Energy storage device ac charging power control method and system

Abstract

The application discloses an AC charging power control method of an energy storage device, which comprises the following steps: dynamically and real-timely calculating and adjusting a dead time according to the amplitude of a load current, calculating a compensation voltage, and superimposing the compensation voltage into the PWM signal generation logic of a controller; when the energy storage device is in a micro-disturbance working condition, a fuzzy PI control algorithm is adopted, and the proportional gain and integral time of the fuzzy PI control are real-timely adjusted according to the size of the load current and the power fluctuation; when the energy storage device is in a small power charging condition, a proportional resonance (PR) control algorithm is adopted; when the energy storage device is in a light-load energy-saving mode, the controller enters a pulse skipping mode or a burst mode; and when the real-time grid voltage fluctuation exceeds a voltage fluctuation range threshold, the modulation ratio is dynamically adjusted through voltage feedforward control according to the fluctuation amplitude of the grid voltage.

Description

Technical Field

[0001] This invention relates to the field of energy storage device control technology, and in particular to a method and system for controlling the AC charging power of an energy storage device. Background Technology

[0002] In practical applications, outdoor energy storage devices often face complex external environments such as grid voltage fluctuations, harmonic pollution, and temperature changes. Furthermore, traditional control strategies have significant limitations in adaptability under low-power charging conditions. Dead time effect: The fixed dead time set to prevent short circuits in the converter bridge arm will cause distortion of the output current waveform during low-power charging, which will in turn cause power fluctuations.

[0003] Control algorithm lag: Traditional PI control algorithms are optimized for heavy-load conditions, but their response to load disturbances is lagging in low-power scenarios, and they are prone to overshoot or oscillation.

[0004] Light load loss problem: The proportion of switching losses increases under low load. In traditional control mode, the switch operates frequently, accumulating losses and disrupting power balance.

[0005] Sensitive to grid interference: When grid voltage fluctuations exceed ±10%, the converter modulation ratio is not adjusted in time, and the charging power changes synchronously with the voltage, resulting in poor stability.

[0006] In existing technologies, the solutions to the above problems are singular and fail to be optimized in a coordinated manner from multiple dimensions such as hardware characteristics, control strategies, and external environmental interference, resulting in the inability of outdoor energy storage devices to meet user needs for AC charging power stability. Summary of the Invention

[0007] Based on the above situation, the main objective of this invention is to provide a method for stable control of AC charging power of energy storage devices. By synergistically applying dynamic dead zone compensation, adaptive control algorithm, light load energy-saving mode and grid voltage feedforward compensation, this method effectively solves the problem of large fluctuations in AC charging power of outdoor energy storage devices and improves user experience.

[0008] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A method for controlling the AC charging power of an energy storage device includes: dynamically calculating and adjusting the dead time in real time based on the amplitude of the load current, calculating a compensation voltage, and superimposing the compensation voltage into the PWM signal generation logic of the controller; employing a fuzzy PI control algorithm when the energy storage device is under a small disturbance condition, and adjusting the proportional gain and integral time of the fuzzy PI control in real time according to the magnitude of the load current and the power fluctuation; employing a proportional resonant PR control algorithm when the energy storage device is under low-power charging; entering a pulse jump mode or a burst mode when the energy storage device is in a light-load energy-saving mode; and dynamically adjusting the modulation ratio through voltage feedforward control according to the fluctuation amplitude of the grid voltage when the real-time grid voltage fluctuation exceeds the voltage fluctuation range threshold.

[0009] Preferably, the step of dynamically calculating and adjusting the dead time in real time according to the amplitude of the load current includes: when the load current is greater than a first current threshold, using a fixed dead time; when the load current is less than or equal to the first current threshold, linearly adjusting the dead time according to the amplitude of the load current.

[0010] Preferably, the dead time is linearly adjusted according to the amplitude of the load current using the following formula: t_dead_adj= t_dead_base*|i| / i_rated*0.1 Where t_dead_adj is the adjusted dead time; t_dead_base is the base dead time; |i| represents the magnitude of the load current; i_rated is the rated current.

[0011] Preferably, the compensation voltage is calculated using the following formula: Delta u=(t_dead_adj / T_s)*U_dc*sign(i) Where t_dead_adj is the adjusted dead time; T_s is the switching cycle; U_dc is the DC bus voltage; sign(i) is the current direction function, which takes +1 for the positive direction and -1 for the negative direction.

