A Resonance Suppression Method and System for Multi-module Inverters of Mobile Energy Storage Systems

Abstract

The present invention relates to the technical field of converters, and particularly to a method and system for suppressing resonance of a multi-module converter in a mobile energy storage system. By optimizing the dynamic response of the system through a controller, the present invention can ensure that the system maintains good stability and performance under different operating conditions. Through the precise design of mathematical modeling and control algorithms, the robustness of the multi-module converter system under different working conditions can be improved. Through real-time monitoring and frequency identification mechanisms, the control strategy can be adjusted according to the frequency characteristics of resonance. By adjusting the switching state of the converter in real time, the control algorithm can actively intervene in the resonance phenomenon of the system. By adjusting the control parameters in real time, the system can automatically adapt to different loads, environmental conditions, and equipment states to ensure long-term stable operation. By actively suppressing resonance and reducing excessive oscillation of the system, the energy waste and equipment loss caused by resonance can be significantly reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of converters, and particularly to a method and system for suppressing resonance of a multi-module converter in a mobile energy storage system. Background Art

[0002] In the design and application of mobile energy storage systems, multi-module converter technology is widely adopted to improve the flexibility and reliability of the system. However, during the application of multi-module converters, due to the mutual interference between modules and internal non-linear factors, resonance has become a key technical problem. Especially in the case of high-frequency conversion and large transmission power, the resonance effect will significantly increase the system loss, affect the stability and efficiency of the system, and may cause overheating problems in some modules, and even affect the normal operation of the entire system. Therefore, exploring effective resonance suppression methods is of great significance for improving the performance of mobile energy storage systems.

[0003] Traditional resonance suppression methods mainly rely on hardware-level designs, such as adding resonance suppression filters. Although resonance problems can be alleviated to a certain extent, they also bring negative effects such as increased cost, increased volume, and increased system complexity. In recent years, resonance suppression methods based on control strategies have received extensive attention. These methods adjust the operating state of the system from the software level by implementing advanced control algorithms to achieve the purpose of harmonic suppression and stable control. Although these control algorithms can effectively alleviate resonance problems in theory, in practical applications, they still face many challenges, such as the delay problem of control algorithms, the optimization of system dynamic response, and the robustness under different working conditions. Therefore, developing a more efficient and robust resonance suppression method is of great significance for improving the performance and reliability of mobile energy storage systems. Summary of the Invention

[0004] The main purpose of the present invention is to provide a method for suppressing resonance of a multi-module converter in a mobile energy storage system, aiming to solve the technical problems in the prior art.

[0005] The present invention proposes a method for suppressing resonance of a multi-module converter in a mobile energy storage system, including:

[0006] Mathematically modeling the multi-module converter system, including constructing the electrical parameters and topological structure of each module, and clarifying the control objectives of the multi-module converter system, where the control objectives include harmonic suppression, dynamic response, and robustness;

[0007] Real-time monitoring of the voltage and current waveforms of the multi-module converter system through sensors and controllers, detecting whether there is a resonance phenomenon. When a resonance phenomenon is detected, further identify the resonance frequency, and take corresponding control measures according to the identified resonance frequency;

[0008] The designed control algorithm actively adjusts the switching state of the converter, detects the resonance frequency in the multi-module converter system, generates reverse harmonic current according to the resonance frequency, inputs the reverse harmonic current into the multi-module converter system through the control algorithm to obtain the dynamic damping of the multi-module converter system, and repeats the above control actions within each resonance period to ensure continuous cancellation of the resonance current;

[0009] Adjust the control parameters in real time according to the state of the multi-module converter system to enhance the dynamic stability of the multi-module converter system. Use the predictive control algorithm to predict the occurrence of resonance and take measures in advance to suppress it;

[0010] Verify the effect of the adopted control algorithm in the simulation environment and suppress resonance under various working conditions. By designing a fault-tolerant control strategy, handle abnormal situations in the multi-module converter system, where the abnormal situations include sensor failures and communication interruptions.

[0011] Preferably, the mathematical modeling of the multi-module converter system includes: analyzing the overall behavior of the multi-module converter and building a model according to the DC side or the AC side. The DC side model is as follows:

[0012] ;

[0013] Among them, is the DC bus voltage, is the DC bus capacitor, is the DC input current, is the DC output current;

[0014] The AC side model is as follows:

[0015] ;

[0016] ;

[0017] Among them, is the AC side voltage, is the AC side current, is the grid voltage, is the AC side resistance, is the AC side inductor, is the AC side filter capacitor, is the load current.

[0018] Preferably, the mathematical modeling of the multi-module converter system further includes:

[0019] Reduce the harmonic components in the system and improve the waveform quality of the output voltage and current;

[0020] By injecting reverse harmonic current to cancel the resonant current and repeating the same control action in each cycle to suppress periodic resonance;

[0021] Add an LCL filter to the system and design a corresponding control algorithm to filter out harmonics, improve the dynamic response speed of the system, and ensure quick restoration of stability under conditions such as load changes and grid fluctuations;

[0022] Adjust the control parameters in real time according to the system state to enhance the dynamic response of the system. Use a predictive control algorithm to predict system changes in advance and take measures;

[0023] The proportional-resonant controller has a high gain at a specific frequency and effectively suppresses resonance. Its expression is as follows:

[0024] ;

[0025] where, is the complex frequency domain variable in the Laplace transform, is the proportional gain, is the resonant gain, is the resonant frequency;

[0026] The repetitive controller eliminates periodic harmonics by periodically injecting the same control signal. Its expression is as follows:

[0027] ;

[0028] where, is the number of system cycles, is the forgetting factor, is the transformation variable of the discrete-time system, representing the discrete frequency characteristics of the system.

[0029] Preferably, the real-time monitoring of the voltage and current waveforms of the system by the sensor and the controller includes:

[0030] Measure the DC bus voltage and the AC side voltage through a voltage sensor;

[0031] Measure the DC side current and the AC side current through a current sensor;

[0032] Set up a high-speed data acquisition card with a high sampling rate and high precision to collect sensor data in real time, ensuring the real-time and reliable transmission of data from the sensor to the controller;

[0033] Preprocess the collected signals, including filtering, to remove high-frequency noise and retain signals within a specific frequency range for easy resonance detection;

[0034] Convert the analog signal into a digital signal, identify and select the corresponding sampling frequency to ensure that the frequency components of the resonant signal can be captured. The sampling frequency should be at least twice the resonant frequency or more.

[0035] Preferably, the conversion of the analog signal into a digital signal and the identification and selection of the corresponding sampling frequency include:

[0036] Convert the time-domain signal into a frequency-domain signal and analyze the peaks in the spectrum:

[0037] Collect the voltage and current waveform data over a period of time and perform Fourier transform on the collected data;

[0038] Analyze the spectrogram, find the peaks of the harmonic components, and determine whether the peaks exceed a preset threshold;

[0039] If the peaks exceed the preset threshold, it is considered that there is a resonance phenomenon in the system;

[0040] Perform time-frequency domain analysis to accurately identify transient resonance phenomena and select appropriate wavelet basis functions;

[0041] Perform wavelet transform on the collected data, analyze the wavelet coefficients, and find the peaks of the harmonic components;

[0042] If the peaks exceed the preset threshold, it is considered that there is a resonance phenomenon in the system;

[0043] In the spectrogram of Fourier or wavelet transform, find the peak frequency of the harmonic components, which is the resonant frequency:

[0044] Calculate the spectrogram, find the maximum peak in the spectrogram, and identify the sampling frequency corresponding to the peak.

