of each battery cell; The second obtaining subunit is configured to input the normalized data into the logical judgment model, and obtain the second comprehensive operation index of each battery cell; The third obtaining subunit is configured to input the first comprehensive operation index and the second comprehensive operation into the logical decision - making module for analysis, and obtain the target battery cell and the abnormal level of the target battery cell in the current monitoring period.

[0061] In one embodiment, the first obtaining subunit is specifically configured to: Input the data after normalization processing into the multi - dimensional threshold condition model, and the multi - dimensional threshold condition model analyzes the data after normalization processing based on a multi - level threshold system to obtain the first comprehensive operation index of each battery cell.

[0062] In one embodiment, the logical judgment model is a group - even space model constructed based on preset logical rules; the second obtaining subunit is specifically configured to: Input the data after normalization processing into the group - even space model, and the group - even space model analyzes based on the preset logical rules and judgment combinations to obtain the second comprehensive operation index of each battery cell.

[0063] In one embodiment, the third obtaining subunit is specifically configured to: Input the first comprehensive operation index and the second comprehensive operation index into the logical decision - making module, and the logical decision - making module analyzes the first comprehensive operation index and the second comprehensive operation index through a predefined decision matrix to obtain the comprehensive operation score of each battery cell; identify the target battery cell and the abnormal level of the target battery cell based on the comprehensive operation score. Make real - time operation and maintenance decisions on the target battery based on this abnormal level.

[0064] Please refer to Figure 3 , Figure 3Schematic diagram of a battery cell dynamic regulation device provided by an embodiment of the present application. As can be seen from Figure 3 , the battery cell dynamic regulation device 300 includes: a processor 310, a memory 320, and a computer program 330 stored in the memory 320 and executable on the processor 310; when the processor 310 executes the computer program 330, the steps in the above-mentioned embodiments of various battery cell dynamic regulation methods are implemented, such as Figure 1 the steps S101 to S103 shown. Alternatively, when the processor 310 executes the computer program 330, the functions of each module / unit in the above-mentioned device embodiments are implemented, such as Figure 2 the functions of the modules 210 to 230 shown.

[0065] Exemplarily, the computer program 330 can be divided into one or more modules / units. One or more modules / units are stored in the memory 320 and executed by the processor 310 to complete the present application. One or more modules / units can be a series of computer program instruction segments capable of performing specific functions, and these instruction segments are used to describe the execution process of the computer program 330 in the battery cell dynamic regulation device. For example, the computer program 330 can be divided into an acquisition module, a determination module, and an adjustment module.

[0066] The battery cell dynamic regulation device provided in this embodiment may include, but is not limited to, a processor and a memory. Those skilled in the art can understand that Figure 3 this is only an example of the battery cell dynamic regulation device, and does not constitute a limitation on the battery cell dynamic regulation device. It may include more or fewer components than shown in the figure, or combine certain components, or different components. For example, the battery cell dynamic regulation device may further include input / output devices, network access devices, buses, etc.

[0067] The so-called processor 310 may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0068] The memory 320 may be an internal storage unit of the battery cell dynamic regulation device, such as the hard disk or memory of the battery cell dynamic regulation device. The memory 320 may also be an external storage device of the battery cell dynamic regulation device, such as a plug-in hard disk equipped on the battery cell dynamic regulation device, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. Further, the battery cell dynamic regulation device may also include both an internal storage unit of the battery cell dynamic regulation device and an external storage device. The memory 320 is used to store computer programs and other programs and data required by the battery cell dynamic regulation device. The memory 320 may also be used to temporarily store data that has been output or will be output.

[0069] It should be noted that for the content such as information interaction and execution process between the above-mentioned devices / units, since it is based on the same concept as the method embodiment of the present application, for its specific functions and the technical effects brought, reference can be specifically made to the method embodiment part, and details are not described herein again.

[0070] The embodiment of the present application also provides a network device, which includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor. When the processor executes the computer program, the steps in any of the above method embodiments are implemented.

[0071] The embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps in the above method embodiments can be implemented.

[0072] The embodiment of the present application provides a computer program product. When the computer program product runs on a mobile terminal, the mobile terminal is enabled to implement the steps in the above method embodiments when executed.

[0073] When the integrated unit 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, to implement all or part of the processes in the above method embodiments of this application, a computer program can be used to instruct the relevant hardware to complete. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the photographing device / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium. For example, USB flash drive, mobile hard disk, magnetic disk or optical disc, etc. In some jurisdictions, according to legislation and patent practice, the computer-readable medium cannot be an electrical carrier signal and a telecommunication signal.

