Active equalization system and method for energy storage power pack based on fuzzy control

Abstract

The invention discloses an energy storage power pack active equalization system and method based on fuzzy control, and the method comprises the steps: obtaining the current state information of each single battery in an energy storage power pack, and the current state information comprises a state of charge (SOC) and a voltage; based on a fuzzy logic control model, taking the current state information as an input variable, and outputting a corresponding equalizing current signal; and generating a corresponding control instruction based on the output equalization current signal, adjusting an equalization circuit of each single battery in the energy storage power pack, and implementing active equalization operation. The energy difference between the single batteries can be effectively reduced, the overall performance of the battery pack is improved, and the service life is prolonged.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage power supply, and in particular to an active balancing system and method for an energy storage power supply group based on fuzzy control. Background Art

[0002] With the transformation of the global energy structure and the enhancement of environmental protection awareness, the use of renewable energy has become an important direction for global energy development. As an important part of the renewable energy system, energy storage technology is of great significance for improving energy utilization efficiency and ensuring the stable operation of the power grid. Among them, lithium-ion batteries have been widely used in the field of energy storage due to their high energy density, long cycle life and environmental protection characteristics. However, in actual applications, due to differences in the manufacturing process, battery aging and different use environments, the single cells in the series energy storage power pack often have inconsistency problems, which seriously affects the performance and life of the entire battery pack.

[0003] Existing technologies are mainly divided into two categories: passive balancing and active balancing. Passive balancing methods usually achieve voltage or SOC (State of Charge) balance between battery cells by dissipating excess energy, but their efficiency is low and will accelerate the loss of battery energy. In contrast, active balancing technology achieves balance between battery cells by transferring or redistributing energy, thereby improving the overall system efficiency and battery pack life.

[0004] Therefore, there is an urgent need for an active balancing system and method for energy storage power supply groups based on fuzzy control. Summary of the invention

[0005] The present invention provides an active balancing system and method for an energy storage power supply group based on fuzzy control to solve the above-mentioned problems existing in the prior art.

[0006] In order to achieve the above object, the present invention provides the following technical solutions:

[0007] The active balancing method of energy storage power supply group based on fuzzy control includes:

[0008] S101: Acquire current status information of each single cell in the energy storage power supply group, where the current status information includes the state of charge SOC and voltage;

[0009] S102: Based on the fuzzy logic control model, the current state information is used as an input variable, and a corresponding balanced current signal is output;

[0010] S103: Based on the output balancing current signal, a corresponding control instruction is generated to adjust the balancing circuit of each single cell in the energy storage power supply group to implement active balancing operation.

[0011] Wherein, step S101 includes:

[0012] S1011: Obtain distribution data of each single battery in the energy storage power supply group, and generate an energy storage power supply topology network according to the battery distribution data;

[0013] S1012: Determine the connection relationship between each single cell in the energy storage power supply group based on the energy storage power supply topology network, and respectively obtain the status monitoring data of the temperature, SOC and voltage of each single cell on the energy storage power supply topology network;

[0014] S1013: Determine the interaction interface between each single battery based on the status monitoring data;

[0015] S1014: Match the interactive interface with each single battery, and determine the current state information corresponding to each interface based on the current temperature, SOC and voltage of the matching single battery corresponding to each interface.

[0016] Wherein, step S102 includes:

[0017] S1021: based on the fuzzy logic control model, convert the input SOC value and voltage value into corresponding fuzzy set representation;

[0018] S1022: Input the fuzzy set into the fuzzy reasoning engine, perform logical reasoning according to the preset fuzzy rule set, and generate a fuzzy balanced current;

[0019] S1023: The fuzzy balancing current is converted into an accurate balancing current value as a control output through a defuzzification device.

[0020] Wherein, step S103 includes:

[0021] S1031: Determine the amount of balancing current required for each single cell according to the precise balancing current value, and calculate the corresponding balancing current flow direction and magnitude;

[0022] S1032: Generate a control instruction according to the flow direction and magnitude of the balancing current, for adjusting the balancing circuit of each single cell in the energy storage power supply group;

[0023] S1033: Send a control instruction to the balancing circuit of the energy storage power pack to adjust the current direction and flow rate in the battery pack, so that the voltage difference between each single battery is kept within a preset range, thereby realizing active balancing operation of the battery pack.

[0024] Among them, the fuzzy logic control model includes:

[0025] According to the SOC value and the voltage value, the fuzzy set of the input parameters is defined, and the membership range of the input parameters is determined;

[0026] Configure the inference engine and fuzzifier of the fuzzy logic controller based on a preset set of fuzzy rules;

[0027] Determine the fuzzy set membership range of the output balancing current;

[0028] The fuzzy set of input parameters, fuzzy rule set and output fuzzy set are integrated to build a complete fuzzy logic control model.

[0029] Among them, the fuzzy set of input parameters is defined, including:

[0030] The fuzzy set is defined according to the range of SOC values. When the SOC value is between 20% and 80%, the SOC is used as the core control parameter to implement the fuzzy control strategy. In this range, the membership ranges of the input and variation of SOC are defined as [0%-20%] and [0%-60%] respectively.

[0031] When the SOC value falls into the interval of 0%-20% or 80%-100%, the voltage value is used as the control variable, and the fuzzy set of the voltage input and its variation is defined. The membership ranges of the voltage input and variation are set to [0V-0.2V] and [0V-1.2V] respectively;

[0032] The fuzzy sets of SOC value and voltage value are refined into five fuzzy subsets respectively. The fuzzy subsets of SOC value include: extremely small (VS), small (S), medium (M), large (L), and extremely large (VL); the fuzzy subsets of voltage value include: extremely small (VS), small (S), medium (M), large (L), and extremely large (VL);

[0033] The current value is limited to the range of [0-5]A and is divided into five levels according to this range, including: very small (VS), small (S), medium (M), large (L), and very large (VL).

[0034] Among them, the fuzzy set membership range for determining the output balanced current includes:

[0035] Determine whether the SOC value is within the range of 20% to 80%;

[0036] The voltage difference of the battery is judged according to the SOC value, and whether the balancing current needs to be adjusted intelligently. If the SOC value is between 20% and 80% and the battery voltage difference is large, the balancing current is increased to accelerate the balancing process and shorten the balancing time. On the contrary, if the battery voltage difference is small, a conservative strategy is adopted to reduce the balancing current and reduce battery loss or stress.

[0037] When the SOC value is in the range of 0% to 20% or 80% to 100%, the balancing current is adjusted according to the voltage difference; if the battery voltage difference is large, a larger balancing current is output to accelerate the balancing process; if the battery voltage difference is small, the balancing current is reduced to prevent the risk of overcharging or over-discharging;

[0038] Monitor the voltage and current status of the battery in real time, dynamically adjust the output balancing current according to the real-time status of the battery, and calculate the corresponding balancing current value according to the current situation of the battery pack to ensure that the balancing process strikes a balance between efficiency and safety;

[0039] Using the fuzzy logic control model, the real-time monitoring parameters of the battery voltage difference and SOC value are input into the fuzzy set, and the membership value corresponding to each parameter is calculated. According to the combination of different membership values, the corresponding balancing current adjustment strategy is output to realize intelligent adjustment of the balancing current.

