Graph theory-based dynamic reconfigurable inter-battery module circulating current suppression method and device

Abstract

The application discloses a dynamic reconfigurable battery inter-module circulating current suppression method and device based on graph theory, and relates to the field of battery equalization control. The method comprises the following steps: constructing a dynamic reconfigurable battery network equivalent circuit model; constructing a directed graph based on graph theory for the dynamic reconfigurable battery network equivalent circuit model to obtain a dynamic reconfigurable battery network directed graph model; for each sub-network directed graph model: constructing and solving a target state equation of the sub-network to obtain a solving result, and traversing a sub-network switch matrix combination based on the solving result to obtain a sub-network circulating current suppression switch matrix set; based on the sub-network circulating current suppression switch matrix set, constructing a circulating current suppression strategy library of the dynamic reconfigurable battery network, and utilizing the circulating current suppression strategy database to perform circulating current suppression control on the dynamic reconfigurable battery network. The application improves the inter-module circulating current suppression efficiency of the dynamic reconfigurable battery network, and further improves the overall energy efficiency and safety of the dynamic reconfigurable battery network.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of battery equalization control, in particular to a dynamic reconfigurable inter-module circulating current suppression method and device based on graph theory. BACKGROUND

[0002] With the increasing proportion of renewable energy installed capacity year by year, the influence of renewable energy represented by wind and light on the power grid is also more and more significant. In order to better cope with the intermittency and volatility of renewable energy grid-connected problems, battery energy storage as an effective and feasible solution has entered people's field of vision. The capacity of common battery monomer is limited, and it cannot balance the power shortage of the power grid through a single battery monomer. Therefore, the commonly used battery system at present is connected together by a large number of battery monomers in fixed series and parallel connection, so that the overall capacity and voltage, current meet the requirements.

[0003] However, for the fixed series and parallel battery system, the difference between the batteries is accumulated with the increase of working time, and finally it is reflected in the difference of battery SOC, that is, the short board effect is generated. The dynamic reconfigurable battery scheme is to connect the battery and the power electronic switch flexibly, so that the poor performance battery can be isolated or cut off, thereby effectively avoiding the short board effect. However, due to the flexible connection of the battery in the reconfigurable battery network, different batteries are connected in parallel, which may cause circulating current, thereby damaging the battery life and limiting the overall performance of the battery system. In some cases, the control algorithm of the reconfigurable battery network is mostly modeled from the optimization problem, and the running process of the battery system is modeled and solved as an optimization problem. However, the circulating current suppression between the battery units of the reconfigurable battery is insufficient, which makes the inter-module circulating current suppression efficiency of the dynamic reconfigurable battery network low, and further leads to the insufficient overall energy efficiency and safety of the dynamic reconfigurable battery network. SUMMARY

[0004] The purpose of the present application is to provide a dynamic reconfigurable inter-module circulating current suppression method and device based on graph theory, which can improve the inter-module circulating current suppression efficiency of the dynamic reconfigurable battery network, and further improve the overall energy efficiency and safety of the dynamic reconfigurable battery network.

[0005] To achieve the above purpose, the present application provides the following scheme.

[0006] In a first aspect, the application provides a graph-based dynamic reconfigurable battery inter-module circulating current suppression method, which comprises: constructing an equivalent circuit model of a dynamic reconfigurable battery network; the dynamic reconfigurable battery network comprises a plurality of sub-networks; the sub-networks comprise a plurality of battery monomers; constructing a directed graph based on the graph theory for the equivalent circuit model of the dynamic reconfigurable battery network to obtain a dynamic reconfigurable battery network directed graph model; the dynamic reconfigurable battery network directed graph model comprises a plurality of sub-network directed graph models; for each sub-network directed graph model: constructing and solving a target state equation of the sub-network to obtain a solution, and traversing the sub-network switch matrix combination based on the solution to obtain a sub-network circulating current suppression switch matrix set; the target state equation comprises a state of charge equation and a polarization voltage state equation; the solution is the predicted state of charge and the predicted polarization voltage of each battery monomer in the sub-network; based on the sub-network circulating current suppression switch matrix set, constructing a circulating current suppression strategy library of the dynamic reconfigurable battery network, and using the circulating current suppression strategy database to control the circulating current suppression of the dynamic reconfigurable battery network.

