A battery cluster dynamic balancing control method and system of an industrial and commercial energy storage system

Abstract

The application provides a battery cluster dynamic balancing control method and system of a commercial energy storage system, and relates to the technical field of electric energy storage systems. The method is based on a master-slave architecture, and the following core steps are executed by the master node: monitoring all slave node SOC data update states, and starting the balancing process when the global trigger condition is met; classifying and initially locking the battery cluster based on the composite conditions of SOC, state of charge and fault flag; dynamically executing the scheduling strategy of unlocking the high SOC cluster or locking the low SOC cluster according to the qualified cluster information and the operating scene; and finally performing forced safety verification and globally synchronizing the control instruction. The corresponding system comprises a control module, a plurality of battery cluster management modules and a communication module. Through the composite condition verification, scene adaptive scheduling and hierarchical delay locking technology, the application effectively solves the problem of unbalanced electricity between multiple battery clusters, and improves the system energy utilization, operating stability and battery life.

Description

Technical Field

[0001] This invention relates to the field of energy storage system technology, and in particular to a method and system for dynamic equalization control of battery clusters in industrial and commercial energy storage systems. Background Technology

[0002] With the widespread application of renewable energy and the improvement of power system intelligence, commercial and industrial energy storage (hereinafter referred to as "commercial and industrial storage") systems are playing an increasingly important role in peak-valley electricity price arbitrage, demand-side response, backup power supply, and smoothing of new energy fluctuations. As an important load and energy interaction unit in commercial and industrial storage systems, the charging pile module and its coordinated control efficiency with the energy storage body directly determine the operating efficiency, stability, and economy of the entire system.

[0003] In existing industrial and commercial energy storage systems, multiple battery modules are typically connected in parallel to meet power and capacity requirements. However, due to inherent differences in manufacturing processes, initial conditions, operating environments, and cycle life, the actual State of Charge (SOC) of each module exhibits significant inconsistencies after multiple charge-discharge cycles. When the system discharges through a charging station, this inconsistency leads to more severe energy dispatching problems: modules with higher SOCs bear a greater discharge load, while modules with lower SOCs may reach their cutoff voltage prematurely, triggering the system's minimum protection threshold and forcing the entire charging station module to shut down. At this point, some high-SOC modules often have unused remaining charge, while low-SOC modules may experience accelerated aging or even damage due to over-discharge.

[0004] Currently, mainstream solutions to battery imbalance problems in the industry are mostly focused on static or semi-static Battery Management Systems (BMS), such as trickle balancing at the end of charging or dissipative balancing when batteries are idle. While these methods can alleviate voltage differences at the cell level to some extent, they have inherent drawbacks such as slow balancing speed, high energy loss, and the inability to perform dynamic and proactive inter-cluster energy scheduling during system operation (especially high-current discharge). In addition, existing systems lack deep integration with the charging pile's discharge control logic, and cannot intelligently determine which battery clusters to engage or disengage based on real-time load demand and the SOC state of each battery cluster.

[0005] Another common approach is to use a simple rotation or fixed priority strategy, but this is slow to respond and cannot adapt to rapid changes in load. Furthermore, when a single battery cluster fails, the system's redundancy switching and fault recovery mechanisms are not robust enough, which can easily trigger a chain reaction of failures and reduce system reliability.

[0006] Therefore, there is an urgent need in this field for a multi-battery cluster balancing control method that can be linked in real time with the discharge control of charging piles, dynamically sense the status of each battery cluster, and have intelligent decision-making capabilities, in order to solve the problems of low energy utilization, short system running time, rapid battery life loss, and insufficient overall reliability in the existing technology. Summary of the Invention

[0007] To address these issues, embodiments of the present invention provide a method and system for dynamic equalization control of battery clusters in industrial and commercial energy storage systems, which solves problems such as low energy utilization, short system operating time, rapid battery life loss, and insufficient overall reliability in the prior art.

[0008] To address the aforementioned technical problems, embodiments of the present invention provide a dynamic equalization control method for battery clusters in an industrial and commercial energy storage system. The system includes a master node and multiple slave nodes, with each slave node managing one battery cluster. The method includes:

[0009] Step S1: The master node continuously monitors the SOC data update status from all slave nodes. When it determines that the preset global triggering conditions are met, it initiates a load balancing control process.

