A ferromagnetic resonance flexible device based on a power electronic converter

Abstract

The application belongs to the technical field of power system overvoltage protection, and particularly relates to a ferromagnetic resonance flexible device based on a power electronic converter, wherein a full-bridge uncontrolled rectification and a double-switch BUCK chopper circuit topology are adopted in the power electronic converter module, and a dynamic equivalent damping resistor is simulated through duty cycle adjustment of a MOSFET switch; a signal acquisition module integrates a GMR sensor, a T-shaped thermocouple and a voltage detection unit; a control module performs ferromagnetic resonance feature identification based on an FFT algorithm, combines critical conduction mode control and a model reference self-adaptive PI control algorithm, dynamically generates a PWM signal to drive the converter to work, and realizes rapid self-adaptive dissipation of resonance energy. Through multi-parameter fusion detection and a composite control strategy, the application effectively improves the response speed and the regulation accuracy of ferromagnetic resonance suppression, has state self-diagnosis, parameter visual configuration and remote data interaction functions, and significantly improves the operation reliability of a power system.

Description

Technical Field

[0001] This invention belongs to the field of power system overvoltage protection technology, specifically relating to a ferromagnetic resonant flexible device based on a power electronic converter. Background Technology

[0002] Ferromagnetic resonance is a sustained resonance phenomenon in power systems (especially 10kV–35kV neutral-point non-effectively grounded systems) caused by parameter mismatch between nonlinear inductive elements (such as electromagnetic voltage transformers) and the system's capacitance to ground. It is often accompanied by overvoltage and overcurrent, leading to serious faults such as equipment insulation damage, fuse blowing, surge arrester explosion, and transformer burnout. Specifically, when a disturbance occurs in the system (such as circuit breaker tripping or single-phase grounding faults), the magnetizing inductance of the electromagnetic voltage transformer (PT) easily enters a saturated state, forming a resonant circuit with the line-to-ground capacitance, posing a direct threat to power grid safety.

[0003] Current measures to suppress ferromagnetic resonances mainly include passive harmonic suppression circuits, active harmonic suppression circuits, and superconducting technology, but all of them have significant limitations.

[0004] A typical passive harmonic suppression circuit consists of a fixed damping resistor and a saturated reactor (composed of a reactor and a series resistor) connected in parallel. It relies on the series resistor to dissipate energy after the reactor saturates, but this method has a slow response (requiring several cycles), and the fixed resistor value is difficult to adapt to multi-mode resonances such as fundamental frequency, sub-frequency, and chaotic resonances. Furthermore, its suppression effectiveness decreases sharply under low load or high-frequency resonance scenarios. While resonant RLC filters can suppress resonance by blocking the resonant frequency, this degrades the system's frequency response characteristics and affects the accuracy of harmonic measurements. Metal oxide varistors (MOVs), limited by their fixed conduction threshold and energy capacity, are ill-suited to handling complex and variable resonant modes.

[0005] Active harmonic suppression schemes based on thyristor damping resistor switching can shorten the suppression time to within 2 cycles. However, thyristor state switching can easily cause discontinuous changes in equivalent resistance, posing a risk of re-exciting resonance, and the complex control circuit leads to decreased reliability. Patent CN 119134245 A proposes controlling the activation of the harmonic suppression module by detecting inrush current and offset voltage. Although this improves the targeting of the action, it still has the problem of multi-stage switching, and its control logic relies on steady-state parameter calibration, which may lead to misjudgment in transient processes or chaotic modes.

[0006] To improve resonance suppression, a series of hybrid schemes and emerging technologies have been proposed. RLC tuned filters combined with dynamic impedance adjustment technology using harmonic current injection require precise matching of the resonant frequency and are susceptible to parameter drift at high frequencies. Intelligent algorithms such as fuzzy PID still suffer from adjustment lag in chaotic resonance modes. Some designs attempt to combine MOVs with reactors or series DC reactor fault current limiters, which improves suppression but increases system complexity, and parameter optimization relies on manual experience, lacking dynamic adaptability. Patent CN 118137420A proposes using circuit breakers with phase-selective tripping function to suppress resonance, weakening transient excitation by controlling the tripping phase; however, its suppression effect is affected by the coupling of circuit breaker operation timing and system operating conditions, resulting in insufficient reliability in complex multimodal resonance. While superconducting fault current limiters can simultaneously suppress short-circuit current and resonance, their low-temperature cooling system increases maintenance costs, making them unsuitable for the large-scale requirements of medium-voltage distribution networks. Patent CN 117805518A detects fundamental frequency ferroresonance based on the second derivative of zero-sequence voltage, but this method is sensitive to high-frequency noise, easily affected by electromagnetic interference, and difficult to coordinate efficiently with dynamic suppression strategies, resulting in lag or overcompensation. Patent CN 117826059B predicts resonance faults by establishing models and parameter analysis, but it is not adaptable to dynamic changes in the power grid topology and relies on high-precision parameter input, which limits its practical application.

[0007] In summary, existing methods have technical bottlenecks in terms of speed, wideband multimodal adaptability, coordination between detection methods and control strategies, and reliability. There is an urgent need for a flexible suppression device that combines fast response, dynamic impedance matching, multimodal adaptation, and high reliability to meet the stringent requirements of distribution networks for ferroresonant suppression. Summary of the Invention

[0008] To address the technical bottlenecks in existing methods regarding speed, wideband multimodal adaptability, coordination between detection methods and control strategies, and reliability, this invention provides a ferromagnetic resonance flexible device based on a power electronic converter, aiming to achieve rapid detection, accurate identification, and efficient energy dissipation of ferromagnetic resonance.

