Charging pile energy storage connector system with self-adaptive current distribution function and method

Abstract

The invention relates to the technical field of current distribution, and discloses a charging pile energy storage connector system and method with a self-adaptive current distribution function, and the method comprises the steps: carrying out the data collection and filtering processing of each charging port of a charging pile, and obtaining a port real-time operation parameter matrix; port load power calculation is carried out on the port real-time operation parameter matrix to obtain port load power, and the load unbalance degree and the charging efficiency are calculated according to the port load power; calculating an adaptive distribution index of each charging port based on the load unbalance degree and the charging efficiency; calculating an optimal current distribution value of each charging port according to the adaptive distribution index; according to the optimal current distribution value, PWM signal duty ratio modulation and current dynamic adjustment are carried out on the power electronic converter of each charging port, and the real-time output current of each charging port is obtained, so that the accurate control of the charging process is realized, and the safety and reliability of the charging process are ensured.

Description

Technical Field

[0001] The present application relates to the technical field of current distribution, and in particular to a charging pile energy storage connector system and method with adaptive current distribution function. Background Art

[0002] With the rapid development of the new energy vehicle industry, the construction and operation of charging infrastructure are facing increasing challenges. Traditional charging pile systems generally adopt a fixed current distribution strategy, which cannot dynamically adjust the charging power of each port according to the actual load conditions, resulting in low overall charging efficiency of the system. Especially in the scenario of multiple vehicles charging at the same time, due to the differences in the load characteristics of each charging port, it is easy to cause uneven distribution of charging resources, affecting the user's charging experience.

[0003] In addition, the existing charging pile system often ignores the influence of the characteristics of the energy storage connector during the current distribution process, which makes it difficult to ensure the power transmission efficiency during the actual charging process. Since the impedance characteristics of the energy storage connector under different working conditions are significantly different, if this factor is not accurately considered, it will affect the stability and reliability of the charging system. Summary of the invention

[0004] The present application provides a charging pile energy storage connector system and method with adaptive current distribution function, thereby achieving precise control of the charging process and ensuring the safety and reliability of the charging process.

[0005] In a first aspect, the present application provides a method for controlling a charging pile energy storage connector with an adaptive current distribution function, the method comprising:

[0006] Perform data collection and filtering on each charging port of the charging pile to obtain the real-time operation parameter matrix of the port;

[0007] Calculating the port load power of the port real-time operation parameter matrix to obtain the port load power, and calculating the load imbalance and charging efficiency according to the port load power;

[0008] Calculating an adaptive allocation index of each charging port based on the load imbalance and the charging efficiency;

[0009] Calculating an optimal current distribution value for each charging port according to the adaptive distribution index;

[0010] According to the optimal current distribution value, the PWM signal duty cycle modulation and current dynamic adjustment are performed on the power electronic converter of each charging port to obtain the real-time output current of each charging port.

[0011] A second aspect of the present application provides a charging pile energy storage connector system with an adaptive current distribution function, the charging pile energy storage connector system with an adaptive current distribution function comprising:

[0012] The data acquisition module is used to collect and filter data from each charging port of the charging pile to obtain a real-time operating parameter matrix of the port;

[0013] A power calculation module, used to calculate the port load power of the port real-time operation parameter matrix to obtain the port load power, and calculate the load imbalance and charging efficiency according to the port load power;

[0014] An index calculation module, configured to calculate an adaptive allocation index of each charging port based on the load imbalance and the charging efficiency;

[0015] A current calculation module, used to calculate the optimal current distribution value of each charging port according to the adaptive distribution index;

[0016] The dynamic adjustment module is used to perform PWM signal duty cycle modulation and current dynamic adjustment on the power electronic converter of each charging port according to the optimal current distribution value, so as to obtain the real-time output current of each charging port.

[0017] Compared with the prior art, the present application has the following beneficial effects: by real-time monitoring and filtering of the voltage, current and power factor of the charging port, an accurate port operation parameter matrix is ​​obtained, which improves the stability of the system operation. An adaptive allocation index calculation method based on load imbalance and charging efficiency is adopted, and correction is made in combination with the characteristics of the energy storage connector to achieve a reasonable allocation of charging resources and significantly improve the overall charging efficiency of the system. A genetic algorithm is introduced for multi-objective optimization, and the optimal balance point is found between multiple objectives such as minimizing system losses, maximizing charging efficiency and maximizing load balance by screening the Pareto optimal solution. A PWM modulation method based on a feedforward-feedback composite control strategy is designed, and a rapid response to load changes is achieved through dynamic current regulation, thereby improving the dynamic performance of the system. Dead time compensation and dislocation delay control technology are adopted to effectively reduce the switching loss of the power electronic converter and improve the energy conversion efficiency of the system. Through closed-loop tracking control and real-time output current prediction, precise control of the charging process is achieved, ensuring the safety and reliability of the charging process. Through the synergy of multi-level optimization and control strategies, the efficient operation of the charging pile system under different working conditions is achieved, and the utilization rate of the charging equipment is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0019] The structures, proportions, sizes, etc. illustrated in the drawings of this specification are only used to match the contents disclosed in the specification so as to facilitate understanding and reading by persons familiar with this technology. They are not used to limit the conditions under which the present invention can be implemented, and therefore have no substantive technical significance. Any structural modification, change in proportion or adjustment of size, without affecting the effects and purposes that can be achieved by the present invention, should still fall within the scope of the technical contents disclosed by the present invention.

[0020] Figure 1 It is a flow chart of a method for controlling a charging pile energy storage connector with an adaptive current distribution function provided by an embodiment of the present invention;

[0021] Figure 2 It is a schematic block diagram of the structure of a charging pile energy storage connector system with adaptive current distribution function provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0022] 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 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.

[0023] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.

[0024] It should also be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0025] It should be further understood that the term "and / or" used in the specification and appended claims of this application refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations. Figure 1 , an embodiment of a control method for a charging pile energy storage connector with an adaptive current distribution function in an embodiment of the present application includes:

[0026] Step 100: collect and filter data from each charging port of the charging pile to obtain a real-time operating parameter matrix of the port;

[0027] It is understandable that the execution subject of the present application can be a charging pile energy storage connector system with an adaptive current distribution function, or a terminal or a server, which is not limited here. The present application embodiment is described by taking a server as the execution subject as an example.

[0028] Specifically, voltage sensors are configured at each charging port of the charging pile, and these sensors collect the original voltage data of the port in real time. The original signal is filtered. The high-pass filter and the low-pass filter are connected in series. The low-frequency interference in the signal, such as the DC component or the trend item with slow changes, is eliminated by high-pass filtering, and then the high-frequency noise is removed by low-pass filtering, and the useful frequency components in the signal are retained to obtain the voltage effective value data of the port. At the same time, a current sensor is set at each charging port in the charging pile to collect the original data of the port current. The original data of the port current is processed in series with high-pass filtering and low-pass filtering. The high-pass filter removes the low-frequency components in the current signal, while the low-pass filter filters out the high-frequency interference to obtain the port current effective value data. The port voltage effective value data and the current effective value data are input into the power analyzer for processing. The power analyzer performs a product operation on the input voltage and current signals to calculate the active power data of the port, and analyzes the phase difference between the voltage and current signals at the same time, and calculates the reactive power data of the port using the phase difference and the amplitude of the signal. The active power data characterizes the actual energy consumed by the port, while the reactive power data reflects the useless power cycle in the port due to inductive or capacitive loads. The power factor data of the port is obtained by performing trigonometric function calculations on the active power data and reactive power data of the port. The power factor is an important parameter for measuring the efficiency of electric energy utilization. Its value is the ratio of active power to apparent power. It is calculated by the following formula: The power factor is equal to the active power divided by the apparent power, and the apparent power is equal to the product of the effective value of the voltage and the effective value of the current. This calculation can intuitively reflect the power characteristics of the charging port. The port voltage effective value data, port current effective value data, port active power data, port reactive power data, and port power factor data are integrated into a port real-time operation parameter matrix through the matrix splicing method. The construction of the matrix represents the operating status of different ports in a unified structure, forming the following form: each row corresponds to a charging port, and each column corresponds to a parameter, such as voltage, current, active power, reactive power, and power factor, to construct a multidimensional data matrix that can fully reflect the operating status of the charging pile.

