A method, system, device and product for controlling power balance of a mobile power supply

Abstract

The present invention belongs to the field of power management technology, and its purpose is to provide a method, system, device and product for power balancing control of a mobile power supply. The method includes: collecting multi-dimensional status information of each battery cell in the mobile power supply; performing SOC estimation processing on each battery cell according to the multi-dimensional status information of each battery cell, and obtaining the SOC estimation value of each battery cell; performing standard deviation calculation on the SOC estimation values ​​of all battery cells, and obtaining the SOC standard deviation between battery cells; judging whether the SOC standard deviation between battery cells is greater than a preset standard deviation threshold; if so, determining that power balancing operation needs to be performed on the mobile power supply, and performing battery cell energy scheduling processing on the mobile power supply according to the SOC estimation value of each battery cell; if not, determining that power balancing operation does not need to be performed on the mobile power supply, and re-collecting the multi-dimensional status information of each battery cell in the mobile power supply. The battery cell state estimation of the present invention has high accuracy, and can also perform adaptive balancing control, which is conducive to improving power balancing efficiency.

Description

Technical Field

[0001] The present invention belongs to the technical field of power management, and in particular relates to a power balancing control method, system, device and product for a mobile power supply. Background Art

[0002] With the widespread use of mobile devices, mobile power banks (also known as power banks) have become an essential tool in users' daily lives as portable power supplies. To improve power capacity and stability, existing mobile power banks typically utilize battery packs consisting of multiple lithium-ion cells connected in series or parallel. However, differences in production processes, operating environments, and aging rates can easily lead to inconsistent charge states among individual cells, impacting the overall performance, safety, and lifespan of the battery pack. Consequently, cell balancing control technology has gained widespread application in mobile power banks.

[0003] Traditional power balancing methods mainly use passive balancing methods, which usually dissipate excess power as heat through resistors. Although low-cost and simple to control, this method has problems such as severe energy waste and high heat dissipation pressure, making it unsuitable for high-capacity or high-density mobile power applications.

[0004] In order to improve the efficiency of electric energy utilization and address the technical defects of passive balancing methods, active balancing methods have emerged in the prior art. These methods use circuit structures such as inductors, capacitors, or charge pumps to actively transfer energy between different battery cells. Compared with passive balancing methods, they can achieve more efficient balancing control. The fixed-cycle voltage balancing method is a commonly used active balancing control strategy. It uses the battery cell voltage as the only criterion for power balancing. However, in the process of using this prior art, the inventors found that there are at least the following problems in the prior art:

[0005] The fixed-cycle voltage balancing method ignores key factors such as temperature, cycle count, and cell aging, which can easily lead to inaccurate SOC (State of Charge) estimation and affect balancing effectiveness. This active balancing strategy is particularly unable to promptly identify and differentiate between abnormalities in cell aging or some cells exhibiting abnormalities, leading to safety hazards such as overcharging and over-discharging, and in severe cases, even thermal runaway. Summary of the Invention

[0006] The present invention aims to at least to some extent solve the technical problems of inaccurate cell state estimation and poor exception handling capability in the prior art. The present invention provides a power balancing control method, system, device and product for a mobile power supply.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions:

[0008] In a first aspect, the present invention provides a power balancing control method for a mobile power supply, comprising:

[0009] Collect multi-dimensional status information of each battery cell in the mobile power supply;

[0010] According to the multi-dimensional state information of each battery cell, the SOC of each battery cell is estimated to obtain the estimated SOC value of each battery cell;

[0011] Calculate the standard deviation of the estimated SOC values ​​of all cells to obtain the SOC standard deviation between cells;

[0012] Determine whether the SOC standard deviation between the battery cells is greater than a preset standard deviation threshold;

[0013] If yes, it is determined that a power balancing operation needs to be performed on the mobile power supply, and the mobile power supply is subjected to a cell energy scheduling process based on the estimated SOC value of each cell;

[0014] If not, it is determined that the power balancing operation does not need to be performed on the mobile power supply, and the multi-dimensional status information of each battery cell in the mobile power supply is re-collected.

[0015] In a possible design, the multi-dimensional state information includes terminal voltage, current, temperature, internal resistance and cycle number; correspondingly, the first i The estimated SOC value of each battery cell is:

[0016] ;

[0017] Where, SOC i ( t- 1) is the first i The SOC value of each cell in the previous control cycle, I i ( t ) is the first i The current of each cell, Δ t is the duration of the current control cycle, Q nom,i The first i The nominal capacity of each battery cell, α i is the preset voltage correction coefficient, V i ( t ) is the first i The terminal voltage of each cell, T i ( t ) is the first i The temperature of each cell, Voc,i ( SOC i ( t- 1), T i ( t )) is the first i The estimated open circuit voltage of each battery cell under the state of charge of the previous control cycle and the current temperature conditions.