[0045] Preferably, verify the effect of the adopted control algorithm in the simulation environment and suppress resonance under various working conditions. By designing a fault-tolerant control strategy, dealing with abnormal situations in the multi-module converter system includes:

[0046] Verify the voltage and current waveforms of the simulation system under normal operating conditions;

[0047] Verify the resonance suppression effect of the control algorithm under normal working conditions and simulate sensor failures and communication interruptions;

[0048] Verify the system stability of the fault-tolerant control strategy under fault conditions and record the responses of the system before and after the implementation of the control strategy, where the responses include voltage, current waveforms, and system states;

[0049] Obtain the control effect according to the responses, and the control effect includes resonance suppression speed and system recovery time;

[0050] Obtain the simulation effect according to the control effect, and optimize the control parameters according to the simulation effect to improve the control effect;

[0051] Adjust the thresholds and default control inputs in the fault-tolerant control strategy to ensure the stability and reliability of the system under various fault conditions.

[0052] This application also provides a resonant suppression system for a multi-module converter of a mobile energy storage system, including:

[0053] A mathematical modeling module for performing mathematical modeling on the multi-module converter system, including the electrical parameters and topological structures of each module, and clarifying the control objectives of the system, including harmonic suppression, dynamic response, and robustness;

[0054] A real-time monitoring module for real-time monitoring of the voltage and current waveforms of the system through sensors and controllers, detecting whether there is a resonance phenomenon, and when resonance is detected, further identifying the resonance frequency and taking corresponding control measures;

[0055] A suppression module for designing a control algorithm to actively adjust the switching state of the converter, increase the dynamic damping of the system, and suppress resonance, including injecting reverse harmonic current to cancel the resonance current, and repeating the same control action in each cycle to suppress periodic resonance;

[0056] An adjustment module for real-time adjusting the control parameters according to the system state, enhancing the dynamic stability of the system, using a predictive control algorithm to predict the occurrence of resonance and taking measures in advance to suppress it;

[0057] A control module for verifying the effect of the adopted control algorithm in a simulation environment and suppressing resonance under various working conditions, and dealing with abnormal situations in the system by designing a fault-tolerant control strategy, where the abnormal situations include sensor failures and communication interruptions.

[0058] Preferably, a resonant suppression system for a multi-module converter of a mobile energy storage system further includes:

[0059] A data acquisition module for real-time collecting key parameters such as voltage, current, and temperature in the system, transmitting the data collected by the sensors to the control unit, and using a high-speed communication protocol;

[0060] A real-time monitoring and diagnosis module for preprocessing the collected signals, such as filtering and sampling, to improve the accuracy and reliability of the signals, using signal analysis methods such as Fourier transform and wavelet transform to real-time detect whether there is a resonance phenomenon in the system, and diagnosing the cause of resonance after detecting resonance;

[0061] The control strategy module designs and implements an active damping control algorithm to increase the dynamic damping of the system by adjusting the switching state of the converter, suppress resonance, uses a predictive control algorithm to predict the occurrence of resonance in advance and take measures to suppress it, and designs an adaptive control algorithm to adjust the control parameters in real time according to the system state to enhance the dynamic stability of the system;

[0062] The parameter optimization module uses an optimization algorithm to optimize the control parameters to improve the control effect, and adjusts the control parameters in real time according to the system operation state to ensure that the performance of the control algorithm remains optimal under various working conditions;

[0063] The communication and coordination module ensures efficient data exchange and command transmission between various modules, realizes the coordinated control of multi-module converters, and optimizes the performance of the overall system;

[0064] The execution and drive module is responsible for driving the switching devices of the converter, performing switching operations according to control instructions, and protecting the converter in a timely manner to prevent equipment damage when the system has an abnormality.

[0065] Preferably, the real-time monitoring module includes:

[0066] The first measurement unit is used to measure the DC bus voltage and the AC side voltage through a voltage sensor;

[0067] The second measurement unit is used to measure the DC side current and the AC side current through a current sensor;

[0068] The acquisition unit is used to set a high-speed data acquisition card with a high sampling rate and high precision to acquire sensor data in real time to ensure the real-time and reliability of data transmission from the sensor to the controller;

[0069] The preprocessing unit is used to preprocess the acquired signals, including filtering processing to remove high-frequency noise and retain signals within a specific frequency range for easy resonance detection;

[0070] The conversion unit is used to convert analog signals into digital signals, identify and select the corresponding sampling frequency to ensure that the frequency components of the resonance signal can be captured, and the sampling frequency should be at least twice the resonance frequency or more.

[0071] The present invention also provides a computer device, including a memory and a processor, where the memory stores a computer program, and when the processor executes the computer program, the steps of the above-mentioned method for suppressing resonance of a multi-module converter of a mobile energy storage system are implemented.

[0072] The present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above-mentioned method for suppressing resonance of a multi-module converter of a mobile energy storage system are implemented.

[0073] The beneficial effects of the present invention are as follows: By real-time monitoring the voltage and current waveforms of the system, the present invention can detect in a timely manner the possible resonance phenomena in the system. By optimizing the dynamic response of the system through the controller, it can ensure that the system maintains good stability and performance under different operating conditions. Through the precise design of mathematical modeling and control algorithms, the robustness of the multi-module converter system under different working conditions can be improved. Through the real-time monitoring and frequency identification mechanism, the system can adjust the control strategy according to the frequency characteristics of resonance, thereby realizing more flexible and adaptive resonance suppression. By real-time adjusting the switching state of the converter, the control algorithm can actively intervene in the resonance phenomenon of the system. By enhancing the damping, it can not only effectively reduce the amplitude of resonance, but also speed up the response speed, reduce the transient process of the system, and improve the overall performance. By repeating the same control action in each cycle, the periodic resonance can be effectively suppressed. The control algorithm, based on the periodic characteristics of the system, applies appropriate control signals in each cycle to ensure that the resonance can be accurately suppressed in each cycle. By precisely adjusting the converter switching state and reverse harmonic injection, the system can timely reduce the loss of useless energy when the resonance phenomenon occurs, and improve the overall efficiency. By the way of real-time adjusting the control parameters, the system can automatically adapt according to different loads, environmental conditions and equipment states, enabling the system to flexibly cope with these changes and ensuring long-term stable operation. By actively suppressing resonance and reducing the excessive oscillation of the system, the energy waste and equipment loss caused by resonance can be significantly reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] Figure 1 It is a schematic flowchart of the method according to an embodiment of the present invention.

[0075] Figure 2 It is a schematic structural diagram of the device according to an embodiment of the present invention.

[0076] Figure 3 It is a schematic internal structure diagram of a computer device according to an embodiment of the present application.

[0077] The realization, functional features and advantages of the object of the present invention will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0078] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0079] As Figures 1 - 3 shown, the present application provides a method for suppressing resonance of a multi-module converter in a mobile energy storage system, including:

[0080] S1. Conduct mathematical modeling on the multi-module converter system, including the electrical parameters and topological structures of each module, and clarify the control objectives of the system, including harmonic suppression, dynamic response, and robustness.

[0081] S2. Real-time monitor the voltage and current waveforms of the system through sensors and controllers, detect whether there is a resonance phenomenon. When resonance is detected, further identify the resonance frequency and take corresponding control measures.