[0029] Step 200: Calculate the port load power of the port real-time operation parameter matrix to obtain the port load power, and calculate the load imbalance and charging efficiency according to the port load power;

[0030] Specifically, the active power data of each charging port is extracted from the port real-time operation parameter matrix, the active power data is classified and processed, and the active power information of different ports is sorted according to time or other specific dimensions to obtain the port active power distribution data, which describes the power distribution of each charging port in the system and reflects the actual operation status of different port loads. The standard deviation and mean calculation of the active power distribution data are performed to determine the fluctuation range of the port power. The standard deviation is used to measure the degree to which the power of each port deviates from the average level, while the mean provides a reference for the overall power level. By calculating these indicators, the fluctuation range of the port power is obtained, so as to evaluate the stability of the system at different times. Based on this fluctuation range, the active power distribution data is filtered, that is, outliers or power data that exceeds a reasonable range are removed to improve the accuracy of the analysis. The filtered data is then calculated by the average value to obtain the load power of the port, reflecting the actual load level of each charging port. The maximum value and minimum value retrieval of the port load power are performed. By finding the maximum and minimum values ​​of the port load power respectively, the difference in load distribution within the system can be intuitively judged. This difference directly affects the load balance of the system. The load imbalance is calculated based on the difference between the maximum port power and the minimum port power of the system and the sum of the port load powers. The difference between the maximum port power and the minimum port power is divided by the sum of the port load powers and then multiplied by 100% to obtain the load imbalance, which reflects the uniformity of the system load distribution. The smaller the value, the more uniform the load and the smoother the system operation. At the same time, the output active power data and the input apparent power data in the real-time operation parameter matrix of the port are processed to calculate the instantaneous charging efficiency of each charging port. The instantaneous charging efficiency is calculated by the ratio of the output active power to the input apparent power, reflecting the energy conversion efficiency of each port at a certain moment. Since the instantaneous charging efficiency will be affected by the fluctuation of the system in a short period of time, it is exponentially weighted averaged. The exponential weighted average can more realistically reflect the dynamic trend of the average charging efficiency of the port by giving higher weights to recent data and gradually reducing the weights of earlier data. According to the weighted summation calculation of the average charging efficiency of the port and the proportion of the load power of each port in the total power of the system, the overall charging efficiency of the system is obtained. The weighted summation process can comprehensively consider the impact of each port in the overall power distribution, and sum up the charging efficiency of each port after weighting it according to its importance, ensuring that the calculation of system efficiency is global and representative.

[0031] Step 300: Calculate the adaptive allocation index of each charging port based on the load imbalance and charging efficiency;

[0032] It should be noted that by multiplying the load imbalance by the first weight coefficient, the influence weight in the score is adjusted to obtain the load balance score. By multiplying the charging efficiency by the second weight coefficient, the charging efficiency score is generated. The power factor data in the real-time operation parameter matrix of the port is multiplied by the third weight coefficient for weighted calculation to generate a power factor score. The load balance score, the charging efficiency score and the power factor score are added to obtain the system operation status score. The port load power is divided by the rated load of each charging port to obtain a standardized load rate, eliminate the absolute value difference of the port load power, and make the load conditions of different ports comparable. At the same time, by dividing the charging efficiency by the maximum charging efficiency of the system, a relative efficiency value is obtained, which reflects the deviation of the efficiency level of the current port from the optimal state of the system. In order to optimize the allocation index, the power factor score is divided by the target power factor to generate a correction coefficient, which reflects the degree of deviation of the actual power factor from the ideal target, and is used to correct the final allocation result. Based on the above calculation results, the standardized load rate, relative efficiency value and correction coefficient are weighted with the preset weight coefficient to obtain the initial allocation index. The voltage and current data of the input and output terminals of the charging pile energy storage connector are collected in real time to calculate the power transmission efficiency of the energy storage connector. The power transmission efficiency is combined with the initial allocation index, and the initial allocation index is dynamically adjusted using the correction algorithm to obtain an adaptive allocation index that takes into account the characteristics of the energy storage connector.

[0033] Step 400, calculating the optimal current distribution value of each charging port according to the adaptive distribution index;

[0034] Specifically, the target allocation ratio is calculated for the standardized load rate, relative efficiency value and correction coefficient of each charging port to form the initial allocation weight of each charging port. The calculation of the weight reflects the allocation priority of the port under the current load condition. Based on the standardized index of the port's own operating status, the initial estimate of the current distribution is both comparable and reflects the port difference. After the calculation of the initial allocation weight is completed, multiple independent sub-populations are generated by replication construction, each of which contains several chromosome individuals, and the encoding of each chromosome represents the current allocation value of each charging port. After the population is generated, the fitness of the chromosome individuals in each sub-population is evaluated to measure the pros and cons of the current allocation scheme corresponding to each individual. The fitness evaluation is constructed based on the three goals of minimizing system loss, maximizing charging efficiency and maximizing load balancing. By comprehensively considering the impact of these indicators on system performance, it is ensured that the evaluation results can fully reflect the pros and cons of the current allocation scheme. In this process, the performance of each chromosome individual on multiple objectives is quantified through a mathematical model, such as characterizing the energy utilization efficiency by calculating the total power loss of the system, and describing the stability of the system through the load balancing index. After completing the fitness evaluation, the tournament selection strategy is used to screen the high-quality individuals of the chromosome individuals of each sub-population to generate parent individuals. The tournament selection strategy randomly selects several individuals from the sub-population and compares their fitness values ​​to select the best performing individuals as the parent individuals. This selection mechanism helps to improve the overall quality of the population while avoiding premature convergence. The parent individuals are subjected to simulated binary crossover operations and polynomial mutation operations to generate the sub-population. The simulated binary crossover operation generates new chromosome individuals between the parent individuals by imitating the gene exchange in the genetic process, thereby increasing the diversity of the population, while the polynomial mutation operation improves the adaptability and exploration ability of the population by applying small random perturbations to certain genes of the chromosome. In order to promote information exchange between sub-populations, the sub-population is migrated at regular intervals, and the ring topology structure is used to exchange the best individuals between adjacent sub-populations. The migration operation transfers the high-quality individuals of a sub-population to the adjacent population, so that the entire population evolution process can make full use of the optimal solutions of each sub-population, thereby improving the efficiency and quality of global optimization. After the migration operation is completed, the current constraint and power constraint verification are performed on the individuals in the migrated population. The current constraint ensures that the allocated current of each charging port does not exceed its rated value, thereby protecting the safety of the hardware equipment; the power constraint ensures that the total allocated power of the system does not exceed the maximum output power of the energy storage device to ensure the overall stability of the system operation. After passing the constraint verification, the feasible solution set is non-dominated sorting and congestion distance calculation is performed to identify the solution set on the Pareto optimal frontier. Non-dominated sorting compares the multi-objective dominance relationship between individuals to screen out a set of individuals that are not dominated by other solutions. These solutions achieve a balance in system loss, charging efficiency, and load balancing.The congestion distance calculation is used to evaluate the distribution of solutions on the Pareto front surface, thereby guiding the population to evolve in a more uniform and diverse direction. The solution set on the Pareto optimal front surface is weighted and scored based on the system loss, charging efficiency, and load balance of each individual, and the solution with the best overall performance is selected as the final optimal current distribution value. The weighted summation process can combine the actual operating needs of the system and prioritize the importance of different goals by adjusting the weight coefficients, thereby achieving a dynamic balance between efficiency, stability, and safety, ensuring that the current distribution plan not only meets technical constraints, but also maximizes system performance.

