AC / DC charging pile bidirectional power flow control method, device and equipment

Abstract

The invention relates to the technical field of bidirectional power flow control, and discloses an AC / DC charging pile bidirectional power flow control method, device and equipment, and the method comprises the steps: carrying out the detection and parameter collection of an AC / DC charging pile, a power converter and a grid connection point, and obtaining a charging pile system operation parameter set; trapezoidal voltage edge calculation is carried out on the switching process of the power converter, and the dead time compensation amount is superposed on a PWM control signal of the power converter to obtain a target PWM control signal; calculating to obtain an optimal PWM control sequence, and taking the first control quantity of the optimal PWM control sequence as the current control output; when it is detected that the direction of the power flow needs to be changed, the direct-current bus voltage of the power converter is controlled to be stabilized at a set value and then switched to the target working mode, and a new power output control quantity is obtained, the robustness of the alternating-current and direct-current charging pile is enhanced, the alternating-current and direct-current charging pile can adapt to the operation requirements under different working conditions, and the reliability of the charging pile is improved. And the fault rate of the AC / DC charging pile is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of bidirectional power flow control, and in particular to a method, device and equipment for bidirectional power flow control of an AC / DC charging pile. Background Art

[0002] AC and DC charging piles are an important part of the charging infrastructure for electric vehicles. Their bidirectional power flow control technology is of great significance to improving charging efficiency and grid interaction capabilities. At present, in the process of bidirectional power flow in traditional charging piles, low-order harmonic distortion often occurs due to the influence of parasitic capacitance and dead time of the switch tube in the power converter, which not only reduces the power quality of the system, but also may cause electromagnetic interference, affecting the stable operation of the charging pile.

[0003] With the development of electric vehicle and network interaction technology, charging piles need to have bidirectional power flow capabilities. However, during the power flow switching process, voltage fluctuations and power oscillations are prone to occur due to the dynamic response characteristics of voltage and current. Traditional power control methods often use simple PI control, which cannot effectively respond to system parameter changes and external disturbances, resulting in poor system dynamic performance, especially in high-power fast charging and discharging scenarios. Summary of the invention

[0004] The present invention provides a bidirectional power flow control method, device and equipment for an AC / DC charging pile. The present invention enhances the robustness of the AC / DC charging pile, enables the AC / DC charging pile to adapt to the operating requirements under different working conditions, and reduces the failure rate of the AC / DC charging pile.

[0005] In a first aspect, the present invention provides a bidirectional power flow control method for an AC / DC charging pile, the bidirectional power flow control method for an AC / DC charging pile comprising: Detect and collect parameters of AC and DC charging piles, power converters and grid connection points to obtain the charging pile system operation parameter set; Performing trapezoidal voltage edge calculation on the switching process of the power converter according to the system operation parameter set to obtain a dead time compensation amount, and superimposing the dead time compensation amount on the PWM control signal of the power converter to obtain a target PWM control signal; Input the target PWM control signal and the current system state into the prediction controller for discrete mathematical modeling, calculate and obtain the optimal PWM control sequence, and use the first control quantity of the optimal PWM control sequence as the current control output; The working state of the AC / DC charging pile is judged according to the current control output. When it is detected that the power flow direction needs to be changed, the power output of the current working mode is controlled to gradually drop to zero. After the DC bus voltage of the power converter stabilizes at the set value, it switches to the target working mode to obtain a new power output control amount.

[0006] In a second aspect, the present invention provides a bidirectional power flow control device for an AC / DC charging pile, the bidirectional power flow control device for an AC / DC charging pile comprising: The acquisition module is used to detect and collect parameters of AC and DC charging piles, power converters and grid connection points to obtain the charging pile system operation parameter set; a calculation module, configured to perform a trapezoidal voltage edge calculation on a switching process of a power converter according to the system operation parameter set to obtain a dead time compensation amount, and superimpose the dead time compensation amount on a PWM control signal of the power converter to obtain a target PWM control signal; A switching module is used to input the target PWM control signal and the current system state into a prediction controller for discrete mathematical modeling, calculate an optimal PWM control sequence, and use the first control quantity of the optimal PWM control sequence as the current control output; The acquisition module is used to judge the working state of the AC / DC charging pile according to the current control output. When it is detected that the power flow direction needs to be changed, the power output of the current working mode is controlled to gradually drop to zero, and the DC bus voltage of the power converter is switched to the target working mode after it stabilizes at the set value to obtain a new power output control amount.

[0007] A third aspect of the present invention provides a computer device, comprising: a memory and at least one processor, wherein the memory stores instructions; the at least one processor calls the instructions in the memory so that the computer device executes the above-mentioned AC / DC charging pile bidirectional power flow control method.

[0008] A fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the above-mentioned AC / DC charging pile bidirectional power flow control method.

[0009] In the technical solution provided by the present invention, low-order harmonics are effectively suppressed and the power quality of the system is improved by calculating the trapezoidal voltage edge and compensating the dead time of the power converter switching process. A discrete mathematical modeling method based on predictive control is adopted, combined with a rolling optimization algorithm, so that the system has a strong dynamic response capability and shortens the power regulation time. A complete power flow switching control strategy is designed. Through segmented power reduction and voltage stability criteria, the stability of the charging and discharging mode switching process is ensured, and the DC bus voltage fluctuation is controlled within ±2%. An iterative prediction calculation method is introduced to dynamically update the dead time compensation amount, so that the compensation effect remains stable within the entire working range, thereby improving the system efficiency. Through state space modeling and performance index optimization, the robustness of the system is enhanced, so that it can adapt to the operating requirements under different working conditions and reduce the system failure rate. The online iterative optimization algorithm is adopted to reduce the dependence on current sampling, reduce the impact of communication delay on system performance, and improve the real-time and reliability of control. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0011] Figure 1 A schematic diagram of the steps of a bidirectional power flow control method for an AC / DC charging pile in an embodiment of the present invention; Figure 2 It is a schematic diagram of the structure of a bidirectional power flow control device for an AC / DC charging pile in an embodiment of the present invention; Figure 3 It is a schematic block diagram of the structure of a computer device in an embodiment of the present invention. DETAILED DESCRIPTION

[0012] Embodiments of the present invention provide a method, device and equipment for bidirectional power flow control of an AC / DC charging pile. The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0013] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 , an embodiment of the AC / DC charging pile bidirectional power flow control method in the embodiment of the present invention includes: Step S1: Detect and collect parameters of AC and DC charging piles, power converters and grid connection points to obtain a charging pile system operation parameter set; It is understandable that the execution subject of the present invention may be a bidirectional power flow control device for an AC / DC charging pile, or may be a terminal or a server, which is not specifically limited here. The embodiment of the present invention is described by taking a server as the execution subject as an example.

[0014] Specifically, voltage sensor sampling points are set at the input and output ends of the AC / DC charging pile to capture the changes in voltage signals. After these voltage signals are converted to digital quantities, the voltage values ​​at the input and output ends are obtained. The voltage values ​​at the input and output ends are processed, the power frequency components are extracted, and the real-time power data of the AC / DC charging pile is generated by the reactive power calculation method. In this way, the power changes of the charging pile under different operating conditions are dynamically monitored to provide real-time information support for power flow control. The parasitic capacitance test is performed on each switch tube of the power converter, and the rise time and fall time of the voltage at both ends of each switch tube are measured at different switching frequencies to obtain the parasitic capacitance parameters of the switch tube. Parasitic capacitance is an important factor affecting the performance of the power converter, and the accuracy of its parameters is directly related to the reliability of the control signal. In this process, based on the voltage waveform at both ends of the switch tube, the dead time is measured online and the time interval between the rising edge and the falling edge of the voltage waveform is calculated to obtain accurate dead time parameters. The control signal of the power converter and the conduction state of the switch tube are analyzed in time sequence, and the time difference from the effective edge of the control signal to the actual conduction of the switch tube is calculated to obtain the switch delay time parameter. The switch delay time reflects the dynamic response characteristics between the control signal and the actual physical action, and its optimization can significantly improve the dynamic performance of the power converter. At the same time, by setting voltage and current sensors at the grid connection point, the three-phase voltage and current of the grid are sampled, and the sampled signals are analyzed in the frequency domain using discrete Fourier transform to obtain the effective value and frequency value of the grid voltage, reflecting the stability of the grid operation. The input voltage value, output voltage value, real-time power data, switch tube parasitic capacitance parameters, dead time parameters, switch delay time parameters, grid voltage effective value and frequency value are combined into a data matrix to obtain the charging pile system operation parameter set.

