Resonance suppression method and system for multi-module converter of mobile energy storage system

Abstract

The invention relates to the technical field of converters, in particular to a multi-module converter resonance suppression method and system for a mobile energy storage system. The dynamic response of the system is optimized through the controller, it can be ensured that the system can keep good stability and performance under different operation conditions, the robustness of the multi-module converter system under different working conditions can be improved through mathematical modeling and accurate design of a control algorithm, and the real-time monitoring and frequency recognition mechanism is adopted, so that the reliability of the multi-module converter system is improved. A control strategy can be adjusted according to frequency characteristics of resonance, active intervention can be performed on the resonance phenomenon of the system by adjusting the on-off state of the converter in real time and a control algorithm, the system can automatically adapt according to different loads, environment conditions and equipment states by adjusting control parameters in real time, long-term stable operation is ensured, and the system is safe and reliable. By actively suppressing resonance and reducing excessive oscillation of the system, 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 in particular to a method and system for suppressing resonance of a multi-module converter of a mobile energy storage system. Background Art

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

[0003] Traditional resonance suppression methods mainly rely on hardware-level design, such as adding resonance suppression filters. Although this can alleviate the resonance problem to a certain extent, it also brings negative effects such as increased cost, increased volume, and increased system complexity. In recent years, resonance suppression methods based on control strategies have received widespread 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 the resonance problem in theory, they still face many challenges in practical applications, such as the delay problem of the control algorithm, the optimization of the system's dynamic response, and the robustness under different working conditions. Therefore, developing a more efficient and robust resonance suppression method is of great significance to 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 of 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 of a mobile energy storage system, comprising: Mathematically model 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, including harmonic suppression, dynamic response, and robustness; The voltage and current waveforms of the multi-module converter system are monitored in real time through sensors and controllers to detect whether there is a resonance phenomenon. When a resonance phenomenon is detected, the resonance frequency is further identified, and corresponding control measures are taken according to the identified resonance frequency; Design a control algorithm to actively adjust the switching state of the converter, detect the resonant frequency in the multi-module converter system, and generate a reverse harmonic current according to the resonant frequency. The reverse harmonic current is input into the multi-module converter system through the control algorithm to obtain the dynamic damping of the multi-module converter system. Repeat the above control action in each resonant cycle to ensure continuous offset of the resonant current. Adjust control parameters in real time according to the status of the multi-module converter system to enhance the dynamic stability of the multi-module converter system. Use predictive control algorithms to predict the occurrence of resonance and take measures to suppress it in advance. The effect of the adopted control algorithm is verified in a simulation environment, and resonance is suppressed under various working conditions. By designing a fault-tolerant control strategy, abnormal situations in the multi-module converter system are handled, where the abnormal situations include sensor failure and communication interruption.

[0006] 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, wherein the DC side model is as follows: ; in, is the DC bus voltage, is the DC bus capacitor, is the DC input current, is the DC output current; The AC test model is as follows: ; ; in, 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.

[0007] Preferably, the mathematical modeling of the multi-module converter system further comprises: Reduce the harmonic components in the system and improve the waveform quality of output voltage and current; By injecting reverse harmonic current to offset the resonant current, the same control action is repeated in each cycle to suppress periodic resonance; Add LCL filter to the system and design corresponding control algorithm to filter out harmonics, improve the dynamic response speed of the system, and ensure that stability can be quickly restored in the event of load changes, power grid fluctuations, etc. Adjust control parameters in real time according to system status, enhance the dynamic response of the system, use predictive control algorithms to predict system changes in advance and take measures; The proportional resonant controller has a higher gain at a specific frequency and effectively suppresses resonance. Its expression is as follows: ; in, is the complex frequency domain variable in Laplace transform, is the proportional gain, Resonance gain, is the resonant frequency; The repetitive controller periodically injects the same control signal to eliminate periodic harmonics. Its expression is as follows: ; in, is the period number of the system, It's the forgetting factor. is the transformation variable of the discrete-time system, representing the discrete frequency characteristics of the system.

[0008] Preferably, the real-time monitoring of the voltage and current waveforms of the system by sensors and controllers includes: The DC bus voltage and AC side voltage are measured by voltage sensors; Measuring the DC side current and the AC side current by means of current sensors; Set up a high-speed data acquisition card with high sampling rate and high precision to collect sensor data in real time and ensure the real-time and reliability of data transmission from the sensor to the controller; Preprocessing of the collected signals, including filtering, is used to remove high-frequency noise and retain signals within a specific frequency range to facilitate resonance detection; Convert the analog signal into a digital signal, identify and select the corresponding sampling frequency to ensure that the frequency component of the resonant signal can be captured. The sampling frequency should be at least twice the resonant frequency.

[0009] Preferably, converting the analog signal into a digital signal and identifying and selecting the corresponding sampling frequency comprises: Convert the time domain signal to the frequency domain and analyze the peaks in the spectrum: Collect voltage and current waveform data over a period of time, and perform Fourier transform on the collected data; Analyze the spectrum graph, find the peak value of the harmonic component, and determine whether the peak value exceeds a preset threshold; If the peak value exceeds a preset threshold, it is considered that the system has resonance; Conduct time-frequency domain analysis to accurately identify transient resonance phenomena and select appropriate wavelet basis functions; Perform wavelet transform on the collected data, analyze the wavelet coefficients, and find the peak value of the harmonic component; If the peak value exceeds the preset threshold, it is considered that the system is in resonance; In the Fourier or wavelet transformed spectrum, find the peak frequency of the harmonic component, which is the resonant frequency: Calculate the spectrogram, find the maximum peak in the spectrogram, and identify the sampling frequency corresponding to the peak.