[0009] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0010] A ferromagnetic resonant flexible device based on a power electronic converter includes:

[0011] The power electronic converter module, connected to the secondary open delta of the voltage transformer, is configured to dynamically simulate the equivalent damping resistance by adjusting the duty cycle of the switching signal, thereby achieving rapid dissipation of resonant energy.

[0012] The signal acquisition module is connected to the secondary side of the voltage transformer, the GMR sensor with giant magnetoresistance effect and the T-type thermocouple, and is used to acquire the secondary side voltage, zero-sequence voltage, primary side excitation current and transformer core temperature.

[0013] The control module connects the signal acquisition module and the power electronic converter module. It performs ferroresonant identification and recognition based on the acquired signals, generates pulse width modulation (PWM) signals to drive the power electronic converter, and realizes status indication, parameter configuration, and data interaction with the upper-level monitoring system.

[0014] The damping resistor is connected to the output side of the power electronic converter module to dissipate resonant energy.

[0015] The power electronic converter module adopts a composite topology of a full-bridge uncontrolled rectifier circuit and a dual-switch BUCK chopper circuit. The dual-switch BUCK chopper circuit is connected to the output terminal of the full-bridge uncontrolled rectifier circuit, uses MOSFETs as power switching devices, and its output terminal is connected to a damping resistor.

[0016] The control module includes:

[0017] The resonance feature extraction unit performs a fast Fourier transform (FFT) on the excitation current to extract the amplitude and frequency characteristics of the fundamental frequency, sub-frequency, and high-frequency components, and calculates the amplitude and rate of change of the open delta voltage, the amplitude and rate of change of the excitation current, and the core temperature rise rate.

[0018] The multi-parameter fusion diagnostic unit, based on the feature weight fusion algorithm, generates a comprehensive resonance probability value by combining the open delta voltage change rate, excitation current change rate, excitation current distortion rate, and temperature rise rate. When the comprehensive resonance probability value exceeds the threshold, it is determined that ferromagnetic resonance has occurred.

[0019] The composite control unit employs an algorithm that combines fixed on-time control of the critical conduction mode (CrCM) with model reference adaptive PI control based on voltage harmonic amplitude. It dynamically adjusts the PWM duty cycle according to the resonant mode to achieve continuous adjustment of the equivalent damping resistance.

[0020] The control module also includes a protection and status feedback unit, which monitors the core temperature and excitation current in real time. When the temperature exceeds 100°C or the excitation current exceeds 10 times the nominal value, it switches to the maximum damping mode and triggers an alarm. It also uploads the resonance suppression status, damping resistance value and fault code to the upper-level monitoring system via Modbus / TCP protocol and generates a health assessment report.

[0021] The control module continuously monitors the voltage spectrum of the open delta after resonance suppression. If no resonance characteristic is detected within 30 seconds, the damping resistor is gradually reduced to the standby value. The resonance mode prediction model is trained based on historical data, the threshold weights of the multi-parameter fusion diagnosis are optimized, and the sensor and sampling channel are periodically self-calibrated to ensure that the measurement accuracy error is less than 1%.

[0022] A resonance suppression method for a ferromagnetic resonant flexible device based on a power electronic converter includes the following steps:

[0023] S1. Multi-dimensional signal acquisition and preprocessing: The primary excitation current is acquired by the GMR sensor, the secondary three-phase voltage and zero-sequence voltage are acquired by the high-precision voltage sensor, the core temperature is monitored by the T-type thermocouple, and the signal is filtered and noise-reduced.

[0024] S2. Resonance Feature Extraction and Pattern Recognition: Perform FFT spectrum analysis on the excitation current to extract the fundamental frequency, sub-frequency, and high-frequency component features; calculate the zero-sequence voltage change rate, excitation current distortion rate, and core temperature rise rate to identify the risk of core nonlinear saturation and overheating.

[0025] S3. Multi-parameter fusion diagnosis and resonance determination: Based on the feature weight fusion algorithm, a comprehensive resonance probability value is generated by combining the zero-sequence voltage change rate, excitation current distortion rate and temperature rise rate. When the probability value exceeds 80%, resonance is determined to have occurred, and the fundamental frequency, frequency division and high frequency resonance modes are distinguished according to the excitation current spectrum characteristics.

[0026] S4. Dynamic Damping Adjustment and Energy Dissipation: The control strategy is selected according to the resonance mode. The fundamental frequency / sub-frequency resonance adopts CrCM fixed conduction time control, and the high-frequency resonance is combined with model reference adaptive PI control. The equivalent damping resistance (0.1Ω~10kΩ) is dynamically adjusted by adjusting the PWM duty cycle. The resonance energy is dissipated through the damping resistance by the full-bridge rectification and BUCK chopper circuit.

[0027] S5. Protection and Status Feedback: Real-time monitoring of core temperature and excitation current; if limits are exceeded, switching to maximum damping mode and issuing an alarm; uploading status data and generating a health assessment report via Modbus / TCP protocol.

[0028] S6. Continuous monitoring and adaptive optimization: After resonance suppression, continuously monitor the voltage spectrum of the open triangle. If there is no resonance characteristic, reduce the damping to the standby value. Optimize the diagnostic threshold weight based on historical data and periodically self-calibrate the sensor and sampling channel.