[0015] Step S2, performing trapezoidal voltage edge calculation on the switching process of the power converter according to the system operation parameter set to obtain a dead time compensation amount, and superimposing the dead time compensation amount on the PWM control signal of the power converter to obtain a target PWM control signal; Specifically, the switching voltage of the power converter is mathematically modeled based on the parasitic capacitance parameters of the switch tube in the system operation parameter set. By establishing the voltage-time function of the switching voltage, the voltage change trend of the switch tube in different states is described, providing an accurate voltage change model for subsequent analysis. The voltage-time function of the switching process is analyzed by trapezoidal edge characteristics, the dynamic characteristics of voltage change are studied, and the voltage change rate curve is generated. The voltage change rate curve can accurately reflect the voltage waveform characteristics in the switching process and reveal the voltage change rate in different stages. Based on the voltage change rate curve, the conduction process of the switch tube is segmented, where the time parameter t1 is defined as the dead time and t2 is defined as the switching delay time, thereby dividing the switching voltage into three stages. The first stage is represented by the segmented voltage function v1(t), which describes the conduction voltage before switching; the second stage is described by v2(t), which represents the voltage change during the dead time; the third stage is represented by v3(t), which describes the conduction voltage change after switching. By comprehensively analyzing the voltage functions of these three stages, a mathematical expression for the total voltage distortion is established. The expression is expressed in the form of Vd(t)=v1(t)+v2(t)+v3(t), where Vd(t) is the total voltage distortion and t is the time variable. The mathematical model describes the distortion of the voltage waveform during the entire switching process. The voltage distortion mathematical model is expanded by Fourier series, and the total voltage distortion is decomposed into a series of harmonic components to obtain the amplitude and frequency information of each harmonic. These harmonic components reflect the impact of voltage distortion on system performance, especially the interference of high-order harmonics on the power grid and load. Based on this harmonic component, the optimization objective function of dead time compensation is constructed, and the core of the objective function is to minimize harmonic distortion. Under this optimization framework, the optimal dead time compensation amount is accurately solved by iterative calculation method. The iterative calculation process comprehensively considers multiple factors, including the parasitic parameters of the switch tube, the distortion characteristics of the voltage waveform, and the dynamic constraints of the system, so as to ensure the accuracy and effectiveness of the obtained compensation amount. The PWM control signal is corrected based on the optimal dead time compensation amount. The compensation amount is added to the original PWM control signal to eliminate the voltage distortion caused by the dead zone effect. In this way, the compensated control signal can more accurately reflect the ideal switching action and improve the dynamic performance of the power converter. After the correction is completed, the compensated PWM control signal is input into the PWM modulator and compared with the triangular carrier to generate the final target PWM control signal.

[0016] The voltage distortion mathematical model is divided into periods to determine the time interval for Fourier analysis. Based on the delineated Fourier analysis interval, the fundamental component of the voltage distortion function is extracted to separate the contribution of the fundamental to the overall system performance and obtain an accurate expression of the fundamental component. The voltage distortion function is subjected to high-order harmonic calculations to obtain specific information about each harmonic component, including the amplitude and phase of each harmonic. The combination of the fundamental component and the high-order harmonic component can establish a complete Fourier series expression and transform the voltage distortion function from the time domain to the frequency domain representation. The frequency domain representation of voltage distortion has a more intuitive form, allowing harmonic characteristics to be accurately described in the frequency domain. Especially in the process of bidirectional power flow control, this frequency domain information helps to identify and eliminate unnecessary high-order harmonic distortion. Based on the obtained frequency domain representation of voltage distortion, the dead time compensation optimization objective function is constructed. The objective function is in the form of ,in is the weight coefficient related to the harmonic order. As the value increases, the weight coefficient gradually increases. This design enables the objective function to suppress the distortion caused by high-order harmonics to a greater extent during the optimization process. Indicates The square of the subharmonic amplitude is a key parameter for measuring the intensity of harmonic distortion. Through the construction of the objective function, the direction of compensation optimization is clearly defined, that is, minimizing harmonic distortion by minimizing the value of the objective function. In order to optimize the objective function, the gradient calculation is performed to obtain the gradient information of the objective function. The gradient calculation reveals the change trend of the objective function at the current point and provides guidance for subsequent iterations. The gradient of the objective function is substituted into the iteration formula for updating the compensation amount to generate an iteration sequence of compensation time. The generation of the iteration sequence is a dynamic optimization process, the core of which is to gradually adjust the dead time compensation amount so that the objective function value gradually approaches the optimal value. In each iteration, the current compensation value is updated using the compensation amount and gradient information obtained in the previous calculation to ensure that the optimization process converges to the global optimal solution. As the iteration continues, the convergence judgment of the iteration sequence of compensation time is performed to confirm whether the optimization goal has been achieved. When the change amplitude of the iteration sequence is less than the set threshold, it is determined that the iteration process has converged and an accurate dead time compensation amount is obtained. This compensation amount can effectively reduce voltage distortion and significantly reduce the interference of high-order harmonics on system operation by correcting the original PWM control signal.

[0017] Step S3, inputting the target PWM control signal and the current system state into the predictive controller for discrete mathematical modeling, calculating and obtaining the optimal PWM control sequence, and taking the first control quantity of the optimal PWM control sequence as the current control output; Specifically, the target PWM control signal is divided into sampling periods, and the continuous signal is converted into a discrete sampling sequence by a discretization method. Based on the discretized sampling sequence and the current system state, the charging pile system is modeled in state space, and the state equation and output equation that can accurately describe the dynamic behavior of the system are constructed. By solving these equations, a discretized state space model is obtained. The discrete state space model describes the dynamic characteristics of the system in matrix form, including the relationship between the system state variables, input signals, and output signals. According to the discrete state space model, the prediction time domain N and the control time domain M are set to determine the prediction and optimization range of the system. The prediction time domain defines the prediction span of the future state of the system, while the control time domain specifies the time range that the controller can optimize. Based on these settings, the state of the charging pile system in the future A sampling periods is recursively predicted to generate a state prediction sequence. The state prediction sequence is obtained by iterative calculation and can accurately reflect the dynamic changes of the system under different sampling periods. Reference trajectory planning is performed on the state prediction sequence. Target values ​​are set for key indicators of the system (such as voltage, current, and power), and the control performance is evaluated by calculating the deviation between the predicted values ​​and these target values. A performance index function is provided to quantify this deviation. Its form comprehensively considers the weights of multiple objectives to ensure that the optimization result can balance the stability and accuracy of voltage, current and power. After substituting the constructed performance index function into the rolling optimization solver, the control strategy is optimized online. The upper and lower limits of voltage and current are set according to the physical characteristics and operating constraints of the system to ensure that the optimization results meet the actual operating conditions. In the rolling optimization, the optimal PWM control sequence in the control time domain M is obtained through recursive iterative calculation. The advantage of rolling optimization is that only a local range is optimized each time, and the optimization direction is adjusted in real time according to the latest system state to achieve dynamic tracking and optimization of nonlinear systems. The first control quantity of the optimal PWM control sequence is dead-zone compensated and PWM modulated to correct the non-ideal characteristics in the control signal and ensure that the signal can adapt to the actual needs of the power converter. The corrected control signal is used to drive the system and realize the control of the current sampling period to obtain the current control output. The system state is updated in one step based on the current control output. The result of the prediction update is used as the initial state of the next control cycle to form a state update value. After the state update value is input into the predictive controller, the entire optimization calculation process will be repeated. Through this rolling time domain calculation method, the control strategy is updated in real time within each sampling period, and the PWM control signal is continuously adjusted to adapt to the dynamic changes of the system to achieve the optimal control output.