[0010] Preferably, the method of verifying the effect of the adopted control algorithm in a simulation environment and suppressing resonance under various working conditions, and handling abnormal conditions in the multi-module converter system by designing a fault-tolerant control strategy includes: By verifying the voltage and current waveforms of the simulation system under normal operation; Verify the control algorithm’s resonance suppression effect under normal operating conditions and simulate sensor failure and communication interruption conditions; Verify the system stability of the fault-tolerant control strategy under fault conditions and record the system response before and after the control strategy is implemented, wherein the response includes voltage and current waveforms and system status; Acquire a control effect according to the response, wherein the control effect includes a resonance suppression speed and a system recovery time; Acquire a simulation effect according to the control effect, and optimize 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.

[0011] The present application also provides a mobile energy storage system multi-module converter resonance suppression system, comprising: Mathematical modeling module, used to mathematically model the multi-module converter system, including the electrical parameters and topology of each module, and to clarify the control objectives of the system, including harmonic suppression, dynamic response, and robustness; The real-time monitoring module is used to monitor the voltage and current waveforms of the system in real time through sensors and controllers to detect whether there is resonance. When resonance is detected, the resonance frequency is further identified and corresponding control measures are taken; The suppression module is used to 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 offset the resonant current and repeating the same control action in each cycle to suppress periodic resonance; The adjustment module is used to adjust the control parameters in real time according to the system status, enhance the dynamic stability of the system, and use the predictive control algorithm to predict the occurrence of resonance and take measures to suppress it in advance; The control module is used to verify the effect of the adopted control algorithm in a simulation environment and suppress resonance under various working conditions. By designing a fault-tolerant control strategy, it handles abnormal conditions in the system, where the abnormal conditions include sensor failure and communication interruption.

[0012] Preferably, a mobile energy storage system multi-module converter resonance suppression system further includes: Data acquisition module, used to collect key parameters of voltage, current and temperature in the system in real time, and transmit the data collected by the sensor to the control unit using a high-speed communication protocol; The real-time monitoring and diagnosis module pre-processes the collected signals, such as filtering and sampling, to improve the accuracy and reliability of the signals. It uses Fourier transform and wavelet transform signal analysis methods to detect whether there is resonance in the system in real time. After the resonance is detected, it diagnoses the cause of the resonance. Control strategy module, design and implement active damping control algorithm, increase the system's dynamic damping by adjusting the switching state of the converter, suppress resonance, use predictive control algorithm to predict the occurrence of resonance in advance and take measures to suppress it, design adaptive control algorithm, adjust control parameters in real time according to the system status, and enhance the dynamic stability of the system; Parameter optimization module, which uses optimization algorithms to optimize control parameters to improve control effects. It adjusts control parameters in real time according to the system operating status to ensure that the performance of the control algorithm remains optimal under various working conditions. The communication and coordination module ensures efficient data exchange and command transmission between modules, realizes coordinated control between multi-module converters, and optimizes the performance of the overall system; The execution and drive module is responsible for driving the switching devices of the converter and performing switching operations according to the control instructions. When an abnormality occurs in the system, the converter is protected in time to prevent equipment damage.

[0013] Preferably, the real-time monitoring module comprises: A first measuring unit, used for measuring a DC bus voltage and an AC side voltage through a voltage sensor; A second measuring unit, used for measuring a DC side current and an AC side current through a current sensor; The acquisition unit is used to set a high-speed data acquisition card with high sampling rate and high precision to collect sensor data in real time and ensure the real-time and reliability of data transmission from the sensor to the controller; A preprocessing unit, used for preprocessing the collected signals, including filtering processing, for removing high-frequency noise and for retaining signals within a specific frequency range to facilitate resonance detection; The conversion unit is used to convert the analog signal into a digital signal, identify and select the corresponding sampling frequency, and ensure that the frequency component of the resonant signal can be captured. The sampling frequency should be at least twice the resonant frequency.

[0014] The present invention also provides a computer device, including a memory and a processor, wherein 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.

[0015] The present invention also provides a computer-readable storage medium having a computer program stored thereon, 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.

[0016] The beneficial effects of the present invention are as follows: the present invention can timely detect the resonance phenomenon that may exist in the system by real-time monitoring the voltage and current waveforms of the system, and can ensure that the system can maintain good stability and performance under different operating conditions by optimizing the dynamic response of the system through the controller. The robustness of the multi-module converter system under different working conditions can be improved through the precise design of mathematical modeling and control algorithms. Through real-time monitoring and frequency identification mechanisms, the system can adjust the control strategy according to the frequency characteristics of the resonance, thereby achieving more flexible and adaptive resonance suppression. 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 enhancing the damping, not only the amplitude of the resonance can be effectively reduced, but also the response speed can be accelerated, reducing The system's transition process is reduced and the overall performance is improved. By repeating the same control action in each cycle, the 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 that the resonance can be accurately suppressed in each cycle. By accurately adjusting the converter switching state and reverse harmonic injection, the system can timely reduce the loss of useless energy when resonance occurs and improve the overall efficiency. By adjusting the control parameters in real time, the system can automatically adapt to different loads, environmental conditions and equipment conditions, so that the system can flexibly respond to these changes and 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. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 The figure is a schematic diagram of a method flow according to an embodiment of the present invention.

[0018] Figure 2 FIG. 1 is a schematic diagram of a device structure according to an embodiment of the present invention.

[0019] Figure 3 A schematic diagram of the internal structure of a computer device according to an embodiment of the present application.

[0020] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0021] 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.

[0022] like Figure 1-Figure 3 As shown, the present application provides a method for suppressing resonance of a multi-module converter of a mobile energy storage system, comprising: S1. Mathematically model the multi-module converter system, including the electrical parameters and topology of each module, and clarify the control objectives of the system, including harmonic suppression, dynamic response, and robustness; S2. Monitor the voltage and current waveforms of the system in real time through sensors and controllers to detect whether there is resonance. When resonance is detected, further identify the resonance frequency and take corresponding control measures; 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 offset the resonant current and repeating the same control action in each cycle to suppress periodic resonance; S4, adjust the control parameters in real time according to the system status, enhance the dynamic stability of the system, use the predictive control algorithm, predict the occurrence of resonance and take measures to suppress it in advance; S5. Verify the effect of the adopted control algorithm in a simulation environment, suppress resonance under various working conditions, and handle abnormal conditions in the system by designing a fault-tolerant control strategy, wherein the abnormal conditions include sensor failure and communication interruption.