[0029] The method for multi-parameter fusion diagnosis and resonance determination in S3 is as follows:

[0030] S3.1 Based on the feature weight fusion algorithm, the zero-sequence voltage change rate Ku and the excitation current distortion rate I are combined. THDAnd the probability value P of generating comprehensive resonance by the temperature rise rate β:

[0031]

[0032] When P > 80%, ferromagnetic resonance is determined to have occurred;

[0033] S3.2 After ferromagnetic resonance occurs, based on the excitation current spectrum characteristics, ferromagnetic resonance is identified under the following conditions:

[0034] Fundamental frequency resonance: 50Hz component amplitude > 5 times rated excitation current and total excitation current distortion rate > 30%;

[0035] Frequency division resonance: the amplitude of the 25Hz / 17Hz component accounts for more than 60% of the total excitation current and the total distortion rate of the excitation current is greater than 20%;

[0036] High-frequency resonance: Excitation current amplitude > 8 times the rated excitation current, and the amplitude of the 150Hz to 1kHz frequency band component > 20%, and the excitation current distortion rate > 60%.

[0037] The method for dynamic damping adjustment and energy dissipation in S4 is as follows:

[0038] S4.1. Select control strategy based on resonant mode.

[0039] The control circuit adopts a control algorithm that combines fixed on-time control based on critical conduction mode (CrCM) with model reference adaptive PI control based on voltage harmonic amplitude. The aim is to achieve high-precision and stable control of the output voltage while ensuring high system efficiency.

[0040] Fundamental / division resonant: The critical conduction mode CrCM is used for fixed conduction time control, and the equivalent damping resistance is continuously adjusted within the range of 0.1Ω to 1kΩ by adjusting the PWM duty cycle;

[0041] High-frequency resonance: Combining critical conduction mode CrCM, model reference adaptive PI control is enabled, and PI parameters are dynamically optimized based on the resonant energy intensity to adjust the duty cycle and achieve rapid switching of high resistance values ​​from 1kΩ to 10kΩ.

[0042] S4.2 The dual-switch BUCK chopper circuit updates the PWM signal with a 50µs adjustment cycle to ensure smooth and stepless changes in the equivalent resistance.

[0043] S4.3 The resonant energy is converted into a DC component through a full-bridge uncontrolled rectifier circuit and a BUCK chopper circuit, and then rapidly released as heat dissipation through a damping resistor.

[0044] The method for preferentially selecting the control strategy based on the resonant mode in S4.1 is as follows:

[0045] S4.1.1 Fixed On-Time CrCM Control Mode

[0046] Using a fixed conduction time T on The strategy is the CrCM control mode. In the CrCM working mode, the inductor current starts at zero and returns to zero in each switching cycle, which realizes quasi-zero current turn-on (ZCS) and greatly reduces switching losses.

[0047] MOSFET devices Q1 and Q2 are connected via a NOT gate. In each cycle, Q1 and Q2 calculate the output T using model reference adaptive PI control. on Turning on and off. The MOSFET's turn-on is controlled by the inductor current returning to zero, i.e., the leakage current of Q1 is close to zero, determined by the sampling resistor R. Q Characteristic voltage u can be collected Q1 , when u Q1 H: This indicates that the current is not yet zero, Q2 continues to conduct, when u Q1 ≤H: When the inductor current is zero, Q2 is turned off. The control process requires a zero-crossing detection circuit (ZCD) and an RS flip-flop to ensure the CrCM condition and provide a high control response speed. A triangular wave comparator provides a ramp signal, which is compared with a reference voltage to set the on-time.

[0048] S4.1.2 Model Reference Adaptive PI Control Based on Voltage Harmonic Amplitude

[0049] A Model Reference Adaptive Control (MRAC) mechanism is introduced to adaptively adjust the parameters of the PI controller, thereby enhancing the robustness and tracking capability of the system.

[0050] The transfer function of the Buck chopper circuit:

[0051]

[0052] PI controller transfer function:

[0053]

[0054] The transfer function of a closed-loop system: where

[0055]

[0056] Then we get:

[0057]

[0058] The above equation is the duty cycle-impedance mapping model of the Buck chopper circuit. Based on this model, a reference model with a similar structure and ideal output characteristics is defined:

[0059]

[0060] The system obtains the output voltage u through a sampling circuit. o The error is

[0061] e = u ref ―u o

[0062] In the formula: u ref =3kI0λ I R, I0 are the rated excitation currents on the primary side, λ I Where k is the current multiple and k is the transformer ratio;

[0063] Introducing the Lilapunov performance function

[0064]

[0065] According to the MIT gradient rule, the rate of change of θ over time is proportional to the negative gradient J, i.e., In the formula, e represents the model error, and θ represents the controller parameter vector. The component is the sensitivity derivative of the error with respect to θ, and the parameter γ is the adaptive gain;

[0066] Determining the value K of the PI controller parameter using the MIT gradient rule P and K I .

[0067]

[0068] In the formula

[0069]

[0070] The adaptive rule is derived as follows:

[0071]

[0072] In the reference model, a is set m1 =RLC, a m2 =L, a m3 =(1+DK) P R, a m4 =DRK I The value of the adaptive gain γ is defined as follows: γ P =―0.0005, γ I = -0.0005;

[0073] The protection and status feedback method in S5 is as follows:

[0074] S5.1 Real-time monitoring of core temperature and excitation current:

[0075] If the temperature is >100℃ or the excitation current is >10 times the nominal value, immediately switch to the maximum damping mode and trigger an alarm.