[0040] Among them, the fuzzy set membership range of the output balanced current includes:

[0041] The fuzzy set membership range of the output balancing current is adjusted by the following fuzzy control rules:

[0042] When the battery voltage difference is greater than the preset voltage difference value and the SOC value is between 20% and 80%, a balancing current greater than the preset value is output;

[0043] When the battery voltage difference is less than the preset voltage difference value and the SOC value is between 20% and 80%, the output is less than the preset equalization current;

[0044] When the SOC value is between 0% and 20% or between 80% and 100%, and the battery voltage difference is greater than the preset voltage difference value, a balancing current greater than the preset value is output;

[0045] When the SOC value is between 0% and 20% or between 80% and 100%, and the battery voltage difference is smaller than a preset voltage difference value, a balancing current smaller than a preset value is output.

[0046] The amount of balancing current required for each single cell is determined, including:

[0047] Based on the current accurate balancing current value and preset balancing parameters, determine the balancing current required for each single cell, and calculate the corresponding balancing current flow direction and magnitude;

[0048] When the absolute value of the deviation between the average SOC values ​​of two batteries randomly selected during the balancing process exceeds a preset threshold, it is determined that battery balancing is required, the balancing control module is started, and a balancing start instruction is sent to the battery management system;

[0049] Otherwise, it is determined that the current battery pack is in a balanced state, the existing current distribution is maintained, and no balancing operation is performed;

[0050] When the current battery pack needs to be balanced, it includes:

[0051] Based on the real-time SOC value of each single battery in the current battery pack, the absolute value of the deviation between the average SOC values ​​of any two batteries is calculated as the input variable of the fuzzy controller;

[0052] The absolute value of the deviation between the average SOC values ​​of the two batteries randomly selected during the balancing process and the total current load of the battery pack are taken as key parameters. The two key parameters together constitute the input variables of the fuzzy controller. The specific calculation is as follows:

[0053] Calculate the average SOC of the two batteries;

[0054] Calculate the absolute value of the deviation between the average SOC values ​​of the two batteries;

[0055] Adjust the balancing strategy according to the total current load;

[0056] The calculation results are input into the fuzzy controller for processing;

[0057] Among them, represents the average SOC value of the two batteries in the balanced state, and represents the SOC values ​​of the two single cells charged and discharged during the balancing process;

[0058] When using the fuzzy quantity output by the fuzzy controller, defuzzification processing is performed to convert the fuzzy quantity into a clear balanced current value. The specific steps include:

[0059] Based on the area center defuzzification method, the output result of the fuzzy controller is converted into an accurate balanced current value. The calculation formula is as follows:

[0060]

[0061] Among them, ε(S) represents the fuzzy result of reasoning, S represents a variable in the control input space, and the balancing current value obtained by defuzzification is used to guide the balancing operation of each single battery;

[0062] According to the balancing current value obtained by defuzzification processing, the flow direction and magnitude of the balancing current of each single cell are determined, including:

[0063] If the SOC of a single cell is higher than the average value, the cell is discharged through a balancing current;

[0064] If the SOC of a single cell is lower than the average value, the battery is charged by a balancing current;

[0065] Based on the determined balancing current direction and size, the charging and discharging status of each single cell in the battery pack is adjusted in real time to ensure the SOC balance of the entire battery pack.

[0066] Among them, the active balancing system of energy storage power supply group based on fuzzy control includes:

[0067] An acquisition unit is used to acquire current status information of each single cell in the energy storage power supply group, and the current status information includes the state of charge SOC and voltage;

[0068] An information analysis unit, used to take the current state information as an input variable and output a corresponding balanced current signal based on a fuzzy logic control model;

[0069] The instruction generation unit is used to generate corresponding control instructions based on the output balancing current signal, adjust the balancing circuit of each single cell in the energy storage power supply group, and implement active balancing operation.

[0070] Compared with the prior art, the present invention has the following advantages:

[0071] The active balancing method of energy storage power supply group based on fuzzy control includes: obtaining the current state information of each single battery in the energy storage power supply group, the current state information includes the state of charge SOC and voltage; based on the fuzzy logic control model, taking the current state information as the input variable, outputting the corresponding balancing current signal; based on the output balancing current signal, generating the corresponding control instruction, adjusting the balancing circuit of each single battery in the energy storage power supply group, and implementing the active balancing operation. It can more effectively reduce the energy difference between battery monomers and improve the overall performance and service life of the battery pack.

[0072] Other features and advantages of the present invention will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the present invention.

[0073] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0075] Figure 1 It is a flow chart of an active balancing method of an energy storage power supply group based on fuzzy control in an embodiment of the present invention;

[0076] Figure 2 It is a structural diagram of active balancing of energy storage power supply group based on fuzzy control in an embodiment of the present invention;

[0077] Figure 3 This is a bidirectional DC / DC circuit in the fuzzy logic control model in an embodiment of the present invention. DETAILED DESCRIPTION

[0078] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0079] The embodiment of the present invention provides an active balancing method for an energy storage power supply group based on fuzzy control, comprising:

[0080] S101: Acquire current status information of each single cell in the energy storage power supply group, where the current status information includes the state of charge SOC and voltage;

[0081] S102: Based on the fuzzy logic control model, the current state information is used as an input variable, and a corresponding balanced current signal is output;

[0082] S103: Based on the output balancing current signal, a corresponding control instruction is generated to adjust the balancing circuit of each single cell in the energy storage power supply group to implement active balancing operation.

[0083] The working principle of the above technical solution is: first monitor and obtain the current state of charge (SOC) and voltage of each single cell in the energy storage power supply group. These data are the basis of the balancing operation and can reflect the current health status of the battery and the energy storage situation.

[0084] Input and output of fuzzy controller: In fuzzy control system, SOC and voltage are used as input variables and converted into fuzzy set representation by fuzzifier. The function of fuzzifier is to convert precise numerical values ​​(such as SOC=80% and voltage=3.7V) into fuzzy language variables suitable for fuzzy reasoning (such as "lower SOC", "higher voltage", etc.).

[0085] Fuzzy reasoning: Fuzzy variables enter the reasoning engine and are reasoned based on a preset set of fuzzy rules (such as "if the SOC is low and the voltage is high, then output a larger balancing current"). The reasoning engine uses fuzzy logic rules to logically deduce the input information and generate a fuzzy control signal that indicates the need for adjustment of battery balancing.

[0086] Defuzzification and output: After inference, the fuzzy control signal needs to be converted into a specific balancing current value through the defuzzification device. This value will be output as a balancing current signal to drive the balancing circuit to adjust each single cell to ensure that the battery's state of charge and voltage tend to be consistent, thereby achieving battery pack balancing.

[0087] Active balancing operation: Based on the output balancing current signal, the system automatically generates control instructions, and implements active balancing operation by adjusting the current flow direction in the battery balancing circuit or the energy transfer between batteries to optimize the performance and service life of the battery pack.

[0088] like Figure 3 As shown, there are two MOSFETs (Q1 and Q2) and two diodes (D1 and D2). These switching elements can control the direction of current flow and realize bidirectional energy conversion. For example, when Q1 is turned on, the current can flow from the capacitor C1 on the left to the capacitor C2 on the right, and when Q2 is turned on, the reverse energy transfer can be realized. The circuit includes two capacitors (C1 and C2) and an inductor (L). The capacitor is used to store electrical energy, and the inductor is used to smooth the current and reduce the voltage spike during switching. The connection of the circuit presents a push-pull topology, in which Q1 and D1 are paired, and Q2 and D2 are paired. In this configuration, when a MOSFET is in the on state, the corresponding diode is in the off state, and vice versa. This alternating conduction and cutoff mode allows current to flow bidirectionally between the two capacitors and between the external circuit.