[0018] In order to make the performance index function adapt to the solution requirements of the quadratic programming problem, it is transformed into a standard quadratic form. and vector , the optimization problem is formalized as a standard quadratic programming problem, where is the coefficient matrix, represents the transpose of a matrix, is the prediction matrix, is the state weight matrix, To control the weighting matrix, is the optimization vector, is the state prediction matrix, To optimize the variables, is the current sampling time, is the reference trajectory vector. According to the form of the quadratic programming problem, the constraint matrix is ​​set to ensure that the optimization results meet the physical limitations and operating requirements of the system. By constructing the inequality constraint and equality constraints ,in and Leq are the inequality and equality constraint matrices respectively, and beq are the corresponding constraint vectors, which completely define the constraint range of the optimization problem. The constraint conditions effectively limit the range of changes in the control quantity and state variables, avoiding the generation of control strategies that exceed the system capabilities, thereby ensuring the feasibility and physical rationality of the optimization results. Positive definiteness analysis is performed to verify the solvability of the optimization problem and determine the solution conditions. The results of positive definiteness analysis can be used to construct the feasible domain of the optimization problem. This process embeds the boundaries of the feasible domain into the problem description by defining the upper and lower bounds of the control quantity and other physical constraints to form the constraints of the control quantity. The control quantity constraints are substituted into the state recursion equation for forward calculation to generate state quantity constraints. The introduction of state quantity constraints makes the changes in the system state always subject to the constraints of the dynamic model, ensuring that the solution of the optimization problem conforms to the dynamic behavior characteristics of the system. The optimization problem is initialized based on the state quantity constraints. By selecting the initial iteration point and setting the convergence threshold, the necessary initial conditions are provided for subsequent iterative solutions. The selection of initial conditions directly affects the convergence speed of the solver and the accuracy of the final result. The complexity of the optimization problem and the physical constraints should be considered comprehensively during initialization to ensure the stability and efficiency of the iterative process. Based on the initialization conditions, the optimization problem is input into the interior point method solver for iterative calculation. In the interior point method, the constraint conditions are processed by the barrier function method. By converting the constraint conditions into equivalent objective function terms, the complexity of directly solving the constrained optimization problem is avoided. The iterative calculation process updates the optimization variables so that the objective function gradually approaches the optimal solution while strictly satisfying the constraints. In this process, the control sequence within M control cycles is gradually generated through recursive calculation. The optimality of the control sequence is verified, and the optimality of the optimization result is evaluated by calculating the satisfaction degree of the KKT condition (Karush-Kuhn-Tucker condition). The KKT condition is a necessary condition for the quadratic programming problem, and its verification result directly reflects whether the optimization solution has reached the global optimal state. Through verification, it is ensured that the final output control sequence has high accuracy and reliability. After the above steps, the optimal PWM control sequence is generated.

[0019] Step S4: judge the working state of the AC / DC charging pile according to the current control output. When it is detected that the power flow direction needs to be changed, control the power output of the current working mode to gradually drop to zero. After the DC bus voltage of the power converter stabilizes at the set value, switch to the target working mode to obtain a new power output control amount.

[0020] Specifically, the power flow direction state in the current control output is judged. This judgment depends on the calculation formula of the transmission power and the reception power, where the transmission power and received power By measuring the voltage at the sending end and current And the voltage at the receiving end and current Get. When When the power flow direction is positive, the system determines that the power flow direction is positive, otherwise it is reverse. The judgment result of the power flow direction directly determines whether the mode switching needs to be performed. After it is clear that the power flow direction needs to be changed, the power reduction control stage is entered. The power of the current working mode is reduced according to the power flow direction judgment result to generate a power reduction process curve. The shape of the power reduction process curve is determined by the system dynamic performance and the target switching time. Its purpose is to avoid instability or voltage fluctuation caused by power mutation during the switching process by gradually reducing the power output. In order to achieve smooth power reduction control, the power reduction step size and the time interval of each reduction are set based on the power reduction process curve to generate a segmented power reduction control sequence. The design of the segmented power reduction control sequence decomposes the continuous power reduction process into multiple small step adjustment processes through discretization processing, thereby improving the control accuracy and response speed. The segmented power reduction control sequence is modulated by PWM duty cycle and converted into an actual PWM control quantity sequence. The PWM modulation process calculates the corresponding duty cycle according to the control target of each level in the segmented power sequence, and inputs the obtained PWM control quantity sequence into the power converter, so that the converter can perform segmented power reduction operation. In this process, in order to ensure the stability of the system, the fluctuation of the DC bus voltage is monitored in real time, and the voltage stability criterion is calculated. The voltage stability criterion is used to determine whether the bus voltage has returned to the set stable value. When the voltage fluctuation is less than the preset threshold, the system is considered to be in a stable state, and the mode switching operation is triggered at this time. The moment of mode switching is determined by the voltage stability criterion, and a switching instruction is issued to the control system by generating a mode switching trigger signal. Based on the mode switching trigger signal, the control parameter matrix is ​​automatically updated to adapt to the control requirements of the target working mode. After the control parameters are updated, the system enters the new target working mode and performs power output control on the control parameters of the target mode. Through this process, the power output in the target working mode is achieved, and the power output control amount is generated according to the new mode requirements to ensure that the system maintains stable operation in the new working mode.

[0021] In the embodiment of the present invention, by calculating the trapezoidal voltage edge and dead time compensation of the power converter switching process, low-order harmonics are effectively suppressed and the power quality of the system is improved. A discrete mathematical modeling method based on predictive control is adopted, combined with a rolling optimization algorithm, so that the system has a strong dynamic response capability and shortens the power regulation time. A complete power flow switching control strategy is designed. Through segmented power reduction and voltage stability criteria, the stability of the charging and discharging mode switching process is ensured, and the DC bus voltage fluctuation is controlled within ±2%. An iterative prediction calculation method is introduced to dynamically update the dead time compensation amount, so that the compensation effect remains stable within the entire working range, thereby improving the system efficiency. Through state space modeling and performance index optimization, the robustness of the system is enhanced, so that it can adapt to the operating requirements under different working conditions and reduce the system failure rate. The online iterative optimization algorithm is adopted to reduce the dependence on current sampling, reduce the impact of communication delay on system performance, and improve the real-time and reliability of control.

[0022] In a specific embodiment, the process of executing step S1 may specifically include the following steps: The voltage sensor sampling points are respectively set at the input and output ends of the AC and DC charging piles, and the voltage signals are converted into digital quantities to obtain the input voltage value and the output voltage value; The power frequency component is extracted and the reactive power is calculated for the input voltage and the output voltage to obtain the real-time power data of the AC and DC charging piles; Perform parasitic capacitance test on each switch tube of the power converter, measure the voltage rise time and fall time at both ends of the switch tube at different switching frequencies, and obtain the parasitic capacitance parameters of the switch tube; The dead time is measured online based on the voltage waveform at both ends of the switch tube, and the time interval between the rising edge and the falling edge of the voltage waveform is calculated to obtain the dead time parameter; Perform timing analysis on the control signal and the conduction state of the switch tube of the power converter, and calculate the time difference from the effective edge of the control signal to the actual conduction of the switch tube to obtain the switch delay time parameter; The voltage and current sensors set at the grid connection point are used to sample the three-phase voltage and current of the grid and perform discrete Fourier transform calculations to obtain the effective value and frequency value of the grid voltage; The input voltage value, output voltage value, real-time power data, switch tube parasitic capacitance parameters, dead time parameters, switch delay time parameters, grid voltage effective value and frequency value are combined into a data matrix to obtain the charging pile system operation parameter set.