[0023] As described in steps S1-S5 above, reverse harmonic current is injected. When there is a resonant 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 deteriorate or even become unstable. A current with the same resonant frequency but opposite phase is generated by the control algorithm and injected into the system. This current can offset the resonant 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 to periodic changes in the system in a timely manner, especially for periodic resonance phenomena. By periodically injecting reverse harmonic current, the repetitive controller can increase the dynamic damping of the system, making the system response smoother and reducing oscillations.

[0024] Dynamic damping is the ability of a system to respond to rapidly changing loads or disturbances. Increasing dynamic damping can reduce system oscillations and overshoots, making the system more stable. Resonances usually appear as periodic oscillations in the system. By increasing dynamic damping, these periodic oscillations can be effectively suppressed, thereby achieving the effect of suppressing resonances. Resonance suppression means that oscillations in the system are effectively reduced or eliminated. This not only improves system stability, but also reduces energy loss and equipment wear. After suppressing resonances, the dynamic performance of the system is significantly improved, and it can respond to load changes and external disturbances more quickly and accurately.

[0025] The resonant frequency in the system is detected by sensors or analysis tools. Based on the detected resonant frequency, a harmonic current with opposite phase is generated. The generated reverse harmonic current is injected into the system through the control algorithm. The above control action is repeated in each resonant cycle to ensure continuous cancellation of the resonant current. By periodically injecting reverse harmonic current, the system is dynamically damped in each cycle to reduce oscillation. The increase in dynamic damping effectively suppresses the resonance phenomenon and improves the stability and dynamic performance of the system.

[0026] By injecting reverse harmonic current and using repetitive controllers, the dynamic damping of the system can be increased and resonance can be suppressed. The increase in dynamic damping is a means to achieve resonance suppression, while resonance suppression is the effect of increasing dynamic damping. The two are closely related. The former is a step achieved through the control algorithm, and the latter is a direct manifestation of improved system performance. Through this linkage, the system can maintain stability and high performance in the face of periodic resonance. Among them, the control algorithm that actively adjusts the switching state of the converter by designing a control algorithm to increase the dynamic damping of the system usually adopts the principle of real-time feedback control. It determines 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, and the resonance phenomenon is directly suppressed. It is based on the feedback signal of the current system for dynamic adjustment. Common implementation methods include PID control, state feedback control, robust control, etc., and the predictive control algorithm is used to predict the occurrence of resonance and take measures to suppress it in advance. It is a feedforward control strategy that predicts the future state of the system based on the system's historical data, models or other methods, and takes control measures in advance. For example, by predicting the resonant mode, the trend or possibility of resonance can be identified in advance, and system parameters (such as switching frequency or injection current) can be adjusted to prevent resonance from occurring in advance. Common predictive control algorithms include model predictive control (MPC), which requires modeling the system's dynamics and predicting future system behavior based on the model.