[0012] Preferably, the step of adjusting the proportional gain and integral time of the fuzzy PI control in real time according to the magnitude of the load current and the power fluctuation includes: when the load current is less than a second current threshold and the power fluctuation is greater than a first power fluctuation threshold, increasing the proportional gain to M1 times the base value and decreasing the integral time to N1 times the base value; when the load current is between the second current threshold and the third current threshold and the power fluctuation is between the second power fluctuation threshold and the first power fluctuation threshold, maintaining the proportional gain at M2 times the base value and the integral time at N2 times the base value; when the load current is greater than the third current threshold or the power fluctuation is less than the second power fluctuation threshold, using the proportional gain as the base value and the integral time as the base value conventional PI control parameters.

[0013] Preferably, the pulse skipping mode includes: when the load current is less than a third current threshold, the controller adjusts the switching frequency in real time according to the load current, skipping one switching cycle every N clock cycles, and the value of N is linearly adjusted according to the load current.

[0014] Preferably, the value of N is linearly adjusted according to the load current using the following formula: N = round((i_rated * 0.1) / abs(i_load)) Where round() is the rounding function; i_rated is the rated current; i_load is the current load current; abs() is the absolute value function.

[0015] Preferably, the burst mode includes: when the load current is less than a fourth current threshold, the controller outputs a preset number of switching pulse clusters at a fixed frequency, and then enters a sleep period until the output voltage of the energy storage device drops to a preset lower limit and then wakes up the controller.

[0016] Preferably, the modulation ratio is dynamically adjusted via voltage feedforward control based on the fluctuation amplitude of the grid voltage using the following formula: M_adj=M_base *(U_grid_rated / U_grid_actual) Where M_adj is the adjusted modulation ratio; M_base is the base modulation ratio; U_grid_rated is the rated grid voltage; U_grid_actual is the actual grid voltage.

[0017] This invention also discloses an AC charging power control system for an energy storage device. The system includes a dynamic dead-zone compensation module, an adaptive fuzzy PI / PR composite control module, a light-load energy-saving mode collaborative control module, and a grid voltage feedforward compensation module. The dynamic dead-zone compensation module is used to dynamically calculate and adjust the dead time in real time according to the amplitude of the load current, and calculate the compensation voltage, which is then superimposed on the PWM signal generation logic of the controller. The adaptive fuzzy PI / PR composite control module is used to employ a fuzzy PI control algorithm when the energy storage device is under a small disturbance condition, and to adjust the proportional gain and integral time of the fuzzy PI control in real time according to the magnitude of the load current and the power fluctuation. When the energy storage device is under low-power charging, a proportional resonant PR control algorithm is employed. The light-load energy-saving mode collaborative control module is used to allow the controller to enter a pulse jump mode or a burst mode when the energy storage device is in a light-load energy-saving mode. The grid voltage feedforward compensation module is used to dynamically adjust the modulation ratio according to the voltage fluctuation amplitude of the grid voltage when the real-time grid voltage fluctuation exceeds the voltage fluctuation range threshold.

[0018] The technical solution of this invention integrates multi-strategy collaborative operation logic with operating condition criteria to construct a multi-dimensional criterion system based on load level, power fluctuation, and grid status. This system enables seamless switching and priority management of dynamic dead zone, fuzzy control, energy-saving mode, and feedforward compensation, ensuring control continuity and stability under all operating conditions. It reduces current waveform distortion: the dynamic dead zone compensation algorithm can reduce the total harmonic distortion (THD) of the current during low-power charging from over 12% to below 3%, effectively reducing output current waveform distortion. It improves control response speed: the adaptive control algorithm shortens the response time to load disturbances under low-power conditions from 50ms to less than 10ms, avoiding overshoot and oscillation. It reduces light-load losses: the light-load energy-saving mode can reduce switching losses under low load by more than 90%, improving charging efficiency and reducing power fluctuations. It enhances grid adaptability: the grid voltage feedforward compensation mechanism can maintain stable charging power within ±15% of grid voltage fluctuations, controlling the fluctuation amplitude within ±2%.