[0018] In one possible design, after obtaining the estimated SOC value of each battery cell, the method further includes:

[0019] Construct a state vector for each cell based on the multi-dimensional state information and SOC estimation value of each cell;

[0020] Obtaining a preset state vector threshold interval, and performing abnormal state identification processing on each battery cell based on the state vector threshold interval and the state vector of each battery cell;

[0021] If an abnormal battery cell is identified from the mobile power supply, power isolation control is performed on the abnormal battery cell.

[0022] In one possible design, the SOC standard deviation between cells is:

[0023] ;

[0024] Where, N is the total number of cells in the mobile power supply, SOC i ( t ) is the first i The estimated SOC value of each cell in the current control cycle, i ∈{1,2,…, N}, is the average SOC of all cells in the mobile power supply in the current control cycle.

[0025] In one possible design, the mobile power supply performs cell energy scheduling based on the estimated SOC value of each cell, including:

[0026] Construct a directed graph with each cell as a node and the energy transfer path between cells as an edge, and define the weight of the edge of the directed graph as the energy transfer cost; wherein, from the mobile power supply i battery cells v i Point to the j battery cells v j edge e ij The weight is:

[0027] ;

[0028] Where, SOC i ( t ) is the first i The estimated SOC value of each cell in the current control cycle, SOC j ( t ) is the first j The estimated SOC value of each cell in the current control cycle, i , j ∈{1,2,…, N},and i ≠ j , R eq,ij is the total equivalent resistance of the current loop, R eq,ij = R i ( t )+ R j ( t )+ R bal ( t ), R i ( t ) is the first i The dynamic internal resistance of each cell in the current control cycle, R j ( t ) is the first j The dynamic internal resistance of each cell in the current control cycle, R bal ( t ) is the preset equivalent impedance;

[0029] Based on a path optimization algorithm with minimum edge weight, an energy transfer path set consisting of multiple optimal transfer paths is screened from the directed graph;

[0030] Based on the energy transfer path set, the cells to be controlled corresponding to each optimal transfer path in the mobile power supply are controlled to perform energy transfer.

[0031] In one possible design, controlling the controlled cells corresponding to any optimal transfer path in the mobile power supply to transfer energy includes:

[0032] Obtaining the latest SOC estimated values ​​of two to-be-controlled cells in the mobile power supply corresponding to any one of the optimal transfer paths;

[0033] Determine whether the difference between the larger of the latest SOC estimated values ​​of the two cells to be controlled and the average SOC value of all cells to be controlled is greater than a preset SOC deviation threshold. If so, proceed to the next step.

[0034] Determine whether the difference between the smaller of the latest SOC estimated values ​​of the two cells to be controlled and the average SOC value of all cells to be controlled is greater than a preset SOC deviation threshold. If so, skip any of the optimal transfer paths; if not, proceed to the next step.

[0035] The energy of the one with the larger latest SOC estimated value among the two cells to be controlled is driven to be transferred to the one with the smaller latest SOC estimated value until the standard deviation of the cells to be controlled in the mobile power supply is less than a preset termination threshold.

[0036] In one possible design, during the process of controlling the energy transfer of the cells to be controlled corresponding to the optimal transfer paths in the mobile power supply, the method further includes:

[0037] Real-time collection of multi-dimensional state information of the cells to be controlled corresponding to each optimal transfer path, and SOC estimation processing of each cell to be controlled to obtain the latest SOC estimation value of each cell to be controlled;

[0038] Calculate the SOC change rate of each cell to be controlled based on the latest SOC estimated value of each cell to be controlled;

[0039] Determine whether the deviation of the SOC change rate of each cell to be controlled from the rate mean is greater than a preset rate deviation threshold;

[0040] If the SOC change rate of any cell to be controlled deviates from a preset rate threshold, it is determined that any cell to be controlled has an abnormality, and energy regulation of any cell to be controlled is suspended.

[0041] In a second aspect, the present invention provides a power balancing control system for a mobile power supply, comprising:

[0042] Status information acquisition module, used to collect multi-dimensional status information of each battery cell in the mobile power supply;

[0043] An SOC estimation module is communicatively connected to the state information acquisition module and is used to perform SOC estimation processing on each battery cell according to the multi-dimensional state information of each battery cell to obtain an estimated SOC value of each battery cell;

[0044] A power balancing control module is communicatively connected to the SOC estimation module, and is used to calculate the standard deviation of the SOC estimation values ​​of all battery cells to obtain the SOC standard deviation between the battery cells, and determine whether the SOC standard deviation between the battery cells is greater than a preset standard deviation threshold. If so, it is determined that a power balancing operation needs to be performed on the mobile power supply, and the mobile power supply is subjected to power cell energy scheduling processing based on the SOC estimation value of each battery cell. If not, it is determined that a power balancing operation does not need to be performed on the mobile power supply, and the multi-dimensional status information of each battery cell in the mobile power supply is re-collected.