[0027] At present, the traditional resonance suppression method mainly relies on the design at the hardware level, such as adding a resonance suppression filter. Although it can alleviate the resonance problem to a certain extent, it also brings negative effects such as increased cost, increased volume and increased system complexity. In recent years, the resonance suppression method based on the control strategy has received extensive attention. This type of method adjusts 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, they still face many challenges in practical applications, such as the delay problem of the control algorithm, the optimization of the dynamic response of the system, and the robustness under different working conditions. The present invention mathematically models the multi-module converter system, including the electrical parameters and topological structure of each module, 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, the resonance phenomenon that may exist in the system can be detected in time. This real-time feedback mechanism enables the system to respond quickly to the resonance problem, avoid damage to electrical equipment or degradation of system performance caused by resonance, and optimize the dynamic response of the system through the controller, so as to ensure that the system can maintain good stability and performance under different operating conditions. For example, by properly adjusting the control algorithm, the converter system can maintain a fast response and effectively suppress harmonics under load fluctuations, environmental changes or external interference. Through mathematical modeling and precise design of the control algorithm, the robustness of the multi-module converter system under different working conditions can be improved to ensure that the resonance suppression effect in practical applications is not affected by environmental changes or uncertain factors. Through real-time monitoring and frequency identification mechanisms, the system can adjust the control strategy according to the frequency characteristics of the resonance, thereby achieving more flexible and adaptive resonance suppression. This adaptive capability 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, each of which 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: ;in, is the capacitor voltage of the submodule, is the submodule capacitance, is the current flowing into the submodule, 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 interference. An adaptive PID controller can be used, and its parameters are dynamically adjusted according to the system state. The predictive control algorithm predicts the state of the system in advance and takes control measures by establishing a predictive model of the system. A model predictive control algorithm can be used, and its predictive model can be linear or nonlinear to simulate and verify the system. The 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, power grid fluctuations, etc.; analyzing simulation results to verify the effectiveness of the control algorithm; obtaining simulation effects based on the control effects, and optimizing control parameters and algorithms based on the simulation effects. The experimental platform is to build an actual multi-module converter experimental platform, including hardware and software parts. The testing steps include: implementing the control algorithm verified by simulation on the experimental platform; conducting experimental tests to record the response of the system under different working conditions; analyzing the experimental data to verify the actual effect of the control algorithm; and further optimizing the control algorithm and system parameters based on the experimental results. Through the above steps, the multi-module converter system can be mathematically modeled in detail 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 resonance suppression system based on a control strategy, and can be appropriately adjusted and optimized according to specific applications. The switching state of the converter is actively adjusted by designing a control algorithm to increase the dynamic damping of the system and suppress resonance, including injecting reverse harmonic current to offset 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 resonance phenomenon of the system instead of relying solely on passive suppression. This active adjustment mechanism enables the system to respond flexibly to different resonant frequencies and harmonic characteristics, thereby 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 resonance phenomena. Actively adjusting the switching state can increase the dynamic damping of the system, so that the system can quickly suppress oscillations and return to a stable state when disturbed or resonantly excited. By enhancing damping, the system can not only effectively reduce the amplitude of resonance It can also speed up the response speed, reduce the system's transition process, and improve the overall performance. By repeating the same control action in each cycle, the 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 that the resonance can be accurately suppressed in each cycle. This control strategy is particularly suitable for periodic resonance problems, such as harmonic pollution in power systems, and can effectively avoid the accumulation or deterioration of resonance phenomena. Traditional resonance suppression methods often rely on filters or passive components. These methods perform poorly in suppressing resonances with unstable frequency and amplitude, and cannot be flexibly adjusted in the dynamic changes of the system. The method of actively adjusting the switch state and injecting reverse harmonic current can respond to system changes in real time and adapt to the resonance conditions under different working conditions, thereby overcoming the limitations of traditional methods. By accurately adjusting the converter switch state and reverse harmonic injection, the system can timely reduce the loss of useless energy when resonance occurs and improve overall efficiency. Compared with traditional passive filters and resonance suppression methods, this method can be adjusted in real time and maximize the energy efficiency of the system while suppressing resonance. It can adjust the control parameters in real time according to the system status, enhance the dynamic stability of the system, use predictive control algorithms to predict the occurrence of resonance and take measures to suppress it in advance, verify the effect of the adopted control algorithm in a simulation environment, and suppress resonance under various working conditions. By designing a fault-tolerant control strategy, it handles abnormal conditions in the system, where the abnormal conditions include sensor failure and communication interruption. By adjusting the 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 when facing different load changes and disturbances. Before resonance occurs, the predictive control algorithm can identify possible resonance trends in advance, and then adjust the control parameters and take active measures to suppress resonance.Compared with the traditional passive suppression method, this forward-looking control can effectively reduce the response time and avoid serious oscillations in the system. The predictive control algorithm can predict the future resonance trend based on the historical data and current state of the system, and make adjustments in advance, thereby effectively reducing the probability of resonance. This forward-looking design can take necessary control measures before the system resonates, thereby reducing the impact of resonance in practical applications and avoiding large overshoots and oscillations. The fault-tolerant control strategy can cope with abnormal conditions in the system, such as sensor failure and communication interruption. Traditional methods often lead to control failure or performance degradation when facing these faults. Through fault-tolerant control, the normal operation of the system can be maintained by using redundant information or system self-correction when sensor data is lost or communication is interrupted. The system can automatically adapt to different loads, environmental conditions and equipment states by adjusting control parameters in real time. In the converter system, factors such as load fluctuations, input voltage changes, and ambient temperature may affect the resonance characteristics, and real-time parameter adjustment enables the system to flexibly respond to these changes and ensure long-term stable operation. By actively suppressing resonance and reducing excessive oscillations of the system, energy waste and equipment loss caused by resonance can be significantly reduced. Compared with traditional passive filters, active control strategies can more accurately adjust the system operating state and improve the energy efficiency of the system.

[0028] In one embodiment, the mathematical modeling S1 of the multi-module converter system includes: S11. Analyze the overall behavior of the multi-module converter and build a model based on the DC side or AC side. The DC side model is as follows: ; in, is the DC bus voltage, is the DC bus capacitor, is the DC input current, is the DC output current; The AC test model is as follows: ; ; in, 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.

[0029] As described in the above step S11, the converter generally includes a DC side, an AC side and an intermediate circuit part. Assuming that we use a three-phase voltage source converter, the model can include the following parts: DC side model: DC voltage source, DC filter capacitor, DC load, AC side model: three-phase AC power supply, AC filter inductor and capacitor, three-phase AC load, switch model: a switch network composed of IGBT (insulated gate bipolar transistor) or MOSFET (metal oxide semiconductor field effect transistor) to control the power transfer of the converter, outer loop control: control the DC side voltage or AC side power, inner loop control: control the current loop to ensure that the current tracks the command value.

[0030] In one embodiment, the performing mathematical modeling S1 on the multi-module converter system further includes: S12, reduce the harmonic components in the system and improve the waveform quality of output voltage and current; S13, by injecting reverse harmonic current to offset the resonant current, repeating the same control action in each cycle to suppress periodic resonance; S14. Add LCL filter to the system and design corresponding control algorithm to filter out harmonics, improve the dynamic response speed of the system, and ensure that stability can be quickly restored in the event of load changes, power grid fluctuations, etc.; S15, adjust control parameters in real time according to system status, enhance the dynamic response of the system, use predictive control algorithms, predict system changes in advance and take measures; S16, the proportional resonant controller has a higher gain at a specific frequency and effectively suppresses resonance. Its expression is as follows: ; in, is the complex frequency domain variable in Laplace transform, is the proportional gain, Resonance gain, is the resonant frequency; S17, the repetitive controller eliminates periodic harmonics by periodically injecting the same control signal, and its expression is as follows: ; in, is the period number of the system, It's the forgetting factor. is the transformation variable of the discrete-time system, representing the discrete frequency characteristics of the system.