[0010] Step S2: Based on the start of step S1, the master node immediately traverses all battery clusters and classifies each battery cluster into a qualified cluster or a disabled cluster according to the composite conditions composed of its SOC value, charging status and fault flag, and performs initial locking on the disabled clusters.

[0011] Step S3: Based on the qualified cluster information obtained from the classification, the master node first sorts the qualified clusters by SOC, then identifies the system operation scenario based on the comparison between the number of currently running clusters and the number of qualified clusters, and finally dynamically calculates the number and target of battery clusters that need to be unlocked or locked based on the identified operation scenario, and executes the corresponding control operation.

[0012] Step S4: The master node traverses all battery clusters again, performs a final safety check based on the composite conditions in step S2, enforces a lockout on battery clusters that do not meet the conditions, and finally synchronizes the updated global control instructions to all slave nodes.

[0013] Preferably, the preset global triggering condition in step S1 is: within a single computing cycle, confirming receipt of SOC update signals from all slave nodes, or waiting for a duration that reaches a preset timeout threshold.

[0014] Preferably, the composite conditions in step S2 are as follows: the SOC value of the battery cluster is greater than a preset charging threshold, it is not in a charging state, and there is no fault mark; at the same time, for battery clusters that do not meet any of the conditions, a lockout operation is performed and its fault history status is recorded.

[0015] Preferably, in step S3, the identified operating scenarios include insufficient available clusters, overload operation, and redundant operation;

[0016] in,

[0017] When it is identified that there are not enough available clusters, the operation performed is to unlock the highest preset number of battery clusters in the SOC;

[0018] When an overload is detected, the operation performed is to unlock a corresponding number of high-SOC battery clusters based on the number of notches.

[0019] When redundant operation is identified, the operation performed is based on the number of redundancies and, after a variable delay condition is met, the corresponding number of low SOC battery clusters are locked out.

[0020] Preferably, the variable delay condition is dynamically adjusted according to whether the system is in an alarm state, and the delay period in the alarm state is longer than the delay period in the non-alarm state.

[0021] Preferably, the forced locking in step S4 has the highest priority and covers any unlocking operation performed in step S3 to ensure security.

[0022] This invention also provides a dynamic balancing control system for battery clusters in industrial and commercial energy storage systems. This system is used to implement the aforementioned dynamic balancing control method for battery clusters in industrial and commercial energy storage systems, including:

[0023] The control module, configured as the master node, is used to execute the battery cluster dynamic balancing control method of the industrial and commercial energy storage system.

[0024] Multiple battery cluster management modules are configured as slave nodes. Each battery cluster management module is responsible for collecting and managing the status information of a battery cluster and executing control commands from the control module.

[0025] The communication module connects the control module and all battery cluster management modules, and is used to establish a data interaction channel between the master node and the slave node.

[0026] Preferably, the communication module adopts a CAN bus network, and the control module and the battery cluster management module periodically report status data and issue commands through a predefined communication protocol.

[0027] Preferably, the system further includes a power control interface module, which connects to the DC-DC converter of each battery cluster via an emergency stop signal line to achieve emergency shutdown control.

[0028] This invention also provides a computer storage medium storing a computer software product, the computer software product including several instructions to cause a computer device to execute the above-described dynamic equalization control method for battery clusters in industrial and commercial energy storage systems.

[0029] As can be seen from the above technical solutions, this invention application has the following beneficial effects:

[0030] (1) Significantly improves system energy utilization efficiency and power supply reliability: Through the "qualified cluster" priority scheduling strategy based on SOC dynamic sorting, the system can prioritize the use of battery clusters with sufficient power and intelligently unlock high SOC clusters when overloaded. This effectively avoids the "barrel effect" that causes the entire system to stop supplying power prematurely due to the depletion of power in individual battery clusters, ensuring that loads such as charging piles can operate continuously and stably, maximizing the release of available energy in the energy storage system, and significantly improving energy utilization efficiency and system discharge time.