[0019] Other beneficial effects of the present invention will be explained in detail through the introduction of specific technical features and technical solutions in specific embodiments. Those skilled in the art should be able to understand the beneficial technical effects brought about by the technical features and technical solutions through the introduction of these technical features and technical solutions. Attached Figure Description

[0020] The preferred embodiment of the AC charging power control method for an energy storage device according to the present invention will now be described with reference to the accompanying drawings. In the drawings: Figure 1 This is a flowchart of an AC charging power control method for an energy storage device according to a preferred embodiment of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0022] In the description of this invention, "several" means one or more, "multiple" means two or more, "greater than," "less than," and "exceeding" are understood to exclude the stated number, while "above," "below," and "within" are understood to include the stated number. The use of "first" and "second" in the description is merely for distinguishing technical features and should not be construed as indicating or implying relative importance, or implicitly indicating the number of indicated technical features, or implicitly indicating the order of the indicated technical features.

[0023] In the description of this invention, unless otherwise explicitly defined, terms such as "setup" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this invention in conjunction with the specific content of the technical solution.

[0024] In the description of this invention, the terms "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., refer to specific features or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0025] Figure 1The flowchart of an AC charging power control method for an energy storage device according to a preferred embodiment of the present invention includes the following steps: Step S100: dynamically and in real-time calculate and adjust the dead time based on the amplitude of the load current, calculate the compensation voltage, and superimpose the compensation voltage into the PWM signal generation logic of the controller; Step S200: when the energy storage device is under a small disturbance condition, a fuzzy PI control algorithm is adopted, and the proportional gain (Kp) and integral time (Ti) of the fuzzy PI control are adjusted in real-time according to the magnitude of the load current and the power fluctuation; when the energy storage device is under low-power charging, a proportional resonance (PR) control algorithm is adopted; Step S300: when the energy storage device is in a light-load energy-saving mode, the controller enters a pulse skipping mode or a burst mode; Step S400: when the real-time grid voltage fluctuation exceeds the voltage fluctuation range threshold, the modulation ratio is dynamically adjusted through voltage feedforward control according to the fluctuation amplitude of the grid voltage.

[0026] In a specific implementation, a high-precision current sensor can be used to obtain the instantaneous value of the load current, with a sampling frequency of not less than 10kHz, to ensure a rapid response to changes in current.

[0027] The technical solution of this invention integrates multi-strategy collaborative operation logic with operating condition criteria to construct a multi-dimensional criterion system based on load level, power fluctuation, and grid status. This system enables seamless switching and priority management of dynamic dead zone, fuzzy control, energy-saving mode, and feedforward compensation, ensuring control continuity and stability under all operating conditions. Specifically, it can achieve: Reduce current waveform distortion: The dynamic dead zone compensation algorithm can reduce the total harmonic distortion (THD) of the current during low-power charging from more than 12% to less than 3%, effectively reducing the distortion of the output current waveform.

[0028] Improved control response speed: The adaptive control algorithm reduces the response time to load disturbances under low power conditions from 50ms to less than 10ms, avoiding overshoot and oscillation.

[0029] Reduce light-load losses: The light-load energy-saving mode can reduce switching losses by more than 90% under low load, improve charging efficiency, and reduce power fluctuations.

[0030] Enhanced grid adaptability: The grid voltage feedforward compensation mechanism can maintain stable charging power within ±2% of grid voltage fluctuations, with fluctuation amplitude controlled within ±15%.

[0031] In a preferred embodiment, dynamically calculating and adjusting the dead time based on the amplitude of the load current in real time may include: using a fixed dead time when the load current is greater than a first current threshold; and linearly adjusting the dead time based on the amplitude of the load current when the load current is less than or equal to the first current threshold. In a specific embodiment, the first current threshold may be 10% of the rated current, and the fixed dead time may be 2-5 μs. These parameters can be set according to actual needs, and the present invention does not impose any limitations.

[0032] In a preferred embodiment, the dead time can be adjusted according to the amplitude of the load current using the following formula: t_dead_adj= t_dead_base*|i| / i_rated*0.1 Where t_dead_adj is the adjusted dead time; t_dead_base is the base dead time; |i| represents the magnitude of the load current; i_rated is the rated current.

[0033] In a preferred embodiment, the compensation voltage can be calculated using the following formula: Delta u=(t_dead_adj / T_s)*U_dc*sign(i) Where t_dead_adj is the adjusted dead time; T_s is the switching cycle; U_dc is the DC bus voltage; sign(i) is the current direction function, which takes +1 for the positive direction and -1 for the negative direction.