[0045] In a third aspect, the present invention provides an electronic device, comprising:

[0046] a memory for storing computer program instructions; and

[0047] The processor is configured to execute the computer program instructions to thereby complete the operation of the power balancing control method for a mobile power supply as described in any one of the above.

[0048] In a fourth aspect, the present invention provides a computer program product, comprising a computer program or instructions, wherein when the computer program or instructions are executed by a computer, the computer program or instructions implement a power balancing control method for a mobile power supply as described in any one of the above.

[0049] The beneficial effects of the present invention are:

[0050] The present invention discloses a method, system, device and product for controlling power balancing of a mobile power supply. The method has high accuracy in estimating the state of battery cells and can perform adaptive balancing control, which is beneficial to improving power balancing efficiency. Specifically, during the implementation of the present invention, first, the multi-dimensional state information of each battery cell in the mobile power supply is collected, and the SOC estimation processing is performed on each battery cell according to the multi-dimensional state information of each battery cell to obtain the SOC estimation value of each battery cell; then, the standard deviation of the SOC estimation values ​​of all battery cells is calculated to obtain the SOC standard deviation between the battery cells; then, it is determined whether the SOC standard deviation between the battery cells is greater than a preset standard deviation threshold. If so, it is determined that the mobile power supply needs to be subjected to power balancing operation, and the mobile power supply performs battery cell energy scheduling processing according to the SOC estimation value of each battery cell; if not, it is determined that the mobile power supply does not need to be subjected to power balancing operation, and the multi-dimensional state information of each battery cell in the mobile power supply is re-collected. Based on this, the present invention realizes battery cell state estimation through multi-dimensional state information, effectively solving the hysteresis and misjudgment problems of traditional voltage estimation methods, and has higher SOC estimation accuracy. At the same time, power balancing operation is performed through the SOC standard deviation between battery cells, which is beneficial to improving the stability, safety and practicality of mobile power supplies and has good application and promotion value.

[0051] Other beneficial effects of the present invention will be further described in the specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 is a flow chart of the power balancing control method of the mobile power supply in Example 1;

[0053] Figure 2 This is a module block diagram of the power balancing control system of the mobile power supply in Example 2;

[0054] Figure 3 This is a module block diagram of the electronic device in Example 3. DETAILED DESCRIPTION

[0055] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the present invention will be briefly introduced below in conjunction with the drawings and the description of the embodiments or the prior art. Obviously, the following description of the structure of the drawings is only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work. It should be noted that the description of these embodiments is used to help understand the present invention, but does not constitute a limitation of the present invention.

[0056] Example 1:

[0057] This embodiment discloses a power balancing control method for a mobile power supply, which can be executed by, but is not limited to, a computer device or a virtual machine with certain computing resources, such as a personal computer, a smart phone, a personal digital assistant, or a wearable device, or by a virtual machine.

[0058] like Figure 1 As shown, a power balancing control method for a mobile power supply may include, but is not limited to, the following steps:

[0059] S1. Collecting multi-dimensional status information of each battery cell in the mobile power supply. It should be noted that this embodiment is applicable to battery packs composed of any number of battery cells and is compatible with mobile power supply systems of different structures (battery cells in series, parallel or mixed), with strong scalability.

[0060] S2. Perform SOC estimation processing on each battery cell based on the multi-dimensional state information of each battery cell to obtain an estimated SOC value of each battery cell.

[0061] Specifically, the multi-dimensional state information includes terminal voltage, current, temperature, internal resistance and cycle number; correspondingly, the first i The estimated SOC value of each battery cell is:

[0062] ;

[0063] Where, SOC i ( t- 1) is the first i The SOC value of each cell in the previous control cycle, I i ( t ) is the first i The current of each cell (positive for charging, negative for discharging), Δ t is the duration of the current control cycle, Q nom,i The first i The nominal capacity of each battery cell, α i is the preset voltage correction coefficient, V i ( t ) is the first i The terminal voltage of each cell, T i ( t ) is the first i The temperature of each cell (core or shell temperature), V oc,i ( SOC i ( t- 1), T i ( t )) is the first i The state of charge of each cell in the previous control cycle SOC i ( t- 1) and current temperature T i ( t ) condition, which is a reference value for correcting the current terminal voltage. It is given by the open-circuit voltage model and can be obtained through offline experimental calibration.

[0064] The open circuit voltage model is usually obtained by experimental calibration. As an example, the open circuit voltage estimation value is obtained by fitting the following bivariate polynomial:

[0065] V oc,i ( SOC i ( t- 1), T i ( t ))= a 0+ a 1. SOC i (t- 1)+ a 2. SOC i 2 ( t- 1)+ a 3. T i ( t )+ a 4. SOC i ( t- 1) T i ( t );

[0066] Where, a 0. a 1. a 3 and a 4 are the model parameters obtained by fitting the battery cell static test experiment.