[0031] (2) Enhancing the safety and robustness of system operation: This invention introduces a composite condition verification mechanism based on SOC, charging status, and fault flags, and a final mandatory safety interlock verification. These two safety defenses ensure that any battery cluster that does not meet the conditions (such as low SOC or faulty battery) will be effectively isolated, fundamentally preventing safety risks such as over-discharge and fault propagation. At the same time, the graded delay interlock technology dynamically adjusts the operation delay according to the alarm status in redundant scenarios, effectively suppressing frequent equipment switching caused by instantaneous load fluctuations, and improving the stability and anti-interference capability of the system under complex operating conditions.

[0032] (3) Optimize battery cluster lifecycle and achieve intelligent operation and maintenance: This invention uses a scenario-adaptive dynamic scheduling strategy to intelligently adjust the number of battery clusters put into operation according to actual load demand. In redundant scenarios, the system can automatically put low-SOC or redundant battery clusters into hibernation, achieving balanced load distribution and rotation. This "on-demand allocation and orderly rotation" mode reduces the overuse and cycle loss of individual battery clusters, balances system efficiency and battery life, extends the overall service life of the battery pack, and reduces the long-term operation and maintenance cost of the system. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly described below. Referring to the drawings will make the features and advantages of the present invention clearer. The drawings are illustrative and should not be construed as limiting the present invention in any way. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0034] Figure 1This is a flowchart of a dynamic equalization control method for battery clusters in an industrial and commercial energy storage system provided by the present invention.

[0035] Figure 2 This is a block diagram of a battery cluster dynamic balance control system for an industrial and commercial energy storage system provided by the present invention. Detailed Implementation

[0036] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0037] Example 1: To address the problems of low energy utilization, short system uptime, rapid battery life loss, and insufficient overall reliability in existing technologies, such as... Figure 1 As shown, this embodiment provides a method for dynamic balancing control of battery clusters in an industrial and commercial energy storage system. The system includes a master node and multiple slave nodes, with each slave node managing one battery cluster. The method includes:

[0038] Step S1: The master node continuously monitors the SOC data update status from all slave nodes. When it determines that the preset global triggering conditions are met, it initiates a load balancing control process.

[0039] Step S2: Based on the start of step S1, the master node immediately traverses all battery clusters and classifies each battery cluster into a qualified cluster or a disabled cluster according to the composite conditions composed of its SOC value, charging status and fault flag, and performs initial locking on the disabled clusters.

[0040] Step S3: Based on the qualified cluster information obtained from the classification, the master node first sorts the qualified clusters by SOC, then identifies the system operation scenario based on the comparison between the number of currently running clusters and the number of qualified clusters, and finally dynamically calculates the number and target of battery clusters that need to be unlocked or locked based on the identified operation scenario, and executes the corresponding control operation.

[0041] Step S4: The master node traverses all battery clusters again, performs a final safety check based on the composite conditions in step S2, enforces a lockout on battery clusters that do not meet the conditions, and finally synchronizes the updated global control instructions to all slave nodes.

[0042] As can be seen from the above technical solution, the present invention proposes a dynamic equalization control method for battery clusters in industrial and commercial energy storage systems. The present invention realizes intelligent equalization management of multiple battery clusters in industrial and commercial energy storage systems through a closed-loop control process executed by the master node, including trigger monitoring, classification interlocking, dynamic scheduling, and safety synchronization. Specifically: step S1 ensures continuous and timely equalization response; step S2 lays the foundation for the safe and stable operation of the system; step S3 directly achieves the core objectives of load on demand allocation and efficient energy utilization; and step S4 serves as the highest priority final safety barrier, jointly ensuring the overall reliability of the system and battery life.