[0031] 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 collecting voltage and current signals, performing a digital signal processor or wavelet transform, detecting peaks in the spectrum, identifying the resonant frequency, and selecting a corresponding control strategy (such as a PR controller, a repetitive controller) according to the identified resonant frequency, adjusting the control parameters in real time, and suppressing resonance. Sensor and data acquisition card: ensure that the connection between the sensor and the data acquisition card is stable and the sampling frequency is set reasonably. Controller and actuator: ensure that the communication between the controller and the actuator of the converter (such as the driving circuit of the switching device) is stable, and the control signal output by the controller can be quickly and accurately transmitted to the actuator. Experimental platform: construct Build a practical 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 digital signal processors or wavelet transforms to analyze the collected signals and detect whether there is resonance, frequency identification: identify the resonant frequency and record related 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, overvoltage protection: detect whether the voltage exceeds the safety range, if so, immediately shut down the converter, overcurrent Protection: Detect whether the current exceeds the safety range. If so, immediately shut down the converter. Real-time display: Display the system's key parameters such as voltage, current, temperature, and the operating status of the control algorithm in real time through the monitoring interface. Log record: Record the system operation log to facilitate 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 offset 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 sinusoidal waveform, reducing the interference of harmonics on the system. Injecting reverse harmonic current can effectively offset the resonant current, thereby reducing the resonant current in the system. Vibration phenomenon, due to the reduction of harmonics and resonance, the reactive power and loss in the system can be effectively controlled, the use efficiency of electric energy is improved, and unnecessary heat loss and energy waste are reduced. 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 in the case of load changes or large input voltage fluctuations, the system can be kept running stably. LCL filters are added to the system, and corresponding control algorithms are designed to filter out harmonics and improve the dynamic response speed of the system, ensuring that stability can be quickly restored in the case of load changes, power grid fluctuations, etc. The control parameters are adjusted in real time according to the system status to enhance the dynamic response of the system. The use of predictive control algorithms,Predict system changes in advance and take measures. The proportional resonant controller has a higher gain at a specific frequency and effectively suppresses resonance. The repetitive controller periodically injects the same control signal to eliminate periodic harmonics. 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 on load devices, sensors and other sensitive equipment is reduced. A mechanism for adjusting control parameters in real time is designed so that the system can respond quickly and optimize its operating point according to the current state (such as load changes, grid fluctuations, etc.), and quickly recover to a stable state. This can greatly improve the dynamic response speed of the system, especially when the load changes or grid fluctuations are large, to avoid long-term excessive oscillation or Unstable state, dynamic parameter adjustment can ensure that the controller compensates for changes in system parameters in a timely manner to avoid instability caused by system lag or parameter mismatch. The predictive control algorithm enables the system to predict future system state changes in advance and infer future dynamic behaviors based on the current state and historical data. Predictive control can not only reduce the system's delay in responding to external disturbances (such as grid fluctuations or load mutations), but also optimize the control strategy and intervene before resonance or instability occurs. The repetitive controller eliminates periodic harmonics by periodically injecting the same control signal, which can effectively eliminate harmonic problems caused by periodic interference, thereby effectively improving the system's harmonic filtering capability, dynamic response speed and system stability.

[0032] In one embodiment, the real-time monitoring of the voltage and current waveform S2 of the system by the sensor and the controller includes: S21, measuring the DC bus voltage and the AC side voltage through a voltage sensor; S22, measuring the DC side current and the AC side current by using a current sensor; S23, set up a high-speed data acquisition card with high sampling rate and high precision to collect sensor data in real time and ensure the real-time and reliability of data transmission from the sensor to the controller; S24, preprocessing the collected signals, including filtering, for removing high-frequency noise and retaining signals within a specific frequency range to facilitate resonance detection; S25. Convert the analog signal into a digital signal, identify and select the corresponding sampling frequency to ensure that the frequency component of the resonant signal can be captured. The sampling frequency should be at least twice the resonant frequency.

[0033] 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 collects sensor data in real time by setting a high-speed data acquisition card with high sampling rate and high precision, thereby ensuring the real-time and reliability of data transmission from the sensor to the controller. Through the voltage and current sensors, the DC bus voltage, the AC side voltage, the DC side current and the AC side current can be monitored in real time. These data can reflect the operating status of the system in real time, especially in the case of dynamic changes (such as load mutations, power grid fluctuations, etc.). The data acquisition card with high sampling rate and high precision ensures the real-time and reliability of data transmission, and can capture the dynamic changes of the system within milliseconds. The data acquisition system The real-time nature of the system ensures that the data transmission delay from the sensor to the controller is minimal, thereby improving the response speed of the control algorithm. By continuously acquiring real-time data, the control system can detect unstable or abnormal conditions 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 other unstable phenomena. The real-time transmitted data allows the controller to understand the changing trend of the system in a timely manner and then implement accurate dynamic compensation. By fine-tuning the output of the controller, it can effectively suppress resonance or excessive fluctuations caused by changes in 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 current status, making the system more responsive. Rapid and accurate, for example, it can quickly adjust the filter parameters or control strategies when the load changes or power grid fluctuations occur, suppress possible resonance, pre-process the collected signals, including filtering, to remove high-frequency noise, to retain signals within a specific frequency range, to facilitate resonance detection, convert analog signals into digital signals, identify and select the corresponding sampling frequency, and ensure that the frequency components of the resonant signal can be captured. The sampling frequency should be at least twice the resonant frequency. Filtering can effectively remove high-frequency noise from the collected signals and only retain valid signals within a specific frequency range. Through filter design, the target frequency range of the resonant signal can be selectively retained, so that the system can accurately capture the components of the resonant frequency and avoid other frequency bands. Signal interference. For applications that require precise analysis and identification of resonant signals, being able to centrally process and amplify target signals helps improve the sensitivity and accuracy of the analysis. After converting analog signals into digital signals, it is convenient for digital controllers to calculate, analyze and adjust. Digital signals have higher precision and can eliminate errors and instabilities that may occur in analog signals, thereby greatly improving control accuracy and reliability. The sampling frequency is at least twice the resonant frequency (satisfying the Nyquist sampling theorem) to ensure that the digitized signal can accurately capture the frequency components of the resonant signal without distortion or aliasing. A reasonable sampling frequency ensures signal integrity, avoids 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 delays, and improve system response speed, which is particularly important for dynamically changing resonance signals and can adjust the system state in time to avoid excessive oscillation or instability.