[0023] Specifically, voltage sensor sampling points are set at the input and output ends of the AC / DC charging pile, and the voltage signals at the input and output ends are sampled to capture the instantaneous changes of the input and output voltages. The sampled analog signal is converted into a digital quantity through an analog-to-digital converter to obtain the input voltage value. and output voltage Assume the sampling frequency is , the voltage signal is , then the sampling point The corresponding discrete voltage value is ,in is the sampling period. After obtaining the input and output voltage values, the frequency and amplitude characteristics are analyzed by extracting the power frequency components of these voltage values. Assume that the instantaneous value of the input voltage is ,in is the amplitude of the input voltage is the angular frequency, is the phase angle. Fast Fourier transform is used to extract the power frequency component and calculate its amplitude and phase. At the same time, based on the voltage and current signals, real-time power data is calculated, including active power and reactive power. The calculation formula for active power is ,in and are the effective values ​​of voltage and current, respectively, is the phase difference; the formula for reactive power is The real-time power data of the charging pile system is obtained by calculation. The parasitic capacitance test of the switch tube of the power converter is performed. This process involves measuring the rise time and fall time of the voltage across the switch tube at different switching frequencies to obtain the parasitic capacitance parameters of the switch tube. Assume that the equivalent capacitance of the switch tube is , the voltage change rate is d d , according to the capacitor current formula d d , by measuring and d d calculate This parasitic capacitance has an important influence on the dynamic performance of the switch tube and can determine the on and off characteristics of the switch. After the parasitic capacitance test is completed, the voltage waveform of the switch tube is analyzed and the dead time is measured online. , optimize the switching performance. Dead time refers to the time interval when the upper and lower bridge arm switching devices are simultaneously closed during the switching process to avoid shoot-through. By analyzing the rising and falling edges of the voltage of the switch tube, the dead time parameter is calculated. The specific formula is: ,in and The rise time and fall time are respectively. The timing analysis of the control signal and the switch conduction state of the power converter is performed. There is a time difference between the effective edge of the control signal and the actual conduction of the switch. This time difference is defined as the switch delay time By measuring the moment when the control signal changes And the switch tube voltage change time ,calculate This parameter has an important impact on the rapid response capability of the system. At the same time, by setting voltage and current sensors at the grid connection point, the three-phase voltage and current of the grid are sampled. The sampled signal is analyzed in the frequency domain using discrete Fourier transform to obtain the effective value and frequency value of the grid voltage. The formula for the effective value of the three-phase voltage is: ,in is the period; the frequency value is obtained by zero crossing detection or phase difference calculation. , output voltage value , real-time power data , Switching tube parasitic capacitance parameters , Dead time parameters , Switching delay time parameters And the effective value of the grid voltage and frequency value Forming a comprehensive data matrix ,Right now: ; This data matrix comprehensively reflects the operating status of AC and DC charging piles.

[0024] In a specific embodiment, the process of executing step S2 may specifically include the following steps: The switching voltage of the power converter is modeled according to the parasitic capacitance parameters of the switch tube in the system operation parameter set to obtain the voltage-time function of the switching process, and the voltage-time function of the switching process is analyzed by trapezoidal edge characteristics to obtain the voltage change rate curve; The switch conduction process is segmented based on the voltage change rate curve, t1 is set as the dead time parameter, t2 is the switch delay time parameter, and the segmented voltage function v1(t) is the conduction voltage before the switch, v2(t) is the voltage during the dead time, and v3(t) is the conduction voltage after the switch; Substitute the segmented voltage function into the voltage distortion calculation formula Vd(t)=v1(t)+v2(t)+v3(t), where Vd(t) is the total voltage distortion and t is the time variable, to obtain the voltage distortion mathematical model; The voltage distortion mathematical model is expanded by Fourier series to obtain harmonic components, and the dead time compensation optimization objective function is constructed according to the harmonic components. The dead time compensation amount is obtained through iterative calculation. The PWM control signal is corrected based on the dead time compensation amount to obtain a compensated control signal, and the compensated control signal is input into the PWM modulator and compared with the triangular carrier to obtain a target PWM control signal.

[0025] Specifically, the switching voltage of the power converter is modeled according to the parasitic capacitance parameters of the switch tube in the system operation parameter set. The parasitic capacitance parameters directly affect the dynamic behavior of the switch tube. Assume that the parasitic capacitance of the switch tube is , the switching current is , the voltage across the switch tube During the switching process, the capacitor current formula is followed By measuring and fitting the voltage waveform, the voltage-time function of the switching process is constructed. , whose specific form depends on the different states in the switching process, such as the rising stage, stable stage and falling stage of voltage. After the modeling is completed, the voltage-time function is subjected to trapezoidal edge characteristic analysis to analyze the rate of change of the voltage rising and falling edges. The voltage change rate curve is composed of the derivative It can reflect the speed and nonlinear characteristics of voltage changes. For example, when the parasitic capacitance is large, the rate of change of the rising edge is low, while the falling edge shows a steep change. By analyzing the voltage change rate curve, the key time points in the switching process, such as the dead time, can be identified. and switch delay time The switching process is segmented based on the voltage change rate curve, and the entire process is divided into three stages: the pre-switching conduction stage, the dead zone stage, and the post-switching conduction stage. is the dead time, is the switching delay time, and the segment voltage function is defined as: : Describes the voltage change in the pre-conduction stage of the switch. Its characteristics are usually stable or slowly changing, which is approximately ,in is the on-state voltage, is the time constant; : Describes the voltage change during the dead time, usually showing a linear change or a short transition, expressed as ,in and is the linear fitting parameter; : Describes the voltage change during the conduction phase after the switch is turned on, which is approximately an exponential decay function ,in is the voltage after switching. By substituting the segment voltage function into the total voltage distortion formula , a mathematical model of voltage distortion is constructed. This model reflects the comprehensive characteristics of voltage in the entire switching cycle, and its distortion degree directly affects the harmonic components and the operating efficiency of the system. In order to analyze the spectral characteristics of voltage distortion, the mathematical model is expanded by Fourier series. The voltage distortion function It is represented as a superposition of a series of harmonic components: ; in, is the DC component, and Respectively Cosine and sine coefficients of subharmonics, is the fundamental frequency angular velocity, is the harmonic order. The coefficient is calculated as: ; in is the period. According to the harmonic components obtained by Fourier series expansion, the dead time compensation optimization objective function is constructed. The objective function takes the square sum of the harmonic components as the optimization target, for example: ; in is the weight coefficient related to the harmonic order. By minimizing the objective function , reducing the amplitude of high-order harmonics, thereby reducing voltage distortion. The optimization process is achieved through iterative calculation to adjust the dead time compensation amount and , until the objective function Converges to the minimum value. The final compensation amount is used to correct the PWM control signal. By adding the compensation amount to the original PWM signal, the corrected control signal can offset the distortion caused by dead time and switching delay. The corrected control signal is input to the PWM modulator and compared with the triangular carrier signal to generate the target PWM control signal.

[0026] In a specific embodiment, the execution step performs Fourier series expansion on the voltage distortion mathematical model to obtain harmonic components, and constructs a dead time compensation optimization objective function according to the harmonic components. The process of obtaining the dead time compensation amount by iterative calculation can specifically include the following steps: The voltage distortion mathematical model is divided into periods to obtain a Fourier analysis interval, and the fundamental component of the voltage distortion function is extracted according to the Fourier analysis interval to obtain the fundamental component; The voltage distortion function is subjected to high-order harmonic calculation to obtain each harmonic component, and a Fourier series expression is established based on the fundamental component and each harmonic component to obtain the frequency domain representation of the voltage distortion; Based on the frequency domain representation of voltage distortion, the dead time compensation optimization objective function J=Σkn×(an 2 +bn 2 ), where kn is the nth harmonic weight coefficient, which increases with the increase of the harmonic number n. 2 +bn 2 It represents the square of the amplitude of the nth harmonic; The gradient of the dead time compensation optimization objective function is calculated to obtain the objective function gradient, and the objective function gradient is substituted into the iterative formula to update the compensation amount to obtain the iterative sequence of compensation time; The convergence of the iterative sequence of compensation time is judged to obtain the dead time compensation amount.