[0089] The design advantages of this bidirectional DC / DC converter include: By utilizing the bidirectional characteristics of MOSFETs and diodes, the need for additional protection or control components is reduced. The energy loss that may be caused by traditional transformers is reduced, and the inductance and capacitance in the circuit also help optimize the storage and release of energy, improving conversion efficiency. The design of the circuit supports efficient and smooth transfer of energy from one power supply to another. Based on this circuit diagram, a fuzzy logic control model can be designed to dynamically adjust the switch state to cope with different load and power supply conditions. Fuzzy logic control can optimize the opening and closing time of the switch, further improving the efficiency and response speed of the circuit.

[0090] The beneficial effects of the above technical solution are as follows: the fuzzy logic controller can optimize the state of charge and voltage balance between the cells in the battery pack by accurately controlling the balancing current. Compared with the traditional balancing method, fuzzy control can handle complex situations in the battery pack more flexibly, especially when the battery status changes rapidly or varies greatly. Through active balancing control, the system can ensure that each cell works in its optimal state, avoid overcharging or over-discharging of some cells, and reduce the imbalance between cells, thereby effectively extending the service life of the battery pack and improving the reliability of the system.

[0091] In another embodiment, step S101 includes:

[0092] S1011: Obtain distribution data of each single battery in the energy storage power supply group, and generate an energy storage power supply topology network according to the battery distribution data;

[0093] S1012: Determine the connection relationship between each single cell in the energy storage power supply group based on the energy storage power supply topology network, and respectively obtain the status monitoring data of the temperature, SOC and voltage of each single cell on the energy storage power supply topology network;

[0094] S1013: Determine the interaction interface between each single battery based on the status monitoring data;

[0095] S1014: Match the interactive interface with each single battery, and determine the current state information corresponding to each interface based on the current temperature, SOC and voltage of the matching single battery corresponding to each interface.

[0096] The working principle of the above technical solution is as follows: First, the system collects the distribution data of each single cell in the energy storage power supply group. These data include the location of the battery, the connection method, and the specific parameters of the battery (for example, the battery number, location coordinates, etc.). Based on these distribution data, the system constructs a topological network of the energy storage power supply, that is, a network diagram of the connection relationship and relative position relationship between the batteries. Topological network: It is analogous to a "map" of the batteries inside the battery pack, which helps to understand the specific location of each battery in the entire system and how it is connected to other batteries.

[0097] Based on the topological network of the energy storage power supply, the system can clearly identify the connection relationship between the individual cells in the energy storage power supply group, such as which cells are connected in series and which are connected in parallel. In this way, the system can obtain the status monitoring data of each battery in the battery pack, including: Temperature: reflects the operating temperature of the battery and affects the battery performance. SOC (state of charge): indicates the current power of the battery, usually expressed as a percentage. Voltage: indicates the potential difference of the battery, which is an important indicator of the battery's working status.

[0098] Based on the analysis of the status monitoring data, the system determines the "interaction interfaces" between the batteries. These interaction interfaces refer to the connection points where information and energy can be exchanged between batteries. They are usually physical interfaces, such as cables, battery management system (BMS) interfaces, etc. Interaction interfaces: They are the "communication bridge" between batteries, responsible for transmitting battery status information and energy.

[0099] The system matches each interactive interface with the battery, and determines the specific status information corresponding to each interactive interface according to the current status of the single battery connected to each interface (including temperature, SOC, voltage, etc.). For example, if an interface is connected to battery A, and the status of battery A is 30℃, SOC is 80%, and voltage is 3.7V, the system will match this status information with the interface.

[0100] The beneficial effects of the above technical solution are: by obtaining the status monitoring data (temperature, SOC, voltage, etc.) of each battery and matching it with the interactive interface of the battery, the system can monitor the health status of the battery in real time. This helps to promptly detect problems in the battery pack, such as excessive temperature, unbalanced SOC or abnormal voltage, to ensure the stable operation of the battery pack. According to the connection relationship and topological structure of the battery, the system can reasonably distribute the energy between batteries according to the current state of each battery. For example, if the SOC of a battery is low and the SOC of other batteries is high, the system can start energy exchange between batteries to improve the overall battery efficiency. The system can perform intelligent health management by analyzing the status information of the battery. For example, if the temperature of a battery rises abnormally or the voltage is low, the system can issue an alarm or take measures in time to avoid the occurrence of failures.

[0101] In another embodiment, step S102 includes:

[0102] S1021: based on the fuzzy logic control model, convert the input SOC value and voltage value into corresponding fuzzy set representation;

[0103] S1022: Input the fuzzy set into the fuzzy reasoning engine, perform logical reasoning according to the preset fuzzy rule set, and generate a fuzzy balanced current;

[0104] S1023: The fuzzy balancing current is converted into an accurate balancing current value as a control output through a defuzzification device.

[0105] The fuzzy set is input into the fuzzy inference engine, including:

[0106] Based on the sensor, the current state parameters of the battery system are obtained, including the state of charge (SOC) and voltage level of the battery, and these parameters are converted into corresponding fuzzy sets and input into the fuzzy inference engine;

[0107] Based on a preset fuzzy rule set, fuzzy logic reasoning is performed to determine the balancing requirements of the battery system, specifically including: matching the input SOC and voltage fuzzy sets with the preset fuzzy rules;

[0108] Perform fuzzification on each fuzzy rule and determine the activation level of the rule (activation level refers to the effectiveness or degree of a fuzzy rule under a given input, for example, when the SOC is 50% and the voltage is low, the activation level of a rule (such as "if the SOC is low and the voltage is low, charging is required") is 80%);

[0109] All activated fuzzy rules are integrated and fuzzy reasoning mechanism is applied to generate preliminary output of fuzzy balanced current.

[0110] The working principle of the above technical solution is as follows: the battery balancing controller adopts a control model based on fuzzy logic, which aims to optimize the charging and discharging process of the battery pack and ensure that the battery can be balanced efficiently and smoothly under different states of charge (SOC) and voltages. The core idea is to dynamically adjust the balancing current according to the SOC and voltage of the battery through fuzzy control strategy, optimize the battery balancing efficiency and avoid the risk of overcharging or over-discharging.

[0111] First, the battery SOC and voltage are used as input signals, and these precise input values ​​are converted into corresponding fuzzy sets (i.e., fuzzy variables) through the fuzzifier. These fuzzy variables represent the fuzzy levels of SOC and voltage in different intervals, such as "low SOC", "medium SOC" and "high SOC".

[0112] Next, the fuzzy set is input into the fuzzy inference engine. The engine performs inference based on a preset set of fuzzy rules. Fuzzy rules usually include logical relationships such as "if the SOC is low and the voltage is also low, then output a larger balancing current" or "if the SOC is high and the voltage is high, then output a smaller balancing current". These rules combine the actual characteristics of the battery and the optimization goals to avoid overcharging and over-discharging caused by extreme SOC ranges.

[0113] The inference result is converted into an accurate balancing current value through the defuzzification device. The defuzzification process returns the fuzzy variable to an accurate value that can be directly used for control. The controller uses this value to drive the output of the battery balancing current to ensure that the voltage and SOC of the battery pack are balanced.

[0114] The beneficial effect of the above technical solution is that through this control process, the SOC of the battery pack during the charge and discharge cycle can be controlled more accurately and stably, avoiding the over-discharge or over-charge problems that may be caused by traditional control strategies, thereby improving the use efficiency and safety of the battery pack.

