Battery series capacity grading method and system and storage medium
By constructing a mathematical model of the battery series structure, determining the potential flow relationship of the nodes and performing hierarchical clustering, the problem of complex operation in the battery capacity grading process is solved, and efficient battery capacity grading is achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ANHUI SHARP INNOVATION ENERGY TECH CO LTD
- Filing Date
- 2025-12-31
- Publication Date
- 2026-04-21
AI Technical Summary
The existing battery capacity sorting process is complex, resulting in low sorting efficiency and high performance requirements for the sorting equipment.
By constructing a mathematical model of a single-cell series structure, the potential flow relationship of the nodes is determined, the internal parameter values are calculated, and hierarchical clustering is performed to achieve battery capacity classification.
It simplifies the amount of data, reduces the time and cost of capacity allocation, enables dynamic capacity allocation, and avoids the need for complex working modes.
Smart Images
Figure CN121899657A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of battery capacity testing technology, and more specifically to a battery series capacity testing method, system, and storage medium. Background Technology
[0002] During battery capacity testing, data from each testing point is obtained through computer management to determine the battery's quality level. This data volume is enormous and requires a lot of calculation, making the capacity testing process complex and time-consuming. Existing technologies typically require determining the battery's cutoff voltage and setting the working mode of the capacity testing equipment, which is complex to operate and follow, placing high demands on the performance of the capacity testing equipment. Summary of the Invention
[0003] The purpose of this invention is to provide a battery series capacity classification method, system, and storage medium, which solves the problem of complex operation and low classification efficiency when classifying batteries.
[0004] To achieve the above objectives, embodiments of the present invention provide a battery series capacity testing method, the capacity testing method comprising: Construct a mathematical model of a single-cell series structure; The potential flow relationship of the nodes is determined based on the mathematical model. The internal parameter values of a single cell are determined based on the described potential-current relationship; The internal parameters of each individual battery cell are combined into an array; Calculate the minimum spacing between each array to achieve hierarchical clustering.
[0005] Optionally, a mathematical model of a single-cell battery series structure is constructed, including: Multiple individual cells are connected in series; A node with 1 represents an equicurrent node, a node with 0 represents an equipotential node, and the arrows connected to the nodes represent keys; The single cell contains six bonds, each of which contains two variables: voltage and current. When there are vertical lines between the key and the node it is connected to, it indicates that the key provides voltage to the node. When there are no vertical lines between the key and the node it connects to, it indicates that the key provides current to the node.
[0006] Optionally, determining the potential flow relationship at the nodes based on the mathematical model includes: The current-voltage relationship at node 1 of the mathematical model is determined according to formula (1). (1) in, For single cell battery key The current, For single cell battery key The current, For single cell battery key The current, For single cell battery key The current, For single cell battery key voltage, For single cell battery key voltage, For single cell battery key voltage, For single cell battery key The voltage.
[0007] Optionally, determining the potential flow relationship of the nodes based on the mathematical model further includes: The current-voltage relationship at node 0 of the mathematical model is determined according to formula (2). (2) in, For single cell battery key The current, For single cell battery key The current, For single cell battery key voltage, For single cell battery key The voltage.
[0008] Optionally, determining the internal parameter values of a single cell based on the potential-current relationship includes: The current-voltage relationship of a single-cell series battery is determined according to formula (3). (4) in, This is the open-circuit voltage of the first individual cell. The charging and discharging voltage provided for the capacity divider operating in constant voltage mode, and this voltage value is constant. The ohmic internal resistance of the first single cell. The polarization internal resistance of the first single cell. The polarization capacitor for the first single cell; The internal parameter values of the battery are determined according to formula (4). (4) in, The charging and discharging current provided for the capacity distribution cabinet.
[0009] Optionally, the minimum spacing between the arrays is calculated to achieve hierarchical clustering, including: Each array of individual cells is treated as a class; Calculate the minimum distance between each class; The two classes with the closest distance are merged into a new class based on the minimum distance, and the average value of the arrays corresponding to the two classes is taken as the array of the new class. Calculate the minimum distance between the new class and all other classes; Determine whether the minimum distance is greater than a preset threshold; If the minimum distance is greater than the preset threshold, the hierarchical clustering is determined to be complete. If it is determined that the minimum distance is not greater than the preset threshold, the step is to merge the two closest classes into a new class based on the minimum distance.