[0067] This model can better reflect the law of change of actual open-circuit voltage with SOC value and temperature, which helps to introduce voltage correction in SOC estimation, thereby compensating for the error caused by integral drift or cell capacity change in the Coulomb integration method, and improving the accuracy and stability of the overall estimation.

[0068] It should be noted that this SOC estimation method combines the Coulomb integral method with voltage state correction, taking into account both real-time responsiveness and long-term accuracy and stability. On the one hand, the Coulomb integral method accurately reflects the changes in the battery cell's charge during each control cycle through real-time integration of the current, achieving a rapid response to the SOC. On the other hand, the voltage correction term uses the deviation between the battery cell terminal voltage and the open-circuit voltage model for dynamic correction, effectively suppressing the cumulative deviation caused by current acquisition errors, integral drift, or capacity aging, significantly improving long-term estimation accuracy and system robustness. Especially in application scenarios where mobile power supplies are frequently charged and discharged and their operating states change significantly, this estimation method can effectively track the actual charge level of the battery cell, providing a reliable basis for subsequent charge balancing control, thereby enhancing the operating efficiency and safety of the entire system.

[0069] In this embodiment, after obtaining the estimated SOC value of each battery cell, the method further includes:

[0070] Construct a state vector for each cell based on the multi-dimensional state information and SOC estimation value of each cell;

[0071] Obtaining a preset state vector threshold interval, and performing abnormal state identification processing on each battery cell based on the state vector threshold interval and the state vector of each battery cell;

[0072] If an abnormal battery cell is identified from the mobile power supply, power isolation control is performed on the abnormal battery cell.

[0073] In this embodiment, by performing an abnormal battery cell identification process, the identified abnormal battery cells can be automatically isolated, thereby reducing system risks, reducing the impact of aging or faulty battery cells on the overall system, and effectively avoiding the risk of thermal runaway caused by overcharging and over-discharging, thereby ensuring system stability and safety.

[0074] S3. Calculate the standard deviation of the estimated SOC values ​​of all battery cells to obtain the SOC standard deviation between battery cells.

[0075] Specifically, the SOC standard deviation between the cells is:

[0076] ;

[0077] Where, N is the total number of cells in the mobile power supply, SOC i ( t ) is the first i The estimated SOC value of each cell in the current control cycle, i ∈{1,2,…, N}, is the average SOC of all cells in the mobile power supply in the current control cycle.

[0078] S4. Determine whether the SOC standard deviation between the cells is greater than a preset standard deviation threshold σ th .

[0079] S5. If yes, it is determined that a power balancing operation needs to be performed on the mobile power supply, and the mobile power supply is subjected to a cell energy scheduling process based on the estimated SOC value of each cell.

[0080] In step S5, the mobile power supply is subjected to a cell energy scheduling process based on the estimated SOC value of each cell, including:

[0081] S501. Construct a directed graph with each cell as a node and the energy transfer path between cells as an edge, and define the weight of the edge of the directed graph as the energy transfer cost; specifically, in this embodiment, the directed graph can be expressed as G = (V, E), where each cell is a node v i ∈V, if i battery cells v i The estimated SOC value is greater than j battery cells v j The estimated SOC value, that is, SOC i ( t )> SOC j ( t ), there is a path from the mobile power supply to the i battery cells v i Point to the j battery cells v j edge e ij , represents the energy transfer path. i battery cells v i Point to the j battery cells v j edge e ij The weight is:

[0082] ;

[0083] Where, SOC i ( t ) is the first i The estimated SOC value of each cell in the current control cycle, SOC j ( t ) is the first j The estimated SOC value of each cell in the current control cycle, i , j ∈{1,2,…, N},and i ≠ j , R eq,ij is the total equivalent resistance of the current loop, R eq,ij = R i ( t )+ R j ( t )+ R bal ( t ), R i ( t ) is the first i The dynamic internal resistance of each cell in the current control cycle, R j ( t ) is the first jThe dynamic internal resistance of each cell in the current control cycle, R bal ( t ) is the preset equivalent impedance. R bal ( t ) includes components such as the on-resistance of the on-MOS tube, the current sampling resistor, and the PCB trace impedance. It is a fixed value set during system design. Its value can be obtained through actual measurement or based on the hardware circuit parameter model, and is input as a constant or weak function in the balance control.

[0084] S502. Based on a path optimization algorithm with minimum edge weight (such as minimum weight matching method, greedy matching method, etc.), an energy transfer path set consisting of multiple optimal transfer paths is screened from the directed graph; wherein the energy transfer path set can be expressed as P ={( i , j )}, i , j ∈{1,2,…, N},and i ≠ j It should be noted that, based on the multiple optimal transfer paths in the energy transfer path set, energy can be transferred from the battery cell with a high SOC estimated value to the battery cell with a low SOC estimated value.