[0035] Step 500: According to the optimal current distribution value, the power electronic converter of each charging port is subjected to PWM signal duty cycle modulation and current dynamic regulation to obtain the real-time output current of each charging port.

[0036] Specifically, the optimal current distribution value is input into the controller of each charging port to set the target output value of each port. These target values ​​reflect the current distribution amount that each port needs to bear under the current operating conditions of the charging pile system. The current sensor of the charging port is used for real-time data acquisition to obtain the real-time output current value of each port. By performing a difference operation between the real-time current value and the aforementioned port control target value, the current tracking error value of each port is obtained, reflecting the deviation between the actual output current of the current port and the target value. The current tracking error value is input into the PI (proportional-integral) controller, and the feedback control output value is generated through proportional integral operation. The role of the PI controller is to correct the current output in real time by adjusting the proportional and integral coefficients so that it quickly follows the target value changes and eliminates the steady-state error as much as possible. In this process, the rate of change of the port control target value is analyzed to evaluate the dynamic characteristics of the load and predict the response behavior of the load. The load dynamic response prediction value can reflect the possible current adjustment requirements of the system when the target value changes in advance. Based on the load dynamic response prediction value, a feedforward compensation calculation is performed to generate a feedforward control output value. The role of feedforward control is to pre-adjust the control signal in advance according to the trend of target value change, so as to reduce the response time of the system and the fluctuation in the adjustment process. Feedback control is combined with feedforward control to achieve accurate and fast control of the output current, while improving the dynamic performance and stability of the system. The feedback control output value and the feedforward control output value are weighted and superimposed to generate a PWM modulation control signal. The weighted superposition process combines the error correction capability of feedback control and the dynamic compensation effect of feedforward control to ensure that the control signal can meet the requirements of steady-state accuracy and dynamic response at the same time. The PWM modulation control signal is carrier modulated to generate the IGBT (insulated gate bipolar transistor) switch tube drive waveform of the power electronic converter. Carrier modulation uses methods such as sinusoidal pulse width modulation (SPWM) or space vector pulse width modulation (SVPWM) to generate a switch signal that meets the requirements by comparing the control signal with the carrier. The drive waveform directly determines the switching state of the power electronic converter, thereby affecting the waveform and amplitude of the output current. The generated IGBT switch tube drive waveform is input into the drive circuit of the power electronic converter to complete the real-time switch control of the switch tube. The drive circuit realizes DC to AC or DC to DC power conversion by controlling the on and off of the IGBT, and adjusts the output current according to the duty cycle of the PWM signal to obtain the real-time output current of each charging port.

[0037] Data is extracted from the PWM modulated control signal to generate a sampling sequence of the control signal. The sampling sequence captures the dynamic characteristics of the PWM signal through uniform sampling and retains its amplitude change information. In order to ensure the standardization and compatibility of subsequent calculations, the sampling sequence is amplitude normalized to generate a normalized modulation wave. The triangular carrier signal is frequency multiplied to obtain a high-frequency carrier signal. The high-frequency carrier signal increases the modulation accuracy of the system by increasing the frequency, ensuring that the output current can more accurately follow the target value. The normalized modulation wave and the high-frequency carrier signal are phase synchronized to generate a synchronous carrier modulation signal. The phase synchronization operation is intended to ensure the matching degree between the modulation wave and the carrier and reduce the influence of the phase error on the final output waveform. Based on the synchronous carrier modulation signal, the feedforward-feedback composite control strategy is applied to dynamically calculate the duty cycle and generate a duty cycle modulation waveform. The feedforward control part directly adjusts the duty cycle according to the change of the input target to improve the dynamic response speed of the system, while the feedback control part compensates for the shortcomings of the feedforward control through real-time error correction, thereby ensuring output accuracy. The duty cycle modulation waveform is voltage clamped and overmodulation suppressed to effectively control the amplitude range of the modulation waveform and prevent unreasonable modulation overshoot, thereby protecting the safe operation of the power electronic converter. On this basis, the optimized modulation waveform is compensated for dead time to eliminate the influence of dead time on the output waveform during the IGBT switching process, and the compensated PWM drive signal is obtained. The compensated PWM drive signal is input into the optoelectronic isolation module of the driver for electrical isolation operation to generate an isolated drive voltage. The role of optoelectronic isolation is to achieve electrical isolation between the control circuit and the power circuit, and enhance the anti-interference ability and safety of the system. The isolated drive voltage is further controlled by the dislocation delay to generate a dislocation drive signal to prevent the parallel switch tube from overlapping when it is turned on and off, and avoid the risk of short circuit. After the gate drive voltage clamping and overcurrent protection operation are performed on the dislocation drive signal, the IGBT switch tube drive waveform is generated. This waveform ensures the efficiency and reliability of the IGBT switch operation by accurately controlling the amplitude and timing of the drive voltage. The generated drive waveform passes through the power electronic converter drive circuit and ultimately controls the current change at the output end. Based on the transfer function model of the duty cycle of the IGBT switch drive waveform and the output current of the charging port, the system is dynamically analyzed and the predicted value of the output current is calculated. The predicted value of the output current reflects the output trend under the current control state through real-time calculation, providing a basis for closed-loop control. By performing closed-loop tracking control on the predicted value of the output current and correcting the deviation, accurate control of the real-time output current of each charging port is finally achieved.

[0038] In the embodiment of the present application, by real-time monitoring and filtering of the voltage, current and power factor of the charging port, an accurate port operation parameter matrix is ​​obtained, which improves the stability of the system operation. An adaptive allocation index calculation method based on load imbalance and charging efficiency is adopted, and correction is made in combination with the characteristics of the energy storage connector to achieve a reasonable allocation of charging resources and significantly improve the overall charging efficiency of the system. A genetic algorithm is introduced for multi-objective optimization, and the optimal balance point is found between multiple objectives such as minimizing system losses, maximizing charging efficiency and maximizing load balance by screening the Pareto optimal solution. A PWM modulation method based on a feedforward-feedback composite control strategy is designed, and a rapid response to load changes is achieved through dynamic current regulation, thereby improving the dynamic performance of the system. Dead time compensation and dislocation delay control technology are adopted to effectively reduce the switching loss of the power electronic converter and improve the energy conversion efficiency of the system. Through closed-loop tracking control and real-time output current prediction, precise control of the charging process is achieved, ensuring the safety and reliability of the charging process. Through the synergy of multi-level optimization and control strategies, the efficient operation of the charging pile system under different working conditions is achieved, and the utilization rate of the charging equipment is improved.

[0039] In a specific embodiment, the process of executing step 100 may specifically include the following steps:

[0040] The voltage sensor provided at each charging port of the charging pile is used to collect data to obtain the original data of the port voltage, and the original data of the port voltage is processed in series with high-pass filtering and low-pass filtering to obtain the effective value data of the port voltage;

[0041] The current sensor provided at each charging port of the charging pile is used to collect data to obtain the original data of the port current, and the original data of the port current is processed in series with high-pass filtering and low-pass filtering to obtain the effective value data of the port current;

[0042] Input the port voltage effective value data and the port current effective value data into the power analyzer for product operation and phase difference calculation to obtain the port active power data and the port reactive power data;

[0043] Perform trigonometric function calculation on the port active power data and the port reactive power data to obtain the port power factor data;

[0044] The port voltage effective value data, the port current effective value data, the port active power data, the port reactive power data and the port power factor data are matrix-joined to obtain the port real-time operation parameter matrix.