[0082] S3. Design a control algorithm to actively adjust the switching state of the converter, increase the dynamic damping of the system, and suppress resonance, including injecting reverse harmonic current to cancel the resonance current, and repeating the same control action in each cycle to suppress periodic resonance.

[0083] S4. Adjust the control parameters in real time according to the system state to enhance the dynamic stability of the system. Use the predictive control algorithm to predict the occurrence of resonance and take measures in advance to suppress it.

[0084] S5. Verify the effectiveness of the adopted control algorithm in the simulation environment, suppress resonance under various working conditions, and handle abnormal situations in the system by designing a fault-tolerant control strategy, where the abnormal situations include sensor failures and communication interruptions.

[0085] As described in the above steps S1 - S5, inject reverse harmonic current. When there is a resonance frequency in the system, such as 50 Hz or its multiples (100 Hz, 150 Hz, etc.), resonance will cause the dynamic performance of the system to decline or even become unstable. Generate a current with the same frequency but opposite phase to the resonance frequency through the control algorithm and inject it into the system. This current can cancel out the resonance current, thereby suppressing resonance. The repetitive controller repeats the same control action in each cycle (such as the 50 Hz cycle of the power grid). This means that the controller can respond in a timely manner to the periodic changes of the system, especially for periodic resonance phenomena. By periodically injecting reverse harmonic current, the repetitive controller can increase the dynamic damping of the system, making the response of the system smoother and reducing oscillations.

[0086] Dynamic damping is the ability of the system to respond to rapidly changing loads or disturbances. Increasing dynamic damping can reduce the oscillations and overshoots of the system, making the system more stable. Resonance usually manifests as periodic oscillations of the system. By increasing dynamic damping, these periodic oscillations can be effectively suppressed, thereby achieving the effect of suppressing resonance. Resonance suppression means that the oscillations in the system will be effectively reduced or eliminated. This not only improves the stability of the system but also reduces energy losses and equipment wear. After suppressing resonance, the dynamic performance of the system is significantly improved, and it can respond more quickly and accurately to load changes and external disturbances.

[0087] Detect the resonant frequency in the system through sensors or analysis tools. Based on the detected resonant frequency, generate harmonic currents with opposite phases. Inject the generated reverse harmonic currents into the system through a control algorithm. Repeat the above control actions within each resonant cycle to ensure continuous cancellation of the resonant current. By periodically injecting reverse harmonic currents, the system is dynamically damped in each cycle, reducing oscillations. The increase in dynamic damping effectively suppresses the resonant phenomenon, improving the stability and dynamic performance of the system.

[0088] By injecting reverse harmonic currents and using a repetitive controller, the dynamic damping of the system can be increased and resonance can be suppressed. The increase in dynamic damping is the means to achieve resonance suppression, while resonance suppression is the effect of increasing dynamic damping. These two are closely related. The former is the step achieved through the control algorithm, and the latter is the direct manifestation of the improvement of system performance. Through this linkage method, the system can maintain stability and high performance in the face of periodic resonance. Among them, by designing a control algorithm to actively adjust the switching state of the converter, the control algorithm for increasing the dynamic damping of the system usually adopts the principle of real-time feedback control. It judges whether resonance occurs based on the current state of the system (such as current, voltage, frequency, etc.). By actively adjusting the switching state of the converter, the dynamic damping of the system is increased, directly suppressing the resonant phenomenon. It is dynamically adjusted based on the feedback signal of the current system. Common implementation methods include PID control, state feedback control, robust control, etc. The predictive control algorithm used to predict the occurrence of resonance and take preventive measures in advance is a feedforward control strategy. It predicts the future state of the system based on the historical data, model or other methods of the system and takes control measures in advance. For example, by predicting the resonant mode, the trend or possibility of resonance occurrence can be identified in advance, and system parameters (such as switching frequency or injected current) can be adjusted to prevent resonance from occurring in advance. Common predictive control algorithms include model predictive control (MPC), etc. These algorithms require modeling the dynamics of the system and predicting the future behavior of the system based on the model.