[0076] S5.2 Upload the resonance suppression status, damping resistance value and fault code to the upper-level monitoring system via Modbus / TCP protocol;

[0077] S5.3 Generates a health assessment report every 5 minutes, including cumulative energy consumption, device temperature rise, and control parameter offset.

[0078] The method for continuous monitoring and adaptive optimization in S6 is as follows:

[0079] S6.1 After resonance suppression, continuously monitor the voltage spectrum of the open delta. If no resonance characteristic is detected within 30 seconds, gradually reduce the damping to make the damping resistance change to the standby value.

[0080] S6.2 Training a resonant mode prediction model based on historical data and optimizing the threshold weights for multi-parameter fusion diagnosis;

[0081] S6.3 Regularly self-calibrate the GMR sensor and voltage sampling channel to ensure measurement accuracy error <1%.

[0082] Compared with the prior art, the beneficial effects of this invention are:

[0083] 1. This invention, through the synergy of FFT spectrum analysis and multi-parameter threshold criteria, can identify fundamental frequency, sub-frequency, and high-frequency resonances within one power frequency cycle, shortening the resonance detection time to less than 20ms, and controlling the suppression action throughout within three power frequency cycles (<60ms), which is more than 5 times better than traditional passive solutions; it supports wide frequency domain resonance suppression from 10Hz to 2kHz, covering fundamental frequency, sub-frequency, and high-frequency multi-mode scenarios.

[0084] 2. This invention is based on the duty cycle-impedance mapping model of the BUCK chopper circuit. Through a composite algorithm of CrCM and adaptive PI control, the equivalent damping resistance is continuously and steplessly adjusted according to the resonant energy intensity to adapt to the impedance requirements of different resonant modes, eliminate the risk of secondary resonance caused by thyristor switching, and avoid the underdamping or overdamping problems caused by traditional fixed resistors.

[0085] 3. This invention activates temperature-current coordinated protection when the core temperature exceeds the limit (threshold 100℃) or the excitation current exceeds the threshold (10 times the nominal value), automatically switching to maximum damping mode and triggering an alarm to prevent equipment overheating and damage, ensuring high reliability and compatibility. Furthermore, this invention uses a GMR sensor, avoiding measurement distortion caused by traditional CT saturation. This invention supports Modbus / TCP protocol interaction with the upper-level monitoring system, enabling remote parameter tuning and status monitoring. Attached Figure Description

[0086] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are merely exemplary, and those skilled in the art can derive other embodiments based on the provided drawings without creative effort.

[0087] The structures, proportions, sizes, etc. illustrated in this specification are only for the purpose of assisting those skilled in the art in understanding and reading the content disclosed herein, and are not intended to limit the conditions under which the present invention can be implemented. Therefore, they have no substantial technical significance. Any modifications to the structure, changes in the proportions, or adjustments to the size, without affecting the effects and objectives that the present invention can produce, should still fall within the scope of the technical content disclosed in the present invention.

[0088] Figure 1 This is a block diagram of the overall structure of the device of the present invention;

[0089] Figure 2 This is a control structure diagram of the power electronic converter of the present invention;

[0090] Figure 3 This is a flowchart of the control algorithm of the present invention;

[0091] Figure 4 This is a control block diagram of the model reference adaptive PI control based on voltage harmonic amplitude according to the present invention.

[0092] Wherein: 1 is the power electronic converter module, 2 is the signal acquisition module, 3 is the control module, and 4 is the damping resistor. Detailed Implementation

[0093] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. These descriptions are only for further illustrating the features and advantages of the present invention, and not for limiting the claims of the present invention. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0094] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0095] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0096] This embodiment provides a ferromagnetic resonant flexible device based on a power electronic converter, such as... Figure 1 As shown, it includes:

[0097] Power electronic converter module 1: It adopts a composite topology of full-bridge uncontrolled rectifier circuit and dual-switch BUCK chopper circuit, and the dual-switch BUCK circuit is composed of MOSFET power devices. This module is connected to the secondary open delta winding of the voltage transformer, and the output is connected to damping resistor 4. By adjusting the PWM duty cycle, the equivalent damping resistance value (range 0.1Ω~10kΩ) is dynamically adjusted to achieve rapid and flexible dissipation of resonant energy.

[0098] Signal acquisition module 2: A sensor based on the giant magnetoresistance effect (GMR) acquires the excitation current of the primary side of the three phases ABC in real time with a sensitivity of 0.1A; a high-precision voltage sensor acquires the three-phase voltage of the secondary side and the zero-sequence voltage of the open delta, with a sampling frequency of 10kHz; a pre-embedded T-type thermocouple monitors the core temperature of the transformer (resolution ±0.5℃) to construct multi-dimensional resonant characteristic quantities.

[0099] Control Module 3: Integrates ferromagnetic resonance identification, adaptive control, and communication functions, including:

[0100] Resonance feature extraction: Based on Fast Fourier Transform (FFT) analysis of the excitation current spectrum, the fundamental frequency (50Hz), frequency division (25Hz / 17Hz) and high frequency (150Hz~1kHz) resonance modes are identified.