[0034] In one embodiment, the step of converting the analog signal into a digital signal and identifying and selecting a corresponding sampling frequency includes: S31. Convert the time domain signal into a frequency domain signal and analyze the peak value in the spectrum: S32, collecting voltage and current waveform data within a period of time, and performing Fourier transform on the collected data; S33, analyzing the spectrum graph, finding the peak value of the harmonic component, and determining whether the peak value exceeds a preset threshold; If the peak value exceeds a preset threshold, it is considered that the system has resonance; S34, perform time-frequency domain analysis, accurately identify transient resonance phenomena, and select appropriate wavelet basis functions; S35, performing wavelet transform on the collected data, analyzing the wavelet coefficients, and finding the peak value of the harmonic component; S36, if the peak value exceeds the preset threshold, it is considered that the system has resonance phenomenon; S37. In the Fourier or wavelet transformed spectrum, find the peak frequency of the harmonic component, which is the resonant frequency: S38, calculating the spectrum graph, finding the maximum peak in the spectrum graph, and identifying the sampling frequency corresponding to the peak.

[0035] As described in the above steps S31-S38, the present invention converts the time domain signal into a frequency domain signal, analyzes the peak value in the spectrum, collects the voltage and current waveform data within a period of time, performs Fourier transform on the collected data, analyzes the spectrum diagram, finds the peak value of the harmonic component, and determines whether the peak value exceeds the preset threshold value. If the peak value exceeds the preset threshold value, it is considered that there is a resonance phenomenon in the system. By converting the time domain signal into a frequency domain signal, the Fourier transform can effectively decompose the various frequency components of the signal, so that it can be clearly identified whether there are harmonic components in the system. If some frequency peaks in the system exceed the preset threshold value, the resonance phenomenon corresponding to the frequency can be directly determined. Compared with traditional time domain analysis, this method can more accurately identify the specific frequency and amplitude of the resonance. The Fourier transform can provide real-time data in the frequency domain, so that the system can monitor possible resonance phenomena during operation and make timely adjustments when abnormalities occur. By analyzing the spectrum diagram, it can adapt to different working conditions and identify harmonic components under different working conditions.For example, under the influence of load fluctuations, system parameter changes or external interference, frequency domain signal processing can still be used to detect whether there is a potential resonance problem. After frequency domain analysis is combined with modern digital signal processing and automatic control technology, the control algorithm can be quickly enabled to intervene when the resonance phenomenon is detected. By adjusting the working state of the system or enabling resonance suppression measures, the impact of resonance can be effectively reduced or eliminated, further improving the stability and reliability of the system. The spectrum diagram can be archived for a long time and used for historical data analysis, which is helpful for long-term monitoring of the operating status of the system and comparison of historical resonance trends. Time-frequency domain analysis is performed to accurately identify transient resonance phenomena, and appropriate wavelet basis functions are selected. The collected data is wavelet transformed, and the wavelet coefficients are analyzed to find the peak value of the harmonic component. If the peak value exceeds the preset threshold, it is considered that the system has a resonance phenomenon. In the Fourier or wavelet transform spectrum diagram, the peak frequency of the harmonic component is found, which is the resonance frequency. The spectrum diagram is calculated and the spectrum is found The maximum peak in the figure, identify the frequency corresponding to the peak, and through time-frequency domain analysis (such as wavelet transform), it is possible to capture the changes of transient signals more accurately, while Fourier transform focuses on the spectrum analysis of steady-state signals. Transient resonance is usually manifested as amplitude fluctuations and frequency changes in a short period of time. The time-frequency domain method can effectively distinguish these transient characteristics. Wavelet transform can provide time and frequency information at the same time, which is particularly suitable for processing non-stationary signals and transient phenomena. Choosing a suitable wavelet basis function can effectively extract harmonic components, especially identifying peaks near the resonant frequency, avoiding the limitations of Fourier transform (Fourier transform has poor analysis capabilities for transient signals). Wavelet transform has the ability of multi-resolution analysis, and can view the details of the signal at different scales, which is helpful for feature extraction in dynamic changes. Through Fourier transform and wavelet transform, the spectrum diagram of the system can be obtained, and the peak values ​​of the harmonic components can be extracted from it. By monitoring the frequency peaks in the spectrum, it can be accurately determined whether the system is in a resonant state.

[0036] In one embodiment, the verification of the effect of the adopted control algorithm in the simulation environment and the suppression of resonance under various working conditions, and the processing of abnormal conditions in the system by designing a fault-tolerant control strategy S5 include: S51, verifying the voltage and current waveforms of the simulation system under normal operation; S52, verifying the resonance suppression effect of the control algorithm under normal working conditions, and simulating sensor failure and communication interruption conditions; S53, verifying the system stability of the fault-tolerant control strategy under fault conditions, and recording the response of the system before and after the control strategy is implemented, wherein the response includes voltage and current waveforms and system status; S54, obtaining a control effect according to the response, wherein the control effect includes a resonance suppression speed and a system recovery time; S55, obtaining a simulation effect according to the control effect, and optimizing control parameters according to the simulation effect to improve the control effect; 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.

[0037] As described in the above steps S51-S56, the present invention verifies the resonance suppression effect of the control algorithm under normal conditions by verifying the voltage and current waveforms of the simulation system under normal operation, verifies the system stability of the fault-tolerant control strategy under fault conditions by simulating sensor failures and communication interruptions, and records the response of the system before and after the implementation of the control strategy, wherein the response includes voltage, current waveforms and system status. By simulating the voltage and current waveforms under normal conditions through the simulation system, the effect of the control algorithm on resonance suppression can be intuitively verified. If the simulation system successfully suppresses the resonance and can keep the voltage and current waveforms stable, it means that the design of the control algorithm is effective. The simulation environment can help designers quickly adjust the control algorithm parameters, such as feedback gain, resonance suppression frequency, etc., so as 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 failure or communication interruption, it can verify whether the fault-tolerant control strategy can maintain system stability without complete information. This is difficult to do with 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 in the event of hardware or communication failures, thereby preventing system crashes due to single point failures. The simulation system can help quickly identify delay problems in the control algorithm, especially when responding to resonant signals, which may cause problems such as feedback delay or over-response. 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, the control effect is obtained according to the response, and the control effect includes the resonance suppression speed and the system recovery time. The simulation effect is obtained according to the control effect, and the control parameters are optimized according to the simulation effect to improve the control effect, adjust the threshold and the default control input in the fault-tolerant control strategy, and ensure the stability and reliability of the system under various fault conditions. By optimizing the control parameters, such as the gain and the resonant frequency, the resonance suppression speed can be significantly improved, and the threshold and the default control input in the fault-tolerant control strategy can be adjusted to ensure that the system suppresses the resonance more accurately and timely, so that it can respond faster and stabilize the system in actual applications. By improving the control algorithm and adjusting the control parameters, the system can recover from disturbances or faults faster. For example, when a fault occurs, the system can quickly stabilize through the adjustment of the fault-tolerant control strategy, avoiding long-term shutdown or unstable state. The optimized control parameters can enable the system to quickly return to normal working state after encountering disturbances, reduce recovery time, and improve system availability and stability. By optimizing the fault-tolerant control strategy, especially adjusting the threshold and default control input, the system can better cope with different faults or disturbance conditions, which enables the system to maintain efficient operation under various working conditions, reduce the probability of failure and improve the robustness of the system.

