Charging power distribution method and device for multi-gun charging pile

Abstract

The invention relates to the technical field of charging power management of charging piles, and particularly discloses a charging power distribution method and device for a multi-gun charging pile, and the method comprises the steps: calculating the theoretical power of each charging gun through collecting the battery information, including the current electric quantity, the battery capacity, the rated charging power and the charging demand, of each vehicle in real time; the safety and the stability are comprehensively evaluated according to the dynamic change of the battery temperature and the load rate of the charging gun; according to the method, the charging power can be dynamically adjusted, the safety and the high efficiency of the charging process are ensured, and the problems of battery damage and unstable charging caused by improper power distribution are avoided; the invention further provides a real-time monitoring interface and an alarm mechanism, abnormal conditions can be found and processed in time, and it is ensured that the charging process is carried out smoothly.

Description

Technical Field

[0001] The present invention relates to the technical field of charging power management of charging piles, and in particular to a charging power distribution method and device for a multi-gun charging pile. Background Art

[0002] With the popularity of electric vehicles and the growth of market demand, the construction of charging infrastructure has become one of the key factors in promoting the development of the electric vehicle industry. However, most existing charging stations use a fixed power distribution method and cannot be flexibly adjusted according to the specific needs of each vehicle. This not only leads to low charging efficiency, but also may cause battery overheating and charging instability due to improper power distribution, which in turn affects the battery life and charging safety. In addition, when multiple vehicles are charging at the same time, the total power capacity of the charging pile is limited. How to reasonably allocate limited power resources while ensuring charging efficiency has become an urgent problem to be solved.

[0003] The existing technology is lacking. Each vehicle is charged based on the calculated theoretical power, and the battery temperature and charging gun load rate data are collected in time series during the process. By establishing an ARIMA model to analyze the impact of battery temperature changes on battery health, and by calculating the load rate gradient deviation index to evaluate the stability of the charging power, the battery temperature influencing factor and the charging gun load rate influencing factor are obtained. Combining these two influencing factors, the safety factor of each vehicle at the current charging power is calculated to judge the safety of the charging process. For situations where the safety factor is lower than the preset threshold, dynamic power adjustment measures are taken, including recalculating power allocation, performing power adjustment, and continuously monitoring the adjustment effect to ensure that the entire charging process is both efficient and safe. Summary of the invention

[0004] The object of the present invention is to provide a charging power distribution method and device for a multi-gun charging pile to solve the above-mentioned problems.

[0005] The purpose of the present invention can be achieved through the following technical solutions: A charging power distribution method for a multi-gun charging pile comprises the following steps: S1: Collect the battery information of each vehicle in real time, including the current power, battery capacity, rated charging power and current charging demand. According to the battery information of each vehicle, calculate the theoretical power required by each charging gun; S2: Charge the vehicle with each charging gun according to the corresponding theoretical power, set a predetermined charging time, collect the battery temperature change data of the vehicle within the predetermined charging time, and establish a corresponding time series. According to the fluctuation amplitude of the temperature data in the time series, determine the degree of interference of the abnormal fluctuation of the battery temperature during the vehicle charging process on the battery charging process; S3: Collect the charging gun load rate data of the vehicle within the predetermined charging time, establish a corresponding time series, analyze the fluctuation range of the charging gun load rate within the time series, and determine the influence of the change of the charging gun load rate on the stability of the charging power; S4: Comprehensively analyze the factors affecting battery temperature and stun gun load rate during the charging process to evaluate whether the charging process is safe under the current theoretical power; S5: Dynamically adjust the power of the charging gun according to the evaluation results; The rated charging power indicates the maximum charging power that the vehicle can receive.

[0006] As a further solution of the present invention: the calculation of the theoretical power required by each charging gun according to the battery information of each vehicle specifically includes: The process of obtaining the theoretical power is as follows: Calculate the initial power distribution of each vehicle, the calculation expression is: ; In the formula, represents the initial power allocation for each vehicle, Indicates The maximum acceptable charging power of the vehicle, Indicates The charging needs of the vehicle, Indicates The vehicle's preset charging time; Use a linear programming algorithm to iterate and gradually adjust the power allocation of each charging gun to minimize the objective function and meet all constraints to obtain the theoretical power required by each charging gun. Among them, the calculation expression of the objective function is: ; In the formula, Indicates the maximum number of charging vehicles, Indicates The maximum preset charging time of the vehicle; The constraints include: Total power constraint: The total power of all charging guns cannot exceed the total power capacity of the charging pile; Single-gun power constraint: The power of each charging gun cannot exceed the corresponding rated power. Vehicle maximum power constraint: The charging power of each vehicle cannot exceed its maximum acceptable charging power; Charging demand constraint: The actual charging capacity of each vehicle should meet its charging demand.