[0034] The dead time is adjusted in real time according to the load current. When the load current is less than or equal to the first current threshold, the dead time is dynamically and linearly adjusted, and a compensation voltage is injected to offset the voltage deviation. The total harmonic distortion (THD) of the current under low power conditions is reduced from more than 12% to less than 3%, effectively suppressing the distortion of the output current waveform, which is better than fixed dead time or single compensation scheme.

[0035] In a preferred embodiment, step S200, which involves adjusting the proportional gain (Kp) and integral time (Ti) of the fuzzy PI control in real time based on the magnitude of the load current and the power fluctuation, may include: when the load current is less than a second current threshold and the power fluctuation is greater than a first power fluctuation threshold, increasing the proportional gain to M1 times the base value and decreasing the integral time to N1 times the base value; when the load current is between the second and third current thresholds and the power fluctuation is between the second and first power fluctuation thresholds, maintaining the proportional gain at M2 times the base value and the integral time at N2 times the base value; when the load current is greater than the third current threshold or the power fluctuation is less than the second power fluctuation threshold, using the proportional gain and integral time as the base values. The base values ​​of the proportional gain and integral time are the traditional PI control parameters, or the PI control parameters before adjustment. The traditional PI control parameters can be set according to requirements.

[0036] In a specific implementation, the second current threshold can be 5% of the rated current, the first power fluctuation threshold can be 10%, M1 can be 1.5, and N1 can be 0.5; the third current threshold can be 10% of the rated current, the second power fluctuation threshold can be 5%, M2 can be 1.2, and N2 can be 0.8. When the load current is less than 5% of the rated current and the power fluctuation is greater than 10%, increasing Kp to 1.5 times the base value and decreasing Ti to 0.5 times the base value can improve the response speed. When the load current is between 5% and 10% of the rated current and the power fluctuation is between 5% and 10%, keeping Kp at 1.2 times the base value and Ti at 0.8 times the base value can balance response speed and stability. When the load current is greater than 10% of the rated current or the power fluctuation is less than 5%, using traditional PI control parameters can ensure stability under heavy load conditions.

[0037] Under light load or minor disturbance conditions, fuzzy PI control is adopted to dynamically adjust the Kp and Ti parameters based on load current and power fluctuations; when charging at low power, PR control is switched to achieve zero steady-state error tracking of the fundamental frequency, improve the ability to suppress grid harmonics, and reduce power fluctuations caused by harmonic currents.

[0038] In a preferred embodiment, the pulse skipping mode may include: when the load current is less than a third current threshold, the controller adjusts the switching frequency in real time according to the load current, skipping one switching cycle every N clock cycles, where the value of N can be linearly adjusted according to the load current. Specifically, the third current threshold may be 10% of the rated current.

[0039] In a specific implementation, the value of N can be linearly adjusted according to the load current using the following formula: N = round((i_rated * 0.1) / abs(i_load)) Where round() is the rounding function; i_rated is the rated current; i_load is the current load current; abs() is the absolute value function.

[0040] In a preferred embodiment, the burst mode may include: when the load current is less than a fourth current threshold, the controller outputs a preset number of switching pulse clusters at a fixed frequency, then enters a sleep period until the output voltage of the energy storage device drops to a preset lower limit, at which point the controller is awakened. For example, the fourth current threshold may be 5% of the rated current, the fixed frequency may be 100kHz, the preset number may be 3-10, and the number of pulse clusters can be adjusted according to the load current; the smaller the load current, the fewer the number of pulse clusters. The preset lower limit of the output voltage can be set as needed.

[0041] In the above embodiments, a dual energy-saving mechanism of pulse jump mode and burst mode is introduced. When the load current is less than the third current threshold, the controller enables pulse jump. When the load current is less than the fourth current threshold, the controller enters burst mode to reduce unnecessary switching actions and reduce switching losses by more than 90%.

[0042] In a preferred embodiment, the modulation ratio can be dynamically adjusted via voltage feedforward control based on the fluctuation amplitude of the grid voltage using the following formula: M_adj=M_base *(U_grid_rated / U_grid_actual) Where M_adj is the adjusted modulation ratio; M_base is the base modulation ratio; U_grid_rated is the rated grid voltage; U_grid_actual is the actual grid voltage.