[0010] Optionally, the minimum distance between classes is calculated, including: Calculate the minimum distance between each class according to formula (5).
[0011] in, For the minimum distance, For the first The ohmic internal resistance of a single cell For the first The ohmic internal resistance of a single cell For the first The polarization internal resistance of a single cell, For the first The polarization internal resistance of a single cell, For the first The polarization capacitance of a single cell For the first The polarization capacitor of a single cell.
[0012] Optionally, determining that hierarchical clustering is complete includes: classifying the individual cells corresponding to the clustered array into the same category.
[0013] On the other hand, the present invention also provides a battery series capacity grading system, the system including a processor for executing the capacity grading method as described above.
[0014] In another aspect, the present invention also provides a computer-readable storage medium storing instructions for being read by a machine to cause the machine to perform any of the above-described capacity partitioning methods.
[0015] Through the above technical solution, this invention provides a battery series capacity assessment method, system, and storage medium. By establishing a mathematical model of the battery series structure, it quantitatively analyzes the potential-current relationship of various parameters within the battery pack, derives formulas for the influence of internal battery parameters on the potential-current relationship, and, based on the voltage and current data detected during the capacity assessment process, reversely derives the internal parameter values of each individual battery cell. The internal parameters of each individual battery cell are combined into an array, and the minimum distance between the arrays is calculated according to the parameter dimension, thereby performing hierarchical clustering and ultimately achieving battery capacity assessment. Compared with existing technologies, this invention only requires testing in the middle of the SOC phase, eliminating the need to determine the battery's cutoff voltage, thus simplifying the data volume and achieving dynamic capacity assessment. Furthermore, the capacity assessment cabinet only needs to be set to constant current mode, eliminating the need for complex operating modes, which reduces capacity assessment time and cost.
[0016] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description section. Attached Figure Description
[0017] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings: Figure 1 This is a flowchart of a battery series capacity grading method according to an embodiment of the present invention; Figure 2 This is a flowchart illustrating the construction of a mathematical model according to one embodiment of the present invention; Figure 3 This is a schematic diagram of a mathematical model of a battery series structure according to an embodiment of the present invention; Figure 4 This is a flowchart of obtaining the potential flow relationship according to one embodiment of the present invention; Figure 5 This is a flowchart of obtaining internal parameters of a single cell according to an embodiment of the present invention; Figure 6 This is a flowchart of array-based hierarchical clustering according to one embodiment of the present invention. Detailed Implementation
[0018] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the scope of the present invention.
[0019] In the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, they do not mean that the applicant has used or necessarily used the solution.
[0020] Figure 1 This is a flowchart of a capacity-sharing method according to an embodiment of the present invention, in which the capacity-sharing method includes: In step S1, a mathematical model of the single-cell series structure is constructed.
[0021] In step S2, the potential flow relationship of the nodes is determined based on the mathematical model.
[0022] In step S3, the internal parameter values of a single cell are determined based on the potential flow relationship.
[0023] In step S4, the internal parameters of each individual cell are combined into an array.
[0024] In step S5, the minimum spacing between each array is calculated to achieve hierarchical clustering.
[0025] In steps S1 to S5, a mathematical model of the battery series structure is established to quantitatively analyze the potential-current relationship of each parameter within the battery pack. Formulas for the influence of internal battery parameters on the potential-current relationship are derived. Based on the voltage and current data detected during the capacity testing process, the internal parameter values of each individual battery cell are derived in reverse. The internal parameters of each individual battery cell are then combined into an array. The parameters constitute dimensional array, Each individual cell makes up Grouping arrays, ultimately forming Group The system uses a dimensional array to calculate the minimum distance between arrays according to the parameter dimension, thereby performing hierarchical clustering and ultimately realizing the capacity classification of batteries.