[0085] S503. Based on the energy transfer path set, control the cells to be controlled corresponding to each optimal transfer path in the mobile power supply to perform energy transfer.

[0086] In step S503, controlling the battery cells to be controlled corresponding to any optimal transfer path in the mobile power supply to perform energy transfer includes:

[0087] a1 obtain the latest SOC estimated value of the two cells to be controlled in the mobile power supply corresponding to any one of the optimal transfer paths;

[0088] a2. Determine whether the difference between the larger of the latest SOC estimated values ​​of the two cells to be controlled and the average SOC of all cells to be controlled is greater than the preset SOC deviation threshold. If so, proceed to the next step;

[0089] a3. Determine whether the difference between the smaller of the two latest SOC estimated values ​​of the cells to be controlled and the mean SOC of all cells to be controlled is greater than a preset SOC deviation threshold. If so, skip any of the optimal transfer paths. If not, proceed to the next step.

[0090] a4. Drive the energy of the two currently controlled cells with the larger latest estimated SOC value to transfer it to the cell with the smaller latest estimated SOC value until the standard deviation of the controlled cells in the mobile power supply is less than a preset termination threshold, indicating that the mobile power supply has achieved an overall balanced state of charge.

[0091] It should be noted that, if the difference between the latest SOC estimation value of the two cells to be controlled and the SOC average value of all cells to be controlled is greater than the preset SOC deviation threshold, it indicates that the current power difference between the two cells to be controlled is not sufficient to support effective balancing, and there is a risk of overcharging or energy waste. Therefore, during the power balancing control process, any optimal transfer path corresponding to the two cells to be controlled is skipped.

[0092] Specifically, this embodiment uses a controllable conduction device or charge pump circuit to achieve real-time energy transfer between any two battery cells. PWM (Pulse Width Modulation) is used for fine-grained regulation of the transferred current, thereby achieving fast, low-loss dynamic balancing. PWM control is simple, fast, and has low implementation costs and strong practicality.

[0093] In step S503, during the process of controlling the cells to be controlled corresponding to the optimal transfer paths in the mobile power supply to transfer energy, the method further includes:

[0094] b1. Real-time collection of multi-dimensional state information of the cells to be controlled corresponding to the optimal transfer path, and SOC estimation processing of each cell to be controlled to obtain the latest SOC estimated value of each cell to be controlled;

[0095] b2. Calculate the SOC change rate of each cell to be controlled based on the latest estimated SOC value of each cell to be controlled; the SOC change rate of any cell to be controlled is: d ( SOC i ( t )) / dt ;

[0096] b3. Determine whether the SOC change rate of each cell to be controlled deviates from the rate mean by a magnitude greater than a preset rate deviation magnitude threshold; wherein the rate mean can be expressed as μ dSOC / dt , which is the average of the SOC change rates of all cells to be controlled. The rate deviation amplitude threshold can be expressed as θ , such as | d ( SOC i ( t )) / dt-μ dSOC / dt |> θ, which means that the deviation of the SOC change rate of any cell to be controlled from the rate mean is greater than the preset rate deviation amplitude threshold.

[0097] b4. If the SOC change rate of any cell to be controlled deviates from a preset rate threshold, it is determined that any cell to be controlled has an abnormality, and energy regulation of any cell to be controlled is suspended.

[0098] Based on this, this embodiment can further start an abnormality identification mechanism during the process of performing power balancing operation on the mobile power supply, which is beneficial to ensuring system security.

[0099] Based on the above steps S501 to S503, this embodiment plans the energy flow path between battery cells through the graphical model, and uses the graphical model minimum energy consumption path optimization algorithm to achieve selective and directional power transfer, avoid invalid or inefficient energy movement, and avoid the control imbalance problem caused by "average regulation" in traditional methods.

[0100] It should be noted that within each control cycle, the system can further update the status of each battery cell according to the battery cell energy scheduling processing results and perform the next round of processing, thereby achieving closed-loop control and adaptive adjustment.

[0101] S6. If not, it is determined that it is not necessary to perform a power balancing operation on the mobile power supply, and the multi-dimensional status information of each battery cell in the mobile power supply is re-collected.