[0045] Specifically, a high-precision voltage sensor is installed on each charging port of the charging pile to collect the original voltage data of each port. Assume that the original voltage data of a port is V raw(t), which is a continuous function of voltage over time. raw (t) Perform high-pass filtering and low-pass filtering in series. The purpose of high-pass filtering is to remove low-frequency interference. Suppose the transfer function of the high-pass filter is H high (f), its frequency response satisfies when f>f c Time high (f) = 1, where f c is the cutoff frequency; otherwise H high (f) = 0. After high-pass filtering, the signal becomes:

[0046] V high (t) = F -1 {H high (f)·F{V raw (t)}};

[0047] Among them, F and F -1 Denote Fourier transform and inverse transform respectively. The low-pass filter is used to eliminate high-frequency noise. Assume that the transfer function of the low-pass filter is H low (f), when f <f c Time low (f) = 1, otherwise H low (f) = 0. The signal after low-pass filtering is:

[0048] V low (t) = F -1 {H low (f)·F{V high (t)}};

[0049] After high-pass and low-pass filtering in series, the voltage RMS data of the port is obtained, which is recorded as V eff , calculated using the square mean formula:

[0050]

[0051] Where T is the period of the signal. Similar to the voltage signal processing, the raw data I collected by the current sensor of the port raw (t) Perform high-pass and low-pass filtering in series to obtain high-pass filtered signals I high (t) and the low-pass filtered signal I low (t), and finally calculate the effective value of current I eff :

[0052]

[0053] The obtained V eff and I effInput into the power analyzer, by calculating the product and phase difference of the two, the active power and reactive power data of the port are obtained. The active power P is defined as:

[0054] P=V eff I eff ·cosφ;

[0055] Where φ is the phase difference between voltage and current, describing the time delay relationship between the two. Reactive power Q is defined as:

[0056] Q=V eff I eff ·sinφ;

[0057] The P and Q obtained from the above calculations are used to solve the power factor cosφ, and the formula is:

[0058]

[0059] In order to construct the port real-time operation parameter matrix, the voltage RMS value V eff , Current effective value I eff , active power P, reactive power Q, and power factor cosφ are integrated. The final operating parameter matrix is ​​expressed as:

[0060]

[0061] Where n is the number of charging ports.

[0062] In a specific embodiment, the process of executing step 200 may specifically include the following steps:

[0063] Extract and classify the port active power data in the port real-time operation parameter matrix to obtain the active power distribution data of each charging port, and calculate the standard deviation and mean of the active power distribution data to obtain the port power fluctuation range;

[0064] According to the port power fluctuation range, the active power distribution data is filtered and the average value is calculated to obtain the port load power, and the maximum value and minimum value of the port load power are retrieved to obtain the system maximum port power and the system minimum port power;

[0065] The load imbalance is obtained by dividing the difference between the maximum port power and the minimum port power of the system by the sum of the port load powers and multiplying by 100%.

[0066] Perform division operation on the output active power data and the input apparent power data in the port real-time operation parameter matrix to obtain the instantaneous charging efficiency of each charging port;

[0067] The instantaneous charging efficiency is exponentially weighted averaged to obtain the average charging efficiency of the port, and the charging efficiency is obtained by weighted summation based on the average charging efficiency of the port and the proportion of the load power of each port in the total system power.

[0068] Specifically, the active power data of each port is extracted from the port real-time operation parameter matrix. Suppose the port real-time operation parameter matrix is ​​M 参数 , where the i-th row represents the operating data of the i-th port, including the voltage V eff,i 、Current I eff,i , Active power P i , reactive power Q i , and power factor cosφ i The active power data of all ports are extracted and sorted according to time series to form an active power distribution data set {P i,t}, where P i,t Represents the active power of the i-th port at time t. The standard deviation and mean of the active power distribution data of each port are calculated to measure the power fluctuation range. The standard deviation is used to describe the discrete degree of power data, and the mean represents the overall level of power. The standard deviation σ of the i-th port i and mean μ i Calculated by the following formula:

[0069]

[0070] Where T is the total number of sampling time points, P i,t is the power value at a certain moment. By calculating σ i and μ i , get the power fluctuation range of the port and describe the dynamic characteristics of the port power. Filter the active power distribution data according to the power fluctuation range to remove abnormal values ​​or noise. By setting the filtering threshold, for example, limiting the power value to [μ i -2σ i ,μ i +2σ i ], only the power data within this range is retained for subsequent calculation. The filtered power data is averaged to obtain the load power P of the port. load,i :

[0071]

[0072] Where N i is the number of valid data points remaining after filtering, P i,t,filtered Indicates the filtered power data. For all ports, the load power {P load,i} Perform maximum and minimum value retrieval to obtain the system maximum port power P maxand the system minimum port power P min On this basis, the system load imbalance is calculated, which is defined as the ratio of the difference between the maximum port power and the minimum port power to the total load power. The formula for load imbalance δ is:

[0073]

[0074] Where n is the number of ports. The smaller the value of load imbalance, the more evenly the system load is distributed. After completing the load analysis, calculate the charging efficiency. i And input apparent power data S i =V eff,i I eff,i Perform division operation to obtain the instantaneous charging efficiency η of each port i,t :

[0075]

[0076] The instantaneous charging efficiency varies with time. In order to obtain a more stable efficiency value, an exponentially weighted average is calculated. The average charging efficiency of the i-th port Calculated by the following recursive formula:

[0077]

[0078] Where α is the weighting coefficient, which ranges from 0<α<1, indicating the weight of recent data. The overall charging efficiency η of the system is calculated by weighted summing the average charging efficiency of the port and the proportion of its load power in the total system power. sys :

[0079]

[0080] In a specific embodiment, the process of executing step 300 may specifically include the following steps:

[0081] The load imbalance is multiplied by the first weight coefficient to obtain a load balance score, and the charging efficiency is multiplied by the second weight coefficient to obtain a charging efficiency score;

[0082] The power factor data in the real-time operation parameter matrix of the port is multiplied by a third weight coefficient for weighted calculation to obtain a power factor score;

[0083] The load balance score, charging efficiency score and power factor score are added together to obtain the system operation status score;

[0084] Divide the port load power by the rated load of each charging port to obtain the standardized load rate, and divide the charging efficiency by the system maximum charging efficiency to obtain the relative efficiency value;

[0085] The power factor score is divided by the target power factor to obtain a correction factor, and a weighted calculation is performed with the preset weight factor according to the standardized load rate, the relative efficiency value and the correction factor to obtain an initial allocation index;

[0086] The voltage and current data of the input and output terminals of the charging pile energy storage connector are collected to obtain the power transmission efficiency of the energy storage connector. The initial allocation index is corrected and calculated based on the power transmission efficiency to obtain an adaptive allocation index that takes into account the characteristics of the energy storage connector.