[0007] As a further solution of the present invention: the calculation of the battery temperature influence factor according to the fluctuation amplitude of the temperature data in the time series specifically includes: During the charging process, the battery temperature data is collected in time series to form a time series data set , where i represents the number of acquisition time points, represents the battery temperature collected at the i-th time point; Establish an ARIMA model, assuming that the battery temperature time series is a stationary time series; The ARIMA model is represented by ARIMA(p,d,q), where p is the order of the autoregressive term, d is the order of the difference, and q is the order of the moving average term; The values ​​of p and q are determined by analyzing the autocorrelation function and the partial autocorrelation function; Apply the selected ARIMA model to the battery temperature time series and perform model fitting; The model performs residual analysis to evaluate the fitting effect of the model. The expression of the residual sequence is: ,in, represents the residual at the i-th time point; The ARIMA model expression is: ; In the formula, is the observed value of the time series, is the residual of the time series, is the weight coefficient of the observation value of the time series, The weight coefficient of the residual of the time series; Calculate the battery temperature influence factor, the calculation expression is: ; In the formula, Represents the battery temperature impact factor, and n represents the maximum number of acquisition time points.

[0008] As a further solution of the present invention: the analysis of the fluctuation amplitude of the charging gun load rate in the time series and the calculation of the charging gun load rate influencing factor specifically include: Arrange the collected charging gun load rate data in chronological order to form a time series; For each time point, the rate of change of the load rate over time, that is, the load rate gradient, is calculated. The calculation expression is: ; In the formula, represents the load rate gradient at the jth time point, Indicates The load factor at a time point, Indicates The load factor at a time point, Indicates a time interval; The deviation index of the load rate gradient at each time point is calculated to evaluate the gradient deviation of the load rate distribution. The calculation expression is: ; In the formula, represents the load rate deviation index at the jth time point, represents the load rate gradient at the jth time point, represents the average value of the load rate gradient at all time points, represents the standard deviation of the load rate gradient at all time points; Based on the load rate gradient deviation index, the charging gun load rate influence factor of the load rate on the charging power stability is calculated. The calculation expression is: ; In the formula, Indicates the influencing factor of the charging gun load rate, Indicates the maximum number of collection time locations.

[0009] As a further solution of the present invention: the comprehensive analysis of the battery temperature influencing factor and the electric gun load rate influencing factor during the charging process to evaluate whether the charging process is safe under the current theoretical power specifically includes: The battery temperature influence factor and the electric gun load rate influence factor are normalized, and the safety factor of the charging gun is calculated based on the normalized battery temperature influence factor and the electric gun load rate influence factor. Based on the comparison between the safety factor and the preset threshold, the safety of the charging process under the current theoretical power is evaluated.

[0010] As a further solution of the present invention: the comparison between the safety factor and the preset threshold value specifically includes: It is determined whether the safety factor is greater than or equal to a preset threshold. If so, it is recorded as safe charging; otherwise, it is recorded as unsafe charging.

[0011] As a further solution of the present invention: the dynamic power adjustment of the charging gun according to the evaluation result specifically includes: Extract unsafe charging and record it as the charging gun that needs to be adjusted; Evaluate the gap between its current power and the maximum allowed power, as well as the remaining available power of the charging pile; Prioritize the charging guns that need to be adjusted based on the vehicle's charging needs, current power, and battery temperature; Use linear programming or other optimization algorithms to recalculate the power distribution of each charging gun to ensure that the total power does not exceed the maximum capacity of the charging pile; Send power adjustment instructions and execute power adjustment to ensure smooth power adjustment of each charging gun and avoid sudden power changes from causing impact on the power grid; Continuously monitor the load rate and battery temperature of each charging gun, evaluate the adjustment effect, and further adjust the power distribution if the safety factor of some charging guns is lower than the preset threshold.