[0102] The battery cell state estimation of this embodiment has high accuracy and can also perform adaptive balancing control, which is beneficial to improving the efficiency of battery balancing. Specifically, during the implementation of this embodiment, first, the multi-dimensional state information of each battery cell in the mobile power supply is collected, and the SOC estimation processing is performed on each battery cell based on the multi-dimensional state information of each battery cell to obtain the SOC estimated value of each battery cell; then, the standard deviation of the SOC estimated values ​​of all battery cells is calculated to obtain the SOC standard deviation between the battery cells; then, it is determined whether the SOC standard deviation between the battery cells is greater than a preset standard deviation threshold. If so, it is determined that the mobile power supply needs to be subjected to battery balancing operation, and the mobile power supply performs battery cell energy scheduling processing based on the SOC estimated value of each battery cell; if not, it is determined that the mobile power supply does not need to be subjected to battery balancing operation, and the multi-dimensional state information of each battery cell in the mobile power supply is re-collected. Based on this, this embodiment realizes battery cell status estimation through multi-dimensional status information, effectively solving the hysteresis and misjudgment problems of traditional voltage estimation methods, and has higher SOC estimation accuracy. At the same time, power balancing operation is performed through the SOC standard deviation between battery cells, which is beneficial to improving the stability, safety and practicality of mobile power supplies and has good application and promotion value.

[0103] Example 2:

[0104] This embodiment discloses a mobile power supply power balancing control system for implementing the mobile power supply power balancing control method in embodiment 1; Figure 2 As shown, the power balancing control system of the mobile power supply includes:

[0105] Status information acquisition module, used to collect multi-dimensional status information of each battery cell in the mobile power supply;

[0106] An SOC estimation module is communicatively connected to the state information acquisition module and is used to perform SOC estimation processing on each battery cell according to the multi-dimensional state information of each battery cell to obtain an estimated SOC value of each battery cell;

[0107] A power balancing control module is communicatively connected to the SOC estimation module, and is used to calculate the standard deviation of the SOC estimation values ​​of all battery cells to obtain the SOC standard deviation between the battery cells, and determine whether the SOC standard deviation between the battery cells is greater than a preset standard deviation threshold. If so, it is determined that a power balancing operation needs to be performed on the mobile power supply, and the mobile power supply is subjected to power cell energy scheduling processing based on the SOC estimation value of each battery cell. If not, it is determined that a power balancing operation does not need to be performed on the mobile power supply, and the multi-dimensional status information of each battery cell in the mobile power supply is re-collected.

[0108] It should be noted that the working process, working details and technical effects of the power balancing control system of the mobile power supply provided in this embodiment 2 can be found in embodiment 1 and will not be described in detail here.

[0109] Example 3:

[0110] Based on the embodiment 1 or 2, this embodiment discloses an electronic device, which may be a smart phone, a tablet computer, a laptop computer or a desktop computer. The electronic device may be called a user terminal, a portable terminal, a desktop terminal, etc. Figure 3 As shown, the electronic equipment includes:

[0111] a memory for storing computer program instructions; and

[0112] The processor is configured to execute the computer program instructions to thereby complete the operation of the power balancing control method for a mobile power supply as described in any one of the embodiments 1.

[0113] Specifically, the processor 301 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 301 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 301 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 301 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen.

[0114] The memory 302 may include one or more computer-readable storage media, which may be non-transitory. The memory 302 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices and flash memory storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 302 is used to store at least one instruction, which is executed by the processor 301 to implement the power balancing control method for a mobile power supply provided in Example 1 of the present application.

[0115] In some embodiments, the terminal may optionally include a communication interface 303 and at least one peripheral device. The processor 301, memory 302, and communication interface 303 may be connected via a bus or signal lines. Each peripheral device may be connected to the communication interface 303 via a bus, signal lines, or circuit boards. Specifically, the peripheral device may include at least one of a radio frequency circuit 304, a display screen 305, and a power supply 306.

[0116] The communication interface 303 can be used to connect at least one I / O (Input / Output)-related peripheral device to the processor 301 and the memory 302. In some embodiments, the processor 301, the memory 302, and the communication interface 303 are integrated on the same chip or circuit board. In other embodiments, any one or two of the processor 301, the memory 302, and the communication interface 303 can be implemented on separate chips or circuit boards, which is not limited in this embodiment.

[0117] The radio frequency circuit 304 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit 304 communicates with a communication network and other communication devices via electromagnetic signals.

[0118] The display screen 305 is used to display a UI (User Interface). The UI may include any combination of graphics, text, icons, and videos.

[0119] The power supply 306 is used to supply power to various components in the electronic device.

[0120] Example 4:

[0121] Based on any one of Embodiments 1 to 3, this embodiment discloses a computer program product, including a computer program or instructions. When executed by a computer, the computer program or instructions implement the power balancing control method for a mobile power supply as described in any one of Embodiment 1. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.