[0038] The present application also provides a mobile energy storage system multi-module converter resonance suppression system, comprising: Mathematical modeling module, used to mathematically model the multi-module converter system, including the electrical parameters and topology of each module, and to clarify the control objectives of the system, including harmonic suppression, dynamic response, and robustness; The real-time monitoring module is used to monitor the voltage and current waveforms of the system in real time through sensors and controllers to detect whether there is resonance. When resonance is detected, the resonance frequency is further identified and corresponding control measures are taken; The suppression module is used to 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 offset the resonant current and repeating the same control action in each cycle to suppress periodic resonance; The adjustment module is used to adjust the control parameters in real time according to the system status, enhance the dynamic stability of the system, and use the predictive control algorithm to predict the occurrence of resonance and take measures to suppress it in advance; The control module is used to verify the effect of the adopted control algorithm in a simulation environment and suppress resonance under various working conditions. By designing a fault-tolerant control strategy, it handles abnormal conditions in the system, where the abnormal conditions include sensor failure and communication interruption.

[0039] In one embodiment, a mobile energy storage system multi-module converter resonance suppression system further includes: Data acquisition module, used to collect key parameters of voltage, current and temperature in the system in real time, and transmit the data collected by the sensor to the control unit using a high-speed communication protocol; The real-time monitoring and diagnosis module pre-processes the collected signals, such as filtering and sampling, to improve the accuracy and reliability of the signals. It uses Fourier transform and wavelet transform signal analysis methods to detect whether there is resonance in the system in real time. After the resonance is detected, it diagnoses the cause of the resonance. Control strategy module, design and implement active damping control algorithm, increase the system's dynamic damping by adjusting the switching state of the converter, suppress resonance, use predictive control algorithm to predict the occurrence of resonance in advance and take measures to suppress it, design adaptive control algorithm, adjust control parameters in real time according to the system status, and enhance the dynamic stability of the system; Parameter optimization module, which uses optimization algorithms to optimize control parameters to improve control effects. It adjusts control parameters in real time according to the system operating status to ensure that the performance of the control algorithm remains optimal under various working conditions. The communication and coordination module ensures efficient data exchange and command transmission between modules, realizes coordinated control between multi-module converters, and optimizes the performance of the overall system; The execution and drive module is responsible for driving the switching devices of the converter and performing switching operations according to the control instructions. When an abnormality occurs in the system, the converter is protected in time to prevent equipment damage.

[0040] In the above, the system provides a user-friendly operation interface, which is convenient for users to set control parameters, view system status, etc., and displays key parameters such as voltage, current, temperature, and the operating status of the control algorithm in real time. Record the system's operating data and control logs to facilitate subsequent analysis and troubleshooting. Integrate each module into an overall system to ensure compatibility and collaboration between modules. Perform system tests in laboratories and actual environments 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, improving the stability and performance of the system. The specific module design and implementation method can be adjusted and optimized according to the actual application scenarios and technical requirements.

[0041] In one embodiment, the real-time monitoring module includes: A first measuring unit, used for measuring a DC bus voltage and an AC side voltage through a voltage sensor; A second measuring unit, used for measuring a DC side current and an AC side current through a current sensor; The acquisition unit is used to set a high-speed data acquisition card with high sampling rate and high precision to collect sensor data in real time and ensure the real-time and reliability of data transmission from the sensor to the controller; A preprocessing unit, used for preprocessing the collected signals, including filtering processing, for removing high-frequency noise and for retaining signals within a specific frequency range to facilitate resonance detection; The conversion unit is used to convert the analog signal into a digital signal, identify and select the corresponding sampling frequency, and ensure that the frequency component of the resonant signal can be captured. The sampling frequency should be at least twice the resonant frequency.

[0042] The present invention also provides a computer device, including a memory and a processor, wherein 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.

[0043] The present invention also provides a computer-readable storage medium having a computer program stored thereon, 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.

[0044] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided in this application and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many 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.

[0045] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0046] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also 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: include: Mathematically modeling the multi-module converter system, including constructing electrical parameters and topological structures of each module, and determining control objectives of the multi-module converter system, wherein the control objectives include harmonic suppression, dynamic response, and robustness; The voltage and current waveforms of the multi-module converter system are monitored in real time through sensors and controllers to detect whether there is a resonance phenomenon. When a resonance phenomenon is detected, the resonance frequency is further identified, and corresponding control measures are taken according to the identified resonance frequency; Designing a control algorithm to actively adjust the switching state of the converter, detecting the resonant frequency in the multi-module converter system, and generating a reverse harmonic current according to the resonant frequency, inputting the reverse harmonic current into the multi-module converter system through the control algorithm, increasing the dynamic damping of the multi-module converter system, and repeating the above control action in each resonant period to suppress periodic resonance; Adjust control parameters in real time according to the status of the multi-module converter system to enhance the dynamic stability of the multi-module converter system. Use predictive control algorithms to predict the occurrence of resonance and take measures to suppress it in advance. The effect of the adopted control algorithm is verified in a simulation environment, and resonance is suppressed under various working conditions. By designing a fault-tolerant control strategy, abnormal situations in the multi-module converter system are handled, where the abnormal situations include sensor failure and communication interruption.