[0089] Currently, traditional resonance suppression methods mainly rely on hardware-level designs, such as adding resonance suppression filters. Although it can alleviate the resonance problem to a certain extent, it also brings negative effects such as increased cost, enlarged volume, and enhanced system complexity. In recent years, resonance suppression methods based on control strategies have received extensive attention. Such methods adjust the operating state of the system from the software level by implementing advanced control algorithms to achieve the purpose of harmonic suppression and stable control. Although these control algorithms can effectively alleviate the resonance problem in theory, in practical applications, they still face many challenges, such as the delay problem of control algorithms, the optimization of system dynamic response, and the robustness under different working conditions. The present invention conducts mathematical modeling on the multi-module converter system, including the electrical parameters and topological structures of each module, and clarifies the control objectives of the system, including harmonic suppression, dynamic response, and robustness. By real-time monitoring the voltage and current waveforms of the system, possible resonance phenomena in the system can be detected in a timely manner. This real-time feedback mechanism enables the system to quickly respond to the resonance problem and avoid damage to electrical equipment or degradation of system performance caused by resonance. By optimizing the dynamic response of the system through the controller, it can be ensured that the system can maintain good stability and performance under different operating conditions. For example, by appropriately adjusting the control algorithm, the converter system can still maintain a fast response and effectively suppress harmonics under load fluctuations, environmental changes, or external disturbances. Through the precise design of mathematical modeling and control algorithms, the robustness of the multi-module converter system under different working conditions can be improved, ensuring that the resonance suppression effect in practical applications is not affected by environmental changes or uncertain factors. Through the real-time monitoring and frequency identification mechanism, the system can adjust the control strategy according to the frequency characteristics of resonance, thereby achieving more flexible and adaptive resonance suppression. This adaptive ability enables the system to automatically adjust control parameters under various working conditions to cope with different resonance modes and changes. As described in step S1 above, the multi-module converter includes several sub-modules, and each sub-module includes a half-bridge or full-bridge circuit and a corresponding capacitor. By monitoring the state of each sub-module, the state function is as follows: ; where is the capacitor voltage of the sub-module, is the sub-module capacitor, is the current flowing into the sub-module, is the charging and discharging current of the capacitor; the adaptive controller adjusts the control parameters in real time according to the system state to adapt to parameter changes and external disturbances. An adaptive PID controller can be used, and its parameters are dynamically adjusted according to the system state. The predictive control algorithm establishes a predictive model of the system, predicts the system state in advance and takes control measures. A model predictive control algorithm can be used, and its predictive model can be linear or non-linear, and the system is simulated and verified. Its simulation steps include: establishing a simulation model of the system, including multi-module converters, loads, power grids, etc.; simulating different working conditions, such as load changes, grid fluctuations, etc.; analyzing the simulation results to verify the effectiveness of the control algorithm; obtaining the simulation effect according to the control effect, and optimizing the control parameters and algorithms according to the simulation effect. The experimental platform is to construct an actual multi-module converter experimental platform, including hardware and software parts. Its test steps include: implementing the control algorithm verified by simulation on the experimental platform; conducting experimental tests and recording the responses of the system under different working conditions; analyzing the experimental data to verify the actual effect of the control algorithm; further optimizing the control algorithm and system parameters according to the experimental results; through the above steps, a detailed mathematical model of the multi-module converter system can be established, and an effective control strategy can be designed to achieve harmonic suppression, improve dynamic response and enhance the robustness of the system.These steps and methods are the basis for the design of a resonant suppression system based on a control strategy and can be appropriately adjusted and optimized according to specific applications. By designing a control algorithm to actively regulate the switching state of the converter, the dynamic damping of the system is increased to suppress resonance. This includes injecting reverse harmonic current to cancel the resonant current and repeating the same control action in each cycle to suppress periodic resonance. By adjusting the switching state of the converter in real time, the control algorithm can actively intervene in the resonant phenomenon of the system instead of simply relying on passive suppression. This active regulation mechanism enables the system to flexibly respond to different resonant frequencies and harmonic characteristics, thus significantly improving the suppression effect. Dynamic damping refers to increasing the damping of the system through control means to reduce or eliminate system oscillations and resonant phenomena. Actively adjusting the switching state can increase the dynamic damping of the system, enabling the system to quickly suppress oscillations and return to a stable state when subjected to interference or resonant excitation. By enhancing the damping, the system can not only effectively reduce the amplitude of resonance but also accelerate the response speed, reduce the transient process of the system, and improve the overall performance. By repeating the same control action in each cycle, periodic resonance can be effectively suppressed. The control algorithm applies appropriate control signals in each cycle based on the periodic characteristics of the system to ensure accurate suppression of resonance in each cycle. This control strategy is particularly suitable for periodic resonance problems such as harmonic pollution in power systems and can effectively prevent the accumulation or deterioration of resonant phenomena. Traditional resonant suppression methods often rely on filters or passive components, which perform poorly in suppressing resonances with unstable frequencies and amplitudes and cannot be flexibly adjusted during system dynamic changes. However, the method of actively adjusting the switching state and injecting reverse harmonic current can respond to system changes in real time and adapt to resonant conditions under different operating conditions, thus overcoming the limitations of traditional methods. By precisely adjusting the converter switching state and reverse harmonic injection, the system can reduce the loss of useless energy in a timely manner when resonance occurs, improving the overall efficiency. Compared with traditional passive filters and resonant suppression methods, this method can be adjusted in real time, maximize the energy efficiency of the system while suppressing resonance, adjust control parameters according to the system state in real time, enhance the dynamic stability of the system, use a predictive control algorithm to predict the occurrence of resonance and take measures in advance to suppress it, verify the effectiveness of the adopted control algorithm in a simulation environment, and suppress resonance under various operating conditions. By designing a fault-tolerant control strategy to handle abnormal situations in the system, where the abnormal situations include sensor failures and communication interruptions. By adjusting control parameters in real time, the system can dynamically adjust the control strategy according to the current state (such as voltage, current, harmonic frequency, etc.). This flexibility can ensure that the system always maintains stability in the face of different load changes and disturbances. Before resonance occurs, the predictive control algorithm can identify possible resonant trends in advance, and then adjust control parameters to actively take measures to suppress resonance.Compared with traditional passive suppression methods, this predictive control can effectively reduce the response time, avoid severe oscillations in the system. The predictive control algorithm can predict future resonance trends based on the historical data and current state of the system, make adjustments in advance, and thus effectively reduce the probability of resonance occurrence. This predictive design can take necessary control measures before resonance occurs in the system, thereby reducing the impact of resonance in practical applications, avoiding large overshoots and oscillations. The fault-tolerant control strategy can handle abnormal situations in the system, such as sensor failures, communication interruptions, etc. Traditional methods often lead to control failures or performance degradation when facing these faults, while through fault-tolerant control, in the case of sensor data loss or communication interruption, redundant information can be used or the system can continue to maintain normal operation through methods such as system self-correction. By adjusting control parameters in real time, the system can automatically adapt according to different loads, environmental conditions, and equipment states. In the converter system, factors such as load fluctuations, input voltage changes, and environmental temperature may affect the resonance characteristics, and real-time parameter adjustment enables the system to flexibly respond to these changes, ensuring long-term stable operation. By actively suppressing resonance and reducing excessive oscillations in the system, the energy waste and equipment losses caused by resonance can be significantly reduced. Compared with traditional passive filters, the active control strategy can more precisely adjust the system operation state and improve the energy utilization efficiency of the system.

[0090] In one embodiment, the mathematical modeling S1 of the multi-module converter system includes:

[0091] S11. Analyze the overall behavior of the multi-module converter, and build a model according to the DC side or the AC side. The DC side model is as follows:

[0092] ;

[0093] Where, is the DC bus voltage, is the DC bus capacitor, is the DC input current, is the DC output current;

[0094] The AC side model is as follows:

[0095] ;

[0096] ;

[0097] Where, is the AC side voltage, is the AC side current, is the grid voltage, is the AC side resistance, is the AC side inductance, is the AC-side filtering capacitor, is the load current.

[0098] As described in the above step S11, the converter generally includes a DC side, an AC side, and an intermediate circuit section. Assuming that we are using a three-phase voltage source converter, the model can include the following parts: DC side model: DC voltage source, DC filtering capacitor, DC load; AC side model: three-phase AC power source, AC filtering inductor and capacitor, three-phase AC load; switch model: a switch network composed of IGBTs (Insulated Gate Bipolar Transistors) or MOSFETs (Metal Oxide Semiconductor Field Effect Transistors), controlling the power transfer of the converter; outer loop control: controlling the DC side voltage or AC side power; inner loop control: controlling the current loop to ensure that the current tracks the command value.

[0099] In one embodiment, the mathematical modeling S1 of the multi-module converter system further includes:

[0100] S12. Reducing the harmonic components in the system and improving the waveform quality of the output voltage and current;

[0101] S13. By injecting reverse harmonic current to cancel the resonant current and repeating the same control action in each cycle to suppress periodic resonance;

[0102] S14. Adding an LCL filter to the system and designing a corresponding control algorithm to filter out harmonics, improve the dynamic response speed of the system, and ensure that it can quickly recover stability under conditions such as load changes and grid fluctuations;

[0103] S15. Adjusting the control parameters in real time according to the system state, enhancing the dynamic response of the system, using a predictive control algorithm to predict the changes in the system in advance and taking measures;

[0104] S16. The proportional-resonant controller has a high gain at a specific frequency and can effectively suppress resonance. Its expression is as follows:

[0105] ;

[0106] Where, is the complex frequency domain variable in the Laplace transform, is the proportional gain, is the resonant gain, is the resonant frequency;

[0107] S17. The repetitive controller eliminates periodic harmonics by periodically injecting the same control signal. Its expression is as follows:

[0108] ;

[0109] Where, is the period number of the system, is the forgetting factor, is the transformation variable of the discrete-time system, representing the discrete frequency characteristics of the system.

