A method for calculating the maximum allowable current of a reconfigurable battery system

Abstract

The application discloses a kind of reconfigurable battery system maximum allowable current calculation method.The main steps are as follows:(1) based on the connection between battery and switch Construct directed graph model;(2) with switch state as variable, battery current through current does not exceed battery allowable current as constraint condition, system output current as objective function, establish optimization model;(3) the shortest path of each battery in directed graph model is solved respectively;(4) a certain number of shortest paths are selected to form a series of reconfigured circuit structures, which are brought into the optimization model to solve the maximum allowable current value under this condition;(5) the number of selected shortest path is updated, and the above steps are repeated until the maximum allowable current value of the system is solved.The method proposed in the application can calculate the maximum allowable current value of any reconfigurable battery system, and can be applied to guide the design and optimization of the reconfigurable battery system, and evaluate the current overload risk of the system in actual operation.

Description

Technical Field

[0001] This invention proposes a method for calculating the maximum allowable current of a reconfigurable battery system, which belongs to the field of energy storage. Background Technology

[0002] Reconfigurable battery systems are attracting increasing attention due to their flexible circuit topologies and high reliability. The complex interconnections between the battery and switches in reconfigurable battery systems offer flexibility in design and control, but also present challenges. Unlike traditional battery energy storage systems with fixed output, the output of a reconfigurable battery system is dynamically adjusted by controlling the switch states to meet external load demands. Incorrect switch control strategies can lead to battery short circuits or overloads, jeopardizing the entire system. The maximum allowable current is a crucial performance indicator for reconfigurable battery systems, guiding designers in addressing this issue. Currently, the maximum allowable current of reconfigurable battery systems is typically calculated manually, a time-consuming and error-prone method that fails to meet the needs of practical applications. Therefore, a universal and automated method for calculating the maximum allowable current of reconfigurable battery systems is urgently needed. Summary of the Invention

[0003] To address the problems of time-consuming and error-prone calculation methods for the maximum allowable current of reconfigurable battery systems in existing technologies, this invention proposes a method for calculating the maximum allowable current of reconfigurable battery systems that can automatically calculate the maximum allowable current of reconfigurable battery systems and has universality.

[0004] A method for calculating the maximum allowable current of a reconfigurable battery system includes the following steps:

[0005] Step 1: Let N be the number of batteries in the reconfigurable battery system to be solved. b The number of switches is N s Based on the battery and switch connection relationships of this system, a directed graph model is constructed.

[0006] Specifically, in this directed graph model, nodes represent connection points between adjacent batteries and switches in the reconfigurable battery system; edges represent batteries, switches, and external loads in the reconfigurable battery system, where batteries are represented by directed edges pointing from the negative terminal to the positive terminal, switches are represented by a pair of directed edges in opposite directions, and external loads are represented by directed edges pointing from the positive terminal to the negative terminal; each edge in the directed graph model is assigned two attributes: voltage difference and resistance, where the edge representing the battery has the attribute (u). b ,r b ), representing the battery's electromotive force and internal resistance, respectively, and representing the switch's edge having the property (0, r). s ), r s For a switching resistor, the side representing the external load has the property (0, R). o ), Ro This is the equivalent resistance of the external load.

[0007] Step 2: Based on the directed graph model constructed in Step 1, with the switch state as the variable, the current flowing through it not exceeding the allowable current of each battery as the constraint, and the reconfigurable system output current as the objective function, an optimization model is established. First, based on the directed graph model constructed in Step 1, the correlation matrix A is determined according to the following relationship:

[0008]

[0009] Secondly, the correlation matrix A is rearranged and simplified: the last row of A is omitted, resulting in the degenerate correlation matrix. Arrange the columns representing batteries according to the battery order in the directed graph to obtain a submatrix. Arrange the columns representing switches according to the switch order in the directed graph. For two columns representing the same switch, retain only one of them to obtain a submatrix. The column representing external load will be treated as a separate submatrix.

[0010] Next, the system switching state matrix X is established according to the following relationship. s :

[0011]

[0012] Then, the current matrix I passing through each battery in the system is calculated using the following formula. b :

[0013]

[0014] Where, r b U is the internal resistance of the battery. b Y is a column vector composed of the voltages of each battery. n The system node conductance matrix is ​​calculated using the following formula:

[0015]

[0016] Calculate the system's output current I using the following formula. o The following formula is used to calculate:

[0017]

[0018] The final optimized model is as follows:

[0019] max I o (X s )

[0020] stI b (X s )≤Ib,m ,

[0021] Among them, I b,m It is a column vector composed of the maximum allowable current of each battery.