[0043] Specifically, this embodiment provides a concrete implementation of a dynamic balancing control method for battery clusters in an industrial and commercial energy storage system. The system adopts a master-slave architecture, including one master node and multiple slave nodes, with each slave node managing one battery cluster. The specific process of this method includes the following steps:

[0044] In step S1, trigger condition judgment is performed: After the master node powers on, it confirms its master node identity by checking its own address (e.g., uwParallelAddress==1). The master node continuously monitors the SOC data update status from all slave nodes. In this embodiment, a loop counter (e.g., WaitTime) and an update flag (e.g., ubPallSocUpdata) are set. The preset global trigger condition is: within a single calculation cycle, it confirms that it has received SOC update signals from all slave nodes (i.e., ubPallSocUpdata>= the total number of nodes connected in parallel in the system), or the number of loop waits reaches a preset timeout threshold (e.g., 500 loops). Once either condition is met, the master node resets the counter and update flag, and sets the calculation start flag (e.g., StartCalFlag=1), thereby starting a new equalization control process.

[0045] In step S2, battery cluster state classification and initial locking are performed: Based on the startup in step S1, the master node immediately traverses all battery clusters in the system. It classifies and filters the state of each battery cluster according to a composite condition, which includes:

[0046] 1. The SOC value is greater than a preset charging threshold (for example, it can be set to 30% of the total battery capacity).

[0047] 2. Not in charging state (this can be determined by checking if the corresponding bit of the status word ChgstaRUnio is 1);

[0048] 3. No fault flag (i.e., ubPallFaultFlag[i]==0).

[0049] Battery clusters that meet all three conditions are classified as "qualified clusters". Battery clusters that do not meet any of the conditions (i.e., low SOC, charging, or faulty) are classified as "disabled clusters". The master node immediately performs an initial latching operation on these disabled clusters (e.g., by setting the corresponding DC-DC latching control bit) and records their fault history state (e.g., ubPallFaultFlagLast) for verification during fault recovery.

[0050] In step S3, dynamic scheduling is performed: Following step S2, the master node performs dynamic scheduling based on the qualified cluster information obtained after classification.

[0051] First, the master node sorts all eligible clusters in descending order of their SOC values ​​(e.g., using a bubble sort algorithm) to prioritize scheduling battery clusters with high SOC values.

[0052] Subsequently, the master node identifies the current operating scenario of the system by comparing the number of clusters currently in operation (UsedPackNum) with the total number of qualified clusters (EnablePackNum). The main scenarios include:

[0053] Scenario 1: Insufficient available clusters. When EnablePackNum is too small to meet basic operating requirements, the system executes a conservative strategy, directly unlocking the highest preset number of battery clusters (e.g., 2) of the SOC to quickly ensure system power supply.

[0054] Scenario 2: Overload Operation. When UsedPackNum is less than EnablePackNum, but the system still senses insufficient power, it indicates an overload scenario. The system calculates the number of battery clusters that need to be unlocked, NeedNum, using the formula NeedNum = (EnablePackNum + 2) - UsedPackNum. Then, in descending order of SOC, the first NeedNum high-SOC battery clusters are unlocked.

[0055] Scenario 3: Redundant Operation. When UsedPackNum is much smaller than EnablePackNum, indicating resource redundancy, the system sorts qualified clusters in ascending order of SOC. Then, it calculates the number of redundant clusters to be latched, NeedNum (e.g., NeedNum = UsedPackNum - EnablePackNum). To avoid frequent switching due to load fluctuations, this embodiment introduces a tiered delay mechanism: in the absence of alarms, the latching operation is performed after a delay of 10 system cycles; in the presence of alarms, the delay is extended to 100 system cycles to enhance stability. After the delay, the system latches the top-ranked (i.e., lowest SOC) NeedNum battery clusters.

[0056] In step S4, safety verification and global synchronization are performed: After the dynamic scheduling in step S3, the master node again traverses all battery clusters and performs a final safety verification based on the same composite conditions in step S2. This step is the highest priority mandatory safety measure. For battery clusters with a SOC value below the charging threshold or whose faults have not yet been resolved, a mandatory latch-up operation is performed regardless of their state in step S3. This ensures that, under any circumstances, unsafe or unstable battery clusters will not be put into operation.

[0057] Finally, the master node synchronously sends the updated global control commands (represented by the final state of all DC-DC control bits, such as the uwControlDcdcFlag bitmap) to all slave nodes through the communication network, thereby completing a full balanced control cycle.