[0026] Compared with existing technologies, this invention only requires testing in the middle of the SOC phase, eliminating the need to determine the battery's cutoff voltage, thus simplifying data processing and enabling dynamic capacity grading. Furthermore, the capacity grading cabinet only needs to be set to constant current mode, eliminating the need for complex operating modes, thereby reducing grading time and cost.
[0027] In this embodiment, the methods for constructing the mathematical model can be various and known to those skilled in the art. In one example of the present invention, the steps for constructing the mathematical model can be... Figure 2 The method shown is illustrated. Figure 2 The capacity-sharing method also includes: In step S11, multiple individual cells are connected in series.
[0028] In step S12, node 1 represents an equicurrent node, node 0 represents an equipotential node, and the arrow connected to the node represents a key.
[0029] In step S13, a single cell contains six bonds, each of which contains two variables: voltage and current.
[0030] In step S14, when there is a vertical line between the key and the connected node, it indicates that the key provides voltage to the connected node.
[0031] In step S15, when there are no vertical lines between the key and the connected node, it indicates that the key provides current to the connected node.
[0032] In steps S11 to S15, a mathematical model of the series battery structure was constructed. For example... Figure 3 As shown in the diagram, "1" represents an equipotential node, "0" represents an equipotential node, and the arrows connecting the nodes represent "bonds." A series-connected battery consists of six bonds: (1-1), (1-2), ..., (1-6). Each bond contains two variables: voltage and current. For example, the voltage and current of bond (1-1) are... and The voltage and current of keys (1-2) are respectively and Similarly, the voltage and current of keys (1-6) are respectively and The direction of the arrow indicates the reference direction of voltage and current.
[0033] Specifically, when a key and its connected node have a vertical line, it indicates that the key provides voltage to the connected node; when a key and its connected node do not have a vertical line, it indicates that the key provides current to the connected node. Taking the leftmost node "1" as an example, the keys connected to it are (1-1), (1-2), (1-3), and (1-6). Among them, key (1-6) has no vertical line connected to this node, so key (1-6) provides current to this node, while the other keys provide voltage to this node.
[0034] In this invention, let there be a total If batteries are connected in series, the bonds of the 2nd to Nth batteries and the voltage and current on each bond can also be determined.
[0035] In this implementation, since node "1" represents an equicurrent node, the current on all bonds connected to this node is equal, and the vector sum of the voltages is 0. Taking the leftmost node "1" as an example, specifically, as follows... Figure 4 As shown, determining the potential flow relationship at a node based on a mathematical model can include: In step S21, the current-voltage relationship at node 1 of the mathematical model is determined according to formula (1). (1) in, For single cell battery key The current, For single cell battery key The current, For single cell battery key The current, For single cell battery key The current, For single cell battery key voltage, For single cell battery key voltage, For single cell battery key voltage, For single cell battery key The voltage.
[0036] In this implementation, since the "0" node represents an equipotential node, the voltages on all bonds connected to this node are equal, and the vector sum of the currents is 0. Taking the leftmost "0" node as an example, ... Figure 4 As shown, determining the potential flow relationship at a node based on a mathematical model can include: In step S22, the current-voltage relationship at node 0 of the mathematical model is determined according to formula (2). (2) in, For single cell battery key The current, For single cell battery key The current, For single cell battery key voltage, For single cell battery key The voltage.
[0037] After deriving the formula for the influence of battery internal parameters on the potential-current relationship, the internal parameter values of each individual cell are derived in reverse based on the voltage and current data detected during the capacity testing process. Figure 3 middle, ~ for Open-circuit voltage of a single cell ~ For an individual The ohmic internal resistance of a single cell, ~ for The polarization internal resistance of a single cell, ~ for The polarization capacitor of a single cell. The charging and discharging current provided to the capacity testing cabinet operating in constant current mode is constant; therefore, the capacity testing cabinet only needs to be set to constant current mode. Specifically, for the first single cell, the method for obtaining the internal parameter values of that single cell can be... Figure 5 The method shown is illustrated. Figure 5 The capacity-sharing method also includes: In step S31, the current-voltage relationship of a single cell is determined according to formula (3). (4) in, This is the open-circuit voltage of the first individual cell. The charging and discharging voltage provided for the capacity divider operating in constant voltage mode, and this voltage value is constant. The ohmic internal resistance of the first single cell. The polarization internal resistance of the first single cell. The polarization capacitor for the first single cell; In step S32, the internal parameter values of the battery are determined according to formula (4). (4) in, The charging and discharging current provided for the capacity distribution cabinet. For the terminal voltage of a single cell, Given a constant current source, both are known quantities. It can be measured in an open circuit and is a known quantity; therefore, the only unknown quantity is the battery parameter. , and Therefore, given The internal parameters of the battery can be derived by using three different constant current values.