[0012] A charging power distribution device for a multi-gun charging pile, comprising: A data acquisition module, which is used to collect battery information of each vehicle in real time, including current power, battery capacity, rated charging power and current charging demand; A charging gun charging power determination module, which calculates the theoretical power required by each charging gun according to the battery information of each vehicle; A battery temperature influence factor calculation module, wherein each charging gun charges the vehicle according to the corresponding theoretical power, and sets a predetermined charging time, collects the battery temperature change data of the vehicle within the predetermined charging time, and establishes a corresponding time series, and calculates the corresponding battery temperature influence factor according to the fluctuation amplitude of the temperature data in the time series; A charging safety assessment module, which comprehensively analyzes the battery temperature influencing factors and the stun gun load rate influencing factors during the charging process to assess whether the charging process is safe under the current theoretical power; A dynamic adjustment module is used to dynamically adjust the power of the charging gun according to the evaluation result.

[0013] Beneficial effects of the present invention: (1) The present invention can significantly improve the charging efficiency and resource utilization of multi-gun charging piles through an intelligent charging power allocation method. Traditional charging piles often adopt a fixed power allocation strategy, which cannot flexibly respond to the charging needs of different vehicles, resulting in low charging efficiency and serious waste of resources. The present invention collects the battery information of each vehicle in real time, including the current power, battery capacity, rated charging power and current charging demand, accurately calculates the theoretical power required by each charging gun, and dynamically adjusts the charging power according to the actual charging needs of the vehicle. This method can not only ensure that each vehicle can complete charging in the shortest time, but also maximize the use of the total power capacity of the charging pile, avoiding energy waste caused by unreasonable power allocation. For example, when multiple vehicles are charging at the same time, the system will give priority to vehicles with small battery capacity and high charging demand, and give them higher charging power, while for vehicles with large battery capacity and low charging demand, the charging power will be appropriately reduced to ensure the efficiency and fairness of the overall charging process. In addition, through real-time monitoring and analysis of the load rate of the charging gun, the present invention can timely discover and solve the power instability problem that may occur during the charging process, further improving the stability and reliability of the charging system.

[0014] (2) While improving the charging efficiency, the present invention also pays special attention to the safety of the charging process and the health protection of the battery. By real-time monitoring the battery temperature changes and the charging gun load rate during the charging process, the present invention can effectively prevent battery damage and safety accidents caused by excessively high or low temperatures, unstable charging power, etc. Specifically, the system collects battery temperature data in time series, uses the ARIMA model to analyze the changing trend of the battery temperature, calculates the battery temperature influencing factor, and reflects the health status of the battery during the charging process. At the same time, by calculating the rate of change and deviation index of the charging gun load rate, the charging gun load rate influencing factor is obtained to evaluate the stability of the charging power. Combining these two influencing factors, the system can calculate the safety factor of each vehicle at the current charging power, promptly identify charging processes that may be risky, and take corresponding dynamic power adjustment measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The present invention will be further described below in conjunction with the accompanying drawings.

[0016] Figure 1 It is a flowchart of a charging power distribution method for a multi-gun charging pile of the present invention; Figure 2 It is a flowchart of the implementation of charging power distribution of a multi-gun charging pile in the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] See also Figure 1 As shown, the present invention is a charging power distribution method for a multi-gun charging pile, comprising the following steps: S1: Collect the battery information of each vehicle in real time, including the current power, battery capacity, rated charging power and current charging demand. According to the battery information of each vehicle, calculate the theoretical power required by each charging gun; S2: Charge the vehicle with each charging gun according to the corresponding theoretical power, set a predetermined charging time, collect the battery temperature change data of the vehicle within the predetermined charging time, and establish a corresponding time series. According to the fluctuation amplitude of the temperature data in the time series, determine the degree of interference of the abnormal fluctuation of the battery temperature during the vehicle charging process on the battery charging process; S3: Collect the charging gun load rate data of the vehicle within the predetermined charging time, establish a corresponding time series, analyze the fluctuation range of the charging gun load rate within the time series, and determine the influence of the change of the charging gun load rate on the stability of the charging power; S4: Comprehensively analyze the factors affecting battery temperature and stun gun load rate during the charging process to evaluate whether the charging process is safe under the current theoretical power; S5: Dynamically adjust the power of the charging gun according to the evaluation results; Wherein, the charging demand represents the desired charging amount set by the vehicle user or the system; The charging gun load rate is the ratio of the actual charging power of the charging gun to the maximum charging power; The rated charging power indicates the maximum charging power that the vehicle can receive.