[0007] In a second aspect, the application provides a computer system, comprising: a memory, a processor to store a computer program on the memory and executable on the processor, and the processor executes the computer program to implement the above-mentioned graph-based dynamic reconfigurable battery inter-module circulating current suppression method.

[0008] According to the specific embodiments provided by the application, the following technical effects are disclosed.

[0009] The application constructs an equivalent circuit model of a dynamic reconfigurable battery network, and converts it into a directed graph model, solves the state equation of each sub-network, traverses the switch combination to obtain a feasible circulating current suppression scheme, and establishes a strategy library to realize intelligent control of the dynamic reconfigurable battery network. The application combines graph theory analysis with power electronic control, significantly improves the inter-module circulating current suppression efficiency of the dynamic reconfigurable battery network through topology optimization, and at the same time realizes accurate circulating current suppression, greatly improves the overall energy efficiency and operation safety of the dynamic reconfigurable battery network. BRIEF DESCRIPTION OF DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in the embodiments of the application or the related art, the following will briefly introduce the drawings needed in the embodiments. Obviously, the drawings in the following description are only some embodiments of the application, and for those skilled in the art, other drawings can also be obtained without creative labor based on these drawings.

[0011] Figure 1A flowchart of a dynamic reconfigurable battery inter-module circulating current suppression method based on graph theory provided by an embodiment of the present application.

[0012] Figure 2 A circuit diagram of a battery cell first-order Thevenin model provided by an embodiment of the present application.

[0013] Figure 3 A simplified equivalent circuit diagram of a battery cell first-order Thevenin model provided by an embodiment of the present application.

[0014] Figure 4 A battery system topology diagram of a dynamic reconfigurable battery network provided by an embodiment of the present application.

[0015] Figure 5 A battery system network architecture diagram of a dynamic reconfigurable battery network provided by an embodiment of the present application.

[0016] Figure 6 A structure diagram of a dynamic reconfigurable battery network directed graph model provided by an embodiment of the present application.

[0017] Figure 7 A battery cell current comparison effect diagram after current suppression by a dynamic reconfigurable battery inter-module circulating current suppression method based on graph theory provided by an embodiment of the present application.

[0018] Figure 8 A structure diagram of a computer system provided by an embodiment of the present application. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0020] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application will be further described in detail below with reference to the drawings and specific embodiments.

[0021] Embodiment 1, as shown in the present embodiment provides a dynamic reconfigurable battery inter-module circulating current suppression method based on graph theory, which includes the following steps. Figure 1

[0022] S1. Construct an equivalent circuit model of a dynamic reconfigurable battery network; the dynamic reconfigurable battery network includes a plurality of sub-networks; the sub-networks include a plurality of battery cells. ​

[0023] Step S1 specifically comprises the following steps.

[0024] S11. The MOSFET switch and the like for controlling the on-off of each battery monomer in the dynamic reconfigurable battery network is equivalent to a variable resistor, and an equivalent circuit model of the battery monomer is constructed; the equivalent circuit model of the battery monomer is a first-order Thevenin model.

[0025] In the actual application process, the construction process of the equivalent circuit model of the battery monomer is as follows.

[0026] First, as shown in the figure, Figure 2 the equivalent model of the battery monomer adopted in the embodiment is a first-order RC model, which can better reflect the nonlinear characteristics of the battery, and the calculation amount is relatively moderate. The model is composed of an open-circuit voltage corresponding voltage source, ohmic internal resistance, polarization capacitance and polarization internal resistance. Among them , , , , , are the open-circuit voltage, ohmic internal resistance, polarization capacitance, polarization internal resistance, output voltage and battery current of the battery.

[0027] At the same time, the open-circuit voltage can be regarded as a function of the state of charge of the battery, which is as follows.