[0087] Specifically, the load imbalance of the system is multiplied by the first weight coefficient for weighted calculation to obtain a load balance score. The load imbalance δ is an important indicator for describing the uniformity of load distribution of each port in the system, and its formula is:

[0088]

[0089] Where P max and P min are the maximum and minimum port load power of the system, P load,i represents the load power of the i-th port, and n is the total number of ports. The load balance score S is obtained by multiplying the load imbalance degree by the first weight coefficient w1. balance :

[0090] S balance =w1·(1-δ);

[0091] Among them, 1-δ is used to convert to load balance. The closer the value is to 1, the more evenly distributed it is. The charging efficiency is multiplied by the second weight coefficient for weighted calculation to obtain the charging efficiency score. Charging efficiency η sys represents the energy conversion efficiency of the system, which is defined as:

[0092]

[0093] where η i is the charging efficiency of the i-th port, and the charging efficiency score S is obtained by multiplying it with the weight w2. efficiency :

[0094] S e ffi c i ency =w2·η sys ;

[0095] The power factor data in the port real-time operation parameter matrix is ​​multiplied by the third weight coefficient to calculate the power factor score. Power factor cosφ i Indicates the energy utilization efficiency of the i-th port. By weighting it, the power factor performance of the entire system is quantified. System power factor score S power_factor The calculation formula is:

[0096]

[0097] Where w3 is the third weight coefficient. The load balancing score S balance , Charging efficiency score S efficiency and power factor rating S power_facton Add them together to get the system operation status score S system :

[0098]

[0099] To optimize the allocation decision, the normalized load factor, relative efficiency value and power factor correction coefficient are calculated. Normalized load factor λ i Indicates the ratio of each port's load power to its rated load:

[0100]

[0101] Where P rated,i is the rated load power of the i-th port. Relative efficiency value ρ i Indicates the port charging efficiency relative to the system's maximum charging efficiency η max Ratio of:

[0102]

[0103] Power factor correction coefficient γ i It is used to correct the actual power factor and the target power factor cosφ target The deviation between them is calculated as:

[0104]

[0105] The normalized load factor λ i , relative efficiency value ρ i and correction factor γ i Respectively with the preset weight coefficient w λ ,w ρ ,w γ Perform weighted calculation to obtain the initial allocation index I i :

[0106] I i =w λ ·λ i+w ρ ·ρ i +w γ γ i ;

[0107] After obtaining the initial allocation index, it is corrected in combination with the power transmission efficiency of the energy storage connector. in ,V out and current I in ,I out , calculate the power transfer efficiency η connector :

[0108]

[0109] Modified adaptive allocation index The calculation formula is:

[0110]

[0111] In a specific embodiment, the process of executing step 400 may specifically include the following steps:

[0112] The target allocation ratio is calculated for the standardized load rate, relative efficiency value and correction coefficient of each charging port to obtain the initial allocation weight of each charging port;

[0113] The initial allocation weights are replicated and constructed to obtain N independent sub-populations, where each sub-population contains M chromosome individuals, and each chromosome individual encodes the current allocation value of each charging port;

[0114] The fitness of the chromosome individuals in each subpopulation is evaluated to obtain the individual fitness value, where the fitness evaluation is constructed based on the system loss minimization index, the charging efficiency maximization index and the load balance maximization index;

[0115] Based on the tournament selection strategy, the chromosome individuals of each sub-population are screened for high-quality individuals to obtain the parent individuals, and the parent individuals are simulated by binary crossover operations and polynomial mutation operations to obtain the offspring population;

[0116] The migration operation is performed on the offspring population every P generations to obtain the population after migration, where the migration operation uses a ring topology structure to exchange the best individuals between adjacent sub-populations;

[0117] The current constraints and power constraints of the individuals in the population after migration are verified to obtain a feasible solution set, where the current constraint ensures that the current of each port does not exceed the rated value, and the power constraint ensures that the total system power does not exceed the maximum output power of the energy storage device;

[0118] The feasible solution set is non-dominated sorted and the congestion distance is calculated to obtain the solution set on the Pareto optimal frontier surface. The system loss, charging efficiency and load balance of each individual in the solution set on the Pareto optimal frontier surface are weighted and summed to obtain the optimal current distribution value.

[0119] Specifically, the target allocation ratio is calculated for the standardized load rate, relative efficiency value and correction coefficient of each charging port to obtain the initial allocation weight. Assume that the standardized load rate of the i-th port is Where P load,i Indicates the current load power of the port, P rated,i is the rated load power of the port; the relative efficiency value is where η i is the port charging efficiency, η max is the maximum charging efficiency of the system; the correction factor is where cosφ i is the port power factor, cosφ target is the target power factor. The initial allocation weight w i The calculation formula is:

[0120] w i =w λ ·λ i +w ρ ·ρ i +w γ γ i ;

[0121] where w λ 、w ρ and w γ are the weight factors of the standardized load rate, relative efficiency value and correction coefficient respectively. The initial allocation weight is used to generate the population, and N independent sub-populations are constructed by replication, each of which contains M chromosome individuals. The encoding of the chromosome individual contains the current allocation value of all charging ports {I i}, where each I i Represents the allocated current value of the i-th port. The purpose of population construction is to perform evolutionary optimization of the genetic algorithm based on diverse individuals. The fitness of the chromosome individuals in each subpopulation is evaluated to measure the pros and cons of each allocation scheme. The fitness evaluation is constructed based on three optimization objectives: minimizing system loss, maximizing charging efficiency, and maximizing load balancing. The objective function of minimizing system loss is expressed as:

[0122]

[0123] Where R i is the equivalent resistance of the i-th port. The objective function for maximizing charging efficiency is:

[0124]

[0125] The objective function of maximizing load balancing is calculated by calculating the load uniformity index δ balance accomplish:

[0126]

[0127] The comprehensive evaluation of the fitness function adopts the weighted summation method:

[0128] f fitness =w loss ·f loss +w efficiency ·f efficiency +w balance ·δ balance ;

[0129] where w loss 、w efriciency and w balance is the weight coefficient of each optimization objective. After the fitness evaluation is completed, the tournament selection strategy is used to select high-quality individuals from the sub-population as the parent generation. The tournament selection randomly selects several individuals, compares their fitness values, and selects the individuals with the best fitness to enter the parent generation. The parent individuals are simulated by binary crossover operations and polynomial mutation operations to generate the sub-population. The crossover operation simulates the gene recombination in the genetic process, and controls the crossover probability P c Realize the exchange of information between individuals; polynomial mutation enhances the diversity of the population by introducing small random changes and prevents the algorithm from falling into local optimality. Every P generations, the sub-population is migrated, and the best individuals are exchanged between adjacent sub-populations through the ring topology. The migration operation accelerates the convergence of the global optimal solution through the crossover and propagation of the best individuals. After the migration is completed, the current constraint and power constraint verification are performed on the individuals in the population. The current constraint ensures that each port is assigned a current I i Not exceeding its rated value I rated,i :

[0130] I i ≤I rated,i ;

[0131] The power constraint ensures that the total allocated power does not exceed the maximum output power P of the energy storage device. max :

[0132]

[0133] After constraint verification, the feasible solution set is non-dominated sorting and congestion distance calculation is performed to screen out the solution set on the Pareto optimal frontier. Non-dominated sorting compares the pros and cons between solutions to find those solution sets that are not dominated by other solutions on all objectives; the congestion distance is used to evaluate the distribution uniformity of solutions on the Pareto frontier to encourage the diversity of solution sets. The solution set on the Pareto optimal frontier is weighted and scored to comprehensively evaluate the system loss, charging efficiency, and load balance of the solution, and the solution with the best fitness is selected as the final optimal current distribution value. For example, assuming there are three ports, after optimization, three solutions {I 1,j ,I 2,j ,I 3,j}, the corresponding fitness values ​​are {f fitness,1 ,f fitness,2 ,f fitness,3}. By comparing the fitness values, the best solution is selected As the final allocation plan.

[0134] In a specific embodiment, the process of executing step 500 may specifically include the following steps:

[0135] Inputting the optimal current distribution value into the controller of each charging port to set the target value, and obtaining the port control target value;

[0136] Perform difference calculation on the real-time current value collected by the current sensor of each charging port and the port control target value to obtain the current tracking error value;

[0137] The current tracking error value is input into the PI controller for proportional-integral operation to obtain the feedback control output value, and the load characteristic is analyzed according to the change rate of the port control target value to obtain the load dynamic response prediction value;

[0138] Perform feedforward compensation calculation on the load dynamic response prediction value to obtain the feedforward control output value;

[0139] Perform weighted superposition operation on the feedback control output value and the feedforward control output value to obtain a PWM modulation control signal;

[0140] Carrier modulation calculation is performed on the PWM modulation control signal to obtain the IGBT switch tube driving waveform of the power electronic converter, and the IGBT switch tube driving waveform is input into the driving circuit of the power electronic converter for switch control to obtain the real-time output current of each charging port.