[0110] As described in the above steps S12 - S17, the present invention implements the above control algorithm by using a digital signal processor or a field - programmable gate array. Specifically, it collects voltage and current signals, performs digital signal processing or wavelet transform, detects the peaks in the spectrum, identifies the resonant frequency, and selects the corresponding control strategy (such as a PR controller, a repetitive controller) according to the identified resonant frequency, and adjusts the control parameters in real - time to suppress resonance. Sensor and data acquisition card: Ensure the stable connection between the sensor and the data acquisition card, and set a reasonable sampling frequency. Controller and actuator: Ensure the stable communication between the controller and the actuator of the converter (such as the drive circuit of the switching device), and the control signal output by the controller can be transmitted to the actuator quickly and accurately. Experimental platform: Build an actual multi - module converter experimental platform, including hardware and software parts. Signal acquisition: Use sensors and data acquisition cards to collect the voltage and current waveforms of the system in real - time. Signal analysis: Use a digital signal processor or wavelet transform to analyze the collected signals to detect whether there is a resonance phenomenon. Frequency identification: Identify the resonant frequency and record relevant data. Control strategy implementation: Select and implement the corresponding control strategy according to the identified resonant frequency. System response analysis: Record the response of the system before and after the implementation of the control strategy, and obtain the control effect according to the response. Parameter optimization: Optimize the control parameters and algorithms according to the experimental results to improve the control effect. Over - voltage protection: Detect whether the voltage exceeds the safe range. If it does, immediately turn off the converter. Over - current protection: Detect whether the current exceeds the safe range. If it does, immediately turn off the converter. Real - time display: Real - time display of key parameters of the system such as voltage, current, temperature, etc., and the running status of the control algorithm through a monitoring interface. Log record: Record the system operation log for easy troubleshooting and system debugging. The present invention improves the waveform quality of the output voltage and current by reducing the harmonic components in the system. By injecting reverse harmonic current to cancel the resonant current, the same control action is repeated in each cycle to suppress periodic resonance. By reducing the harmonic components, the output voltage and current waveforms can be made closer to the ideal sine waveform, reducing the interference of harmonics on the system. Injecting reverse harmonic current can effectively cancel the resonant current, thus reducing the resonance phenomenon in the system. Due to the reduction of harmonics and resonance, the reactive power and losses in the system can be effectively controlled, improving the use efficiency of electric energy, reducing unnecessary heat loss and energy waste. By suppressing periodic resonance, the dynamic response of the system under different working conditions can be optimized, reducing the system instability caused by harmonics and resonance, especially when the load changes or the input voltage fluctuates greatly, and the stable operation of the system can be maintained. An LCL filter is added to the system, and the corresponding control algorithm is designed to filter out harmonics and improve the dynamic response speed of the system, ensuring that it can quickly recover stability under conditions such as load changes and grid fluctuations. Adjust the control parameters in real - time according to the system state to enhance the dynamic response of the system. Use a predictive control algorithm,Predict system changes in advance and take measures. The proportional-resonant controller has a high gain at a specific frequency, effectively suppressing resonance. The repetitive controller eliminates periodic harmonics by periodically injecting the same control signal. By reducing the harmonic content in the output current or voltage, the waveform quality of the power system is improved, and the interference of harmonics to load devices, sensors, and other sensitive devices is reduced. Design a mechanism for real-time adjustment of control parameters so that the system can quickly respond to the current state (such as load changes, grid fluctuations, etc.) and optimize its operating point, quickly returning to a stable state. This can greatly improve the dynamic response speed of the system, especially when the load changes or the grid fluctuates greatly, avoiding long-term excessive oscillation or unstable state of the system. Dynamic parameter adjustment can ensure that the controller compensates for system parameter changes in a timely manner, avoiding instability caused by system lag or parameter mismatch. The predictive control algorithm enables the system to predict future system state changes in advance, inferring future dynamic behavior based on the current state and historical data. Predictive control can not only reduce the delay of the system in responding to external disturbances (such as grid fluctuations or load mutations), but also optimize the control strategy to intervene before resonance or instability occurs. The repetitive controller eliminates periodic harmonics by periodically injecting the same control signal, effectively eliminating harmonic problems caused by periodic interference, thereby effectively improving the harmonic filtering ability, dynamic response speed, and system stability of the system.

[0111] In one embodiment, the real-time monitoring of the voltage and current waveforms of the system by the sensor and the controller in S2 includes:

[0112] S21. Measuring the DC bus voltage and the AC side voltage through a voltage sensor;

[0113] S22. Measuring the DC side current and the AC side current through a current sensor;

[0114] S23. Setting a high-speed data acquisition card with a high sampling rate and high precision to collect sensor data in real time, ensuring the real-time and reliability of data transmission from the sensor to the controller;

[0115] S24. Preprocessing the collected signals, including filtering, to remove high-frequency noise and retain signals within a specific frequency range for easy resonance detection;

[0116] S25. Converting the analog signal to a digital signal, identifying and selecting the corresponding sampling frequency to ensure that the frequency components of the resonance signal can be captured. The sampling frequency should be at least twice the resonance frequency or more.

[0117] As described in the above steps S21 - S25, the present invention measures the DC bus voltage and the AC side voltage through a voltage sensor, measures the DC side current and the AC side current through a current sensor, and by setting a high-speed data acquisition card with high sampling rate and high precision, it can collect sensor data in real time to ensure the real-time and reliability of data transmission from the sensor to the controller. Through the voltage and current sensors, it can monitor the DC bus voltage, the AC side voltage, the DC side current, and the AC side current in real time. These data can reflect the operating state of the system in real time, especially in dynamic change situations (such as load mutation, grid fluctuation, etc.). The high sampling rate and high-precision data acquisition card ensure the real-time and reliability of data transmission, and can capture the dynamic changes of the system within milliseconds. The real-time nature of the data acquisition system ensures that the data transmission delay from the sensor to the controller is minimized, thereby improving the response speed of the control algorithm. By continuously obtaining real-time data, the control system can detect unstable or abnormal states in a timely manner and intervene quickly, such as adjusting the control signal or modifying the filter settings, to ensure that the system does not resonate or exhibit other unstable phenomena. The real-time transmitted data enables the controller to understand the change trend of the system in a timely manner, and then implement precise dynamic compensation. By finely adjusting the output of the controller, it can effectively suppress the resonance or excessive fluctuation caused by the change of the system state and optimize the dynamic response of the system. By continuously collecting real-time data, the control system can dynamically adjust the control algorithm parameters based on historical data and the current state, making the response of the system faster and more accurate. For example, it can quickly adjust the filter parameters or control strategy when the load changes or the grid fluctuates, and suppress the possible resonance. Preprocessing the collected signals, including filtering, is used to remove high-frequency noise and retain the signals within a specific frequency range for easy resonance detection. Convert the analog signal to a digital signal, identify and select the corresponding sampling frequency to ensure that the frequency components of the resonance signal can be captured. The sampling frequency should be at least twice the resonance frequency or more. Filtering can effectively remove the high-frequency noise in the collected signal and only retain the valid signals within a specific frequency range. Through filter design, the target frequency range of the resonance signal can be selectively retained, enabling the system to accurately capture the frequency components of the resonance frequency and avoid interference from signals in other frequency bands. For applications that require precise analysis and identification of resonance signals, concentrating on processing and amplifying the target signal helps to improve the sensitivity and accuracy of the analysis. After converting the analog signal to a digital signal, it is convenient for the digital controller to perform calculations, analysis, and adjustment. Digital signals have higher precision and can eliminate the errors and instabilities that may occur in analog signals, thereby greatly improving the control precision and reliability. The sampling frequency is at least twice the resonance frequency or more (meeting the Nyquist sampling theorem) to ensure that the digitalized signal can accurately capture the frequency components of the resonance signal without distortion or aliasing. A reasonable sampling frequency ensures the integrity of the signal, avoids the loss of high-frequency information, and provides sufficient data support for subsequent signal analysis.Through high-precision signal processing and digital control, more accurate resonance detection and feedback control can be achieved in the system, which helps to improve the dynamic response of the system and enhance the ability to suppress resonance. Digital signal processing can perform fast calculations more efficiently, reduce control delay, and improve the system response speed, which is particularly important for dynamically changing resonance signals and can timely adjust the system state to avoid excessive oscillation or instability.