[0022] Step 3: Based on the directed graph model constructed in Step 1, solve for the shortest path for each battery. The distance of path p is calculated using the following formula:

[0023] ω(p)=N s n b (p)+n s (p),

[0024] Where, n b n represents the number of batteries contained in this pathway. s This represents the number of switches contained in the path.

[0025] Step 4: Let N be the number of shortest paths selected. set Its initial value is N b .

[0026] Step 5: Select N from the shortest paths for each battery obtained in Step 4. set One path, generating Various combination methods.

[0027] Step 6: For each combination generated in Step 5, set the switch state of the selected path to closed and the other switches to open to obtain the reconstructed circuit structure.

[0028] Step 7: For each reconstructed circuit structure in Step 6, substitute it into the optimization model established in Step 2, and solve for the system in closed N... set The maximum allowable current when there are multiple paths;

[0029] Step 8: Update N in step 4 using binary search. set Value: If the current maximum allowable current value of the system is greater than the allowable current value of the system in the previous cycle, then use the binary search method to update the integer N upwards. set The calculation is terminated and the maximum allowable current value is output if the current system maximum allowable current value is equal to the previous cycle system allowable current value; otherwise, the binary search method is used to update the integer N downwards. set The value is obtained; repeat steps five through seven until the maximum allowable current of the system is obtained. Attached Figure Description

[0030] Figure 1 This is a flowchart illustrating the steps of the method for calculating the maximum allowable current of a reconfigurable battery system according to an embodiment of the present invention.

[0031] Figure 2 This is a circuit diagram of the reconfigurable battery system to be solved according to an embodiment of the present invention.

[0032] Figure 3 This is a directed graph model with physical information used in the calculation process of the maximum allowable current of the reconfigurable battery system in this embodiment of the invention.

[0033] Figure 4 This is the shortest path solution result in the calculation process of the maximum allowable current of the reconfigurable battery system in this embodiment of the invention.

[0034] Figure 5 The calculation results are for the maximum allowable current of the reconfigurable battery system according to an embodiment of the present invention. Detailed Implementation

[0035] The method for calculating the maximum allowable current of the reconfigurable battery system proposed in this invention will be further explained below with reference to the accompanying drawings and specific implementation examples.

[0036] like Figure 1 As shown, a method for calculating the maximum allowable current of a reconfigurable battery system includes the following steps:

[0037] S1. In this embodiment, using Figure 2 The reconfigurable battery system shown, with 4 batteries and 19 switches, is the object of calculation, i.e., N. b =4, N s =19. Construct a directed graph with nodes representing the connections between adjacent batteries and switches; and edges representing batteries, switches, and external loads. Batteries are represented by directed edges pointing from the negative terminal to the positive terminal (dashed arrows in the diagram), switches by a pair of opposite directed edges (solid arrows in the diagram), and external loads by directed edges pointing from the positive terminal to the negative terminal (dotted arrows in the diagram). Each edge in the directed graph model is assigned two attributes: voltage difference and resistance. The edge representing the battery has the attribute (u...). b ,r b ), representing the battery's electromotive force and internal resistance, respectively, and representing the switch's edge having the property (0, r). s ), r s For a switching resistor, the side representing the external load has the property (0, R). o ), R o This is the equivalent resistance of the external load. In this example, the internal resistance r of the battery in the system is... b =50mΩ, resistance R of external load o = 2Ω, the internal resistance of the switch is r s =0.1mΩ, maximum battery operating current I b,max =5A, battery voltage U b =3.6V.

[0038] S2. According to Figure 3 The established directed graph model with physical information, degenerates the correlation matrix. for:

[0039]

[0040]

[0041]

[0042]

[0043] Let N be the system s The state of each switch is X. s In the system, N b The current of each battery is calculated using the following formula:

[0044]

[0045] Among them, Y n (X s The result is obtained through the following formula:

[0046]

[0047] The system's output current is calculated using the following formula:

[0048]

[0049] Finally, the optimization model in the following form is obtained:

[0050] max I o (X s )

[0051] stI b (X s )≤5A.

[0052] S3. To Figure 3 The shortest paths for the four batteries are calculated using the following formula:

[0053] ω(p)=19·n b (p)+n s (p),

[0054] Where, n b n represents the number of batteries in the circuit. s Let be the number of switches in the circuit. The solution is as follows: Figure 4 As shown, the bolded part is the shortest path.

[0055] S4. Let N be the number of shortest paths selected. set =4, its initial value is N b =4.

[0056] S5. From Figure 4 Among the four shortest paths obtained from the solution, N is selected by combination. set One path, generating Various combination methods.