[0141] Specifically, the optimal current distribution value {I opt,i} is input into the controller of each charging port to set the target output value I of the port target,i For each port i, the target value I target,iIt directly reflects the current that the port should output and is the key reference quantity of the control process. The optimal allocation scheme is converted into specific control indicators to guide real-time current regulation. The output current I of each charging port is collected in real time through the current sensor. actual,i (t), and the corresponding target value I target,i Perform difference calculation to calculate the current tracking error value ΔI i (t):

[0142] ΔI i (t) = I target,i -I actual,i (t);

[0143] Where ΔI i (t) represents the error magnitude of port i at time t, reflecting the deviation between the actual output current and the target value. i (t) is input into the proportional integral (Pl) controller to perform proportional integral operation to generate the feedback control output value U feedback,i (t). The core formula of the PI controller is:

[0144]

[0145] Where K p is the proportional gain, K i is the integral gain, The proportional part is used to quickly respond to instantaneous changes in the error, while the integral part eliminates the steady-state error, ensuring that the output current can accurately track the target value. At the same time, based on the target value I target,i The rate of change dI target,i / dt, analyze the dynamic characteristics of the load and obtain the load dynamic response prediction value U predict,i (t). This predicted value is used to describe the system current response behavior caused by the change in the target value, and its calculation formula is:

[0146]

[0147] Where K f is the feedforward gain, Indicates the instantaneous rate of change of the target value. predict,i (t) Input the feedforward controller, perform feedforward compensation calculation, and generate the feedforward control output value U feedforward,i (t). Feedforward control aims to adjust the output signal in advance according to the dynamic changes of the target value, thereby improving the rapid response capability of the system. feedback,i (t) and the feedforward control output value U feedforward,i (t) Perform weighted superposition operation to generate PWM modulation control signal U PWM,i (t):

[0148] U PWM,i (t) = w d ·U feedback,i (t)+w ff ·U feedforward,i (t);

[0149] where w f and w ff is the weight factor of feedback control and feedforward control, which is determined through system debugging to achieve a balance between response speed and control accuracy. PWM,i (t) Carrier modulation calculation is performed to obtain the IGBT switch tube drive waveform of the power electronic converter. Carrier modulation adopts sinusoidal pulse width modulation (SPWM) or space vector pulse width modulation (SVPWM) method. Taking SPWM as an example, the modulation signal is compared with the high-frequency triangular carrier to generate the switching signal:

[0150]

[0151] Among them U carrier (t) is the carrier signal, S IGBT,i (t) is a binary signal of the driving waveform, indicating the on (1) and off (0) of the IGBT. IGBT,i (t) Input power electronic converter drive circuit, control the on and off state of the switch tube, and adjust the output current. Output current I output,i (t) and target value I target,i Dynamic matching completes the entire current control process.

[0152] In a specific embodiment, the execution step performs carrier modulation calculation on the PWM modulation control signal to obtain the IGBT switch tube drive waveform of the power electronic converter, and inputs the IGBT switch tube drive waveform into the drive circuit of the power electronic converter for switch control, and the process of obtaining the real-time output current of each charging port can specifically include the following steps:

[0153] Extracting data from the PWM modulation control signal to obtain a control signal sampling sequence, and performing amplitude normalization processing on the control signal sampling sequence to obtain a normalized modulation wave;

[0154] The triangular carrier signal is frequency-multiplied to obtain a high-frequency carrier signal, and the normalized modulation wave and the high-frequency carrier signal are phase-synchronized to obtain a synchronous carrier modulation signal;

[0155] Based on the feedforward-feedback composite control strategy, the duty cycle of the synchronous carrier modulation signal is dynamically calculated to obtain the duty cycle modulation waveform;

[0156] Perform voltage clamping and overmodulation suppression on the duty cycle modulation waveform to obtain an optimized modulation waveform, and perform dead time compensation on the optimized modulation waveform to obtain a compensated PWM drive signal;

[0157] The compensated PWM drive signal is input into the photoelectric isolation module of the driver for electrical isolation to obtain an isolated drive voltage, and the isolated drive voltage is subjected to dislocation delay control to obtain a dislocation drive signal;

[0158] The gate drive voltage is clamped and overcurrent protection is performed on the misaligned drive signal to obtain the IGBT switch tube drive waveform;

[0159] A dynamic response analysis is performed based on the transfer function model of the duty cycle of the IGBT switch tube driving waveform and the output current of the charging port to obtain the output current prediction value, and the output current prediction value is tracked and controlled in a closed loop to obtain the real-time output current of each charging port.

[0160] Specifically, data is extracted from the PWM modulation control signal to obtain the sampling sequence of the signal. Assume that the PWM control signal is U PWM (t), and perform discrete sampling to obtain the sampling sequence {U PWM,n}, where n represents the discrete time step. The sampling sequence describes the discrete change of the PWM signal in time and retains the amplitude information of the signal. In order to facilitate subsequent processing, the sampling sequence is amplitude normalized to obtain the normalized modulation wave The normalization formula is:

[0161]

[0162] Among them U max and U min are the maximum and minimum values ​​of the sampling sequence respectively. The normalized signal range is limited to [0,1], which is convenient for matching and modulation with the carrier signal. Generate a high-frequency carrier signal for modulation. The carrier signal uses a triangular wave with an initial frequency of f carrier In order to improve the modulation accuracy, the frequency is multiplied to obtain a high-frequency carrier signal. Assuming the frequency multiplication factor is k, the frequency of the high-frequency carrier is f carrier,high = k·f carrier The expression of high frequency carrier signal is:

[0163]

[0164] Where T carrier =1 / f carrier,high is the period of the high frequency carrier, Indicates the rounding down operation. The normalized modulation wave With high frequency carrier signal Perform phase synchronization calculation to obtain the synchronous carrier modulation signal Phase synchronization ensures that the modulation operations of the two are consistent in time and amplitude, thereby reducing modulation errors. Based on the synchronous carrier modulation signal, the duty cycle of the signal is dynamically calculated using the feedforward-feedback composite control strategy to generate a duty cycle modulation waveform The feedforward control part predicts the output based on the dynamic rate of change of the modulation signal, and the feedback control part uses the error to correct the signal deviation. The dynamic calculation formula of the duty cycle is:

[0165]

[0166] in is the real-time error of the modulation signal, K p and K f They are proportional gain and feedforward gain respectively. In order to ensure the safety and stability of the modulation waveform, the duty cycle modulation waveform is voltage clamped and overmodulation suppressed to obtain the optimized modulation waveform. Voltage clamping limits the waveform amplitude to the range of [0,1], while overmodulation suppression prevents overload of the drive signal by adjusting the duty cycle dynamic range. Dead time compensation is performed on the optimized waveform to generate a compensated PWM drive signal. The expression for dead time compensation is:

[0167]

[0168] Where ΔT dead Is the setting value of the dead time. The compensated PWM drive signal is input to the driver's photoelectric isolation module for electrical isolation to generate an isolated drive voltage The purpose of photoelectric isolation is to provide electrical isolation between the control circuit and the power circuit to improve the anti-interference ability and safety of the system. On this basis, the isolation drive voltage is controlled by offset delay to generate an offset drive signal The setting of the offset delay is based on the specific current requirements to ensure that the operations of different channels do not interfere with each other. The gate drive voltage is clamped and overcurrent protection is performed on the offset drive signal to generate the IGBT switch tube drive waveform S IGBT (t). Gate clamping ensures that the amplitude of the drive signal is within the safe operating range of the IGBT, while overcurrent protection prevents overload damage by monitoring the current. Through dynamic response analysis, the duty cycle of the IGBT switch drive waveform is Transfer function model of charging port output current Combined, the predicted output current

[0169]

[0170] Among them and -1Represents Laplace transform and its inverse transform respectively. Closed-loop tracking control is performed on the predicted output current, and the output current is ensured by dynamically adjusting the PWM signal. Exactly match target value I target .