[0118] In one embodiment, the conversion of the analog signal to a digital signal and the identification and selection of the corresponding sampling frequency include:

[0119] S31. Convert the time-domain signal to a frequency-domain signal and analyze the peaks in the spectrum:

[0120] S32. Collect voltage and current waveform data within a period of time and perform Fourier transform on the collected data;

[0121] S33. Analyze the spectrogram, find the peaks of the harmonic components, and determine whether the peaks exceed a preset threshold;

[0122] If the peak exceeds the preset threshold, it is considered that there is a resonance phenomenon in the system;

[0123] S34. Perform time-frequency domain analysis, accurately identify transient resonance phenomena, and select appropriate wavelet basis functions;

[0124] S35. Perform wavelet transform on the collected data, analyze the wavelet coefficients, and find the peaks of the harmonic components;

[0125] S36. If the peak exceeds the preset threshold, it is considered that there is a resonance phenomenon in the system;

[0126] S37. In the spectrogram of Fourier or wavelet transform, find the peak frequency of the harmonic components, which is the resonance frequency:

[0127] S38. Calculate the spectrogram, find the maximum peak in the spectrogram, and identify the sampling frequency corresponding to the peak.

[0128] As described in the above steps S31 - S38, the present invention converts the time - domain signal into a frequency - domain signal, analyzes the peaks in the spectrum, collects the voltage and current waveform data over a period of time, performs Fourier transform on the collected data, analyzes the spectrogram, finds the peaks of the harmonic components, and determines whether the peaks exceed a preset threshold. If the peaks exceed the preset threshold, it is considered that there is a resonance phenomenon in the system. By converting the time - domain signal into a frequency - domain signal, Fourier transform can effectively decompose the various frequency components of the signal, enabling the clear identification of whether there are harmonic components in the system. If the peak values of certain frequencies in the system exceed the preset threshold, the resonance phenomenon corresponding to that frequency can be directly determined. Compared with the traditional time - domain analysis, this method can more accurately identify the specific frequency and amplitude of the resonance. Fourier transform can provide real - time data in the frequency domain, enabling the system to monitor possible resonance phenomena during operation and make timely adjustments when abnormalities occur. By analyzing the spectrogram, it can adapt to different working conditions and identify the harmonic components under different working conditions.For example, under the influence of load fluctuations, system parameter changes, or external disturbances, potential resonance problems can still be detected through frequency-domain signal processing. After combining frequency-domain analysis with modern digital signal processing and automatic control technologies, when a resonance phenomenon is detected, a control algorithm can be quickly enabled for intervention. By adjusting the working state of the system or enabling resonance suppression measures, the influence of resonance can be effectively reduced or eliminated, further improving the stability and reliability of the system. The spectrogram can be archived for a long time and used for historical data analysis, which helps to monitor the operating state of the system in the long term and compare the resonance trends in history. Perform time-frequency domain analysis, accurately identify transient resonance phenomena, select appropriate wavelet basis functions, perform wavelet transform on the collected data, and analyze the wavelet coefficients to find the peak value of the harmonic component. If the peak value exceeds the preset threshold, it is considered that there is a resonance phenomenon in the system. In the spectrogram of Fourier or wavelet transform, find the peak frequency of the harmonic component, which is the resonance frequency. Calculate the spectrogram, find the maximum peak value in the spectrogram, and identify the frequency corresponding to the peak value. Through time-frequency domain analysis (such as wavelet transform), the changes of transient signals can be captured more accurately, while Fourier transform focuses more on the spectral analysis of steady-state signals. Transient resonance usually manifests as amplitude fluctuations and frequency changes within a short period of time. Time-frequency domain methods can effectively distinguish these transient characteristics. Wavelet transform can provide information about both time and frequency, and is particularly suitable for processing non-stationary signals and transient phenomena. Selecting appropriate wavelet basis functions can effectively extract harmonic components, especially identifying peak values near the resonance frequency, avoiding the limitations of Fourier transform (poor analysis ability of Fourier transform for transient signals). Wavelet transform has the ability of multi-resolution analysis and can view the details of signals at different scales, which helps in feature extraction during dynamic changes. Through Fourier transform and wavelet transform, the spectrogram of the system can be obtained, and the peak value of the harmonic component can be extracted from it. By monitoring the frequency peak in the spectrum, it is possible to accurately determine whether the system is in a resonant state.

[0129] In one embodiment, verifying the effect of the adopted control algorithm in a simulation environment and suppressing resonance under various working conditions, and dealing with abnormal situations in the system by designing a fault-tolerant control strategy, S5 includes:

[0130] S51. Verify the voltage and current waveforms of the simulation system under normal operating conditions;

[0131] S52. Verify the resonance suppression effect of the control algorithm under normal working conditions, and simulate sensor failures and communication interruptions;

[0132] S53. Verify the system stability of the fault-tolerant control strategy under fault conditions, and record the responses of the system before and after the implementation of the control strategy, where the responses include voltage, current waveforms, and system states;

[0133] S54. Obtain the control effect according to the response, where the control effect includes the resonance suppression speed and the system recovery time;

[0134] S55. Obtain the simulation effect according to the control effect, and optimize the control parameters according to the simulation effect to improve the control effect;

[0135] S56. Adjust the thresholds and default control inputs in the fault-tolerant control strategy to ensure the stability and reliability of the system under various fault conditions.

[0136] As described in the above steps S51 - S56, the present invention verifies the voltage and current waveforms of the simulation system under normal operating conditions to verify the resonance suppression effect of the control algorithm under normal working conditions, and verifies the system stability of the fault - tolerant control strategy under fault conditions by simulating sensor faults and communication interruptions, and records the responses of the system before and after the implementation of the control strategy, where the responses include voltage, current waveforms and system states. By simulating the voltage and current waveforms under normal working conditions through the simulation system, the effect of the control algorithm in resonance suppression can be intuitively verified. If the simulation system successfully suppresses resonance and can maintain the stability of the voltage and current waveforms, it indicates that the design of the control algorithm is effective. The simulation environment can help designers quickly adjust control algorithm parameters, such as feedback gain, resonance suppression frequency, etc., in order to achieve better performance in the actual system. This verification method reduces the uncertainty in the experimental process and improves the robustness and adaptability of the algorithm. By simulating fault conditions such as sensor faults or communication interruptions, it can be verified whether the fault - tolerant control strategy can still maintain system stability without complete information, which is difficult for many traditional control methods because many traditional methods assume that the system can obtain complete and accurate sensor data at all times. The fault - tolerant control strategy ensures that the system can still operate normally when hardware or communication faults occur, thus preventing system crashes caused by single - point failures. The simulation system can help quickly identify the delay problems of the control algorithm, especially when responding to resonance signals, problems such as feedback delay or over - response may occur. Different control strategies (such as predictive control, model predictive control, etc.) can be tested through simulation to optimize the response time of the system and reduce the negative impact of delay on the resonance suppression effect. Obtain the control effect according to the response, where the control effect includes resonance suppression speed and system recovery time. Obtain the simulation effect according to the control effect, and optimize the control parameters according to the simulation effect to improve the control effect. Adjust the thresholds and default control inputs in the fault - tolerant control strategy to ensure the stability and reliability of the system under various fault conditions. By optimizing control parameters, such as adjusting the gain and resonance frequency, the resonance suppression speed can be significantly improved. Adjust the thresholds and default control inputs in the fault - tolerant control strategy to ensure that the system suppresses resonance more accurately and timely, so that it can respond and stabilize the system faster in practical applications. By improving the control algorithm and adjusting the control parameters, the system can be accelerated to recover from disturbances or faults. For example, when a fault occurs, through the adjustment of the fault - tolerant control strategy, the system can quickly stabilize, avoiding long - term downtime or unstable states. The optimized control parameters can make the system quickly return to the normal working state after encountering disturbances, reducing the recovery time and improving the availability and stability of the system. By optimizing the fault - tolerant control strategy, especially by adjusting the thresholds and default control inputs, the system can better cope with different fault or disturbance conditions, which enables the system to operate efficiently under various working conditions, reduces the probability of faults and improves the robustness of the system.