[0019] In S1, the battery information of each vehicle is collected in real time, including the current power, battery capacity, rated charging power and current charging demand. Based on the battery information of each vehicle, the theoretical power required by each charging gun is calculated, including: The vehicle's battery management system (BMS) monitors the current power in real time and transmits it to the charging station; The BMS measures the battery's voltage, current, temperature and other parameters through internal sensors and calculates the current power percentage. The MS transmits the current power data to the charging pile through a communication interface (such as CAN bus, Ethernet or wireless communication). The charging pile receives and stores this data for subsequent calculations and monitoring. Obtain the battery capacity through the vehicle's BMS or the vehicle's electronic control unit (ECU); Battery capacity is a fixed parameter when the vehicle leaves the factory and is stored in the BMS or ECU; Get battery capacity information from BMS or ECU; Transmit battery capacity data to the charging pile through a communication interface (such as ISO 15118, OCPP standard communication protocol); Get the rated charging power through the vehicle's BMS or vehicle's ECU; The rated charging power is a fixed parameter when the vehicle leaves the factory, indicating the maximum charging power of the vehicle under ideal conditions; The rated charging power data is transmitted to the charging pile through a communication interface (such as ISO 15118, OCPP standard communication protocol); The current charging demand is obtained through the charging pile's human-machine interface (HMI) or the user's mobile application; the central control system stores the charging demand data and uses it for subsequent calculations and allocation.

[0020] According to the battery information of each vehicle, the theoretical power required by each charging gun is calculated, including: The process of obtaining the theoretical power is as follows: Calculate the initial power distribution of each vehicle, the calculation expression is: ; In the formula, represents the initial power allocation for each vehicle, Indicates The maximum acceptable charging power of the vehicle, Indicates The charging needs of the vehicle, Indicates The vehicle's preset charging time; Use a linear programming algorithm to iterate and gradually adjust the power allocation of each charging gun to minimize the objective function and meet all constraints to obtain the theoretical power required by each charging gun. Among them, the calculation expression of the objective function is: ; In the formula, Indicates the maximum number of charging vehicles, Indicates The maximum preset charging time of the vehicle; The constraints include: Total power constraint: The total power of all charging guns cannot exceed the total power capacity of the charging pile; Single-gun power constraint: The power of each charging gun cannot exceed the corresponding rated power. Vehicle maximum power constraint: The charging power of each vehicle cannot exceed its maximum acceptable charging power; Charging demand constraint: The actual charging capacity of each vehicle should meet its charging demand.

[0021] In S2, each charging gun is used to charge the vehicle according to the corresponding theoretical power, and a predetermined charging time is set. The battery temperature change data of the vehicle within the predetermined charging time is collected, and a corresponding time series is established. According to the fluctuation amplitude of the temperature data in the time series, the interference degree of the abnormal fluctuation of the battery temperature during the vehicle charging process on the battery charging process is judged, which specifically includes: Obtain battery temperature data during the charging process in time series (e.g., every minute). Analyze the impact of battery temperature changes on battery health status based on changes in battery temperature data. Calculate the corresponding battery temperature impact factor based on temperature fluctuations, including: During the charging process, the battery temperature data is collected in time series to form a time series data set , where i represents the number of acquisition time points, represents the battery temperature collected at the i-th time point; Establish an ARIMA model, assuming that the battery temperature time series is a stationary time series; The ARIMA model is represented by ARIMA(p,d,q), where p is the order of the autoregressive term, d is the order of the difference, and q is the order of the moving average term; The values ​​of p and q are determined by analyzing the autocorrelation function and the partial autocorrelation function; Apply the selected ARIMA model to the battery temperature time series and perform model fitting; The model performs residual analysis to evaluate the fitting effect of the model. The expression of the residual sequence is: ,in, represents the residual at the i-th time point; The ARIMA model expression is: ; In the formula, is the observed value of the time series, is the residual of the time series, is the weight coefficient of the observation value of the time series, The weight coefficient of the residual of the time series; Calculate the battery temperature influence factor, the calculation expression is: ; In the formula, Indicates the battery temperature impact factor, and n indicates the maximum number of acquisition time points It should be noted that the battery temperature impact factor reflects the change in battery temperature during the charging process, and when the value of the battery temperature impact factor is larger, the corresponding battery charging process is more abnormal, and it needs to be processed in time to avoid the battery temperature being too high or too low and affecting the performance of the electric vehicle.