[0043] Specifically, the grid voltage can be collected in real time using a voltage sensor, with a sampling frequency of no less than 5kHz. The voltage fluctuation range threshold can be ±10%. By monitoring the grid voltage in real time, when the fluctuation exceeds the voltage fluctuation range threshold, the modulation ratio is dynamically adjusted through feedforward control to keep the charging power stable within a voltage fluctuation range of ±15%, with the fluctuation amplitude controlled within ±2%.

[0044] This invention also discloses an AC charging power control system for an energy storage device, comprising a dynamic dead-zone compensation module, an adaptive fuzzy PI / PR composite control module, a light-load energy-saving mode collaborative control module, and a grid voltage feedforward compensation module. The dynamic dead-zone compensation module dynamically calculates and adjusts the dead-zone time in real time based on the amplitude of the load current, calculates a compensation voltage, and superimposes the compensation voltage into the controller's PWM signal generation logic. The adaptive fuzzy PI / PR composite control module employs a fuzzy PI control algorithm when the energy storage device is under minor disturbance conditions, and adjusts the proportional gain and integral time of the fuzzy PI control in real time according to the magnitude of the load current and power fluctuations. When the energy storage device is under low-power charging, it employs a proportional resonant PR control algorithm. The light-load energy-saving mode collaborative control module allows the controller to enter a pulse jump mode or a burst mode when the energy storage device is in light-load energy-saving mode. The grid voltage feedforward compensation module dynamically adjusts the modulation ratio based on the grid voltage fluctuation amplitude when the real-time grid voltage fluctuation exceeds a voltage fluctuation range threshold.

[0045] Specifically, based on the embodiments disclosed above in this application, reference is made to... Figure 1 The processes described in the flowcharts of the embodiments can be implemented as computer programs. For example, embodiments of this application also provide a computer program product including a computer program carried on a computer-readable medium, the computer program comprising methods for executing... Figure 1 The flowchart of the embodiment describes the program code for the method. In such an embodiment, the computer program can be downloaded and installed from a network via a communication interface, or installed from memory. When the computer program is executed by a processor, it performs the functions defined in the method of the above embodiment.

[0046] It should be noted that the aforementioned computer-readable media may include, but is not limited to: volatile memory, such as random access memory (RAM); non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid-state drive (SSD); and combinations of the above types of memory.

[0047] In this application, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0048] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0049] In an optional embodiment, this application also provides a computer storage medium that can be used for computer software instructions, including a computer program. When the computer program is run by a processor, it executes the AC charging power control method for the energy storage device as described in the above embodiments. The storage medium includes, but is not limited to, flash memory, hard disk, and solid-state drive.

[0050] It should be noted that the use of step numbers (letter or number) to refer to certain specific method steps in this invention is merely for the purpose of convenience and brevity in description, and is by no means intended to restrict the order of these method steps. Those skilled in the art will understand that the order of the relevant method steps should be determined by the technology itself and should not be unduly restricted by the existence of step numbers.

[0051] Those skilled in the art will understand that, without conflict, the above-mentioned preferred solutions can be freely combined and superimposed.

[0052] It should be understood that the above embodiments are merely exemplary and not restrictive. Various obvious or equivalent modifications or substitutions that can be made by those skilled in the art regarding the above details without departing from the basic principles of the present invention will be included within the scope of the claims of the present invention.

Claims

1. A method for controlling the AC charging power of an energy storage device, characterized in that, include: The dead time is dynamically calculated and adjusted in real time based on the amplitude of the load current, and the compensation voltage is calculated and superimposed on the PWM signal generation logic of the controller. When the energy storage device is under a small disturbance condition, a fuzzy PI control algorithm is adopted, and the proportional gain and integral time of the fuzzy PI control are adjusted in real time according to the magnitude of the load current and the power fluctuation. When the energy storage device is under low power charging, a proportional resonant PR control algorithm is adopted. When the energy storage device is in light-load energy-saving mode, the controller enters pulse jump mode or burst mode; When the real-time grid voltage fluctuation exceeds the voltage fluctuation range threshold, the modulation ratio is dynamically adjusted through voltage feedforward control based on the fluctuation amplitude of the grid voltage.