[0038] After obtaining the internal parameter values of the battery, the internal parameters of each individual battery cell are combined into an array, i.e. The parameters constitute dimensional array, Each individual cell makes up Grouping arrays, ultimately forming Group The dimensional array can be obtained from the above calculations. Then it can be expressed according to formula (6). Group dimensional array, (6) in, The internal resistance of the second individual cell is ohmic. The polarization internal resistance of the second individual cell. For the polarization capacitor of the second single cell, For the first The ohmic internal resistance of a single cell, For the first The polarization internal resistance of a single cell, For the first The polarization capacitor of a single cell.
[0039] After obtaining the array, hierarchical clustering is performed based on the array. Specifically, it could be... Figure 6 The method shown is illustrated. Figure 6 The capacity-sharing method also includes: In step S51, the array of each individual battery cell is treated as a class.
[0040] In step S52, the minimum distance between each class is calculated. Specifically, calculating the minimum distance between each class includes: Calculate the minimum distance between each class according to formula (5).
[0041] in, For the minimum distance, For the first The ohmic internal resistance of a single cell For the first The ohmic internal resistance of a single cell For the first The polarization internal resistance of a single cell, For the first The polarization internal resistance of a single cell, For the first The polarization capacitance of a single cell For the first The polarization capacitance of a single cell .
[0042] In step S53, the two classes with the closest distance are merged into a new class based on the minimum distance, and the average value of the arrays corresponding to the two classes is obtained as the array of the new class.
[0043] In step S54, the minimum distance between the new class and other classes is calculated.
[0044] In step S55, it is determined whether the minimum distance is greater than a preset threshold. If the minimum distance is greater than the preset threshold, step S56 is executed; otherwise, step S53 is executed.
[0045] In step S56, it is determined that hierarchical clustering is complete.
[0046] In steps S51 to S56, the distance is The two arrays are merged into a new class. The minimum distance between the other arrays and the corresponding new array of the new class is calculated using formula (6) until the distance is reached. Once the set upper limit is exceeded, hierarchical clustering can be completed. At this point, the batteries corresponding to the clustered array can also be classified into the same category, thereby realizing battery capacity classification.
[0047] On the other hand, the present invention also provides a battery series capacity grading system, the system including a processor for executing any of the capacity grading methods described above.
[0048] In another aspect, the present invention also provides a computer-readable storage medium storing instructions for being read by a machine to cause the machine to perform any of the above-described capacity partitioning methods.
[0049] Through the above technical solution, this invention provides a battery series capacity assessment method, system, and storage medium. By establishing a mathematical model of the battery series structure, it quantitatively analyzes the potential-current relationship of various parameters within the battery pack, derives formulas for the influence of internal battery parameters on the potential-current relationship, and, based on the voltage and current data detected during the capacity assessment process, reversely derives the internal parameter values of each individual battery cell. The internal parameters of each individual battery cell are combined into an array, and the minimum distance between the arrays is calculated according to the parameter dimension, thereby performing hierarchical clustering and ultimately achieving battery capacity assessment. Compared with existing technologies, this invention only requires testing in the middle of the SOC phase, eliminating the need to determine the battery's cutoff voltage, thus simplifying the data volume and achieving dynamic capacity assessment. Furthermore, the capacity assessment cabinet only needs to be set to constant current mode, eliminating the need for complex operating modes, which reduces capacity assessment time and cost.