[0101] Multi-parameter fusion diagnosis: Combining the comprehensive criteria of zero-sequence voltage change rate (threshold > 10V / ms), excitation current distortion rate (threshold > 15%) and core temperature rise rate (threshold > 5℃ / s) improves the reliability of resonance detection;

[0102] Composite control algorithm: It combines critical conduction mode (CrCM) fixed conduction time control with model reference adaptive PI control, and dynamically adjusts the PWM duty cycle (adjustment period <2ms) according to the resonant frequency and energy intensity to achieve continuous and smooth adjustment of the damping resistance value.

[0103] To suppress ferroresonance, the power electronic converter module 1, signal acquisition module 2, control module 3, and damping resistor 4 constitute a complete suppression device in this invention. The power electronic converter control structure diagram is shown below. Figure 2 As shown.

[0104] The control structure diagram of the power electronic converter consists of a power electronic conversion circuit and a control circuit. The key parameters in the power electronic conversion circuit—the damping resistor R and the freewheeling inductor L—are selected as follows:

[0105]

[0106] Set the switching frequency to f. k =20kHz, with a duty cycle of 50%, the turn-on time of MOSFET switch Q2 u △ When the value is 200V and the duty cycle is 50%, u o Given 100V and R = 10Ω, we can obtain L = 25mH from equation (2).

[0107] The control circuit suppresses overvoltage, such as... Figure 3 As shown, follow these steps:

[0108] Step 1: Real-time acquisition and preprocessing of multi-dimensional signals

[0109] The excitation current of the three-phase primary side of the A, B, and C phases is acquired in real time using a giant magnetoresistive (GMR) sensor with a sensitivity of 0.1A and a sampling frequency of 10kHz. A high-precision voltage sensor is used to synchronously acquire the three-phase secondary side voltage and the open delta zero-sequence voltage of the voltage transformer. The core temperature of the transformer is monitored by a pre-embedded T-type thermocouple with a temperature resolution of ±0.5℃. The acquired current, voltage, and temperature signals are filtered and noise-reduced to eliminate high-frequency interference and baseline drift.

[0110] Step 2: Resonance Feature Extraction and Pattern Recognition

[0111] Fast Fourier Transform (FFT) spectrum analysis was performed on the excitation current to extract the amplitude and frequency characteristics of the fundamental frequency (50Hz), sub-frequency (25Hz / 17Hz), and high-frequency (150Hz~1kHz) components; the zero-sequence voltage change rate Ku(ΔU / Δt) was calculated, and if it exceeded the threshold of 10V / ms, it was marked as a transient resonance risk; the waveform distortion rate I of the excitation current was analyzed. THD When the distortion rate is greater than 15%, it is determined to be a nonlinear saturation characteristic of the core; the core temperature rise rate β is monitored, and if it exceeds 5℃ / s, an overheating warning is triggered. When all three conditions are met, a comprehensive judgment is further made.

[0112] Step 3: Multi-parameter fusion diagnosis and resonance determination

[0113] Step 3.1: Based on the feature weight fusion algorithm, comprehensively consider the zero-sequence voltage change rate Ku and the excitation current distortion rate I. THD and the combined resonance probability value P generated by the temperature rise rate β

[0114]

[0115] When P > 80%, ferromagnetic resonance is determined to have occurred.

[0116] Step 3.2: After ferromagnetic resonance occurs, based on the excitation current spectrum characteristics, ferromagnetic resonance is identified under the following conditions.

[0117] Fundamental frequency resonance: 50Hz component amplitude > 5 times rated excitation current and total excitation current distortion rate > 30%;

[0118] Frequency division resonance: the amplitude of the 25Hz / 17Hz component accounts for more than 60% of the total excitation current and the total distortion rate of the excitation current is greater than 20%;

[0119] High-frequency resonance: Excitation current amplitude > 8 times the rated excitation current, and the amplitude of the 150Hz to 1kHz frequency band component > 20%, and the excitation current distortion rate > 60%.

[0120] Step 4: Dynamic Damping Adjustment and Energy Dissipation

[0121] Step 4.1: Select a control strategy based on the resonant mode.

[0122] The control circuit adopts a control algorithm that combines fixed on-time control based on critical conduction mode (CrCM) with model reference adaptive PI control based on voltage harmonic amplitude, aiming to achieve high-precision and stable control of the output voltage while ensuring high system efficiency.

[0123] Fundamental / division resonant: Critical conduction mode (CrCM) fixed conduction time control is adopted, and the equivalent damping resistance is continuously adjusted within the range of 0.1Ω to 1kΩ by adjusting the PWM duty cycle (step size 0.1%).

[0124] High-frequency resonance: Combining critical conduction mode (CrCM), model reference adaptive PI control is enabled, and PI parameters are dynamically optimized based on the resonant energy intensity. The duty cycle is adjusted to achieve rapid switching of high resistance values ​​from 1kΩ to 10kΩ.

[0125] Step 4.1.1, Fixed On-Time CrCM Control Mode

[0126] To simplify the control circuit and reduce the cost and noise introduced by the current detection circuit, this patent adopts a fixed on-time (T). onThe strategy employed is the CrCM control mode. In CrCM mode, the inductor current starts at zero and returns to zero in each switching cycle, achieving near-zero current switching (ZCS) and significantly reducing switching losses. The specific operating process is as follows:

[0127] MOSFET devices Q1 and Q2 are connected via a NOT gate. In each cycle, Q1 and Q2 calculate the output T using model reference adaptive PI control. on Turning on and off. The MOSFET's turn-on is controlled by the inductor current returning to zero, i.e., the leakage current of Q1 is close to zero, determined by the sampling resistor R. Q Characteristic voltage u can be collected Q1 , when u Q1 >H (H is set to 0.2V): This indicates that the current is not yet zero, Q2 continues to conduct, when u Q1 ≤H: When the inductor current is zero, Q2 is turned off. The control process requires a zero-crossing detection circuit (ZCD) and an RS flip-flop to ensure the CrCM condition and provide a high control response speed. A triangular wave comparator provides a ramp signal, which is compared with a reference voltage to set the conduction time.