[0115] In another embodiment, step S103 includes:

[0116] S1031: Determine the amount of balancing current required for each single cell according to the precise balancing current value, and calculate the corresponding balancing current flow direction and magnitude;

[0117] S1032: Generate a control instruction according to the flow direction and magnitude of the balancing current, for adjusting the balancing circuit of each single cell in the energy storage power supply group;

[0118] S1033: Send a control instruction to the balancing circuit of the energy storage power pack to adjust the current direction and flow rate in the battery pack, so that the voltage difference between each single battery is kept within a preset range, thereby realizing active balancing operation of the battery pack.

[0119] Regulate the current direction and flow within the battery pack, including:

[0120] Determine the need to deliver current to a cell with a lower voltage, or to draw current from a cell with a higher voltage;

[0121] Obtain the type of balancing circuit corresponding to each single battery (active balancing circuit such as a DC-DC converter or passive balancing circuit such as a resistive load);

[0122] Depending on the type of balancing circuit, adjust the direction and amount of current flow. For example, when using an active balancing circuit, the direction and amount of current are adjusted by a DC-DC converter; when using a passive balancing circuit, the current flow is controlled by adjusting the resistance load;

[0123] Monitor the adjusted current direction and flow to ensure compliance with the requirements of the balanced control strategy;

[0124] According to the real-time balancing control strategy, the current direction and flow of each single cell are dynamically adjusted, and the voltage difference is continuously monitored to ensure that the voltage difference of the battery pack remains within the preset range. Specifically, it includes: continuously obtaining the voltage and current data of each single cell; comparing the voltage difference of each single cell with the preset range in real time; dynamically adjusting the control instructions to optimize the current direction and flow to cope with the changes in voltage difference; ensuring that the current direction and flow change smoothly during the adjustment process to avoid adverse effects on the performance and life of the battery pack;

[0125] When it is detected that the voltage difference has returned to the preset range, the active balancing operation is stopped to keep the current direction and flow of each single cell in a stable state, including: confirming that the voltage difference of all single cells has fallen back to the preset range; sending a control instruction to stop the balancing operation to the balancing circuit of each single cell; recording the balancing state of the battery pack to the energy storage system management platform for subsequent analysis and optimization;

[0126] The preset ranges include:

[0127] According to the design specifications and usage requirements of the battery pack, the maximum allowable voltage difference between each single battery is set;

[0128] Dynamically adjust the preset range to optimize the balancing strategy based on the working status and environmental conditions of the battery pack;

[0129] The working principle of the above technical solution is as follows: First, the controller determines the amount of balancing current required for each single cell based on the precise balancing current value calculated in the previous step. The balancing current size of each single cell may be different, depending on the current SOC (state of charge) and voltage difference of the battery. According to the charge and discharge status of each battery (such as high or low voltage), the system will calculate the direction of flow of the balancing current. For example, if the voltage of a battery is higher than that of other batteries, the balancing current will flow out of the battery, and vice versa, it will flow from other batteries to the battery. The size of the balancing current will also be dynamically adjusted according to the voltage difference between the batteries and the state of the batteries.

[0130] According to the direction and magnitude of the equalizing current flow calculated in the previous step, the controller will generate corresponding control instructions. These control instructions are used to adjust the equalizing circuits of each single cell in the energy storage power supply group. For example, if the voltage of a certain battery is higher, the control instruction will require the excess power of the battery to be released to other batteries through the equalizing circuit; if the battery voltage is lower, the instruction will require power to be drawn from other batteries.

[0131] The control command is sent to the balancing circuit in the energy storage power pack. Each single cell regulates the current and controls the flow direction through its balancing circuit. For example, the balancing circuit used in the battery pack includes an active balancing circuit (such as a DC-DC converter) or a passive balancing circuit (such as a resistive load), which adjusts the flow direction and flow rate of the current according to the control command.

[0132] The beneficial effects of the above technical solution are: by accurately controlling the balancing current of each battery and adjusting the direction of current flow, the voltage difference between each single battery in the battery pack can be effectively reduced. When the voltage of some batteries in the battery pack is higher, these batteries will actively release excess power, while the batteries with lower voltage will absorb power. This active balancing process can ensure that the voltage of all batteries is at the same level, thereby improving the overall performance of the battery pack. The balancing control of the battery pack can optimize the charging and discharging process of the battery. By dynamically adjusting the current flow direction and size of each battery, some batteries can be prevented from being filled too early or over-discharged, making the entire battery pack more efficient during use. This balancing process can ensure the maximum capacity of the battery pack while avoiding energy loss caused by imbalance.

[0133] In another embodiment, the fuzzy logic control model includes:

[0134] According to the SOC value and the voltage value, the fuzzy set of the input parameters is defined, and the membership range of the input parameters is determined;

[0135] Configure the inference engine and fuzzifier of the fuzzy logic controller based on a preset set of fuzzy rules;

[0136] Determine the fuzzy set membership range of the output balancing current;

[0137] The fuzzy set of input parameters, fuzzy rule set and output fuzzy set are integrated to build a complete fuzzy logic control model.

[0138] The working principle of the above technical solution is: the SOC value represents the current state of charge of the battery, usually ranging from 0% (battery fully discharged) to 100% (battery fully charged). In the fuzzy logic controller, the SOC value will be divided into several fuzzy subsets, such as "low", "medium", "high", etc. For example, when the SOC value is 20%, it may belong to the "low" set, while 40% belongs to the "medium" set.

[0139] The voltage value represents the voltage state of the battery, and the voltage range of the battery is usually related to the SOC. In the fuzzy logic controller, the voltage value will be divided into several fuzzy sets, such as "low voltage", "normal voltage", and "high voltage". For example, when the battery voltage is 3.5V, it may be in the "normal voltage" range, and when the voltage is 4.2V, it belongs to the "high voltage" set.

[0140] Membership: Each input parameter (SOC value and voltage value) has a membership value, which indicates the degree to which the parameter belongs to a fuzzy set. The membership range is generally [0,1], where 0 means it does not belong to the set and 1 means it completely belongs to the set. For example, if the battery's SOC is 30%, it may belong to the "low SOC" set with a membership of 0.7, while it may belong to the "medium SOC" set with a membership of 0.3.

[0141] Fuzzy rule set: Fuzzy rule set is the core of control decision. It is usually based on experience and expert knowledge to build logical relationships between different input parameters and outputs. For example, a fuzzy rule set may contain the following rules: Rule 1: If SOC is "low" and voltage is "high", then the balancing current is "strong".

[0142] Rule 2: If the SOC is "Medium" and the voltage is "Low", the balancing current is "Weak".

[0143] Rule 3: If SOC is "High" and voltage is "Normal", the balancing current is "None".

[0144] Inference engine: The inference engine is used to calculate the output balanced current based on the input fuzzy set, rule set and membership. It derives the conclusion part (such as "balanced current is strong") based on the premise part (such as "SOC is low" and "voltage is high") in the fuzzy rule set. The inference engine usually uses inference methods such as Mamdani method (the most common fuzzy inference method) or Sugeno method for reasoning.

[0145] The output balancing current value also needs to be fuzzy processed. Usually, the output current is divided into several fuzzy sets of "weak", "medium" and "strong" according to the control needs. For example, when the balancing current value is small (such as 50mA), it belongs to the "weak" set; when it is large (such as 500mA), it belongs to the "strong" set.