[0022] In S3, the charging gun load rate data of the vehicle within the predetermined charging time is collected, and a corresponding time series is established. The fluctuation range of the charging gun load rate within the time series is analyzed to determine the influence of the change of the charging gun load rate on the stability of the charging power, including: Arrange the collected charging gun load rate data in chronological order to form a time series; For each time point, the rate of change of the load rate over time, that is, the load rate gradient, is calculated. The calculation expression is: ; In the formula, represents the load rate gradient at the jth time point, Indicates The load factor at a time point, Indicates The load factor at a time point, Indicates a time interval; The deviation index of the load rate gradient at each time point is calculated to evaluate the gradient deviation of the load rate distribution. The calculation expression is: ; In the formula, represents the load rate deviation index at the jth time point, represents the load rate gradient at the jth time point, represents the average value of the load rate gradient at all time points, represents the standard deviation of the load rate gradient at all time points; Based on the load rate gradient deviation index, the charging gun load rate influence factor of the load rate on the charging power stability is calculated. The calculation expression is: ; In the formula, Indicates the influencing factor of the charging gun load rate, Indicates the maximum number of collection time locations.

[0023] It should be noted that the electric gun load rate influence factor reflects the change of charging power during the charging process of the charging gun, and its impact on the performance of the charging gun. The larger the electric gun load rate influence factor, the greater the impact on the corresponding charging gun performance.

[0024] In S4, a comprehensive analysis is performed on the factors affecting battery temperature and the load rate of the electric gun during the charging process to evaluate whether the charging process is safe under the current theoretical power, including: The battery temperature influence factor and the electric gun load rate influence factor are normalized, and the safety factor of the charging gun is calculated by the normalized battery temperature influence factor and the electric gun load rate influence factor. The calculation expression is: ; In the formula, represents the safety factor, and is the preset scale factor, and and All are greater than 0; Compare the safety factor with the preset threshold. If the safety factor is greater than or equal to the preset threshold, it means that the charging power setting of the corresponding charging process is safe, which is recorded as safe charging. If the safety factor is less than the preset threshold, it means that the charging power setting of the corresponding charging process is unsafe, which is recorded as unsafe charging. It should be noted that the safety factor is used to evaluate whether each vehicle is in a safe state under the corresponding charging power, and the larger the value of the safety factor, the safer it is to charge the electric vehicle under the corresponding charging power.

[0025] In S5, according to the evaluation results, the charging gun is dynamically adjusted in terms of power, including: Extract unsafe charging and record it as the charging gun that needs to be adjusted; Evaluate the gap between its current power and the maximum allowed power, as well as the remaining available power of the charging pile; Prioritize the charging guns that need to be adjusted based on the vehicle's charging needs, current power, and battery temperature; Use linear programming or other optimization algorithms to recalculate the power distribution of each charging gun to ensure that the total power does not exceed the maximum capacity of the charging pile; Send power adjustment instructions and execute power adjustment to ensure smooth power adjustment of each charging gun and avoid sudden power changes from causing impact on the power grid; Continuously monitor the load rate and battery temperature of each charging gun, evaluate the adjustment effect, and further adjust the power distribution if the safety factor of some charging guns is still below the preset threshold.

[0026] Provides a real-time monitoring interface to display the charging status, power changes and charging completion status of each vehicle. Sets an alarm mechanism to promptly issue an alarm when an abnormal situation is detected. Records the charging process data of each vehicle for subsequent data analysis and system optimization.

[0027] See also Figure 2 As shown, a charging power distribution device for a multi-gun charging pile includes: A data acquisition module, which is used to collect battery information of each vehicle in real time, including current power, battery capacity, rated charging power and current charging demand; A charging gun charging power determination module, which calculates the theoretical power required by each charging gun according to the battery information of each vehicle; A battery temperature influence factor calculation module, wherein each charging gun charges the vehicle according to the corresponding theoretical power, and sets a predetermined charging time, collects the battery temperature change data of the vehicle within the predetermined charging time, and establishes a corresponding time series, and calculates the corresponding battery temperature influence factor according to the fluctuation amplitude of the temperature data in the time series; A charging gun load rate influence factor calculation module, which collects the charging gun load rate data of the vehicle within the predetermined charging time, establishes a corresponding time series, analyzes the fluctuation range of the charging gun load rate within the time series, and calculates the corresponding charging gun load rate influence factor; A charging safety assessment module, which comprehensively analyzes the battery temperature influencing factors and the stun gun load rate influencing factors during the charging process to assess whether the charging process is safe under the current theoretical power; A dynamic adjustment module is used to dynamically adjust the power of the charging gun according to the evaluation result.