[0058] Fault recovery mechanism: During system operation, if a previously disabled battery cluster is cleared of fault and its SOC value recovers to a level greater than the charging threshold, the system will unlock its blocking state in subsequent traversals and reset the corresponding fault history, allowing it to rejoin the qualified cluster candidate pool and participate in subsequent dynamic scheduling.

[0059] To further verify the advantages of the present invention, the following specific experiments will be conducted.

[0060] Experimental equipment: An experimental platform for an industrial and commercial energy storage system containing ten battery clusters was built, and the control method of this invention was applied for testing.

[0061] Experimental Results: Experimental results show that this method can effectively solve the problem of uneven power distribution among multiple battery modules. Under simulated charging pile discharge conditions, the system can intelligently and smoothly switch the operating battery clusters according to load changes and the SOC status of each cluster, avoiding the problems of over-discharge of a single cluster or premature shutdown of the entire system due to minimum SOC protection. This significantly improves the overall discharge time, energy utilization efficiency, and battery life of the system. At the same time, the stability and safety of the system are effectively guaranteed.

[0062] Example 2: This example provides a dynamic balancing control system for battery clusters in an industrial and commercial energy storage system. This system is used to implement the dynamic balancing control method for battery clusters in the industrial and commercial energy storage system of Example 1. Its system block diagram can be found in [reference needed]. Figure 2 As shown. The system specifically includes:

[0063] The control module, configured as the master node, is used to execute the dynamic balancing control method for battery clusters in industrial and commercial energy storage systems.

[0064] Multiple battery cluster management modules are configured as slave nodes. Each battery cluster management module is responsible for collecting and managing the status information of a battery cluster and executing control commands from the control module.

[0065] The communication module connects the control module and all battery cluster management modules, and is used to build a data interaction channel between the master node and the slave node.

[0066] Specifically, in this embodiment, the control module is configured as the master node. This module typically consists of a high-performance microprocessor or microcontroller, running embedded software, and is responsible for executing all the logic of the aforementioned dynamic balancing control method for battery clusters, including state monitoring, data calculation, strategy decision-making, and instruction generation. It is the brain of the entire system, performing global coordination.

[0067] Multiple battery cluster management modules are configured as slave nodes. Each module is responsible for collecting and managing the status information of one battery cluster and executing control commands from the control module. Each slave node corresponds to one battery cluster and is responsible for collecting analog quantities such as voltage, current, and temperature of that battery cluster in real time and calculating the accurate SOC value. Simultaneously, it receives and executes DC-DC switching commands from the control module, directly controlling the start and stop of the DC-DC converters connected to that battery cluster.

[0068] The communication module connects the control module and all battery cluster management modules, establishing a reliable data exchange channel between the master and slave nodes. The communication module uses a CAN bus network, and the control module and battery cluster management module periodically report status data and issue commands via a predefined communication protocol. In this embodiment, the communication module uses a CAN 2.0B standard-based communication bus network with a communication rate of 500kbps. Its physical layer conforms to the ISO 11898-2 standard, and it employs twisted-pair shielded transmission to enhance anti-interference capabilities. The communication protocol specifies that the node ID is software-defined, ranging from 1 to 10; slave nodes periodically report their status data to the master node every 100ms; and the master node, upon receiving the data, typically completes calculations and responds with control commands within 50ms.

[0069] The system of this invention also includes a power control interface module, which serves as an optional safety enhancement module. This control module is connected to the power control interface module (power control board) via an RS485 bus, and the power control board is connected via hardwired connections (such as emergency stop signal lines) to the DC-DC converters of each battery cluster. This path is used to transmit the highest priority emergency shutdown command, serving as hardware safety redundancy in addition to communication control.

[0070] This embodiment provides a battery cluster dynamic balancing control system for an industrial and commercial energy storage system, used to implement the aforementioned battery cluster dynamic balancing control method for an industrial and commercial energy storage system. Therefore, the specific implementation of the battery cluster dynamic balancing control system for an industrial and commercial energy storage system can be found in the previous section on the embodiment of the battery cluster dynamic balancing control method for an industrial and commercial energy storage system. To avoid redundancy, it will not be repeated here.