[0122] Obviously, those skilled in the art will appreciate that the modules or steps of the present invention described above can be implemented using a general-purpose computing device. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Alternatively, they can be implemented using program code executable by a computing device, which can then be stored in a storage device and executed by the computing device. Alternatively, they can be fabricated into separate integrated circuit modules, or multiple modules or steps can be fabricated into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0123] Finally, it should be noted that the above embodiments are intended only to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art will appreciate that modifications may be made to the technical solutions described in the above embodiments, or that some of the technical features may be replaced with equivalents. Such modifications or replacements do not deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A power balancing control method for a mobile power source, characterized in that: include: Collect multi-dimensional status information of each battery cell in the mobile power supply; According to the multi-dimensional state information of each battery cell, the SOC of each battery cell is estimated to obtain the estimated SOC value of each battery cell; Calculate the standard deviation of the estimated SOC values ​​of all cells to obtain the SOC standard deviation between cells; Determine whether the SOC standard deviation between the battery cells is greater than a preset standard deviation threshold; If yes, it is determined that a power balancing operation needs to be performed on the mobile power supply, and the mobile power supply is subjected to a cell energy scheduling process based on the estimated SOC value of each cell; If not, it is determined that it is not necessary to perform a power balancing operation on the mobile power supply, and the multi-dimensional status information of each battery cell in the mobile power supply is re-collected; Performing cell energy scheduling processing on the mobile power supply according to the estimated SOC value of each cell, including: Construct a directed graph with each cell as a node and the energy transfer path between cells as an edge, and define the weight of the edge of the directed graph as the energy transfer cost; wherein, from the mobile power supply i battery cells v i Point to the j battery cells v j edge e ij The weight is: ； Where, SOC i ( t ) is the first i The estimated SOC value of each cell in the current control cycle, SOC j ( t ) is the first j The estimated SOC value of each cell in the current control cycle, i , j ∈{1,2,…, N },and i ≠ j , R eq,ij is the total equivalent resistance of the current loop, R eq,ij = R i ( t )+ R j ( t )+ R bal ( t ), R i ( t ) is the first i The dynamic internal resistance of each cell in the current control cycle, R j ( t ) is the first j The dynamic internal resistance of each cell in the current control cycle, R bal ( t ) is the preset equivalent impedance; Based on a path optimization algorithm with minimum edge weight, an energy transfer path set consisting of multiple optimal transfer paths is screened from the directed graph; Based on the energy transfer path set, controlling the controlled cells corresponding to each optimal transfer path in the mobile power supply to perform energy transfer; Controlling the controlled cells corresponding to any optimal transfer path in the mobile power supply to perform energy transfer includes: Obtaining the latest SOC estimated values ​​of two to-be-controlled cells in the mobile power supply corresponding to any one of the optimal transfer paths; Determine whether the difference between the larger of the latest SOC estimated values ​​of the two cells to be controlled and the average SOC value of all cells to be controlled is greater than a preset SOC deviation threshold. If so, proceed to the next step. Determine whether the difference between the smaller of the latest SOC estimated values ​​of the two cells to be controlled and the average SOC value of all cells to be controlled is greater than a preset SOC deviation threshold. If so, skip any of the optimal transfer paths; if not, proceed to the next step. Driving the energy transfer from the one with the larger latest SOC estimated value among the two cells to be controlled to the one with the smaller latest SOC estimated value until the standard deviation of the cells to be controlled in the mobile power supply is less than a preset termination threshold; In the process of controlling the energy transfer of the cells to be controlled corresponding to the optimal transfer paths in the mobile power supply, the method further includes: Real-time collection of multi-dimensional state information of the cells to be controlled corresponding to each optimal transfer path, and SOC estimation processing of each cell to be controlled to obtain the latest SOC estimation value of each cell to be controlled; Calculate the SOC change rate of each cell to be controlled based on the latest SOC estimated value of each cell to be controlled; Determine whether the deviation of the SOC change rate of each cell to be controlled from the rate mean is greater than a preset rate deviation threshold; If the SOC change rate of any cell to be controlled deviates from a preset rate threshold, it is determined that any cell to be controlled has an abnormality, and energy regulation of any cell to be controlled is suspended.

2. The method for controlling power balance of a mobile power supply according to claim 1, wherein: The multi-dimensional state information includes terminal voltage, current, temperature, internal resistance and number of cycles; correspondingly, the first i The estimated SOC value of each battery cell is: ； Where, SOC i ( t- 1) is the first i The SOC value of each cell in the previous control cycle, I i ( t ) is the first i The current of each cell, Δ t is the duration of the current control cycle, Q nom,i The first i The nominal capacity of each battery cell, α i is the preset voltage correction coefficient, V i ( t ) is the first i The terminal voltage of each cell, T i ( t ) is the first i The temperature of each cell, V oc,i ( SOC i ( t- 1), T i ( t )) is the first i The estimated open circuit voltage of each battery cell under the state of charge of the previous control cycle and the current temperature conditions.