[0146] Through the fuzzy inference engine, the fuzzy set of input parameters (SOC and voltage) and the fuzzy rule set can deduce the fuzzy set of output current, and the membership range is calculated based on the inference results.

[0147] In the integration stage, fuzzy sets, fuzzy rules and fuzzy sets of output current need to be integrated to form a complete control model. Usually, the integration process includes:

[0148] Defuzzification: Since the output value of a fuzzy set is usually a range (such as "weak" or "strong"), and actual control requires an accurate value, defuzzification is to convert the fuzzy output into a specific balancing current value. Common defuzzification methods include the Centroid Method, which calculates the "center" of the fuzzy set to obtain the final balancing current value. Through this series of steps, the fuzzy logic controller can calculate the required balancing current in real time based on the battery's SOC value and voltage value, and drive the balancing circuit to make adjustments.

[0149] The beneficial effects of the above technical solution are: the fuzzy logic controller can flexibly deal with these imprecise and ambiguous information through fuzzy processing without the need for an accurate mathematical model. This enables the system to better cope with complex changes in actual operation. The fuzzy logic controller performs reasoning based on rules, which can achieve smoother and more precise control. For example, when the battery SOC value approaches the lower limit, the system can gradually increase the balancing current instead of increasing it sharply, thereby reducing system oscillations and unnecessary energy waste. This helps to improve the stability and efficiency of the battery pack.

[0150] In another embodiment, a fuzzy set of input parameters is defined, including:

[0151] The fuzzy set is defined according to the range of SOC values. When the SOC value is between 20% and 80%, the SOC is used as the core control parameter to implement the fuzzy control strategy. In this range, the membership ranges of the input and variation of SOC are defined as [0%-20%] and [0%-60%] respectively.

[0152] When the SOC value falls into the interval of 0%-20% or 80%-100%, the voltage value is used as the control variable, and the fuzzy set of the voltage input and its variation is defined. The membership ranges of the voltage input and variation are set to [0V-0.2V] and [0V-1.2V] respectively;

[0153] The fuzzy sets of SOC value and voltage value are refined into five fuzzy subsets respectively. The fuzzy subsets of SOC value include: extremely small (VS), small (S), medium (M), large (L), and extremely large (VL); the fuzzy subsets of voltage value include: extremely small (VS), small (S), medium (M), large (L), and extremely large (VL);

[0154] The current value is limited to the range of [0-5]A and is divided into five levels according to this range, including: very small (VS), small (S), medium (M), large (L), and very large (VL).

[0155] The working principle of the above technical solution is to adjust the system output current according to the battery SOC (State of Charge) and voltage value to optimize energy management. The system selects different control strategies according to different SOC ranges to ensure that the battery maintains the best state during the charging and discharging process.

[0156] Control strategy when SOC is in the range of 20%-80%: When the SOC value is between 20% and 80%, SOC is used as the core control parameter to implement fuzzy control. In this range, the input and change of SOC are defined as: input membership range: [0%-20%]; change membership range: [0%-60%]. According to these ranges, the fuzzy sets of SOC input and change are divided into five subsets: very small (VS), small (S), medium (M), large (L), and very large (VL). These subsets are described by membership functions to reflect the impact of different SOC values ​​on the control strategy.

[0157] Control strategy when the SOC value is in the range of 0%-20% or 80%-100%: When the SOC value is in the range of 0%-20% or 80%-100%, the system switches to the voltage control strategy. At this time, the voltage value is used as a control variable to control the fuzzy set of its input and change. Input membership range: [0V-0.2V]; change membership range: [0V-1.2V]. The input and change of voltage are also refined into five fuzzy subsets: extremely small (VS), small (S), medium (M), large (L), and extremely large (VL).

[0158] Current output control: Whether it is SOC control or voltage control, output current is the core control parameter. According to the maximum allowable current range [0-5A], the current value is divided into five levels: very small (VS), small (S), medium (M), large (L), and very large (VL). These levels are used to adjust the current output to ensure efficient operation of the system.

[0159] The beneficial effects of the above technical solution are as follows: after adopting the fuzzy control strategy, the system can flexibly adjust the control parameters according to the real-time changes of SOC and voltage. In this way, when the SOC is in different intervals, the current output can be accurately adjusted to avoid overcharging or over-discharging of the battery, thereby improving the stability and efficiency of the system. When the SOC value is between 0% and 20% or 80% and 100%, the system automatically switches to a voltage control strategy, effectively preventing the battery from entering a dangerous range of overcharging or over-discharging, thereby protecting the battery life. The refined levels of current (extremely small, small, medium, large, and extremely large) enable the system to accurately control the current size according to actual needs, avoiding system instability or damage caused by excessive current fluctuations, while ensuring efficient use of energy.

[0160] In another embodiment, determining the fuzzy set membership range of the output balanced current includes:

[0161] Determine whether the SOC value is within the range of 20% to 80%;

[0162] The voltage difference of the battery is judged according to the SOC value, and whether the balancing current needs to be adjusted intelligently. If the SOC value is between 20% and 80% and the battery voltage difference is large, the balancing current is increased to accelerate the balancing process and shorten the balancing time. On the contrary, if the battery voltage difference is small, a conservative strategy is adopted to reduce the balancing current and reduce battery loss or stress.

[0163] When the SOC value is in the range of 0% to 20% or 80% to 100%, the balancing current is adjusted according to the voltage difference; if the battery voltage difference is large, a larger balancing current is output to accelerate the balancing process; if the battery voltage difference is small, the balancing current is reduced to prevent the risk of overcharging or over-discharging;

[0164] Monitor the voltage and current status of the battery in real time, dynamically adjust the output balancing current according to the real-time status of the battery, and calculate the corresponding balancing current value according to the current situation of the battery pack to ensure that the balancing process strikes a balance between efficiency and safety;

[0165] Using the fuzzy logic control model, the real-time monitoring parameters of the battery voltage difference and SOC value are input into the fuzzy set, and the membership value corresponding to each parameter is calculated. According to the combination of different membership values, the corresponding balancing current adjustment strategy is output to realize intelligent adjustment of the balancing current.

[0166] The working principle of the above technical solution is as follows: First, the working range of the battery is determined according to the SOC value of the battery. If the SOC value is between 20% and 80%, the battery balancing adjustment is mainly based on the battery voltage difference. At this time, if the voltage difference between the batteries is large, the system will increase the balancing current to speed up the balancing process and shorten the balancing time; if the voltage difference is small, the system will adopt a conservative strategy to reduce the balancing current to reduce battery loss and stress.

[0167] When the battery's SOC value is between 0% and 20% or 80% and 100%, the battery voltage difference is more critical. Within this range, the battery is prone to the risk of overcharge or over-discharge, so the equalization current should be adjusted more carefully. If the battery voltage difference is large, the system will output a larger equalization current to quickly equalize and prevent extreme situations of overcharge or over-discharge; if the battery voltage difference is small, the system will reduce the equalization current to ensure that the battery operates within a safe range.

[0168] The system dynamically adjusts the balancing current by monitoring the voltage and current status of the battery in real time. This means that during the entire balancing process, the voltage difference and SOC value of the battery will continuously affect the output value of the balancing current, so that the battery always works in a safe and efficient state.

[0169] Through the fuzzy control model, the system uses the battery voltage difference and SOC value as input variables, maps them into fuzzy sets, and calculates the equalization current adjustment strategy based on the membership value of each input variable. The membership value is generated by fuzzy rules, which can output the corresponding equalization current based on the changes in real-time battery status. The benefit of fuzzy logic is that it can handle complex and uncertain battery status, enabling the system to make intelligent decisions based on different situations.