[0027] Specifically, the voltage distortion function is divided into periods to determine the interval of Fourier analysis. In cycle The voltage distortion of the system is described in is the basic cycle, is the fundamental frequency. The Fourier analysis interval is selected as , this interval can completely cover a cycle of voltage waveform, which is conducive to extracting fundamental components and higher harmonic components. The periodic characteristics of the voltage distortion function are decomposed into the superposition of the fundamental wave and the harmonic wave, and the frequency domain representation of the voltage distortion function is expanded. The extraction of the fundamental wave component is based on the basic principle of Fourier transform. The fundamental component corresponds to the frequency The sine or cosine component of is calculated as: ; in and are the cosine and sine coefficients of the fundamental wave respectively. The amplitude of the fundamental wave is expressed as: ; This indicates that the fundamental amplitude It is obtained by taking the square root of the sum of the squares of the sine and cosine components of the fundamental wave. The calculation of higher harmonic components is similar to the extraction of the fundamental wave, but the frequency is an integer multiple of the fundamental wave frequency, that is, ,in is the harmonic order. The corresponding harmonic coefficient and The calculation formula is: ; The amplitude of higher harmonics is: ; Through The amplitude and frequency information of all higher harmonics are obtained by successive calculations. After extracting the fundamental component and higher harmonic components, the voltage distortion function is expressed in the form of Fourier series: ; in is the DC component. The DC component of the symmetrical waveform is zero, so it is usually ignored. This Fourier series expression reflects the characteristics of voltage distortion in the frequency domain. Based on the Fourier series expression, the dead time compensation optimization objective function is constructed. The objective function is in the form of: ; in is the harmonic weight coefficient, which varies with the harmonic order increases with the increase of to reflect the greater weight of the impact of high-order harmonics on the system. It is The square of the subharmonic amplitude represents the intensity of harmonic energy. The optimization goal is to minimize the harmonic energy and thus reduce voltage distortion. In order to optimize the objective function , calculate the gradient and get the gradient information of the objective function. The gradient is the directional derivative of the function change, and its form is: ; in is the dead time compensation, and the result of the gradient calculation is used to update The update formula is: ; in It is The compensation amount for the iteration, is the learning rate, which is used to control the step size of the update. After each iteration, the convergence of the compensation time is judged. If the absolute value of the gradient or the change in the objective function value is less than the set threshold, the iteration is considered to have converged and the optimal dead time compensation amount is obtained. This compensation is used to modify the PWM control signal to reduce the voltage distortion caused by the dead time. For example, assuming the voltage distortion function , where the fundamental frequency Through Fourier analysis, the fundamental amplitude is obtained , the second harmonic amplitude , the third harmonic amplitude Objective function for: ; Assuming weight coefficient , , ,but Through iterative optimization ,make and The magnitude of is significantly reduced, for example, after optimization , ,final This shows that the optimization process effectively reduced harmonic distortion and improved system performance.

[0028] In a specific embodiment, the process of executing step S3 may specifically include the following steps: Divide the sampling period of the target PWM control signal to obtain a discrete sampling sequence; The state space modeling of the charging pile system is carried out based on the discretized sampling sequence and the current system state, and the discrete state space model is obtained by solving the state equation and the output equation; According to the discrete state space model, the prediction time domain N and the control time domain M are set, and the state of the charging pile system in the future A sampling periods is recursively predicted to obtain the state prediction sequence; Perform reference trajectory planning on the state prediction sequence, set tracking target values ​​for voltage, current and power, and obtain the performance indicator function by calculating the deviation between the predicted value and the target value; Substitute the performance index function into the rolling optimization solver, set the voltage and current constraints, and obtain the optimal PWM control sequence within M control cycles through online iterative optimization; The first control quantity of the optimal PWM control sequence is subjected to dead-zone compensation and PWM modulation to obtain the current control output, and the system state is updated in one step based on the current control output. The predicted state is used as the initial state of the next control cycle to obtain the state update value, which is input into the predictive controller. The optimization calculation process is repeated to obtain the optimal control output through rolling time domain calculation.

[0029] Specifically, the target PWM control signal is divided into sampling periods, and a discrete sampling sequence is generated by discretizing the continuous signal. Assume that the sampling period is , the target PWM control signal is , after discretization, the PWM signal is expressed as ,in is the index of the sampling moment. It converts the continuous dynamic system into a mathematical form that can be processed in discrete time. Based on the discretized sampling sequence and the current system state , a discrete state space model of the charging pile system is established. The state space model is described by the state equation and the output equation, which are: ; ; in, is the state transfer matrix, which describes the dynamic characteristics of the system state; is the input matrix, describing the impact of the input on the system state is the output matrix, defining the relationship between states and outputs; is the direct transfer matrix, describing the direct effect of input on output. State variables is the internal state of the system, including variables such as DC bus voltage and current, and input variables is the discrete PWM control signal, the output variable It is the observable quantity of the system, such as output power or load voltage. After constructing the discrete state space model, the prediction time domain is set according to the control objective. and control time domain , and use the model to predict future The prediction process is based on the recursive expansion of the state equation. Assuming that the current state is ,future The predicted state at this moment is: ; in represents the predicted time index, Represents the state transition matrix The recursive formula describes how the system state is affected by the current state and input sequence in the future time domain. Provides dynamic information of the system in the future time domain for reference trajectory planning. In trajectory planning, for voltage , Current and power Set the tracking target value by variables , , , and define the performance indicator function by calculating the deviation between the predicted value and the target value. For example, the performance indicator function takes the quadratic form: ; in represents the cumulative sum of squared prediction deviations, which is the objective function of the optimization problem. Substitute into the rolling optimization solver and combine the voltage and current constraints, such as and , generated during the online iteration process The optimal PWM control sequence within a control cycle. The optimization process uses linear or quadratic programming algorithms to adjust the input sequence Minimize the objective function , and update the predicted state in each iteration to ensure that the constraints are met. After the optimization solution, select the first control quantity of the optimal PWM control sequence , and compensate for its dead time. Assuming the dead time is , the control signal after compensation is: ; in Based on the dead time The corrected PWM control signal is input into the PWM modulator, compared with the triangular carrier signal, and the control output at the current moment is generated. , for system status Perform a one-step prediction update and use the state equation to calculate the state at the next moment: ; The updated status The predictive controller is used as the initial state input for the next control cycle, and the above optimization calculation process is repeated. The control strategy is continuously adjusted through calculations in the rolling time domain to achieve optimal control under dynamic operating conditions and obtain the optimal control output.

[0030] In a specific embodiment, the execution step of substituting the performance index function into the rolling optimization solver, setting the voltage and current constraints, and obtaining the optimal PWM control sequence within M control cycles through online iterative optimization may specifically include the following steps: The performance index function is transformed into a standard quadratic form by constructing a matrix H=2(G T QG+R) and vector f=2G T (Fx(k)-W), where H is the coefficient matrix, T is the transpose of the matrix, G is the prediction matrix, Q is the state weight matrix, R is the control weight matrix, f is the vector, F is the state prediction matrix, x is the optimization variable, k is the sampling time, and W is the reference trajectory vector. The standard quadratic programming problem is obtained; According to the quadratic programming problem, the constraint matrix is ​​set, and the optimization problem is obtained by constructing the inequality constraint Lx≤b and the equality constraint Leqx=beq, where L and Leq are constraint matrices, b and beq are constraint vectors; Based on the coefficient matrix H of the optimization problem, the positive definiteness analysis is performed to obtain the solution conditions of the optimization problem, and the feasible domain of the solution conditions is constructed to obtain the control quantity constraints; Substitute the control quantity constraint into the state recursion equation for forward calculation to obtain the state quantity constraint, and initialize the solution of the optimization problem based on the state quantity constraint. By selecting the initial iteration point and setting the convergence threshold, the initial condition of the iterative solution is obtained; The initial conditions are input into the interior point method solver for iterative calculation. The constraints are processed by the barrier function method to obtain the control sequence within M control cycles. The optimality of the control sequence is verified and the optimal PWM control sequence is obtained by calculating the degree of satisfaction of the KKT conditions.