[0171] Among them, the control method of the charging pile energy storage connector with adaptive current distribution function also includes: designing reverse peak voltage suppression for the solid-state relay drive circuit of the charging pile energy storage connector, wherein a suppression unit composed of a diode and a voltage regulator diode is connected in parallel at the output end of the solid-state relay to obtain a drive circuit that is resistant to voltage shocks; integrating an optocoupler isolation module into the output end of the solid-state relay to obtain a drive module with a feedback signal isolation function, and sampling the output signal of the drive module to obtain a drive state feedback signal; measuring the rising and falling edge time of the drive state feedback signal to obtain drive circuit reset time data, and optimizing and calculating the parameters of the suppression unit according to the reset time data to obtain optimized drive circuit parameters; setting a Hall effect current sensing module at the output end of the charging pile energy storage connector to obtain a current original sampling signal, and performing operational amplification processing on the current original sampling signal , obtain a high-precision current measurement signal; perform dynamic response characteristic analysis on the high-precision current measurement signal to obtain current measurement dynamic error data, and calibrate the gain parameters of the operational amplifier according to the current measurement dynamic error data to obtain compensated measurement circuit parameters; resample and amplify the high-precision current measurement signal based on the compensated measurement circuit parameters to obtain a calibrated current measurement value; compare and analyze the calibrated current measurement value with the preset standard current value to obtain static measurement accuracy data, and correct and compensate the current measurement circuit according to the static measurement accuracy data to obtain a final current measurement result; perform piecewise linear fitting processing on the final current measurement result to obtain a current measurement characteristic curve, and input the current measurement characteristic curve as a feedback calibration signal into a closed-loop control system of the real-time output current of each charging port to obtain the calibrated real-time output current of each charging port.

[0172] In this embodiment, after obtaining the real-time output current of each charging port after calibration, the method further includes: extracting the timing characteristics of the historical operation data of each charging port to obtain a multi-dimensional timing characteristic matrix including voltage, current, power and charging efficiency, and normalizing the multi-dimensional timing characteristic matrix to obtain standardized characteristic data; inputting the standardized characteristic data into the first-layer threshold cycle unit for timing dependency analysis to obtain the timing correlation vector of the port operation state, and performing adaptive threshold function mapping on the timing correlation vector to obtain filtered state characteristics; performing cyclic connection weight calculation on the filtered state characteristics to obtain a state transition probability matrix, and constructing a Markov chain model for port load prediction based on the state transition probability matrix to obtain an initial prediction result; inputting the initial prediction result and the actual operation data into the second-layer threshold cycle unit for error analysis to obtain a prediction deviation sequence, and performing autocorrelation on the prediction deviation sequence. The error correction factor is obtained by performing online analysis on the weight parameters of the double-layer threshold recurrent network according to the error correction factor to obtain the optimized network parameters, and the load changes of the charging port are re-predicted based on the optimized network parameters to obtain the corrected load prediction results; the corrected load prediction results are input into the neural network proxy model for parallel training to obtain the probability distribution model of the port load characteristics, and the confidence interval analysis is performed on the probability distribution model to obtain the uncertainty evaluation result of the load prediction; the charging control strategy is dynamically optimized based on the uncertainty evaluation result to obtain the control parameter set that takes into account the prediction uncertainty, and the control parameter set is input into the adaptive PI controller to obtain the compensated control instruction; the fuzzy rule reasoning is performed on the compensated control instruction to obtain the fuzzy control gain matrix, and the fuzzy control gain matrix is ​​superimposed as a correction amount on the PWM modulation control signal of each charging port.

[0173] The above describes the control method of the charging pile energy storage connector with adaptive current distribution function in the embodiment of the present application. The following describes the charging pile energy storage connector system 10 with adaptive current distribution function in the embodiment of the present application. Figure 2 In the embodiment of the present application, an embodiment of a charging pile energy storage connector system 10 with an adaptive current distribution function includes:

[0174] The data acquisition module 11 is used to collect and filter data from each charging port of the charging pile to obtain a real-time operating parameter matrix of the port;

[0175] The power calculation module 12 is used to calculate the port load power of the port real-time operation parameter matrix to obtain the port load power, and calculate the load imbalance and charging efficiency according to the port load power;

[0176] An index calculation module 13, used to calculate the adaptive allocation index of each charging port based on the load imbalance and charging efficiency;

[0177] A current calculation module 14, used to calculate the optimal current distribution value of each charging port according to the adaptive distribution index;

[0178] The dynamic adjustment module 15 is used to perform PWM signal duty cycle modulation and current dynamic adjustment on the power electronic converter of each charging port according to the optimal current distribution value, so as to obtain the real-time output current of each charging port.

[0179] Through the cooperation of the above components, the voltage, current and power factor of the charging port are monitored and filtered in real time to obtain an accurate port operation parameter matrix, which improves the stability of the system operation. The adaptive allocation index calculation method based on load imbalance and charging efficiency is adopted, combined with the characteristics of the energy storage connector for correction, to achieve the reasonable allocation of charging resources and significantly improve the overall charging efficiency of the system. The genetic algorithm is introduced for multi-objective optimization. Through the screening of Pareto optimal solutions, the optimal balance point is found between multiple objectives such as minimizing system losses, maximizing charging efficiency and maximizing load balance. A PWM modulation method based on the feedforward-feedback composite control strategy is designed, and the current dynamic regulation is used to achieve a rapid response to load changes and improve the dynamic performance of the system. The dead time compensation and staggered delay control technology are used to effectively reduce the switching loss of the power electronic converter and improve the energy conversion efficiency of the system. Through closed-loop tracking control and real-time output current prediction, the charging process is accurately controlled to ensure the safety and reliability of the charging process. Through the synergy of multi-level optimization and control strategies, the efficient operation of the charging pile system under different working conditions is achieved, and the utilization rate of charging equipment is improved.

[0180] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0181] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable an electronic device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program code.

[0182] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for controlling a charging pile energy storage connector with an adaptive current distribution function, characterized in that: The method comprises: Perform data collection and filtering on each charging port of the charging pile to obtain the real-time operation parameter matrix of the port; Calculating the port load power of the port real-time operation parameter matrix to obtain the port load power, and calculating the load imbalance and charging efficiency according to the port load power; Calculating an adaptive allocation index of each charging port based on the load imbalance and the charging efficiency; Calculating an optimal current distribution value for each charging port according to the adaptive distribution index; According to the optimal current distribution value, the PWM signal duty cycle modulation and current dynamic adjustment are performed on the power electronic converter of each charging port to obtain the real-time output current of each charging port.

2. The control method of the charging pile energy storage connector with adaptive current distribution function according to claim 1 is characterized in that: The data collection and filtering process is performed on each charging port of the charging pile to obtain a real-time operation parameter matrix of the port, including: Data is collected from the voltage sensors provided at each charging port of the charging pile to obtain the original data of the port voltage, and the original data of the port voltage is processed in series with high-pass filtering and low-pass filtering to obtain the effective value data of the port voltage; The current sensor provided at each charging port of the charging pile is used to collect data to obtain the original data of the port current, and the original data of the port current is processed in series by high-pass filtering and low-pass filtering to obtain the effective value data of the port current; Inputting the port voltage effective value data and the port current effective value data into a power analyzer for product operation and phase difference calculation to obtain port active power data and port reactive power data; Performing trigonometric function calculation on the port active power data and the port reactive power data to obtain port power factor data; The port voltage effective value data, the port current effective value data, the port active power data, the port reactive power data and the port power factor data are matrix-joined to obtain a port real-time operation parameter matrix.