[0028] .

[0029] At the same time, in order to make the calculation more simple, the above equivalent circuit can be simplified, and the circuit is further simplified while the RC link is reserved. The simplified model only contains ohmic internal resistance and the corresponding equivalent voltage source , as shown in the figure. Figure 3

[0030] The equivalent voltage source is the difference between the open-circuit voltage and the polarization voltage, and the specific formula is as follows.

[0031] .

[0032] S12. Based on the equivalent circuit model of the battery monomer, the equivalent circuit model of the sub-network is constructed by connecting in series and in parallel.

[0033] S13. Based on the equivalent circuit model of the sub-network, the connection mode of the sub-network is dynamically controlled by the switch matrix, and the switch state is coupled with the admittance matrix by using Hadamard product, and the equivalent circuit model of the dynamic reconfigurable battery network is constructed.

[0034] ​S2. Construct a directed graph based on the equivalent circuit model of the dynamic reconfigurable battery network to obtain a directed graph model of the dynamic reconfigurable battery network; the directed graph model of the dynamic reconfigurable battery network comprises a plurality of directed graph models of sub-networks.

[0035] Step S2 specifically comprises the following steps.

[0036] S21. Construct a directed graph based on the equivalent circuit model of the dynamic reconfigurable battery network to obtain a directed graph model of the dynamic reconfigurable battery network; the directed graph model of the dynamic reconfigurable battery network comprises a plurality of directed graph models of sub-networks.

[0037] S3. For each directed graph model of a sub-network: construct and solve a target state equation of the sub-network to obtain a solution, and traverse a combination of a switch matrix of the sub-network based on the solution to obtain a set of switch matrices for suppressing circulating current of the sub-network; the target state equation comprises a state-of-charge equation and a polarization voltage state equation; the solution is a predicted state-of-charge and a predicted polarization voltage of each battery cell in the sub-network.

[0038] Step S3 specifically comprises the following steps. Specifically comprises the following steps.

[0039] S31. For each directed graph model of a sub-network: construct a target state equation of the sub-network by using the directed graph model of the sub-network and adopting a node voltage method.

[0040] Further, the state-of-charge equation is as follows.

[0041] .

[0042] In the formula, is the state-of-charge; is a battery capacity matrix; is a node-branch incidence matrix; is a node admittance matrix; is an admittance matrix; is a battery-branch incidence matrix; is an open-circuit voltage; is a polarization voltage.

[0043] Further, the polarization voltage state equation is as follows.

[0044] .

[0045] In the formula, is the polarization voltage; is a battery capacity matrix; is a node-branch incidence matrix; is a node admittance matrix; is an admittance matrix; is a polarization conductance matrix; is the bus-branch incidence matrix; is the open circuit voltage; is the polarization voltage.

[0046] S32. Solving the target state equation of the sub-network by using the improved Euler method to obtain a solution result.

[0047] The step S32 specifically includes the following steps.

[0048] S321. Solving the target state equation of the sub-network by using the Euler method to obtain an initial estimation result.

[0049] S322. Taking the initial estimation result as input, and solving again by using the Euler method to obtain a correction result.

[0050] S323. Taking the average of the initial estimation result and the correction result to obtain a solution result.

[0051] In actual application, the improved Euler method used in the embodiment is an improvement of the ordinary Euler method, which uses two approximations to calculate the value of the next step, thereby improving the accuracy of the numerical solution.

[0052] The main improvement of the improved Euler method is to estimate the value of the next time step by using two stages, and the specific steps are as follows.

[0053] 1) An initial estimation result (predicted value) is calculated by using the ordinary Euler method.

[0054] 2) The predicted value is used as input, and the ordinary Euler method is applied again to calculate a more accurate value (correction result).

[0055] 3) The average of the initial estimation result and the correction result is taken as the final numerical solution.

[0056] In this way, the improved Euler method improves the accuracy of the numerical solution compared with the ordinary Euler method, especially for some functions with better approximation effect. At the same time, the calculation amount of the Euler method is small, so the approximate solution can be obtained faster in some simple differential equation problems.