[0031] Specifically, the optimization problem of the system is transformed into a standard form to facilitate numerical solution. Assuming that the performance index function of the system is the sum of square deviations of the tracking target value plus the energy term of the control input, its expression is: ; in, is the predicted state vector, is the reference trajectory vector, is the control input vector, is the state weighting matrix, which is used to measure the cost of state deviation. is the control weighting matrix, which is used to suppress the drastic changes of the control input. is the length of the prediction time domain. In order to construct the quadratic programming problem, the performance indicator function is expressed in matrix form. By defining the prediction matrix and the state prediction matrix , the future The state sequence of the step is expressed as a linear combination of the current state and the future control input: ; in, is the stacked vector of future state sequences, is the stacked vector of future control inputs. The matrix and They represent the initial contribution of state transition and the influence of control input respectively, and the specific form is determined by the state space model of the system. After substituting the above state representation into the performance index function, it is rewritten as: ; in, is the stacked vector of the reference trajectory. After incorporating the relevant terms, the performance indicator function is transformed into a standard quadratic form: ; Among them, the coefficient matrix and vector The expression is: ; At this time, the optimization variable Subject to the constraints, we need to further define inequality constraints and equality constraints. Assume that the control input There are upper and lower bounds ,state There are upper and lower bounds , expressed in matrix form as: ; in, and is the constraint matrix, and is the corresponding constraint vector. After constructing the optimization problem, the coefficient matrix A positive definiteness analysis is performed to ensure that the optimization problem is solvable. The positive definiteness analysis is performed by checking the matrix If all eigenvalues ​​are greater than zero, then is a positive definite matrix, the optimization problem has a unique solution. Not correct, need to readjust and The weight parameters are used to enhance the controllability of the system. After determining the positive definiteness of the optimization problem, a feasible domain is constructed to limit the range of control input and state changes. By substituting the control quantity constraint into the state recursion equation, the state quantity constraint is obtained, thereby constructing a stricter feasible domain. In order to improve the efficiency of the optimization calculation, the optimization problem is initialized and the initial iteration point is selected. And set the convergence threshold. The selection of the initial iteration point is based on the predicted value of the current control input, and the convergence threshold is used to determine the end condition of the optimization process. The initialized optimization problem is input into the interior point solver, and the optimal solution is gradually approached through iterative calculation. In the interior point method, the barrier function is introduced The constraints are transformed into part of the objective function to avoid dealing with the constraints directly. The objective function of the optimization problem is adjusted in each iteration as follows: ; in, is a barrier parameter that controls the strength of constraint handling. In each iteration, update And optimize , until the objective function converges. The interior point solver outputs The optimality of the control sequence within a control cycle is verified, and the quality of the optimization solution is judged by calculating whether the KKT condition (Karush-Kuhn-Tucker condition) is met. If the KKT condition is met, it means that the control sequence is the global optimal solution. The first control quantity of the optimal PWM control sequence is used for the current control output, and the subsequent control quantities are reserved for prediction updates at future moments.

[0032] In a specific embodiment, the process of executing step S4 may specifically include the following steps: The power flow direction state in the current control output is judged, and the transmission power Ps=Vs×Is and the receiving power Pr=Vr×Ir are calculated, where Vs and Is are the voltage and current of the transmitting end, and Vr and Ir are the voltage and current of the receiving end, respectively, to obtain the power flow direction judgment result; According to the result of judging the power flow direction, the power of the current working mode is reduced to control the power, and a power reduction process curve is obtained; Based on the power reduction process curve, the power reduction step size and the interval time of each reduction are set to obtain a segmented power reduction control sequence; The PWM duty cycle is modulated on the segmented power reduction control sequence to obtain a PWM control quantity sequence, and the PWM control quantity sequence is input into the power converter to monitor the fluctuation of the DC bus voltage and obtain the voltage stability criterion; Determine the working mode switching time according to the voltage stability criterion and obtain a mode switching trigger signal; The charging pile control strategy is switched based on the mode switching trigger signal, and the control parameters of the target working mode are obtained by updating the control parameter matrix. The power output is controlled on the control parameters of the target working mode to obtain a new power output control amount.

[0033] Specifically, the power flow direction state in the current control output is accurately judged. By measuring the voltage and current at the transmitting and receiving ends, the transmission power is calculated respectively. and received power ,in and represent the voltage and current at the sending end, respectively, and and Represents the voltage and current at the receiving end. These parameters are obtained through real-time sampling, and the sampling period is , so that the power at discrete moments is calculated as and By comparison and The size of determines the direction of power flow: When , the power flow direction is from the transmitter to the receiver; otherwise, it is from the receiver to the transmitter. After determining that the power flow direction needs to be changed, in order to ensure the stability of the system, the power of the current working mode is reduced. This process is achieved by constructing a power reduction process curve. The power curve is in the form of linear, exponential or other smooth functions. The specific form depends on the dynamic characteristics and response requirements of the system. For example, for linear reduction, the power curve is expressed as: ; in is the initial power, is the rate of power decline. For exponential decline, the curve is: ; in is the exponential attenuation coefficient. By selecting a suitable curve form, it is ensured that the power drops to zero smoothly within the specified time to avoid sudden changes that may impact the system. Based on the power reduction process curve, the power reduction step size and the interval time of each reduction are set to generate a segmented power reduction control sequence. Assume that the step size of each power reduction is , the interval time is , then the segmented power control sequence is expressed as ; in is the total number of steps in the segment, is the total time for the power to completely drop to zero. Segmented processing can provide sufficient control flexibility while ensuring dynamic stability. The generated segmented power reduction control sequence is converted into an actual control signal through PWM duty cycle modulation. The principle of duty cycle modulation is to adjust the duty cycle of the PWM signal according to the target power value. Assuming the maximum duty cycle is , then the current power The corresponding duty cycle is: ; in is the maximum power output of the system. The modulated PWM control quantity sequence is directly input into the power converter to adjust the power output. While performing the power reduction operation, the fluctuation of the DC bus voltage is monitored in real time to determine the stability of the system. The calculation formula of the bus voltage fluctuation is: ; in is the current bus voltage, is the reference value of bus voltage. Less than the preset threshold When , the system is considered to have reached a stable state and the mode switching signal is triggered. After the mode switching signal is triggered, the system needs to update the control strategy by reloading the control parameter matrix to adapt to the target working mode. Assume that the control parameter matrix of the current mode is , the control parameter matrix of the target mode is , then the switching process needs to complete the matrix replacement: ; These parameters include specific values ​​such as duty cycle range and frequency adjustment. In the new mode, the power output is controlled for the target working mode by executing the updated control parameters to obtain a new power output. For example, assuming that the system enters the reverse power flow mode after switching, the target power is , the corresponding PWM duty cycle is recalculated as .