3. The control method of the charging pile energy storage connector with adaptive current distribution function according to claim 1, characterized in that: The calculating the port load power of the port real-time operation parameter matrix to obtain the port load power, and calculating the load imbalance and charging efficiency according to the port load power, includes: Extracting and classifying the port active power data in the port real-time operation parameter matrix to obtain active power distribution data of each charging port, and performing standard deviation calculation and mean calculation on the active power distribution data to obtain the port power fluctuation range; The active power distribution data is filtered and averaged according to the port power fluctuation range to obtain the port load power, and the port load power is retrieved for maximum value and minimum value to obtain the system maximum port power and the system minimum port power; The load imbalance degree is obtained by dividing the difference between the maximum port power of the system and the minimum port power of the system by the sum of the port load powers and multiplying by 100%; Performing a division operation on the output active power data and the input apparent power data in the real-time operation parameter matrix of the port to obtain the instantaneous charging efficiency of each charging port; The instantaneous charging efficiency is exponentially weighted averaged to obtain the port average charging efficiency, and a weighted sum is calculated based on the port average charging efficiency and the proportion of the load power of each port in the total system power to obtain the charging efficiency.

4. The control method of the charging pile energy storage connector with adaptive current distribution function according to claim 1, characterized in that: The calculating the adaptive allocation index of each charging port based on the load imbalance and the charging efficiency includes: The load imbalance degree is multiplied by a first weight coefficient to perform weighted calculation to obtain a load balance score, and the charging efficiency is multiplied by a second weight coefficient to perform weighted calculation to obtain a charging efficiency score; Multiplying the power factor data in the real-time operation parameter matrix of the port by a third weight coefficient for weighted calculation to obtain a power factor score; Adding the load balance score, the charging efficiency score and the power factor score to obtain a system operation status score; Dividing the port load power by the rated load of each charging port to obtain a standardized load rate, and dividing the charging efficiency by the maximum charging efficiency of the system to obtain a relative efficiency value; Performing a division operation on the power factor score and the target power factor to obtain a correction coefficient, and performing weighted calculation on the standardized load rate, the relative efficiency value and the correction coefficient with a preset weight coefficient to obtain an initial allocation index; The voltage data and current data of the input and output terminals of the charging pile energy storage connector are collected to obtain the power transmission efficiency of the energy storage connector, and the initial allocation index is corrected and calculated based on the power transmission efficiency to obtain an adaptive allocation index that takes into account the characteristics of the energy storage connector.

5. The control method of the charging pile energy storage connector with adaptive current distribution function according to claim 1, characterized in that: The calculating the optimal current distribution value of each charging port according to the adaptive distribution index includes: The target allocation ratio is calculated for the standardized load rate, relative efficiency value and correction coefficient of each charging port to obtain the initial allocation weight of each charging port; The initial allocation weights are replicated and constructed to obtain N independent sub-populations, wherein each sub-population includes M chromosome individuals, and each chromosome individual encodes a current allocation value of each charging port; Performing fitness evaluation on the chromosome individuals in each subpopulation to obtain individual fitness values, wherein the fitness evaluation is constructed based on a system loss minimization index, a charging efficiency maximization index, and a load balance maximization index; Based on the tournament selection strategy, high-quality individuals are screened for chromosome individuals of each sub-population to obtain parent individuals, and a simulated binary crossover operation and a polynomial mutation operation are performed on the parent individuals to obtain a sub-population; Performing a migration operation on the offspring population every P generations to obtain a migrated population, wherein the migration operation uses a ring topology structure to exchange optimal individuals between adjacent subpopulations; Performing current constraint and power constraint verification on individuals of the migrated population to obtain a feasible solution set, wherein the current constraint ensures that the current of each port does not exceed the rated value, and the power constraint ensures that the total power of the system does not exceed the maximum output power of the energy storage device; The feasible solution set is non-dominated sorted and the congestion distance is calculated to obtain a solution set on the Pareto optimal frontier surface, and a weighted sum score is performed based on the system loss, charging efficiency and load balance of each individual in the solution set on the Pareto optimal frontier surface to obtain the optimal current distribution value.

6. The control method of the charging pile energy storage connector with adaptive current distribution function according to claim 1, characterized in that: According to the optimal current distribution value, the power electronic converter of each charging port performs PWM signal duty cycle modulation and current dynamic regulation to obtain the real-time output current of each charging port, including: Inputting the optimal current distribution value into the controller of each charging port to set a target value, thereby obtaining a port control target value; Performing a difference operation on the real-time current value collected by the current sensor of each charging port and the port control target value to obtain a current tracking error value; The current tracking error value is input into the PI controller for proportional-integral operation to obtain a feedback control output value, and a load characteristic analysis is performed according to the change rate of the port control target value to obtain a load dynamic response prediction value; Performing feedforward compensation calculation on the load dynamic response prediction value to obtain a feedforward control output value; Performing a weighted superposition operation on the feedback control output value and the feedforward control output value to obtain a PWM modulation control signal; Carrier modulation calculation is performed on the PWM modulation control signal to obtain an IGBT switch tube drive waveform of the power electronic converter, and the IGBT switch tube drive waveform is input into the drive circuit of the power electronic converter for switch control to obtain the real-time output current of each charging port.

7. The control method of the charging pile energy storage connector with adaptive current distribution function according to claim 6, characterized in that: The carrier modulation calculation is performed on the PWM modulation control signal to obtain an IGBT switch tube drive waveform of the power electronic converter, and the IGBT switch tube drive waveform is input into the drive circuit of the power electronic converter for switch control to obtain the real-time output current of each charging port, including: Performing data extraction on the PWM modulation control signal to obtain a control signal sampling sequence, and performing amplitude normalization processing on the control signal sampling sequence to obtain a normalized modulation wave; Multiplying the frequency of the triangular carrier signal to obtain a high-frequency carrier signal, and performing phase synchronization calculation on the normalized modulation wave and the high-frequency carrier signal to obtain a synchronous carrier modulation signal; Based on a feedforward-feedback composite control strategy, a duty cycle of the synchronous carrier modulation signal is dynamically calculated to obtain a duty cycle modulation waveform; Performing voltage clamping and overmodulation suppression on the duty cycle modulation waveform to obtain an optimized modulation waveform, and performing dead time compensation on the optimized modulation waveform to obtain a compensated PWM drive signal; Input the compensated PWM drive signal into the photoelectric isolation module of the driver for electrical isolation to obtain an isolated drive voltage, and perform dislocation delay control on the isolated drive voltage to obtain a dislocation drive signal; Performing gate drive voltage clamping and overcurrent protection on the misaligned drive signal to obtain an IGBT switch tube drive waveform; A dynamic response analysis is performed based on a transfer function model of the duty cycle of the IGBT switch tube drive waveform and the output current of the charging port to obtain an output current prediction value, and a closed-loop tracking control is performed on the output current prediction value to obtain a real-time output current of each charging port.

8. A charging pile energy storage connector system with adaptive current distribution function, characterized in that: A method for controlling a charging pile energy storage connector with an adaptive current distribution function according to any one of claims 1 to 7, the system comprising: The data acquisition module is used to collect and filter data from each charging port of the charging pile to obtain a real-time operating parameter matrix of the port; A power calculation module, used to calculate the port load power of the port real-time operation parameter matrix to obtain the port load power, and calculate the load imbalance and charging efficiency according to the port load power; An index calculation module, configured to calculate an adaptive allocation index of each charging port based on the load imbalance and the charging efficiency; A current calculation module, used to calculate the optimal current distribution value of each charging port according to the adaptive distribution index; The dynamic adjustment module is used to perform PWM signal duty cycle modulation and current dynamic adjustment on the power electronic converter of each charging port according to the optimal current distribution value, so as to obtain the real-time output current of each charging port.

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