[0028] The working principle of the present invention is as follows: by collecting the battery information of the connected vehicle in real time, including the current power, battery capacity, rated charging power and the charging requirements set by the user, these data are used to calculate the theoretical power requirements of each charging gun. Then, each vehicle is charged according to the calculated theoretical power, and the battery temperature and charging gun load rate data are collected in time series during this process. By establishing an ARIMA model to analyze the impact of battery temperature changes on battery health, and by calculating the load rate gradient deviation index to evaluate the stability of the charging power, the battery temperature influencing factor and the charging gun load rate influencing factor are obtained. Combining these two influencing factors, the safety factor of each vehicle at the current charging power is calculated to judge the safety of the charging process. For situations where the safety factor is lower than the preset threshold, dynamic power adjustment measures are taken, including recalculating power allocation, performing power adjustment and continuously monitoring the adjustment effect to ensure that the entire charging process is both efficient and safe.

[0029] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0030] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0031] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0032] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0033] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A charging power distribution method for a multi-gun charging pile, characterized in that: The following steps are involved: S1: Collect the battery information of each vehicle in real time, including the current power, battery capacity, rated charging power and current charging demand. According to the battery information of each vehicle, calculate the theoretical power required by each charging gun; S2: Charge the vehicle with each charging gun according to the corresponding theoretical power, set a predetermined charging time, collect the battery temperature change data of the vehicle within the predetermined charging time, and establish a corresponding time series. According to the fluctuation amplitude of the temperature data in the time series, determine the degree of interference of the abnormal fluctuation of the battery temperature during the vehicle charging process on the battery charging process; S3: Collect the charging gun load rate data of the vehicle within the predetermined charging time, establish a corresponding time series, analyze the fluctuation range of the charging gun load rate within the time series, and determine the influence of the change of the charging gun load rate on the stability of the charging power; S4: Comprehensively analyze the factors affecting battery temperature and stun gun load rate during the charging process to evaluate whether the charging process is safe under the current theoretical power; S5: Dynamically adjust the power of the charging gun according to the evaluation results; wherein the charging demand represents the expected charging amount set by the vehicle user or the system; the charging gun load rate represents the ratio of the actual charging power of the charging gun to the maximum charging power; and the rated charging power represents the maximum charging power that the vehicle can receive.

2. The charging power distribution method of a multi-gun charging pile according to claim 1, characterized in that: The theoretical power required by each charging gun is calculated based on the battery information of each vehicle. include: The process of obtaining the theoretical power is as follows: Calculate the initial power distribution of each vehicle, the calculation expression is: ; In the formula, represents the initial power allocation for each vehicle, Indicates The maximum acceptable charging power of the vehicle, Indicates The charging needs of the vehicle, Indicates The vehicle's preset charging time; Use a linear programming algorithm to iterate and gradually adjust the power allocation of each charging gun to minimize the objective function and meet all constraints to obtain the theoretical power required by each charging gun. Among them, the calculation expression of the objective function is: ; In the formula, Indicates the maximum number of charging vehicles, Indicates The maximum preset charging time of the vehicle; The constraints include: Total power constraint: The total power of all charging guns cannot exceed the total power capacity of the charging pile; Single-gun power constraint: The power of each charging gun cannot exceed the corresponding rated power. Vehicle maximum power constraint: The charging power of each vehicle cannot exceed its maximum acceptable charging power; Charging demand constraint: The actual charging capacity of each vehicle should meet its charging demand.

3. The charging power distribution method of a multi-gun charging pile according to claim 1, characterized in that: The calculation of the battery temperature influence factor according to the fluctuation amplitude of the temperature data in the time series specifically includes: During the charging process, the battery temperature data is collected in time series to form a time series data set , where i represents the number of acquisition time points, represents the battery temperature collected at the i-th time point; Establish an ARIMA model, assuming that the battery temperature time series is a stationary time series; The ARIMA model is represented by ARIMA(p,d,q), where p is the order of the autoregressive term, d is the order of the difference, and q is the order of the moving average term; The values ​​of p and q are determined by analyzing the autocorrelation function and the partial autocorrelation function; Apply the selected ARIMA model to the battery temperature time series and perform model fitting; The model performs residual analysis to evaluate the fitting effect of the model. The expression of the residual sequence is: ,in, represents the residual at the i-th time point; The ARIMA model expression is: ; In the formula, is the observed value of the time series, is the residual of the time series, is the weight coefficient of the observation value of the time series, The weight coefficient of the residual of the time series; Calculate the battery temperature influence factor, the calculation expression is: ; In the formula, Represents the battery temperature impact factor, and n represents the maximum number of acquisition time points.