[0057] S6. For each combination generated in S5, set the switch state of the selected path to closed and the other switch states to open to obtain the reconstructed circuit structure.

[0058] S7. Substitute each reconstructed circuit structure from S6 into the optimization model established in the second step to solve for the maximum allowable current of the system when the four paths are closed.

[0059] S8. Update N in S2 using the binary search method. set Value: If the current maximum allowable current value of the system is greater than the allowable current value of the system in the previous cycle, then use the binary search method to update the integer N upwards. set The calculation is terminated and the maximum allowable current value is output if the current system maximum allowable current value is equal to the previous cycle system allowable current value; otherwise, the binary search method is used to update the integer N downwards. set The value is determined. Repeat steps S5 to S7 until the maximum allowable current of the system is obtained.

[0060] The maximum allowable current value of the system in this example is 1.78A, and the corresponding switch closing method is as follows: Figure 5 As shown.

Claims

1. A method for calculating the maximum allowable current of a reconfigurable battery system, characterized in that, Includes the following steps: Step 1: Define the number of batteries in the reconfigurable battery system as follows: The number of switches is Based on the battery and switch connection relationship of the system, a directed graph model is constructed. Step 2: Based on the directed graph model constructed in Step 1, with the switch state as the variable, the current flowing through it not exceeding the allowable current of each battery as the constraint, and the reconfigurable system output current as the objective function, establish an optimization model, including the following: Step 21: Based on the directed graph model constructed in Step 1, determine the incidence matrix according to the following relationship. Step 22: On the correlation matrix Organize and simplify: Omit The last row yields the degenerate incidence matrix; arranging the columns representing batteries according to the battery order in the directed graph yields a submatrix. Arrange the columns representing switches according to the switch order in the directed graph. For two columns representing the same switch, retain only one of them to obtain a submatrix. The column representing the external load will be treated as a separate submatrix. Step 23: Establish the system switch state matrix according to the following relationships. : Step 24: Using the current matrix of each battery in the system. The following formula can be used to calculate: in, This refers to the battery's internal resistance. It is a column vector composed of the voltages of each battery. The system node conductance matrix is ​​calculated using the following formula: Step 25: System output current The following formula can be used to calculate: Step 26: Based on steps 24 and 25, the final optimized model is obtained in the following form: in, The column is composed of the maximum allowable current of each battery. Step 3: Based on the directed graph model constructed in Step 1, solve for the shortest path for each battery, where the path... The distance is calculated using the following formula: in, This represents the number of batteries contained in the pathway. This represents the number of switches contained in the path. Step 4: Let the number of shortest paths selected be... Its initial value is ; Step 5: Select combinations from the shortest paths for each battery obtained in Step 3. There are several pathways, generating various combinations; Step 6: For each combination generated in Step 5, set the switch state of the selected path to closed and the other switches to open to obtain the reconstructed circuit structure. Step 7: For each reconstructed circuit structure in Step 6, substitute it into the optimization model established in Step 2, and solve for the system's closed-loop circuit structure. The maximum allowable current when there are multiple paths; Step 8: Update the results in Step 4 using binary search. Repeat steps 5 through 7 until the maximum allowable current of the system is obtained.

2. The method for calculating the maximum allowable current of a reconfigurable battery system as described in claim 1, characterized in that, Step 1, "constructing a directed graph model based on the battery and switch connection relationship of the system," further includes the following: The nodes in this directed graph model are the connection points between adjacent batteries and switches in the reconfigurable battery system; In this directed graph model, the edges represent the battery, switch, and external load in the reconfigurable battery system. The battery is represented by a directed edge from the negative terminal to the positive terminal, the switch is represented by a pair of directed edges in opposite directions, and the external load is represented by a directed edge from the positive terminal to the negative terminal. Each edge in the directed graph model is assigned two attributes: voltage difference and resistance. The edges representing the battery have these attributes. , respectively, represent the battery's electromotive force and internal resistance; the side representing the switch has properties. , For switching resistors; the side representing the external load has properties. This is the equivalent resistance of the external load.

3. The method for calculating the maximum allowable current of a reconfigurable battery system as described in claim 1, characterized in that, In step 8, "update the data in step 4 using a binary search method" The value of "value" further includes the following: If the current maximum allowable current value of the system is greater than the allowable current value of the system in the previous cycle, then use the binary search method to update the integer value upwards. The value; If the current maximum allowable current value of the system is equal to the allowable current value of the system in the previous cycle, then the calculation is terminated and the maximum allowable current value of the system is output. If the current maximum allowable current value of the system is less than the allowable current value of the system in the previous cycle, then use the binary search method to update the integer value downwards. The value of .

Images