[0170] The beneficial effects of the above technical solution are: by intelligently adjusting the balancing current, the system can adjust the balancing current in real time according to the battery voltage difference and SOC value, thereby greatly improving the efficiency of battery balancing. When the SOC value is in the range of 20% to 80%, when the battery voltage difference is large, increasing the balancing current to accelerate the balancing process can shorten the balancing time and reduce the working time of the entire system. When the battery voltage difference is small, the system will reduce the balancing current output to avoid excessive current causing additional loss or stress to the battery and extend the service life of the battery. This conservative strategy helps to reduce unnecessary battery loss and maintain the stability of the battery pack. When the SOC value is in the range of 0% to 20% or 80% to 100%, overcharging or over-discharging is a potential risk to the battery. By lowering the balancing current when the voltage difference is small, the system can effectively prevent overcharging or over-discharging of the battery and ensure the safe operation of the battery pack.

[0171] To implement the above control logic, two independent sets of fuzzy rules are designed, as shown in Tables 1 and 2.

[0172] Table 1 Fuzzy rules based on SOC

[0173]

[0174] Table 2 Fuzzy rules based on voltage

[0175]

[0176] In another embodiment, the fuzzy set membership range of the output balanced current includes:

[0177] The fuzzy set membership range of the output balancing current is adjusted by the following fuzzy control rules:

[0178] When the battery voltage difference is greater than the preset voltage difference value and the SOC value is between 20% and 80%, a balancing current greater than the preset value is output;

[0179] When the battery voltage difference is less than the preset voltage difference value and the SOC value is between 20% and 80%, the output is less than the preset equalization current;

[0180] When the SOC value is between 0% and 20% or between 80% and 100%, and the battery voltage difference is greater than the preset voltage difference value, a balancing current greater than the preset value is output;

[0181] When the SOC value is between 0% and 20% or between 80% and 100%, and the battery voltage difference is smaller than a preset voltage difference value, a balancing current smaller than a preset value is output.

[0182] The working principle of the above technical solution is as follows: Battery voltage difference: refers to the voltage difference between each single battery in the battery pack. For example, if there are two batteries in a battery pack, one of which has a lower voltage and the other has a higher voltage, then the voltage difference of the two batteries is their voltage difference.

[0183] SOC (State of Charge) value: Indicates the remaining power of the battery, that is, the current charging state of the battery. For example, if the SOC value of the battery is 50%, it means that the remaining power of the battery is half of the total capacity.

[0184] Fuzzy control rules: The system determines the output balancing current through set fuzzy rules according to different combinations of battery voltage differences and SOC values. The specific rules are as follows:

[0185] When the battery voltage difference is greater than the preset value and the SOC value is between 20% and 80%, a larger balancing current is output. This is because when the battery voltage difference is large, a larger current is required to achieve voltage balance between batteries.

[0186] When the battery voltage difference is less than the preset value and the SOC value is between 20% and 80%, a smaller balancing current is output. When the voltage difference is small, only a smaller current is needed to maintain battery balance.

[0187] When the SOC value is between 0% and 20% or between 80% and 100%, the battery power is low or high. At this time, even if the battery voltage difference is large, a large balancing current is still required to avoid battery damage and ensure the stability of the charging process.

[0188] When the SOC value is between 0% and 20% or 80% and 100% and the battery voltage difference is small, a smaller balancing current is output to avoid unnecessary overcharging or discharging.

[0189] Adjustment of fuzzy set membership range:

[0190] The system uses fuzzy logic to determine the voltage difference and SOC value range of the battery. By setting the membership function, the system can convert these input values ​​into corresponding fuzzy values, and then calculate the output balancing current based on the fuzzy rules. The adjustment and optimization of the membership function ensures that the system can output the most corresponding balancing current under different voltage differences and SOC states.

[0191] The beneficial effects of the above technical solution are as follows: the balanced charging process of the battery is the key to maintaining the health of each single cell in the battery pack. By dynamically adjusting the balanced current under different voltage differences and SOC conditions, it is possible to effectively prevent damage to certain batteries due to overcharging or over-discharging, thereby extending the overall service life of the battery pack. The system automatically adjusts the output current according to the real-time changes in the battery voltage difference and SOC value, which can ensure that the efficiency of the battery charging process is maximized and unnecessary energy loss is avoided. Especially when the SOC value is low or high, the charging rate can be increased and energy waste can be reduced through reasonable current regulation. Due to the flexibility of the fuzzy control method, the system can adapt to changes in different battery packs and different charging environments. For example, different batteries may have different voltage differences and SOC ranges. The fuzzy control system can be dynamically adjusted according to the specific conditions of the battery pack to avoid the incompatibility problems that may be caused by traditional rigid rules.

[0192] In another embodiment, determining the amount of balancing current required for each single battery cell includes:

[0193] Based on the current accurate balancing current value and preset balancing parameters, determine the balancing current required for each single cell, and calculate the corresponding balancing current flow direction and magnitude;

[0194] When the absolute value of the deviation between the average SOC values ​​of two batteries randomly selected during the balancing process exceeds a preset threshold, it is determined that battery balancing is required, the balancing control module is started, and a balancing start instruction is sent to the battery management system;

[0195] Otherwise, it is determined that the current battery pack is in a balanced state, the existing current distribution is maintained, and no balancing operation is performed;

[0196] When the current battery pack needs to be balanced, it includes:

[0197] Based on the real-time SOC value of each single battery in the current battery pack, the absolute value of the deviation between the average SOC values ​​of any two batteries is calculated as the input variable of the fuzzy controller;

[0198] The absolute value of the deviation between the average SOC values ​​of the two batteries randomly selected during the balancing process and the total current load of the battery pack are taken as key parameters. The two key parameters together constitute the input variables of the fuzzy controller. The specific calculation is as follows:

[0199] Calculate the average SOC of the two batteries;

[0200] Calculate the absolute value of the deviation between the average SOC values ​​of the two batteries;

[0201] Adjust the balancing strategy according to the total current load;

[0202] The calculation results are input into the fuzzy controller for processing;

[0203] Among them, represents the average SOC value of the two batteries in the balanced state, and represents the SOC values ​​of the two single cells charged and discharged during the balancing process;

[0204] When using the fuzzy quantity output by the fuzzy controller, defuzzification processing is performed to convert the fuzzy quantity into a clear balanced current value. The specific steps include:

[0205] Based on the area center defuzzification method, the output result of the fuzzy controller is converted into an accurate balanced current value. The calculation formula is as follows:

[0206]

[0207] Among them, ε(S) represents the fuzzy result of reasoning, S is a variable in the control input space, and the balancing current value obtained by defuzzification is used to guide the balancing operation of each single battery;

[0208] According to the balancing current value obtained by defuzzification processing, the flow direction and magnitude of the balancing current of each single cell are determined, including:

[0209] If the SOC of a single cell is higher than the average value, the cell is discharged through a balancing current;

[0210] If the SOC of a single cell is lower than the average value, the battery is charged by a balancing current;

[0211] Based on the determined balancing current direction and size, the charging and discharging status of each single cell in the battery pack is adjusted in real time to ensure the SOC balance of the entire battery pack.