[0137] This application also provides a resonant suppression system for a multi-module converter of a mobile energy storage system, including:

[0138] A mathematical modeling module for mathematically modeling the multi-module converter system, including the electrical parameters and topological structures of each module, and clarifying the control objectives of the system, including harmonic suppression, dynamic response, and robustness;

[0139] A real-time monitoring module for real-time monitoring of the voltage and current waveforms of the system through sensors and controllers, detecting whether there is a resonance phenomenon, and when resonance is detected, further identifying the resonance frequency and taking corresponding control measures;

[0140] A suppression module for designing a control algorithm to actively adjust the switching state of the converter, increase the dynamic damping of the system, and suppress resonance, including injecting reverse harmonic current to cancel the resonance current, and repeating the same control action in each period to suppress periodic resonance;

[0141] An adjustment module for real-time adjusting the control parameters according to the system state, enhancing the dynamic stability of the system, using a predictive control algorithm to predict the occurrence of resonance and taking measures in advance to suppress it;

[0142] A control module for verifying the effectiveness of the adopted control algorithm in a simulation environment and suppressing resonance under various working conditions, and dealing with abnormal situations in the system by designing a fault-tolerant control strategy, where the abnormal situations include sensor failures and communication interruptions.

[0143] In one embodiment, a resonant suppression system for a multi-module converter of a mobile energy storage system further includes:

[0144] A data acquisition module for real-time collecting key parameters such as voltage, current, and temperature in the system, transmitting the data collected by the sensors to the control unit, and using a high-speed communication protocol;

[0145] A real-time monitoring and diagnosis module for preprocessing the collected signals, such as filtering and sampling, to improve the accuracy and reliability of the signals, using signal analysis methods such as Fourier transform and wavelet transform to real-time detect whether there is a resonance phenomenon in the system, and diagnosing the cause of resonance after detecting resonance;

[0146] A control strategy module for designing and implementing an active damping control algorithm to increase the dynamic damping of the system and suppress resonance by adjusting the switching state of the converter, using a predictive control algorithm to predict the occurrence of resonance in advance and taking measures to suppress it, and designing an adaptive control algorithm to real-time adjust the control parameters according to the system state to enhance the dynamic stability of the system;

[0147] The parameter optimization module uses an optimization algorithm to optimize the control parameters to improve the control effect. According to the system operating state, it adjusts the control parameters in real time to ensure that the performance of the control algorithm remains optimal under various working conditions;

[0148] The communication and coordination module ensures efficient data exchange and command transmission between each module, realizes the coordinated control of the multi-module converter, and optimizes the performance of the overall system;

[0149] The execution and drive module is responsible for driving the switching devices of the converter, performing switching operations according to control instructions, and protecting the converter in a timely manner to prevent equipment damage when the system has an abnormality.

[0150] In the above, the system provides a user-friendly operation interface, which is convenient for users to set control parameters, view the system status, etc., and displays key parameters such as the voltage, current, and temperature of the system in real time, as well as the operating status of the control algorithm. Records the operating data and control logs of the system for subsequent analysis and troubleshooting. Integrates each module into an overall system to ensure the compatibility and collaborative work between each module. Conducts system tests in the laboratory and actual environment to verify the performance and reliability of the resonance suppression system. Through the collaborative work of these modules, the resonance suppression of the multi-module converter of the mobile energy storage system can be effectively achieved, and the stability and performance of the system can be improved. The specific module design and implementation method can be adjusted and optimized according to the actual application scenario and technical requirements.

[0151] In one embodiment, the real-time monitoring module includes:

[0152] The first measurement unit is used to measure the DC bus voltage and the AC side voltage through a voltage sensor;

[0153] The second measurement unit is used to measure the DC side current and the AC side current through a current sensor;

[0154] The acquisition unit is used to set a high-speed data acquisition card with a high sampling rate and high precision to acquire sensor data in real time, ensuring the real-time and reliability of data transmission from the sensor to the controller;

[0155] The preprocessing unit is used to preprocess the acquired signals, including filtering processing, which is used to remove high-frequency noise and retain signals within a specific frequency range for easy resonance detection;

[0156] The conversion unit is used to convert analog signals into digital signals, identify and select the corresponding sampling frequency to ensure that the frequency components of the resonance signal can be captured, and the sampling frequency should be at least twice the resonance frequency or more.

[0157] The present invention also provides a computer device, including a memory and a processor, where the memory stores a computer program, and when the processor executes the computer program, the steps of the above-mentioned resonance suppression method for the multi-module converter of the mobile energy storage system are implemented.

[0158] The present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above-mentioned resonance suppression method for the multi-module converter of the mobile energy storage system are implemented.

[0159] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. 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 above embodiments of the various methods. Among them, any reference to a memory, storage, database, or other medium provided in the present application and used in the embodiments can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be obtained in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double 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 (RDRAM), etc.

[0160] It should be noted that in this article, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, device, article or method. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of another identical element in the process, device, article or method including that element.

[0161] The above are only the preferred embodiments of the present invention, and do not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of the present invention.

Claims

1. A method for suppressing resonance of a multi-module converter in a mobile energy storage system, characterized in that Including: Performing mathematical modeling on a multi-module converter system, including constructing the electrical parameters and topological structure of each module, and determining the control objectives of the multi-module converter system, where the control objectives include harmonic suppression, dynamic response, and robustness; Real-time monitoring of the voltage and current waveforms of the multi-module converter system through sensors and controllers, detecting whether there is a resonance phenomenon. When a resonance phenomenon is detected, further identifying the resonance frequency and taking corresponding control measures according to the identified resonance frequency; Designing a control algorithm to actively adjust the switching state of the converter, detecting the resonance frequency in the multi-module converter system, generating reverse harmonic current according to the resonance frequency, and inputting the reverse harmonic current into the multi-module converter system through the control algorithm to increase the dynamic damping of the multi-module converter system. Repeat the above control algorithm within each resonance period to suppress periodic resonance; Adjusting the control parameters in real time according to the state of the multi-module converter system to enhance the dynamic stability of the multi-module converter system, using a predictive control algorithm to predict the occurrence of resonance and taking measures in advance to suppress it; Verifying the effectiveness of the adopted control algorithm in a simulation environment and suppressing resonance under various working conditions. By designing a fault-tolerant control strategy, dealing with abnormal situations in the multi-module converter system, where the abnormal situations include sensor failures and communication interruptions; The real-time monitoring of the voltage and current waveforms of the system through sensors and controllers includes: Converting the analog signal into a digital signal, identifying and selecting the corresponding sampling frequency to ensure that the frequency components of the resonance signal can be captured, and the sampling frequency should be at least twice the resonance frequency or more; The converting the analog signal into a digital signal and identifying and selecting the corresponding sampling frequency includes: Converting the time-domain signal into a frequency-domain signal and analyzing the peaks in the spectrum; Collecting the voltage and current waveform data for a period of time and performing Fourier transform on the collected data; Analyzing the spectrogram, finding the peak of the harmonic component, and judging whether the peak exceeds a preset threshold; If the peak exceeds the preset threshold, it is considered that there is a resonance phenomenon in the system; Performing time-frequency domain analysis to accurately identify transient resonance phenomena and selecting appropriate wavelet basis functions; Performing wavelet transform on the collected data and analyzing the wavelet coefficients to find the peak of the harmonic component; If the peak exceeds the preset threshold, it is considered that there is a resonance phenomenon in the system; In the spectrogram of Fourier or wavelet transform, finding the peak frequency of the harmonic component, which is the resonance frequency; Calculating the spectrogram, finding the maximum peak in the spectrogram, and identifying the sampling frequency corresponding to the peak; 2. The method for suppressing resonance of a multi-module converter in a mobile energy storage system according to claim 1, wherein The performing mathematical modeling on the multi-module converter system includes: analyzing the overall behavior of the multi-module converter, building a model according to the DC side or the AC side, where the DC side model is as follows: ； Among them, is the DC bus voltage, is the DC bus capacitor, is the DC input current, is the DC output current; Where the AC side model is as follows: ； ； Among them, is the AC side voltage, is the AC side current, is the grid voltage, is the AC side resistance, is the AC side inductance, is the AC side filter capacitor, is the load current.