[0034] In this embodiment, the above-mentioned AC / DC charging pile bidirectional power flow control method also includes: real-time monitoring of the charging pile operation state according to the system stable operation control parameter set, when a power device or sensor fault is detected, selecting a corresponding controller reconstruction strategy based on the fault diagnosis result, and adaptively adjusting the PWM modulation scheme to obtain fault-tolerant control optimization parameters, including: real-time acquisition of the switch tube voltage and current characteristic parameters of the power converter, by constructing a fault feature vector F(t)={v(t), i(t), dv / dt, di / dt}, where v(t) is the switch tube voltage, i(t) is the switch tube current, dv / dt is the voltage change rate, di / dt is the current change rate, t is the sampling time, and the characteristic vector is analyzed to obtain the fault feature matrix; a fault diagnosis decision tree is constructed according to the fault feature matrix, and the fault type is judged by calculating the fault probability P(F)=P(F|H)×P(H) / P(F), where P(F|H) is the fault condition probability, which represents the characteristic probability when the fault occurs, P(H) is the prior probability, which represents the historical occurrence probability of the fault type, and P(F) is the characteristic probability, and the fault diagnosis result is obtained; the fault diagnosis result is input into the fault-tolerant decision device, and the fault level is calculated based on the fault impact evaluation function I(f)=Σwi×si , where wi is the weight coefficient of each fault indicator, si is the corresponding fault severity indicator, f is the fault type identifier, i is the fault indicator serial number, and the fault level judgment result is obtained; the controller reconstruction scheme is selected according to the fault level judgment result, and the controller parameters are updated online through the reconstruction matrix R=[r1, r2, ..., rn], where ri is the i-th reconstruction parameter, n is the total number of reconstruction parameters, and each ri corresponds to the adjustment amount of a specific controller parameter to obtain the reconstructed controller parameters; the stability analysis of the reconstructed controller parameters is performed by calculating the root distribution of the characteristic equation λI-A=0, where λ is the eigenvalue, A is the system state matrix, I is the unit matrix, and the system is determined to be stable when the real parts of all eigenvalues ​​of the system are less than zero, thus obtaining the system stability criterion; the PWM modulation scheme is adjusted based on the system stability criterion, and the optimized PWM modulation scheme is obtained by calculating the new switch timing t'(k)=t(k)+Δt(k), where t'(k) is the adjusted switch timing, t(k) is the original switch timing at the current sampling period k, Δt(k) is the timing adjustment amount calculated based on the stability criterion, and k is the sampling number; the optimized PWM modulation scheme is compared with the original control strategy, and the performance evaluation function J=Σ(αxi 2 +βui 2) calculates the control performance, where α is the weight coefficient of the state variable, β is the weight coefficient of the control quantity, xi is the i-th state variable of the system, ui is the i-th control quantity, and obtains the performance evaluation result; optimizes the fault-tolerant control parameters according to the performance evaluation result, and updates the parameters through iteration , where θ(k+1) is the control parameter vector for the next moment, θ(k) is the control parameter vector for the current moment, and η is the iterative learning rate used to control the parameter update step size. is the gradient of the performance evaluation function to the control parameters, k is the number of iterations, and the fault-tolerant control optimization parameters are obtained.

[0035] The above describes the bidirectional power flow control method of the AC / DC charging pile in the embodiment of the present invention. The following describes the bidirectional power flow control device of the AC / DC charging pile in the embodiment of the present invention. Figure 2 , an embodiment of the AC / DC charging pile bidirectional power flow control device in the embodiment of the present invention includes: The acquisition module is used to detect and collect parameters of AC and DC charging piles, power converters and grid connection points to obtain the charging pile system operation parameter set; A calculation module, used for performing trapezoidal voltage edge calculation on the switching process of the power converter according to the system operation parameter set, obtaining a dead time compensation amount, and superimposing the dead time compensation amount on the PWM control signal of the power converter to obtain a target PWM control signal; The switching module is used to input the target PWM control signal and the current system state into the predictive controller for discrete mathematical modeling, calculate the optimal PWM control sequence, and use the first control quantity of the optimal PWM control sequence as the current control output; The acquisition module is used to judge the working state of the AC / DC charging pile according to the current control output. When it is detected that the power flow direction needs to be changed, the power output of the current working mode is controlled to gradually drop to zero. After the DC bus voltage of the power converter stabilizes at the set value, it switches to the target working mode to obtain a new power output control amount.

[0036] Through the cooperation of the above components, the trapezoidal voltage edge calculation and dead time compensation of the power converter switching process effectively suppress low-order harmonics and improve the power quality of the system. The discrete mathematical modeling method based on predictive control is adopted, combined with the rolling optimization algorithm, so that the system has a strong dynamic response capability and shortens the power regulation time. A complete power flow switching control strategy is designed. Through the segmented power reduction and voltage stability criteria, the stability of the charging and discharging mode switching process is ensured, and the DC bus voltage fluctuation is controlled within ±2%. The iterative prediction calculation method is introduced to dynamically update the dead time compensation amount, so that the compensation effect remains stable in the entire working range, and the system efficiency is improved. Through state space modeling and performance index optimization, the robustness of the system is enhanced, so that it can adapt to the operating requirements under different working conditions and reduce the system failure rate. The online iterative optimization algorithm is adopted to reduce the dependence on current sampling, reduce the impact of communication delay on system performance, and improve the real-time and reliability of control.

[0037] Reference Figure 3 In an embodiment of the present invention, a computer device is also provided. The computer device may be a server, and its internal structure may be as follows: Figure 3 As shown. The computer device includes a processor, a memory, a display screen, an input device, a network interface and a database connected through a system bus. Among them, the processor designed by the computer is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the corresponding data in this embodiment. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the above method is implemented.

[0038] Those skilled in the art will understand that Figure 3 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied.

[0039] An embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the above method is implemented. It can be understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0040] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided by the present invention and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double-speed data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM.

[0041] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0042] 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 invention is essentially or the part that contributes to the prior art or the whole or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. 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.

[0043] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. 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 invention.

Claims

1. A bidirectional power flow control method for an AC / DC charging pile, characterized in that: The method comprises: Detect and collect parameters of AC and DC charging piles, power converters and grid connection points to obtain the charging pile system operation parameter set; Performing trapezoidal voltage edge calculation on the switching process of the power converter according to the system operation parameter set to obtain a dead time compensation amount, and superimposing the dead time compensation amount on the PWM control signal of the power converter to obtain a target PWM control signal; Input the target PWM control signal and the current system state into the prediction controller for discrete mathematical modeling, calculate and obtain the optimal PWM control sequence, and use the first control quantity of the optimal PWM control sequence as the current control output; The working state of the AC / DC charging pile is judged according to the current control output. When it is detected that the power flow direction needs to be changed, the power output of the current working mode is controlled to gradually drop to zero. After the DC bus voltage of the power converter stabilizes at the set value, it switches to the target working mode to obtain a new power output control amount.

2. The AC / DC charging pile bidirectional power flow control method according to claim 1, characterized in that: The AC / DC charging pile, power converter and grid connection point are detected and parameter collection is performed to obtain a charging pile system operation parameter set, including: The voltage sensor sampling points are respectively set at the input and output ends of the AC and DC charging piles, and the voltage signals are converted into digital quantities to obtain the input voltage value and the output voltage value; Extracting power frequency components and calculating reactive power are performed on the input terminal voltage value and the output terminal voltage value to obtain real-time power data of the AC / DC charging pile; Performing a parasitic capacitance test on each switch tube of the power converter, measuring the voltage rise time and fall time at both ends of the switch tube at different switching frequencies, and obtaining the parasitic capacitance parameters of the switch tube; The dead time is measured online based on the voltage waveform at both ends of the switch tube, and the time interval between the rising edge and the falling edge of the voltage waveform is calculated to obtain the dead time parameter; Performing timing analysis on the control signal and the conduction state of the switch tube of the power converter, and calculating the time difference from the effective edge of the control signal to the actual conduction of the switch tube, to obtain a switch delay time parameter; The voltage and current sensors set at the grid connection point are used to sample the three-phase voltage and current of the grid and perform discrete Fourier transform calculations to obtain the effective value and frequency value of the grid voltage; The input voltage value, output voltage value, real-time power data, switch tube parasitic capacitance parameters, dead time parameters, switch delay time parameters, grid voltage effective value and frequency value are combined into a data matrix to obtain a charging pile system operation parameter set.