[0057] S33. Calculating the predicted battery current of each battery monomer in the sub-network based on the solution result.

[0058] Further, the calculation formula of the predicted battery current of the battery monomer is as follows.

[0059] .

[0060] In the formula, is the battery current; is the bus-branch incidence matrix; Y is the admittance matrix of the node; Y is the admittance matrix of the node; B is the battery-branch incidence matrix; OCV is the open circuit voltage; V is the polarization voltage, I is the output current.

[0061] S34. Traverse the sub-network switch matrix combination, judge whether the predicted battery current of each battery monomer in the sub-network is less than the circulating current action threshold value, if yes, discard the current switch matrix combination, if not, retain the current switch matrix combination, obtain the sub-network circulating current suppression switch matrix set.

[0062] Further, the circulating current action threshold value is -0.05A.

[0063] In the actual application process, taking a 2*2 reconfigurable battery network as an example, for the switch matrix , its meaning is that two battery modules are connected with the load at the same time, and two battery monomers in the module are connected in parallel, if the battery capacity difference of the parallel connection is too large, it may lead to circulating current between the batteries, which is embodied as that the high-capacity battery charges the low-capacity battery, and the current of the low-capacity battery is negative, for example, -5A, since -5<-0.05 (circulating current action threshold value), the constraint is not satisfied, so the switch matrix cannot meet the requirement of circulating current suppression, and other feasible switch matrices need to be traversed.

[0064] The reconfigurable battery system topology architecture adopted in this embodiment is a switch battery topology containing bypass switches, as shown in Figure 4 , and state variables are introduced to represent the state of the switch, 1 and 0 correspond to the two states of the switch being closed and open respectively, so the switch can be modeled as a variable resistor, for the bypass switch branch, its resistance value is as follows.

[0065] .

[0066] For the branch where the battery is located, the branch resistance is the sum of the ohmic internal resistance of the battery and the resistance of the switch, and the specific formula is as follows.

[0067] .

[0068] wherein, R is the ohmic internal resistance of the battery, , are the equivalent resistances of the power electronic switch when it is turned on and turned off respectively, , The equivalent resistance of the branch where the power electronic switch is located and the branch where the battery is located, respectively.

[0069] The system can be converted into a circuit diagram in graph theory, and according to the related knowledge in graph theory, the network can be divided into multiple independent sub-networks, and each sub-network is solved independently. Figures 4-5

[0070] Therefore, the network graph theory of the sub-network is simplified into a directed graph and is modeled and analyzed, as shown in the figure. Figure 6 The graph is composed of two nodes and N+1 branches, branch 1 represents the branch where the bypass switch is located, and branches 2 to N+1 represent the branches where the battery units are located, and the matrix , respectively represent the node-branch association matrix and the battery-branch association matrix. Among them, due to the existence of the bypass switch branch, the battery-branch association matrix is set to represent the mapping relationship from the battery branch to the total branch.

[0071] The vector is defined as the control quantity of the battery system, that is, the load current, . , , are the branch voltage, node voltage and branch current of the network, respectively, and let be the network switch state variable, , , respectively represent the equivalent resistance vectors of the switch in the on and off states, , Therefore, the equivalent resistance vector of all switches in the network can be represented by the Hadamard product between the switch state vector and the switch equivalent resistance: .

[0072] Let , , respectively represent the open-circuit voltage, polarization voltage and ohmic internal resistance of each battery in the network, , , The equivalent voltage source of each battery can be represented as The battery current can be represented as Let be the equivalent voltage source of all branches in the network, The network branch resistance vector can be represented as: .

[0073] ​In order to determine the SOC of the battery over time, the battery current is solved . Let be the branch characteristic constraint equation of the network.

[0074] .

[0075] At the same time, the formula of the topological characteristic equation of the node is as follows.

[0076] .

[0077] Thus, the formula of the battery current is as follows.

[0078] .