4. The charging power distribution method of a multi-gun charging pile according to claim 1, characterized in that: The analysis of the fluctuation range of the charging gun load rate in the time series and the calculation of the influencing factors of the charging gun load rate specifically include: Arrange the collected charging gun load rate data in chronological order to form a time series; For each time point, the rate of change of the load rate over time, that is, the load rate gradient, is calculated. The calculation expression is: ; In the formula, represents the load rate gradient at the jth time point, Indicates The load factor at a time point, Indicates The load factor at a time point, Indicates a time interval; The deviation index of the load rate gradient at each time point is calculated to evaluate the gradient deviation of the load rate distribution. The calculation expression is: ; In the formula, represents the load rate deviation index at the jth time point, represents the load rate gradient at the jth time point, represents the average value of the load rate gradient at all time points, represents the standard deviation of the load rate gradient at all time points; Based on the load rate gradient deviation index, the charging gun load rate influence factor of the load rate on the charging power stability is calculated. The calculation expression is: ; In the formula, Indicates the influencing factor of the charging gun load rate, Indicates the maximum number of collection time locations.

5. The charging power distribution method of a multi-gun charging pile according to claim 1, characterized in that: The comprehensive analysis of the battery temperature influencing factors and the stun gun load rate influencing factors during the charging process is performed to evaluate whether the charging process is safe under the current theoretical power, specifically including: The battery temperature influence factor and the electric gun load rate influence factor are normalized, and the safety factor of the charging gun is calculated based on the normalized battery temperature influence factor and the electric gun load rate influence factor. Based on the comparison between the safety factor and the preset threshold, the safety of the charging process under the current theoretical power is evaluated.

6. A charging power distribution method for a multi-gun charging pile according to claim 5, characterized in that: The comparison between the safety factor and the preset threshold value specifically includes: It is determined whether the safety factor is greater than or equal to a preset threshold. If so, it is recorded as safe charging; otherwise, it is recorded as unsafe charging.

7. The charging power distribution method of a multi-gun charging pile according to claim 1, characterized in that: The dynamic power adjustment of the charging gun according to the evaluation result specifically includes: Extract unsafe charging and record it as the charging gun that needs to be adjusted; Evaluate the gap between its current power and the maximum allowed power, as well as the remaining available power of the charging pile; Prioritize the charging guns that need to be adjusted based on the vehicle's charging needs, current power, and battery temperature; Use linear programming or other optimization algorithms to recalculate the power distribution of each charging gun to ensure that the total power does not exceed the maximum capacity of the charging pile; Send power adjustment instructions and execute power adjustment to ensure smooth power adjustment of each charging gun and avoid sudden power changes from causing impact on the power grid; Continuously monitor the load rate and battery temperature of each charging gun, evaluate the adjustment effect, and further adjust the power distribution if the safety factor of some charging guns is lower than the preset threshold.

8. A charging power distribution device for a multi-gun charging pile, characterized in that: A charging power distribution method for a multi-gun charging pile according to any one of claims 1 to 7, comprising: A data acquisition module, which is used to collect battery information of each vehicle in real time, including current power, battery capacity, rated charging power and current charging demand; A charging gun charging power determination module, which calculates the theoretical power required by each charging gun according to the battery information of each vehicle; A battery temperature influence factor calculation module, wherein each charging gun charges the vehicle according to the corresponding theoretical power, and sets a predetermined charging time, collects the battery temperature change data of the vehicle within the predetermined charging time, and establishes a corresponding time series, and calculates the corresponding battery temperature influence factor according to the fluctuation amplitude of the temperature data in the time series; A charging safety assessment module, which comprehensively analyzes the battery temperature influencing factors and the stun gun load rate influencing factors during the charging process to assess whether the charging process is safe under the current theoretical power; A dynamic adjustment module is used to dynamically adjust the power of the charging gun according to the evaluation result.

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