2. The AC charging power control method for energy storage devices according to claim 1, characterized in that, The dynamic real-time calculation and adjustment of the dead time based on the amplitude of the load current includes: When the load current is greater than the first current threshold, a fixed dead time is used; When the load current is less than or equal to the first current threshold, the dead time is linearly adjusted according to the amplitude of the load current.

3. The AC charging power control method for energy storage devices according to claim 2, characterized in that, The dead time is adjusted linearly based on the amplitude of the load current using the following formula: t_dead_adj= t_dead_base*|i| / i_rated*0.1 Where t_dead_adj is the adjusted dead time; t_dead_base is the base dead time; |i| represents the magnitude of the load current; i_rated is the rated current.

4. The AC charging power control method for energy storage devices according to claim 1, characterized in that, The compensation voltage is calculated using the following formula: Delta u=(t_dead_adj / T_s)*U_dc*sign(i) Where t_dead_adj is the adjusted dead time; T_s is the switching cycle; U_dc is the DC bus voltage; sign(i) is the current direction function, which takes +1 for the positive direction and -1 for the negative direction.

5. The AC charging power control method for energy storage devices according to claim 1, characterized in that, The step of adjusting the proportional gain and integral time of the fuzzy PI control in real time according to the magnitude of the load current and power fluctuations includes: When the load current is less than the second current threshold and the power fluctuation is greater than the first power fluctuation threshold, the proportional gain is increased to M1 times the base value, and the integral time is decreased to N1 times the base value. When the load current is between the second current threshold and the third current threshold and the power fluctuation is between the second power fluctuation threshold and the first power fluctuation threshold, the proportional gain is maintained at M2 times the base value and the integral time is maintained at N2 times the base value. When the load current is greater than the third current threshold or the power fluctuation is less than the second power fluctuation threshold, the proportional gain is used as the base value and the integral time is used as the base value of the traditional PI control parameters.

6. The AC charging power control method for energy storage devices according to claim 1, characterized in that, The pulse skipping mode includes: When the load current is less than the third current threshold, the controller adjusts the switching frequency in real time according to the load current, skipping one switching cycle every N clock cycles, and the value of N is linearly adjusted according to the load current.

7. The AC charging power control method for energy storage devices according to claim 1, characterized in that, The value of N is linearly adjusted according to the load current using the following formula: N = round((i_rated * 0.1) / abs(i_load)) Where round() is the rounding function; i_rated is the rated current; i_load is the current load current; abs() is the absolute value function.

8. The AC charging power control method for energy storage devices according to claim 1, characterized in that, The outbreak modes include: When the load current is less than the fourth current threshold, the controller outputs a preset number of switching pulse clusters at a fixed frequency, and then enters a sleep period until the output voltage of the energy storage device drops to a preset lower limit and then wakes up the controller.

9. The AC charging power control method for energy storage devices according to claim 1, characterized in that, The modulation ratio is dynamically adjusted using voltage feedforward control based on the fluctuation amplitude of the grid voltage according to the following formula: M_adj=M_base *(U_grid_rated / U_grid_actual) Where M_adj is the adjusted modulation ratio; M_base is the base modulation ratio; U_grid_rated is the rated grid voltage; U_grid_actual is the actual grid voltage.

10. An AC charging power control system for an energy storage device, characterized in that, The system includes a dynamic dead-zone compensation module, an adaptive fuzzy PI / PR composite control module, a light-load energy-saving mode collaborative control module, and a grid voltage feedforward compensation module. The dynamic dead-time compensation module is used to dynamically calculate and adjust the dead time in real time according to the amplitude of the load current, and calculate the compensation voltage, which is then superimposed on the PWM signal generation logic of the controller. The adaptive fuzzy PI / PR composite control module is used to employ a fuzzy PI control algorithm when the energy storage device is under a small disturbance condition, and to adjust the proportional gain and integral time of the fuzzy PI control in real time according to the magnitude of the load current and the power fluctuation. When the energy storage device is under low-power charging, a proportional resonant PR control algorithm is employed. The light-load energy-saving mode collaborative control module is used to allow the controller to enter pulse jump mode or burst mode when the energy storage device is in light-load energy-saving mode. The grid voltage feedforward compensation is used to dynamically adjust the modulation ratio based on the grid voltage fluctuation amplitude when the real-time grid voltage fluctuation exceeds the voltage fluctuation range threshold.

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