[0128] Step 4.1.2: Model Reference Adaptive PI Control Based on Voltage Harmonic Amplitude

[0129] CrCM itself is prone to increased output voltage ripple and power supply jitter under light load and input variations, making it difficult for traditional PI controllers to maintain good dynamic response across the entire operating range. Therefore, a Model Reference Adaptive Control (MRAC) mechanism is introduced, such as... Figure 4 As shown, adaptive parameter adjustment of the PI controller enhances the robustness and tracking capability of the system.

[0130] The transfer function of the Buck chopper circuit:

[0131]

[0132] PI controller transfer function:

[0133]

[0134] The transfer function of the closed-loop system: (where )

[0135]

[0136] Then we can obtain:

[0137]

[0138] Equation (7) is the duty cycle-impedance mapping model of the Buck chopper circuit. Based on Equation (7), a reference model with similar structure and ideal output characteristics is set:

[0139]

[0140] The system obtains the output voltage u through a sampling circuit. o The error is

[0141] e = u ref ―u o (9)

[0142] In the formula: u ref =3kI0λ I R, I0 are the rated excitation currents on the primary side, λ I is the current multiple, and k is the transformer ratio.

[0143] Introducing the Lilapunov performance function

[0144]

[0145] According to the MIT gradient rule, the rate of change of θ over time is proportional to the negative gradient J, i.e., In the formula, e represents the model error, and θ represents the controller parameter vector. The component is the sensitivity derivative of the error with respect to θ, and the parameter γ is the adaptive gain.

[0146] The value of the PI controller parameter K in equation (7) is determined by applying the MIT gradient rule. P and K I .

[0147]

[0148] In the formula

[0149]

[0150] The adaptive rule can be obtained from equations (11)-(14).

[0151]

[0152] K P K I The results can be obtained by integrating equations (15) and (16). In the reference model, a is set... m1 =RLC, a m2 =L, a m3 =(1+DK) P R, a m4 =DRK IThe value of the adaptive gain γ is defined as follows: γ P =―0.0005, γ I = -0.0005.

[0153] Step 4.2: The dual-switch BUCK chopper circuit updates the PWM signal with an adjustment period of 50µs to ensure that the equivalent resistance changes smoothly without abrupt changes.

[0154] Step 4.3: The resonant energy is converted into a DC component through a full-bridge uncontrolled rectifier circuit and a BUCK chopper circuit, and then rapidly released as heat dissipation through damping resistor 4.

[0155] Step 5: Protection and Status Feedback

[0156] Step 5.1: Real-time monitoring of core temperature and excitation current:

[0157] If the temperature is greater than 100℃ or the excitation current is greater than 10 times the nominal value, immediately switch to the maximum damping mode (0.1Ω) and trigger an alarm;

[0158] Step 5.2: Upload the resonance suppression status, damping resistance value, and fault code to the upper-level monitoring system via Modbus / TCP protocol;

[0159] Step 5.3: Generate a health assessment report every 5 minutes, including cumulative energy consumption, device temperature rise, and control parameter offset.

[0160] Step 6: Continuous Monitoring and Adaptive Optimization

[0161] Step 6.1: After resonance suppression, continuously monitor the voltage spectrum of the open delta. If no resonance characteristic is detected within 30 seconds, gradually reduce the damping so that the damping resistance 4 changes to the standby value (10kΩ).

[0162] Step 6.2: Train the resonance mode prediction model based on historical data and optimize the threshold weights for multi-parameter fusion diagnosis;

[0163] Step 6.3: Regularly self-calibrate the GMR sensor and voltage sampling channel to ensure measurement accuracy error <1%.

[0164] The above description only illustrates the preferred embodiments of the present invention. However, the present invention is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of the present invention, and all such changes should be included within the protection scope of the present invention.

Claims

1. A ferromagnetic resonant flexible device based on a power electronic converter, characterized in that, include: The power electronic converter module (1), connected to the secondary open delta of the voltage transformer, is configured to dynamically simulate the equivalent damping resistance by adjusting the duty cycle of the pulse width modulation (PWM) signal to achieve rapid dissipation of resonant energy. The signal acquisition module (2) is connected to the secondary side of the voltage transformer, the GMR sensor of giant magnetoresistance effect and the T-type thermocouple respectively, and is used to acquire the three-phase voltage, zero-sequence voltage, primary excitation current and transformer core temperature. The control module (3) is connected to the signal acquisition module (2) and the power electronic converter module (1) respectively. It performs ferromagnetic resonance identification and recognition based on the acquired signals, generates pulse width modulation (PWM) signals to drive the power electronic converter module, and realizes status indication, parameter configuration and data interaction with the upper-level monitoring system. The control module (3) include: The resonant feature extraction unit performs a Fast Fourier Transform (FFT) on the primary excitation current to extract the amplitude and frequency characteristics of the fundamental frequency, sub-frequency, and high-frequency components, and calculates the amplitude and rate of change of the open delta voltage, the amplitude and rate of change of the excitation current, and the core temperature rise rate. The multi-parameter fusion diagnostic unit, based on the feature weight fusion algorithm, generates a comprehensive resonance probability value by combining the zero-sequence voltage change rate, the excitation current distortion rate, and the core temperature rise rate. When the comprehensive resonance probability value exceeds the threshold, it is determined that ferroresonance has occurred. The composite control unit employs an algorithm that combines fixed on-time control of critical conduction mode (CrCM) with model reference adaptive PI control based on voltage harmonic amplitude. It dynamically adjusts the duty cycle of the pulse width modulation (PWM) signal according to the resonant mode to achieve continuous adjustment of the equivalent damping resistance. The damping resistor (4) is connected to the output side of the power electronic converter module (1) to dissipate resonant energy.