[0079] In the formula, I is the battery current; is the node-branch incidence matrix; is the node admittance matrix; is the admittance matrix; is the battery-branch incidence matrix; is the open circuit voltage; is the polarization voltage, is the output current.

[0080] Thus, the state of charge equation and the polarization voltage state equation are constructed.

[0081] In the formula, the formula of the state space equation based on the node is as follows.

[0082] .

[0083] In the formula, the state variable is , and the control variable is .

[0084] S4. Based on the sub-network loop current suppression switch matrix set, a loop current suppression strategy library of the dynamic reconfigurable battery network is constructed, and the loop current suppression strategy database is used for loop current suppression control of the dynamic reconfigurable battery network.

[0085] The simulation experiment verifies the loop current suppression effect of the dynamic reconfigurable battery network, as shown in Figure 7As shown, the embodiment is verified in a simulation platform, and the battery system includes 9 batteries in total, and the initial SOC is 0.65, 0.8, 0.95, 0.5, 0.65, 0.85, 0.9, 0.75 and 0.7 respectively, and the current of each battery is between 0 and 30A, which indicates that no circulating current is generated in the dynamic reconfigurable battery network, and the suppression method proposed in the embodiment can effectively suppress the circulating current between the modules.

[0086] The technical effects of the present application are as follows: the present application constructs an equivalent circuit model of a dynamic reconfigurable battery network, and converts it into a directed graph model, obtains a feasible circulating current suppression scheme by solving the state equations of each sub-network and traversing the switch combination, and establishes a strategy library to realize intelligent control of the dynamic reconfigurable battery network. The present application combines graph theory analysis with power electronic control, significantly improves the circulating current suppression efficiency between the modules of the dynamic reconfigurable battery network through topology optimization, and at the same time realizes accurate circulating current suppression, greatly improves the overall energy efficiency and operation safety of the dynamic reconfigurable battery network.

[0087] In embodiment 2, the present application also provides a computer system which can be a server or a terminal, and the internal structure diagram thereof can be as shown in Figure 8 The computer system includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer system is used to provide computing and control capabilities. The memory of the computer system includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer system is used to store processing data. The input / output interface of the computer system is used to exchange information between the processor and external devices. The communication interface of the computer system is used to communicate with the terminal through the network connection. The computer program is executed by the processor to implement the above-mentioned methods.

[0088] Those skilled in the art can understand, Figure 8 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer system to which the scheme of the present application is applied. The specific computer system can include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0089] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiment methods can be included. Any reference to memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration but not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0090] Any combination of the technical features of the above embodiments can be made. In order to make the description simple, all possible combinations of the technical features in the above embodiments are not described, however, as long as the combination of the technical features does not exist contradictory, it should be considered as the scope of the present application.

[0091] The principles and implementation modes of the present application are described by using specific examples in this paper, and the above-mentioned embodiment is only used to help understand the method and its core idea of the present application; at the same time, for those skilled in the art, according to the idea of the present application, the specific implementation mode and application range will be changed. In conclusion, the content of the present application should not be understood as a limitation.

Claims

1. A method for suppressing circulating current between dynamically reconfigurable battery modules based on graph theory, characterized in that: The graph theory-based method for suppressing circulating current between dynamically reconfigurable battery modules includes: Constructing a dynamic reconfigurable battery network equivalent circuit model; the dynamic reconfigurable battery network includes multiple sub-networks; the sub-network includes multiple battery cells; Based on graph theory, a directed graph is constructed for the dynamic reconfigurable battery network equivalent circuit model to obtain a dynamic reconfigurable battery network directed graph model; the dynamic reconfigurable battery network directed graph model includes multiple sub-network directed graph models; For each sub-network directed graph model: construct and solve the target state equation of the sub-network to obtain the solution result, and traverse the sub-network switch matrix combination based on the solution result to obtain the sub-network circulation suppression switch matrix set, specifically including: for each sub-network directed graph model: use the sub-network directed graph model to construct the target state equation of the sub-network using the node voltage method; use the improved Euler method to solve the target state equation of the sub-network to obtain the solution result; calculate the predicted battery current of each battery cell in the sub-network based on the solution result; traverse the sub-network switch matrix combination to determine whether the predicted battery current of each battery cell in the sub-network is less than the circulation action threshold, if so, discard the current switch matrix combination, if not, retain the current switch matrix combination to obtain the sub-network circulation suppression switch matrix set; the target state equation includes: state of charge equation and polarization voltage state equation; the solution result is the predicted state of charge and predicted polarization voltage of each battery cell in the sub-network; Based on the sub-network circulation suppression switch matrix set, a circulation suppression strategy library for the dynamic reconfigurable battery network is constructed, and the circulation suppression strategy database is used to control the circulation suppression of the dynamic reconfigurable battery network.