[0212] The working principle of the above technical solution is as follows: during the battery pack balancing process, the charge state (SOC) of each single cell is first calculated and compared with the average SOC value of all batteries in the battery pack. If the average value deviation of the SOC of any two batteries exceeds the preset threshold (i.e., the SOC difference is large), it indicates that the battery pack is unbalanced and the system will start the battery balancing operation; if the SOC deviation is less than the threshold, it is considered that the battery pack is in a balanced state and no operation is required.

[0213] The average SOC value of the single battery in the series energy storage power pack As a benchmark, two key parameters are introduced at the same time: one is the absolute value of the deviation of the average SOC value of the two batteries (i, j) selected arbitrarily during the balancing process, ΔSOC1, and the other is ΔSOC. These two parameters together constitute the input variables of the fuzzy controller, and the specific calculation is as follows:

[0214]

[0215]

[0216] ΔSOC=|SOC i -SOC j | (4)

[0217] In the formula: SOC χ Represents the average SOC value of two batteries in a balanced state, SOC i ,SOC j Respectively represent the SOC values ​​of the two single cells during charging and discharging in the balancing process.

[0218] When using the fuzzy quantities output by the fuzzy controller, since these quantities do not directly correspond to the exact current values, it is necessary to implement defuzzification to convert them into clear and accurate values ​​that can be directly applied to the balancing of the series energy storage power supply group. This paper specifically adopts the area center defuzzification method, and its calculation formula is as follows:

[0219]

[0220] In the formula: ε(S) represents the fuzzy result of reasoning, and S is a variable in the control input space.

[0221] According to the balancing current value I obtained after defuzzification, the charge and discharge status of each single battery is determined:

[0222] If the SOC of a single cell is higher than the average SOC of the battery pack, it needs to be discharged to flow current.

[0223] If the SOC of a single cell is lower than the average SOC of the battery pack, it needs to be charged and current flows into it.

[0224] The system adjusts the charge and discharge operations of each battery in real time according to the SOC value of each battery and the direction of the target balancing current to ensure that the SOC of the entire battery pack tends to be balanced.

[0225] During the entire balancing process, the total load current of the battery pack will also affect the balancing strategy. For example, if the battery pack load is large, the balancing strategy may need to be appropriately adjusted to avoid excessive balancing operations affecting overall performance. The system will dynamically adjust the balancing process based on real-time load information.

[0226] The beneficial effect of the above technical solution is that by real-time monitoring and adjusting the SOC difference of each single battery, it is possible to effectively prevent some batteries from aging prematurely due to being in a high or low power state for a long time. This balancing operation helps to extend the overall service life of the battery pack. The imbalance of battery SOC will lead to overcharging or over-discharging, which will affect the safety of the battery pack. Through continuous balancing operation, this situation can be effectively avoided to ensure the safe operation of the battery pack.

[0227] In another embodiment, an active balancing system for energy storage power source groups based on fuzzy control includes:

[0228] An acquisition unit is used to acquire current status information of each single cell in the energy storage power supply group, and the current status information includes the state of charge SOC and voltage;

[0229] An information analysis unit, used to take the current state information as an input variable and output a corresponding balanced current signal based on a fuzzy logic control model;

[0230] The instruction generation unit is used to generate corresponding control instructions based on the output balancing current signal, adjust the balancing circuit of each single cell in the energy storage power supply group, and implement active balancing operation.

[0231] The working principle of the above technical solution is: the acquisition unit acquires the current status information of each single cell in the energy storage power supply group in real time, especially the state of charge (SOC) and voltage of each battery.

[0232] Voltage is the current voltage value of the battery and is also a key parameter for evaluating battery health and performance. By measuring the battery voltage, you can determine the battery's charge condition and whether it is within the normal operating range.

[0233] The information analysis unit processes information based on the fuzzy logic control model. Fuzzy logic is a mathematical method that processes uncertain information through "fuzzy" language. It is different from the traditional binary logic of "0" or "1". Fuzzy logic can handle partially true or partially false situations. The fuzzy logic control model analyzes the current state of each battery according to the SOC and voltage information of the battery and calculates the balancing current signal. This balancing current signal indicates how much current is required for each battery to charge or discharge to ensure that the power of each battery in the battery pack is as balanced as possible. Based on the balancing current signal, the instruction generation unit calculates specific control instructions, which will be used to adjust the balancing circuit of each single cell in the energy storage power supply group. The control instructions control the balancing circuit of each single cell, thereby realizing active balancing operation to ensure that each single cell of the battery pack always maintains a relatively balanced power and voltage state.

[0234] The steps of obtaining the unit operation include:

[0235] Obtain the distribution data of each single battery in the energy storage power supply group, and generate the energy storage power supply topology network based on the battery distribution data;

[0236] Based on the energy storage power supply topology network, determine the connection relationship between each single battery in the energy storage power supply group, and obtain the status monitoring data of the temperature, SOC and voltage of each single battery in the energy storage power supply topology network;

[0237] Determine the interaction interface between each single battery based on the status monitoring data;

[0238] The interactive interface is matched with each single battery, and the current state information corresponding to each interface is determined based on the current temperature, SOC and voltage of the matching single battery corresponding to each interface.

[0239] The information analysis unit operation steps include:

[0240] Based on the fuzzy logic control model, the input SOC value and voltage value are converted into corresponding fuzzy set representations;

[0241] The fuzzy set is input into the fuzzy reasoning engine, and logical reasoning is performed according to the preset fuzzy rule set to generate the fuzzy balanced current;

[0242] The fuzzy balancing current is converted into an accurate balancing current value as the control output through the defuzzification device.

[0243] The instruction generation unit operation steps include:

[0244] According to the precise equalizing current value, determine the equalizing current required for each single cell, and calculate the corresponding equalizing current flow direction and magnitude;

[0245] Generate control instructions based on the flow direction and magnitude of the balancing current to adjust the balancing circuit of each single cell in the energy storage power supply group;

[0246] Send control instructions to the balancing circuit of the energy storage power pack to adjust the current direction and flow in the battery pack, so that the voltage difference between each single cell is kept within the preset range, realizing active balancing operation of the battery pack.

[0247] The beneficial effect of the above technical solution is that by dynamically balancing the battery power and voltage, the aging problem of some batteries due to overcharging or overdischarging is avoided. The balancing operation can prevent the accumulation of performance differences between batteries, thereby reducing the impact of imbalance on battery life.

[0248] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. An active balancing method for energy storage power supply group based on fuzzy control, characterized in that: include: S101: Acquire current status information of each single cell in the energy storage power supply group, where the current status information includes the state of charge SOC and voltage; S102: Based on the fuzzy logic control model, the current state information is used as an input variable, and a corresponding balanced current signal is output; S103: Based on the output balancing current signal, a corresponding control instruction is generated to adjust the balancing circuit of each single cell in the energy storage power supply group to implement active balancing operation.

2. The active balancing method for energy storage power supply group based on fuzzy control according to claim 1 is characterized in that: Step S101 includes: S1011: Obtain distribution data of each single battery in the energy storage power supply group, and generate an energy storage power supply topology network according to the battery distribution data; S1012: Determine the connection relationship between each single cell in the energy storage power supply group based on the energy storage power supply topology network, and respectively obtain the status monitoring data of the temperature, SOC and voltage of each single cell on the energy storage power supply topology network; S1013: Determine the interaction interface between each single battery based on the status monitoring data; S1014: Match the interactive interface with each single battery, and determine the current state information corresponding to each interface based on the current temperature, SOC and voltage of the matching single battery corresponding to each interface.