2. The ferromagnetic resonant flexible device based on a power electronic converter according to claim 1, characterized in that: The power electronic converter module (1) adopts a composite topology of a full-bridge uncontrolled rectifier circuit and a dual-switch BUCK chopper circuit. The dual-switch BUCK chopper circuit is connected to the output terminal of the full-bridge uncontrolled rectifier circuit. MOSFET devices are used as power switching devices, and their output terminals are connected to the damping resistor (4).

3. The ferromagnetic resonant flexible device based on a power electronic converter according to claim 1, characterized in that: The control module (3) also includes a protection and status feedback unit, which monitors the transformer core temperature and primary excitation current in real time. When the transformer core temperature exceeds 100°C or the primary excitation current exceeds 10 times the nominal value, it switches to the maximum damping mode and triggers an alarm. It also uploads the resonance suppression status, damping resistance value and fault code to the upper-level monitoring system via Modbus / TCP protocol and generates a health assessment report. The control module (3) continuously monitors the voltage spectrum of the open triangle after resonance suppression. If no resonance feature is detected within 30 seconds, the damping resistor (4) is gradually reduced to the standby value. The resonance mode prediction model is trained based on historical data, the threshold weight of the multi-parameter fusion diagnostic unit is optimized, and the GMR sensor and sampling channel are self-calibrated regularly to ensure that the measurement accuracy error is less than 1%.

4. A resonance suppression method for a ferromagnetic resonant flexible device based on a power electronic converter according to any one of claims 1-3, characterized in that, Includes the following steps: S1. Multi-dimensional signal acquisition and preprocessing: The primary excitation current is acquired by the GMR sensor, the secondary three-phase voltage and zero-sequence voltage are acquired by the high-precision voltage sensor, and the transformer core temperature is monitored by the T-type thermocouple. The signals are then filtered and noise-reduced. S2. Resonance Feature Extraction and Pattern Recognition: Perform FFT spectrum analysis on the primary excitation current to extract the fundamental frequency, frequency division, and high-frequency component features; Calculate the zero-sequence voltage change rate, excitation current distortion rate, and core temperature rise rate to identify the risk of core nonlinear saturation and overheating; S3. Multi-parameter fusion diagnosis and resonance determination: Based on the feature weight fusion algorithm, a comprehensive resonance probability value is generated by combining the zero-sequence voltage change rate, excitation current distortion rate and core temperature rise rate. When the comprehensive resonance probability value exceeds 80%, resonance is determined to have occurred, and the fundamental frequency, frequency division and high frequency resonance modes are distinguished according to the excitation current spectrum characteristics. S4. Dynamic damping adjustment and energy dissipation: The control strategy is selected according to the resonance mode. The fundamental frequency / sub-frequency resonance adopts the fixed conduction time control of the critical conduction mode CrCM. The high frequency resonance is combined with the model reference adaptive PI control. The equivalent damping resistor is dynamically adjusted by adjusting the duty cycle of the pulse width modulation PWM signal. The resonance energy is dissipated through the damping resistor (4) by the full-bridge uncontrolled rectifier circuit and the double-switch BUCK chopper circuit. S5. Protection and Status Feedback: Real-time monitoring of transformer core temperature and primary side excitation current; if limits are exceeded, switching to maximum damping mode and issuing an alarm; uploading status data and generating a health assessment report via Modbus / TCP protocol; S6. Continuous monitoring and adaptive optimization: After resonance suppression, continuously monitor the voltage spectrum of the open delta. If there is no resonance characteristic, reduce the damping resistance to the standby value. The threshold weights of the multi-parameter fusion diagnostic unit are optimized based on historical data, and the GMR sensor and sampling channel are periodically self-calibrated.

5. The resonance suppression method for a ferromagnetic resonant flexible device based on a power electronic converter according to claim 4, characterized in that, The method for multi-parameter fusion diagnosis and resonance determination in S3 is as follows: S3.1 Based on the feature weight fusion algorithm, the zero-sequence voltage change rate Ku and the excitation current distortion rate I are combined. THD and core temperature rise rate Generate the comprehensive resonance probability value P: When P > 80%, ferromagnetic resonance is determined to have occurred. S3.2 After ferromagnetic resonance occurs, based on the excitation current spectrum characteristics, ferromagnetic resonance is identified under the following conditions: Fundamental frequency resonance: 50Hz component amplitude > 5 times rated excitation current and excitation current distortion rate > 30%; Frequency division resonance: the amplitude of the 25Hz / 17Hz component accounts for more than 60% of the total excitation current and the excitation current distortion rate is greater than 20%; High-frequency resonance: Excitation current amplitude > 8 times the rated excitation current and the amplitude of the 150Hz~1kHz frequency band component > 20% and the excitation current distortion rate > 60%.