[0071] Example 3: This embodiment of the invention provides a computer storage medium storing computer software products. The computer software products include several instructions to cause a computer device to execute the above-described dynamic equalization control method for battery clusters in industrial and commercial energy storage systems.

[0072] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0073] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0074] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The functions specified in one or more boxes. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable apparatus for implementing the process. Figure 1One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0075] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A method for dynamic balancing control of battery clusters of a commercial and industrial energy storage system, the system comprising a master node and a plurality of slave nodes, each slave node managing one battery cluster, characterized in that, The method comprises: Step S1: The master node continuously monitors the SOC data update status from all slave nodes, and initiates a balancing control process when it is determined that a preset global trigger condition is met; the preset global trigger condition is that, within a single calculation period, it is confirmed that the SOC update signals of all slave nodes are received, or the waiting duration reaches a preset timeout threshold; Step S2: Based on the initiation of step S1, the master node immediately traverses all battery clusters, classifies each battery cluster as a qualified cluster or a disabled cluster according to a composite condition composed of the SOC value, the charging state and the fault flag of the battery cluster, and performs initial locking on the disabled cluster; Step S3: Based on the qualified cluster information obtained through classification, the master node first sorts the qualified clusters according to the SOC, then identifies the system running scenario according to the comparison relationship between the number of currently running clusters and the number of qualified clusters, and finally dynamically calculates the number and target of battery clusters that need to be unlocked or locked according to the identified running scenario, and performs corresponding control operations; the identified running scenarios include insufficient available clusters, overload running and redundant running; Wherein, When it is identified as insufficient available clusters, the operation performed is to unlock a preset number of battery clusters with the highest SOC; When it is identified as overload running, the operation performed is to unlock a corresponding number of high-SOC battery clusters based on the gap number; When it is identified as redundant running, the operation performed is to lock a corresponding number of low-SOC battery clusters based on the redundancy number and after a variable delay condition is met; the variable delay condition is dynamically adjusted according to whether the system is in an alarm state, and the delay period in the alarm state is longer than that in the non-alarm state; Step S4: The master node traverses all battery clusters again, performs final safety verification based on the composite condition in step S2, performs forced locking on the battery clusters that do not meet the condition, and finally synchronizes the updated global control instructions to all slave nodes; 2. The battery string dynamic equalization control method of a commercial energy storage system according to claim 1, characterized by, The composite condition in step S2 is specifically that the SOC value of the battery cluster is greater than a preset charging threshold, the battery cluster is not in a charging state, and the battery cluster has no fault flag; at the same time, for the battery cluster that does not meet any condition, a locking operation is performed and its fault history state is recorded.

3. The battery string dynamic equalization control method of commercial and industrial energy storage systems of claim 1, wherein, The forced locking in step S4 has the highest priority and overrides any unlocking operation made in step S3, to ensure safety.

4. A battery cluster dynamic equalization control system for a commercial and industrial energy storage system, characterized by, The system is used to implement the battery cluster dynamic balancing control method of the industrial and commercial energy storage system according to any one of claims 1 to 3, and comprises: A control module configured as the master node, used to execute the battery cluster dynamic balancing control method of the industrial and commercial energy storage system; A plurality of battery cluster management modules configured as the slave nodes, each responsible for collecting and managing the state information of one battery cluster, and executing the control instructions from the control module; A communication module connected between the control module and all battery cluster management modules, used to build a data interaction channel between the master node and the slave nodes.

5. The battery string dynamic equalization control system of claim 4, wherein, The communication module adopts a CAN bus network, and the control module and the battery cluster management modules perform periodic state data reporting and instruction issuing through a pre-defined communication protocol.

6. The battery string dynamic equalization control system of claim 4, wherein, The system further comprises a power control interface module, and the control module is connected to the DCDC converter of each battery cluster in the form of an emergency stop signal line through the power control interface module to realize emergency shutdown control.

7. A computer storage medium, characterized in that The computer storage medium stores a computer software product, and the computer software product comprises a plurality of instructions for causing a computer device to execute the battery cluster dynamic balancing control method of the industrial and commercial energy storage system according to any one of claims 1 to 3.

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