3. The active balancing method for energy storage power supply group based on fuzzy control according to claim 1 is characterized in that: Step S102 includes: S1021: based on the fuzzy logic control model, convert the input SOC value and voltage value into corresponding fuzzy set representation; S1022: Input the fuzzy set into the fuzzy reasoning engine, perform logical reasoning according to the preset fuzzy rule set, and generate a fuzzy balanced current; S1023: The fuzzy balancing current is converted into an accurate balancing current value as a control output through a defuzzification device.

4. The active balancing method for energy storage power supply group based on fuzzy control according to claim 1 is characterized in that: Step S103 includes: S1031: Determine the amount of balancing current required for each single cell according to the precise balancing current value, and calculate the corresponding balancing current flow direction and magnitude; S1032: Generate a control instruction according to the flow direction and magnitude of the balancing current, for adjusting the balancing circuit of each single cell in the energy storage power supply group; S1033: Send a control instruction to the balancing circuit of the energy storage power pack to adjust the current direction and flow rate in the battery pack, so that the voltage difference between each single battery is kept within a preset range, thereby realizing active balancing operation of the battery pack.

5. The active balancing method for energy storage power supply group based on fuzzy control according to claim 3 is characterized in that: Fuzzy logic control models, including: According to the SOC value and the voltage value, the fuzzy set of the input parameters is defined, and the membership range of the input parameters is determined; Configure the inference engine and fuzzifier of the fuzzy logic controller based on a preset set of fuzzy rules; Determine the fuzzy set membership range of the output balancing current; The fuzzy set of input parameters, fuzzy rule set and output fuzzy set are integrated to build a complete fuzzy logic control model.

6. The active balancing method for energy storage power supply group based on fuzzy control according to claim 5 is characterized in that: Define the fuzzy set of input parameters, including: The fuzzy set is defined according to the range of SOC values. When the SOC value is between 20% and 80%, the SOC is used as the core control parameter to implement the fuzzy control strategy. In this range, the membership ranges of the input and variation of SOC are defined as [0%-20%] and [0%-60%] respectively. When the SOC value falls into the interval of 0%-20% or 80%-100%, the voltage value is used as the control variable, and the fuzzy set of the voltage input and its variation is defined. The membership ranges of the voltage input and variation are set to 0V-0.2V and 0V-1.2V respectively. The fuzzy sets of SOC value and voltage value are refined into five fuzzy subsets respectively; The current value is limited to the range of [0-5]A and is divided into five levels according to this range.

7. The active balancing method for energy storage power source group based on fuzzy control according to claim 5 is characterized in that: Determine the fuzzy set membership range of the output balancing current, including: Determine whether the SOC value is within the range of 20% to 80%; The voltage difference of the battery is judged according to the SOC value, and whether the balancing current needs to be adjusted intelligently. If the SOC value is between 20% and 80% and the battery voltage difference is large, the balancing current is increased to accelerate the balancing process and shorten the balancing time. On the contrary, if the battery voltage difference is small, a conservative strategy is adopted to reduce the balancing current and reduce battery loss or stress. When the SOC value is in the range of 0% to 20% or 80% to 100%, the balancing current is adjusted according to the voltage difference; if the battery voltage difference is large, a larger balancing current is output to accelerate the balancing process; if the battery voltage difference is small, the balancing current is reduced to prevent the risk of overcharging or over-discharging; Monitor the voltage and current status of the battery in real time, dynamically adjust the output balancing current according to the real-time status of the battery, and calculate the corresponding balancing current value according to the current situation of the battery pack to ensure that the balancing process strikes a balance between efficiency and safety; Using the fuzzy logic control model, the real-time monitoring parameters of the battery voltage difference and SOC value are input into the fuzzy set, and the membership value corresponding to each parameter is calculated. According to the combination of different membership values, the corresponding balancing current adjustment strategy is output to realize intelligent adjustment of the balancing current.

8. The active balancing method for energy storage power supply group based on fuzzy control according to claim 5 is characterized in that: The fuzzy set membership range of the output balancing current also includes: The fuzzy set membership range of the output balancing current is adjusted by the following fuzzy control rules: When the battery voltage difference is greater than the preset voltage difference value and the SOC value is between 20% and 80%, a balancing current greater than the preset value is output; When the battery voltage difference is less than the preset voltage difference value and the SOC value is between 20% and 80%, the output is less than the preset equalization current; When the SOC value is between 0% and 20% or between 80% and 100%, and the battery voltage difference is greater than the preset voltage difference value, a balancing current greater than the preset value is output; When the SOC value is between 0% and 20% or between 80% and 100%, and the battery voltage difference is smaller than a preset voltage difference value, a balancing current smaller than a preset value is output.

9. The active balancing method for energy storage power source group based on fuzzy control according to claim 4 is characterized in that: Determine the amount of balancing current required for each battery cell, including: Based on the current accurate balancing current value and preset balancing parameters, determine the balancing current required for each single cell, and calculate the corresponding balancing current flow direction and magnitude; When the absolute value of the deviation between the average SOC values ​​of two batteries randomly selected during the balancing process exceeds a preset threshold, it is determined that battery balancing is required, the balancing control module is started, and a balancing start instruction is sent to the battery management system; Otherwise, it is determined that the current battery pack is in a balanced state, the existing current distribution is maintained, and no balancing operation is performed; When the current battery pack needs to be balanced, it includes: Based on the real-time SOC value of each single battery in the current battery pack, the absolute value of the deviation between the average SOC values ​​of any two batteries is calculated as the input variable of the fuzzy controller; The absolute value of the deviation between the average SOC values ​​of the two batteries randomly selected during the balancing process and the total current load of the battery pack are taken as key parameters. The two key parameters together constitute the input variables of the fuzzy controller. The specific calculation is as follows: Calculate the average SOC of the two batteries; Calculate the absolute value of the deviation between the average SOC values ​​of the two batteries; Adjust the balancing strategy according to the total current load; The calculation results are input into the fuzzy controller for processing; Among them, represents the average SOC value of the two batteries in the balanced state, and represents the SOC values ​​of the two single cells charged and discharged during the balancing process; When using the fuzzy quantity output by the fuzzy controller, defuzzification processing is performed to convert the fuzzy quantity into a clear balanced current value. The specific steps include: Based on the area center defuzzification method, the output result of the fuzzy controller is converted into an accurate balanced current value. The calculation formula is as follows: Among them, ε(S) represents the fuzzy result of reasoning, S represents a variable in the control input space, and the balancing current value obtained by defuzzification is used to guide the balancing operation of each single battery; According to the balancing current value obtained by defuzzification processing, the flow direction and magnitude of the balancing current of each single cell are determined, including: If the SOC of a single cell is higher than the average value, the cell is discharged through a balancing current; If the SOC of a single cell is lower than the average value, the battery is charged by a balancing current; Based on the determined balancing current direction and size, the charging and discharging status of each single cell in the battery pack is adjusted in real time to ensure the SOC balance of the entire battery pack.

10. The active balancing system of energy storage power supply group based on fuzzy control is characterized by: include: An acquisition unit is used to acquire the current status information of each single cell in the energy storage power supply group, and the current status information includes the state of charge SOC and voltage; An information analysis unit, used to take the current state information as an input variable and output a corresponding balanced current signal based on a fuzzy logic control model; The instruction generation unit is used to generate corresponding control instructions based on the output balancing current signal, adjust the balancing circuit of each single cell in the energy storage power supply group, and implement active balancing operation.

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