6. The resonance suppression method for a ferromagnetic resonant flexible device based on a power electronic converter according to claim 4, characterized in that, The method for dynamic damping adjustment and energy dissipation in S4 is as follows: S4.

1. Select control strategy based on resonant mode. The control module adopts a control algorithm that combines fixed on-time control based on critical conduction mode (CrCM) with model reference adaptive PI control based on voltage harmonic amplitude, aiming to ensure high system efficiency while achieving high-precision and stable control of the output voltage. Fundamental / division resonant: Fixed on-time control using critical conduction mode (CrCM) is employed. The duty cycle of the pulse width modulation (PWM) signal is adjusted to ensure the equivalent damping resistance is within a certain range. Continuous adjustment within the range; High-frequency resonance: Combining critical conduction mode (CrCM), model reference adaptive PI control is enabled. The PI parameters are dynamically optimized based on the resonant energy intensity, and the duty cycle is adjusted to achieve [high-frequency resonance]. High resistance for rapid switching; S4.2 The dual-switch BUCK chopper circuit updates the pulse width modulation (PWM) signal with a 50µs adjustment period to ensure smooth and stepless changes in the equivalent damping resistance. S4.3 The resonant energy is converted into a DC component through a full-bridge uncontrolled rectifier circuit and a dual-switch BUCK chopper circuit, and then rapidly released as heat dissipation through a damping resistor (4).

7. The resonance suppression method for a ferromagnetic resonant flexible device based on a power electronic converter according to claim 6, characterized in that, The method for preferentially selecting the control strategy based on the resonant mode in S4.1 is as follows: S4.1.1 Fixed On-Time Control Mode of Critical On-Mode CrCM Using fixed conduction time The strategy is the CrCM operating mode. In the CrCM operating mode, the inductor current starts at zero and returns to zero in each switching cycle, which achieves quasi-zero current turn-on (ZCS) and greatly reduces switching losses. MOSFET devices Q1 and Q2 are connected via a NOT gate. In each cycle, the fixed on-time of MOSFET devices Q1 and Q2 is calculated using model reference adaptive PI control. The MOSFETs Q1 and Q2 are controlled to turn on and off. The on-state control is determined by the inductor current returning to zero, i.e., the leakage current of MOSFET Q1 is close to zero, and this is achieved through a sampling resistor R. Q Characteristic voltages can be collected. ,when This indicates that the current is not yet zero, and MOSFET device Q2 continues to conduct. When the inductor current is zero, MOSFET device Q2 is turned off. The control process requires a zero-crossing detection circuit (ZCD) and an RS flip-flop to ensure the CrCM condition and provide a high control response speed. A triangular wave comparator provides a ramp signal, which is compared with a reference voltage to set a fixed on-time. ; S4.1.2 Model Reference Adaptive PI Control Based on Voltage Harmonic Amplitude A model reference adaptive PI control (MRAC) mechanism is introduced to adaptively adjust the parameters of the PI controller, thereby enhancing the robustness and tracking capability of the system. Transfer function of a double-switch BUCK: PI controller transfer function: The transfer function of a closed-loop system: where Then we get: The above equation is the duty cycle-impedance mapping model of the dual-switch BUCK chopper circuit. Based on the duty cycle-impedance mapping model, a reference model with a similar structure and ideal output characteristics is defined: The system obtains the output voltage through the signal acquisition module. The error is In the formula: I0 is the rated excitation current on the primary side. Where k is the current multiple and k is the transformer ratio; Introducing the Lilapunov performance function According to the MIT gradient rule Time rate of change and negative gradient Proportional, that is In the formula, For error, For the controller parameter vector, The component is the error pair The sensitivity derivative, parameter For adaptive gain; Determining the values ​​of PI controller parameters using the MIT gradient rule and ; In the formula , , ; The adaptive rule is derived as follows: Setting in the reference model , , , Adaptive gain The value is defined as follows: , .

8. The resonance suppression method for a ferromagnetic resonant flexible device based on a power electronic converter according to claim 4, characterized in that, The protection and status feedback method in S5 is as follows: S5.1 Real-time monitoring of transformer core temperature and primary excitation current: If the transformer core temperature is >100℃ or the primary excitation current is >10 times the nominal value, immediately switch to maximum damping mode and trigger an alarm; S5.2 Upload the resonance suppression status, damping resistance value and fault code to the upper-level monitoring system via Modbus / TCP protocol; S5.3 Generates a health assessment report every 5 minutes, including cumulative energy consumption, device temperature rise, and control parameter offset.

9. The resonance suppression method for a ferromagnetic resonant flexible device based on a power electronic converter according to claim 4, characterized in that, The method for continuous monitoring and adaptive optimization in S6 is as follows: S6.1 After resonance suppression, continuously monitor the voltage spectrum of the open delta. If no resonance characteristic is detected within 30 seconds, gradually reduce the damping so that the damping resistance (4) becomes the standby value. S6.

2. Train the resonant mode prediction model based on historical data and optimize the threshold weights of the multi-parameter fusion diagnostic unit; S6.3 Regularly self-calibrate the GMR sensor and sampling channel to ensure measurement accuracy error <1%.

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