[0074] In the above embodiments, the descriptions of the respective embodiments have their own focuses. For the parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0075] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0076] In the embodiments provided in this application, it should be understood that the disclosed device / network device and method can be implemented in other ways. For example, the device / network device embodiments described above are only illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some interfaces. The indirect coupling or communication connection of the device or unit can be in an electrical, mechanical or other form.

[0077] The unit described as a separation component may or may not be physically separated. The component shown as a unit may or may not be a physical unit, that is, it may be located in one place or may be distributed across multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0078] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for dynamically adjusting a battery cell, characterized in that, Applied to an energy storage system, the energy storage system includes a plurality of battery cells and a central processing system, and the battery cell dynamic adjustment method is executed by the central processing system, including: Periodically collect the corresponding target operating state parameters for the plurality of battery cells; Input the target operating state parameters and fuse the historical operating data of the battery cells into a pre-constructed comprehensive operating health state evaluation model of the battery cells for analysis to determine the target battery cell and the abnormal level of the target battery cell in the current monitoring period; the target battery cell is the battery cell that needs to adjust its operating state; Dynamically adjust the operating state of the target battery cell according to the abnormal level.

2. The battery cell dynamic regulation method according to claim 1, wherein, The target operating state parameters include battery temperature, state of charge, voltage, and current; the historical operating data includes historical temperature change rates and state of charge change rates in a plurality of different historical collection periods.

3. The battery cell dynamic regulation method according to claim 2, characterized in that, The inputting the target operating state parameters and fusing the historical operating data of the battery cells includes: Based on the historical temperature change rate and the state of charge change rate, remove the operating state parameters with missing values and significantly unrealistic ones in the target operating state parameters, and normalize the remaining operating state parameters.

4. The battery cell dynamic regulation method according to claim 3, characterized in that, The pre-constructed comprehensive operating health state evaluation model of the battery cells includes a multi-dimensional threshold condition model, a logical judgment model, and a logical decision-making module; The inputting the target operating state parameters and fusing the historical operating data of the battery cells into a pre-constructed comprehensive operating health state evaluation model of the battery cells for analysis to determine the target battery cell and the abnormal level of the target battery cell in the current monitoring period includes: Input the normalized data into the multi-dimensional threshold condition model for analysis to obtain the first comprehensive operating index of each battery cell; Input the normalized data into the logical judgment model to obtain the second comprehensive operating index of each battery cell; Input the first comprehensive operating index and the second comprehensive operating index into the logical decision-making module for analysis to obtain the target battery cell and the abnormal level of the target battery cell in the current monitoring period.

5. The battery cell dynamic regulation method according to claim 4, wherein The inputting the normalized data into the multi-dimensional threshold condition model for analysis to obtain the first comprehensive operating index of each battery cell includes: Input the normalized data into the multi-dimensional threshold condition model, and the multi-dimensional threshold condition model analyzes the normalized data based on a multi-level threshold system to obtain the first comprehensive operating index of each battery cell.

6. The method for dynamically adjusting a battery cell according to claim 4, wherein, The logical judgment model is a paired space model constructed based on preset logical rules; Input the normalized data into the logical judgment model to obtain the second comprehensive operating index of each battery cell, including: Input the normalized data into the paired space model, and the paired space model analyzes based on the preset logical rules and judgment combinations to obtain the second comprehensive operating index of each battery cell.

7. The method for dynamically adjusting a battery cell according to claim 4, characterized in that, Inputting the first comprehensive operation index and the second comprehensive operation index into the logical decision module for analysis to obtain the target battery cell and the abnormal level of the target battery cell in the current monitoring period includes: Inputting the first comprehensive operation index and the second comprehensive operation index into the logical decision module, and the logical decision module analyzes the first comprehensive operation index and the second comprehensive operation index through a predefined decision matrix to obtain the comprehensive operation scores of each battery cell; identifying the target battery cell and the abnormal level of the target battery cell based on the comprehensive operation scores; and making real-time operation and maintenance decisions on the target battery based on this abnormal level.

8. A battery cell dynamic regulation device, characterized in that, Including: A collection module for periodically collecting the corresponding target operation state parameters for the multiple battery cells. A determination module for inputting the target operation state parameters and fusing the historical operation data of the battery cells into a pre-constructed battery cell comprehensive operation health state evaluation model for analysis to determine the target battery cell and the abnormal level of the target battery cell in the current monitoring period. An adjustment module for dynamically adjusting the operation states of the multiple battery cells according to the abnormal level.

9. A battery cell dynamic regulation device, characterized in that, Including: A processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the method according to any one of claims 1 to 7.

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