3. The AC / DC charging pile bidirectional power flow control method according to claim 2, characterized in that: The step of performing trapezoidal voltage edge calculation on the switching process of the power converter according to the system operation parameter set to obtain a dead time compensation amount, and superimposing the dead time compensation amount on the PWM control signal of the power converter to obtain a target PWM control signal includes: Modeling the switch voltage of the power converter according to the parasitic capacitance parameters of the switch tube in the system operation parameter set to obtain a voltage-time function of the switching process, and performing a trapezoidal edge characteristic analysis on the voltage-time function of the switching process to obtain a voltage change rate curve; Based on the voltage change rate curve, the switch tube conduction process is segmented, t1 is set as the dead time parameter, t2 is set as the switch delay time parameter, and the segmented voltage function v1(t) is obtained as the conduction voltage before the switch, v2(t) is the voltage during the dead time, and v3(t) is the conduction voltage after the switch; Substitute the segmented voltage function into the voltage distortion calculation formula Vd(t)=v1(t)+v2(t)+v3(t), where Vd(t) is the total voltage distortion and t is the time variable, to obtain a voltage distortion mathematical model; Performing Fourier series expansion on the voltage distortion mathematical model to obtain harmonic components, constructing a dead time compensation optimization objective function based on the harmonic components, and obtaining a dead time compensation amount through iterative calculation; The PWM control signal is corrected based on the dead time compensation amount to obtain a compensated control signal, and the compensated control signal is input into a PWM modulator and compared with a triangular carrier to obtain a target PWM control signal.

4. The AC / DC charging pile bidirectional power flow control method according to claim 3, characterized in that: The voltage distortion mathematical model is expanded by Fourier series to obtain harmonic components, and a dead time compensation optimization objective function is constructed according to the harmonic components, and a dead time compensation amount is obtained by iterative calculation, including: Periodically dividing the voltage distortion mathematical model to obtain a Fourier analysis interval, and extracting a fundamental component of the voltage distortion function according to the Fourier analysis interval to obtain a fundamental component; Performing high-order harmonic calculation on the voltage distortion function to obtain each harmonic component, and establishing a Fourier series expression based on the fundamental component and each harmonic component to obtain a frequency domain representation of the voltage distortion; Based on the frequency domain representation of the voltage distortion, the dead time compensation optimization objective function J = Σkn × (an 2 +bn 2 ), where kn is the nth harmonic weight coefficient, which increases with the increase of the harmonic number n. 2 +bn 2 It represents the square of the amplitude of the nth harmonic; Performing gradient calculation on the dead time compensation optimization objective function to obtain the objective function gradient, and substituting the objective function gradient into an iterative formula to update the compensation amount to obtain an iterative sequence of compensation time; A convergence judgment is performed on the iterative sequence of the compensation time to obtain a dead time compensation amount.

5. The AC / DC charging pile bidirectional power flow control method according to claim 4, characterized in that: The target PWM control signal and the current system state are input into the prediction controller for discrete mathematical modeling, an optimal PWM control sequence is calculated, and the first control quantity of the optimal PWM control sequence is used as the current control output, including: Dividing the target PWM control signal into sampling periods to obtain a discrete sampling sequence; Based on the discrete sampling sequence and the current system state, the charging pile system is modeled in state space, and a discrete state space model is obtained by solving the state equation and the output equation; According to the discrete state space model, a prediction time domain N and a control time domain M are set, and the state of the charging pile system in the future A sampling periods is recursively predicted to obtain a state prediction sequence; Performing reference trajectory planning on the state prediction sequence, setting tracking target values ​​for voltage, current and power, and obtaining a performance indicator function by calculating the deviation between the predicted value and the target value; Substituting the performance index function into the rolling optimization solver, setting the voltage and current constraints, and obtaining the optimal PWM control sequence within M control cycles through online iterative optimization; The first control quantity of the optimal PWM control sequence is subjected to dead-zone compensation and PWM modulation to obtain the current control output, and the system state is predicted and updated in one step based on the current control output. The predicted state is used as the initial state of the next control cycle to obtain a state update value, which is input into the prediction controller, and the optimization calculation process is repeated to obtain the optimal control output through rolling time domain calculation.

6. The AC / DC charging pile bidirectional power flow control method according to claim 5, characterized in that: Substituting the performance index function into the rolling optimization solver, setting the voltage and current constraints, and obtaining the optimal PWM control sequence within M control cycles through online iterative optimization, including: The performance index function is transformed into a standard quadratic form by constructing a matrix H=2(G T QG+R) and vector f=2G T (Fx(k)-W), where H is the coefficient matrix, T is the transpose of the matrix, G is the prediction matrix, Q is the state weight matrix, R is the control weight matrix, f is the vector, F is the state prediction matrix, x is the optimization variable, k is the sampling time, and W is the reference trajectory vector. The standard quadratic programming problem is obtained; According to the quadratic programming problem, a constraint matrix is ​​set, and an optimization problem is obtained by constructing an inequality constraint Lx≤b and an equality constraint Leqx=beq, where L and Leq are constraint matrices, and b and beq are constraint vectors; Performing positive definiteness analysis based on the coefficient matrix H of the optimization problem to obtain solution conditions for the optimization problem, and constructing a feasible domain for the solution conditions to obtain control quantity constraints; Substituting the control quantity constraint into the state recursion equation for forward calculation to obtain the state quantity constraint, and initializing the solution of the optimization problem based on the state quantity constraint, and obtaining the initial condition of the iterative solution by selecting the initial iteration point and setting the convergence threshold; The initial conditions are input into the interior point method solver for iterative calculation, and the constraint conditions are processed by the barrier function method to obtain the control sequence within M control cycles. The optimality of the control sequence is verified, and the optimal PWM control sequence is obtained by calculating the degree of satisfaction of the KKT condition.

7. The AC / DC charging pile bidirectional power flow control method according to claim 6, characterized in that: The working state of the AC / DC charging pile is judged according to the current control output. When it is detected that the power flow direction needs to be changed, the power output of the current working mode is controlled to gradually decrease to zero, and the target working mode is switched after the DC bus voltage of the power converter is stabilized at a set value, and a new power output control amount is obtained, including: The power flow direction state in the current control output is judged, and the transmission power Ps=Vs×Is and the reception power Pr=Vr×Ir are calculated, where Vs and Is are the voltage and current of the transmission end, respectively, and Vr and Ir are the voltage and current of the receiving end, respectively, to obtain the power flow direction judgment result; According to the power flow direction judgment result, the power of the current working mode is reduced in power control to obtain a power reduction process curve; Based on the power reduction process curve, a power reduction step size and an interval time of each reduction are set to obtain a segmented power reduction control sequence; Performing PWM duty cycle modulation on the segmented power reduction control sequence to obtain a PWM control quantity sequence, and inputting the PWM control quantity sequence into the power converter, monitoring the fluctuation of the DC bus voltage, and obtaining a voltage stability criterion; Determining the working mode switching time according to the voltage stability criterion to obtain a mode switching trigger signal; The charging pile control strategy is switched based on the mode switching trigger signal, the control parameters of the target working mode are obtained by updating the control parameter matrix, and the power output is controlled on the control parameters of the target working mode to obtain a new power output control amount.

8. A bidirectional power flow control device for an AC / DC charging pile, characterized in that: Used to execute the AC / DC charging pile bidirectional power flow control method according to any one of claims 1 to 7, the AC / DC charging pile bidirectional power flow control device comprises: The acquisition module is used to detect and collect parameters of AC and DC charging piles, power converters and grid connection points to obtain the charging pile system operation parameter set; a calculation module, configured to perform a trapezoidal voltage edge calculation on a switching process of a power converter according to the system operation parameter set to obtain a dead time compensation amount, and superimpose the dead time compensation amount on a PWM control signal of the power converter to obtain a target PWM control signal; A switching module is used to input the target PWM control signal and the current system state into a prediction controller for discrete mathematical modeling, calculate an optimal PWM control sequence, and use the first control quantity of the optimal PWM control sequence as the current control output; The acquisition module is used to judge the working state of the AC / DC charging pile according to the current control output. When it is detected that the power flow direction needs to be changed, the power output of the current working mode is controlled to gradually drop to zero, and the DC bus voltage of the power converter is switched to the target working mode after it stabilizes at the set value to obtain a new power output control amount.

9. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, the method for controlling the bidirectional power flow of an AC or DC charging pile according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the processor is enabled to execute the bidirectional power flow control method for an AC / DC charging pile as claimed in any one of claims 1 to 7.

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