2. The method for suppressing resonance of a multi-module converter of a mobile energy storage system according to claim 1, characterized in that: 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, wherein the DC side model is as follows: ； in, is the DC bus voltage, is the DC bus capacitor, is the DC input current, is the DC output current; The AC test model is as follows: ； ； in, 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 of a mobile energy storage system according to claim 1, characterized in that: The mathematical modeling of the multi-module converter system further comprises: Reduce the harmonic components in the system and improve the waveform quality of output voltage and current; By injecting reverse harmonic current to offset the resonant current, the same control action is repeated in each cycle to suppress periodic resonance; Add LCL filter to the system and design corresponding control algorithm to filter out harmonics, improve the dynamic response speed of the system, and ensure that stability can be quickly restored in the event of load changes, power grid fluctuations, etc. Adjust control parameters in real time according to system status, enhance the dynamic response of the system, use predictive control algorithms to predict system changes in advance and take measures; The proportional resonant controller has a higher gain at a specific frequency and effectively suppresses resonance. Its expression is as follows: ； in, is the complex frequency domain variable in Laplace transform, is the proportional gain, Resonance gain, is the resonant frequency; The repetitive controller periodically injects the same control signal to eliminate periodic harmonics. Its expression is as follows: ； in, is the period number of the system, It's 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 of 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 by sensors and controllers, including: The DC bus voltage and AC side voltage are measured by voltage sensors; Measuring the DC side current and the AC side current by means of current sensors; Set up a high-speed data acquisition card with high sampling rate and high precision to collect sensor data in real time and ensure the real-time and reliability of data transmission from the sensor to the controller; Preprocessing of the collected signals, including filtering, is used to remove high-frequency noise and retain signals within a specific frequency range to facilitate resonance detection; Convert the analog signal into a digital signal, identify and select the corresponding sampling frequency to ensure that the frequency component of the resonant signal can be captured. The sampling frequency should be at least twice the resonant frequency.

5. The method for suppressing resonance of a multi-module converter of a mobile energy storage system according to claim 4, characterized in that: The converting of the analog signal into a digital signal and identifying and selecting the corresponding sampling frequency comprises: Convert the time domain signal to the frequency domain and analyze the peaks in the spectrum: Collect voltage and current waveform data over a period of time, and perform Fourier transform on the collected data; Analyze the spectrum graph, find the peak value of the harmonic component, and determine whether the peak value exceeds a preset threshold; If the peak value exceeds a preset threshold, it is considered that the system has resonance; Conduct time-frequency domain analysis to accurately identify transient resonance phenomena and select appropriate wavelet basis functions; Perform wavelet transform on the collected data, analyze the wavelet coefficients, and find the peak value of the harmonic component; If the peak value exceeds the preset threshold, it is considered that the system is in resonance; In the Fourier or wavelet transformed spectrum, find the peak frequency of the harmonic component, which is the resonant frequency: Calculate the spectrogram, find the maximum peak in the spectrogram, and identify the sampling frequency corresponding to the peak.

6. The method for suppressing resonance of a multi-module converter of a mobile energy storage system according to claim 1, characterized in that: The effect of the control algorithm adopted is verified in the simulation environment, and resonance is suppressed under various working conditions. The abnormal conditions in the multi-module converter system are handled by designing a fault-tolerant control strategy, including: Obtain voltage and current waveforms under normal operation by verifying the simulation system; Verify the control algorithm’s resonance suppression effect under normal operating conditions and simulate sensor failure and communication interruption conditions; Verify the system stability of the fault-tolerant control strategy under fault conditions and record the system response before and after the control strategy is implemented, wherein the response includes voltage and current waveforms and system status; Acquire a control effect according to the response, wherein the control effect includes a resonance suppression speed and a system recovery time; Acquire a simulation effect according to the control effect, and optimize 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.

7. A mobile energy storage system multi-module converter resonance suppression system, characterized in that: include: Mathematical modeling module, used to mathematically model the multi-module converter system, including the electrical parameters and topology of each module, and to clarify the control objectives of the system, including harmonic suppression, dynamic response, and robustness; The real-time monitoring module is used to monitor the voltage and current waveforms of the system in real time through sensors and controllers to detect whether there is resonance. When resonance is detected, the resonance frequency is further identified and corresponding control measures are taken; The suppression module is used to 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 offset the resonant current and repeating the same control action in each cycle to suppress periodic resonance; The adjustment module is used to adjust the control parameters in real time according to the system status, enhance the dynamic stability of the system, and use the predictive control algorithm to predict the occurrence of resonance and take measures to suppress it in advance; The control module is used to verify the effect of the adopted control algorithm in a simulation environment and suppress resonance under various working conditions. By designing a fault-tolerant control strategy, it handles abnormal conditions in the system, where the abnormal conditions include sensor failure and communication interruption.

8. The mobile energy storage system multi-module converter resonance suppression system according to claim 7, characterized in that: The real-time monitoring module comprises: A first measuring unit, used for measuring a DC bus voltage and an AC side voltage through a voltage sensor; A second measuring unit, used for measuring a DC side current and an AC side current through a current sensor; The acquisition unit is used to set a high-speed data acquisition card with high sampling rate and high precision to collect sensor data in real time and ensure the real-time and reliability of data transmission from the sensor to the controller; A preprocessing unit, used for preprocessing the collected signals, including filtering processing, for removing high-frequency noise and for retaining signals within a specific frequency range to facilitate resonance detection; The conversion unit is used to convert the analog signal into a digital signal, identify and select the corresponding sampling frequency, and ensure that the frequency component of the resonant signal can be captured. The sampling frequency should be at least twice the resonant frequency.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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