2. The method for suppressing circulating current between dynamically reconfigurable battery modules based on graph theory according to claim 1 is characterized in that: Construct a dynamic reconfigurable battery network equivalent circuit model, including: The MOSFET switches that control the on / off of each battery cell in the dynamically reconfigurable battery network are equivalent to variable resistors to construct an equivalent circuit model of the battery cell; the equivalent circuit model of the battery cell is a first-order Thevenin model; Based on the equivalent circuit model of the battery cell, the equivalent circuit model of the sub-network is constructed by connecting the battery cells in series and parallel topology. Based on the equivalent circuit model of the sub-network, the connection mode of the sub-network is dynamically controlled by the switch matrix, and the switch state is coupled with the admittance matrix using the Hadamard product to construct a dynamically reconfigurable battery network equivalent circuit model.

3. The method for suppressing circulating current between dynamically reconfigurable battery modules based on graph theory according to claim 1 is characterized in that: Based on graph theory, a directed graph is constructed for the equivalent circuit model of the dynamic reconfigurable battery network, and a directed graph model of the dynamic reconfigurable battery network is obtained, which specifically includes: With nodes representing electrical connection points and directed edges representing branches of current flow, a directed graph is constructed for the dynamic reconfigurable battery network equivalent circuit model to obtain a dynamic reconfigurable battery network directed graph model.

4. The method for suppressing circulating current between dynamically reconfigurable battery modules based on graph theory according to claim 1 is characterized in that: The improved Euler method is used to solve the target state equation of the subnetwork and obtain the solution, which includes: The Euler method is used to solve the target state equation of the sub-network to obtain the initial estimation result; The initial estimation result is used as input and the Euler method is used again to solve the problem and obtain the correction result. The initial estimation result and the correction result are averaged to obtain the solution.

5. The method for suppressing circulating current between dynamically reconfigurable battery modules based on graph theory according to claim 1, characterized in that: The circulating current threshold is -0.05A.

6. The method for suppressing circulating current between dynamically reconfigurable battery modules based on graph theory according to claim 1, characterized in that: The calculation formula for the predicted battery current of the battery cell is as follows: ； Where, is the battery current; is the node-branch association matrix; is the node admittance matrix; is the admittance matrix; is the battery-branch association matrix; is the open circuit voltage; is the polarization voltage, is the output current.

7. The method for suppressing circulating current between dynamically reconfigurable battery modules based on graph theory according to claim 1, characterized in that: The state of charge equation is as follows: ； Where, is the state of charge; is the battery capacity matrix; is the node-branch association matrix; is the node admittance matrix; is the admittance matrix; is the battery-branch association matrix; is the open circuit voltage; is the polarization voltage.

8. The method for suppressing circulating current between dynamically reconfigurable battery modules based on graph theory according to claim 1 is characterized in that: The polarization voltage state equation is as follows: ； Where, is the polarization voltage; is the battery capacity matrix; is the node-branch association matrix; is the node admittance matrix; is the admittance matrix; is the polarization conductivity matrix; is the battery-branch association matrix; is the open circuit voltage; is the polarization voltage.

9. A computer system comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the graph-theory-based dynamic reconfigurable battery module inter-circulation suppression method according to any one of claims 1 to 8.

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