3. The method for controlling power balance of a mobile power supply according to claim 1, wherein: After obtaining the estimated SOC value of each battery cell, the method further includes: Construct a state vector for each cell based on the multi-dimensional state information and SOC estimation value of each cell; Obtaining a preset state vector threshold interval, and performing abnormal state identification processing on each battery cell based on the state vector threshold interval and the state vector of each battery cell; If an abnormal battery cell is identified from the mobile power supply, power isolation control is performed on the abnormal battery cell.

4. The method for controlling power balance of a mobile power supply according to claim 1, wherein: The SOC standard deviation between the cells is: ； Where, N is the total number of cells in the mobile power supply, SOC i ( t ) is the first i The estimated SOC value of each cell in the current control cycle, i ∈{1,2,…, N }, is the average SOC of all cells in the mobile power supply in the current control cycle.

5. A power balancing control system for a mobile power source, characterized in that: include: Status information acquisition module, used to collect multi-dimensional status information of each battery cell in the mobile power supply; An SOC estimation module is communicatively connected to the state information acquisition module and is used to perform SOC estimation processing on each battery cell according to the multi-dimensional state information of each battery cell to obtain an estimated SOC value of each battery cell; a power balancing control module, communicatively connected to the SOC estimation module, configured to calculate the standard deviation of the estimated SOC values ​​of all battery cells to obtain the SOC standard deviation between the battery cells, and determine whether the SOC standard deviation between the battery cells is greater than a preset standard deviation threshold; if so, determining that a power balancing operation is required for the mobile power supply, and performing a power cell energy scheduling process on the mobile power supply based on the estimated SOC value of each battery cell; if not, determining that a power balancing operation is not required for the mobile power supply, and re-collecting the multi-dimensional status information of each battery cell in the mobile power supply; Performing cell energy scheduling processing on the mobile power supply according to the estimated SOC value of each cell, including: Construct a directed graph with each cell as a node and the energy transfer path between cells as an edge, and define the weight of the edge of the directed graph as the energy transfer cost; wherein, from the mobile power supply i battery cells v i Point to the j battery cells v j edge e ij The weight is: ； Where, SOC i ( t ) is the first i The estimated SOC value of each cell in the current control cycle, SOC j ( t ) is the first j The estimated SOC value of each cell in the current control cycle, i , j ∈{1,2,…, N },and i ≠ j , R eq,ij is the total equivalent resistance of the current loop, R eq,ij = R i ( t )+ R j ( t )+ R bal ( t ), R i ( t ) is the first i The dynamic internal resistance of each cell in the current control cycle, R j ( t ) is the first j The dynamic internal resistance of each cell in the current control cycle, R bal ( t ) is the preset equivalent impedance; Based on a path optimization algorithm with minimum edge weight, an energy transfer path set consisting of multiple optimal transfer paths is screened from the directed graph; Based on the energy transfer path set, controlling the controlled cells corresponding to each optimal transfer path in the mobile power supply to perform energy transfer; Controlling the controlled cells corresponding to any optimal transfer path in the mobile power supply to perform energy transfer includes: Obtaining the latest SOC estimated values ​​of two to-be-controlled cells in the mobile power supply corresponding to any one of the optimal transfer paths; Determine whether the difference between the larger of the latest SOC estimated values ​​of the two cells to be controlled and the average SOC value of all cells to be controlled is greater than a preset SOC deviation threshold. If so, proceed to the next step. Determine whether the difference between the smaller of the latest SOC estimated values ​​of the two cells to be controlled and the average SOC value of all cells to be controlled is greater than a preset SOC deviation threshold. If so, skip any of the optimal transfer paths; if not, proceed to the next step. Driving the energy transfer from the one with the larger latest SOC estimated value among the two cells to be controlled to the one with the smaller latest SOC estimated value until the standard deviation of the cells to be controlled in the mobile power supply is less than a preset termination threshold; In the process of controlling the energy transfer of the cells to be controlled corresponding to the optimal transfer paths in the mobile power supply, the method further includes: Real-time collection of multi-dimensional state information of the cells to be controlled corresponding to each optimal transfer path, and SOC estimation processing of each cell to be controlled to obtain the latest SOC estimation value of each cell to be controlled; Calculate the SOC change rate of each cell to be controlled based on the latest SOC estimated value of each cell to be controlled; Determine whether the deviation of the SOC change rate of each cell to be controlled from the rate mean is greater than a preset rate deviation threshold; If the SOC change rate of any cell to be controlled deviates from a preset rate threshold, it is determined that any cell to be controlled has an abnormality, and energy regulation of any cell to be controlled is suspended.

6. An electronic device, characterized in that: include: a memory for storing computer program instructions; as well as, A processor is configured to execute the computer program instructions to complete the operation of the power balancing control method for a mobile power supply according to any one of claims 1 to 4.

7. A computer program product comprising a computer program or instructions, characterized in that When the computer program or the instruction is executed by a computer, the power balancing control method of a mobile power supply according to any one of claims 1 to 4 is implemented.

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