3. The method for suppressing resonance of a multi-module converter in a mobile energy storage system according to claim 1, characterized in that, The performing mathematical modeling on the multi-module converter system also includes: Reducing the harmonic components in the system and improving the waveform quality of the output voltage and current; By injecting reverse harmonic current to cancel the resonance current, repeating the same control action within each period to suppress periodic resonance; Add an LCL filter to the system and design the corresponding control algorithm to filter out harmonics, improve the dynamic response speed of the system, and ensure that it can quickly restore stability under load changes and grid fluctuations; Adjust the control parameters in real time according to the system state to enhance the dynamic response of the system. Use the predictive control algorithm to predict the changes in the system in advance and take measures; The proportional-resonant controller has a high gain at a specific frequency and can effectively suppress resonance. Its expression is as follows: ； Among them, is the complex frequency domain variable in the Laplace transform, is the proportional gain, resonant gain, is the resonant frequency; The repetitive controller eliminates periodic harmonics by periodically injecting the same control signal. Its expression is as follows: ； Among them, is the period number of the system, is the forgetting factor, is the transformation variable of the discrete-time system, representing the discrete frequency characteristics of the system.

4. The method for suppressing resonance of a multi-module converter in a mobile energy storage system according to claim 1, characterized in that The voltage and current waveforms of the system are monitored in real time through sensors and controllers, and it also includes: Measure the DC bus voltage and the AC side voltage through a voltage sensor; Measure the DC side current and the AC side current through a current sensor; Set a high-speed data acquisition card with a high sampling rate and high precision to collect sensor data in real time, ensuring the real-time and reliability of data transmission from the sensor to the controller; Preprocess the collected signals, including filtering to remove high-frequency noise and retain signals within a specific frequency range for easy resonance detection.

5. The method for suppressing resonance of a multi-module converter in a mobile energy storage system according to claim 1, wherein Verify the effectiveness of the adopted control algorithm in the simulation environment and suppress resonance under various working conditions. By designing a fault-tolerant control strategy, handle abnormal situations in the multi-module converter system, including: Obtain the voltage and current waveforms under normal operating conditions through the verified simulation system; Verify the resonance suppression effect of the control algorithm under normal working conditions and simulate sensor faults and communication interruptions; Verify the system stability of the fault-tolerant control strategy under fault conditions and record the response of the system before and after the implementation of the control strategy, where the response includes voltage, current waveforms, and system status; Obtain the control effect according to the response, and the control effect includes resonance suppression speed and system recovery time; Obtain the simulation effect according to the control effect and optimize the control parameters according to the simulation effect to improve the control effect; Adjust the thresholds and default control inputs in the fault-tolerant control strategy to ensure the stability and reliability of the system under various fault conditions.

6. A resonant suppression system for a multi-module converter of a mobile energy storage system, characterized in that, It includes: A mathematical modeling module for mathematical modeling of the multi-module converter system, including the electrical parameters and topological structure of each module, and clarifying the control objectives of the system, including harmonic suppression, dynamic response, and robustness; A real-time monitoring module for monitoring the voltage and current waveforms of the system in real time through sensors and controllers, detecting whether there is a resonance phenomenon. When resonance is detected, further identify the resonance frequency and take corresponding control measures; A suppression module for designing a control algorithm to actively adjust the switching state of the converter, increase the dynamic damping of the system, and suppress resonance, including injecting reverse harmonic current to cancel the resonance current and repeating the same control action in each cycle to suppress periodic resonance; An adjustment module for adjusting the control parameters in real time according to the system state to enhance the dynamic stability of the system. Use the predictive control algorithm to predict the occurrence of resonance and take measures in advance to suppress it; A control module, which is used to verify the effect of the adopted control algorithm in a simulation environment, suppress resonance under various working conditions, and handle abnormal situations in the system by designing a fault-tolerant control strategy, where the abnormal situations include sensor failures and communication interruptions; The real-time monitoring module includes: A conversion unit, which is used to convert analog signals into digital signals, identify and select corresponding sampling frequencies, ensure that the frequency components of resonance signals can be captured, and the sampling frequency should be at least twice the resonance frequency or more; The conversion unit converts analog signals into digital signals and identifies and selects corresponding sampling frequencies, including: Converting the time-domain signal into a frequency-domain signal and analyzing the peaks in the spectrum; Collecting voltage and current waveform data over a period of time and performing Fourier transform on the collected data; Analyzing the spectrogram, finding the peaks of the harmonic components, and determining whether the peaks exceed a preset threshold; If the peaks exceed the preset threshold, it is considered that there is a resonance phenomenon in the system; Performing time-frequency domain analysis, accurately identifying transient resonance phenomena, and selecting appropriate wavelet basis functions; Performing wavelet transform on the collected data and analyzing the wavelet coefficients to find the peaks of the harmonic components; If the peak exceeds the preset threshold, it is considered that there is a resonance phenomenon in the system; In the spectrogram of Fourier or wavelet transform, finding the peak frequency of the harmonic component, which is the resonance frequency; Calculating the spectrogram, finding the maximum peak in the spectrogram, and identifying the sampling frequency corresponding to the peak.

7. The multi-module converter resonance suppression system of the mobile energy storage system according to claim 6, characterized in that The real-time monitoring module further includes: A first measurement unit, which is used to measure the DC bus voltage and the AC side voltage through a voltage sensor; A second measurement unit, which is used to measure the DC side current and the AC side current through a current sensor; An acquisition unit, which is used to set a high-speed data acquisition card with a high sampling rate and high precision to acquire sensor data in real time, ensuring the real-time performance and reliability of data transmission from the sensor to the controller; A preprocessing unit, which is used to preprocess the acquired signals, including filtering processing, which is used to remove high-frequency noise and retain signals within a specific frequency range for facilitating resonance detection; A conversion unit, which is used to convert analog signals into digital signals, identify and select corresponding sampling frequencies, ensure that the frequency components of resonance signals can be captured, and the sampling frequency should be at least twice the resonance frequency or more.

8. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method described in any one of claims 1 to 5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method described in any one of claims 1 to 5.

Images