[0050] 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.
[0051] 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 1One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0052] 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 function specified in one or more boxes.
[0053] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.
[0054] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.
[0055] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.
[0056] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.
[0057] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.
[0058] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.
Claims
1. A battery series capacity testing method, characterized in that, The capacity-sharing method includes: Construct a mathematical model of a single-cell series structure; The potential flow relationship of the nodes is determined based on the mathematical model. The internal parameter values of a single cell are determined based on the described potential-current relationship; The internal parameters of each individual battery cell are combined into an array; Calculate the minimum spacing between each array to achieve hierarchical clustering.
2. The capacity-sharing method according to claim 1, characterized in that, The mathematical model for constructing a single-cell series structure includes: Multiple individual cells are connected in series; A node with 1 represents an equicurrent node, a node with 0 represents an equipotential node, and the arrows connected to the nodes represent keys; The single cell contains six bonds, each of which contains two variables: voltage and current. When there are vertical lines between the key and the node it is connected to, it indicates that the key provides voltage to the node. When there are no vertical lines between the key and the node it connects to, it indicates that the key provides current to the node.
3. The capacity-sharing method according to claim 1, characterized in that, Determining the potential flow relationship of the nodes based on the mathematical model includes: The current-voltage relationship at node 1 of the mathematical model is determined according to formula (1). ，（1） in, For single cell battery key The current, For single cell battery key The current, For single cell battery key The current, For single cell battery key The current, For single cell battery key voltage, For single cell battery key voltage, For single cell battery key voltage, For single cell battery key The voltage.
4. The capacity-sharing method according to claim 3, characterized in that, Determining the potential flow relationship of nodes based on the mathematical model also includes: The current-voltage relationship at node 0 of the mathematical model is determined according to formula (2). ，（2） in, For single cell battery key The current, For single cell battery key The current, For single cell battery key voltage, For single cell battery key The voltage.
5. The capacity-sharing method according to claim 4, characterized in that, Determining the internal parameter values of a single cell based on the potential-current relationship includes: The current-voltage relationship of a single-cell series battery is determined according to formula (3). ，（4） in, This is the open-circuit voltage of the first individual cell. The charging and discharging voltage provided for the capacity divider operating in constant voltage mode, and this voltage value is constant. The ohmic internal resistance of the first single cell. The polarization internal resistance of the first single cell. The polarization capacitor for the first single cell; The internal parameter values of the battery are determined according to formula (4). ，（4） in, The charging and discharging current provided for the capacity distribution cabinet.
6. The capacity-sharing method according to claim 1, characterized in that, Calculate the minimum distance between each array to achieve hierarchical clustering, including: Each array of individual cells is treated as a class; Calculate the minimum distance between each class; The two classes with the closest distance are merged into a new class based on the minimum distance, and the average value of the arrays corresponding to the two classes is taken as the array of the new class. Calculate the minimum distance between the new class and all other classes; Determine whether the minimum distance is greater than a preset threshold; If the minimum distance is greater than the preset threshold, the hierarchical clustering is determined to be complete. If it is determined that the minimum distance is not greater than the preset threshold, the step is to merge the two closest classes into a new class based on the minimum distance.
7. The capacity-sharing method according to claim 6, characterized in that, Calculate the minimum distance between classes, including: Calculate the minimum distance between each class according to formula (5). in, For the minimum distance, For the first The ohmic internal resistance of a single cell For the first The ohmic internal resistance of a single cell For the first The polarization internal resistance of a single cell, For the first The polarization internal resistance of a single cell, For the first The polarization capacitance of a single cell For the first The polarization capacitor of a single cell.
8. The capacity-sharing method according to claim 6, characterized in that, Determining whether hierarchical clustering is complete includes: classifying the individual cells corresponding to the clustered array into the same category.
9. A battery series capacity grading system, characterized in that, The system includes a processor for performing the capacity partitioning method as described in any one of claims 1 to 8.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions for being read by a machine to cause the machine to perform the capacity partitioning method as described in any one of claims 1 to 8.