Harmonic suppression and dynamic compensation system of active filter based on IGBT multi-modal regulation

Abstract

The application relates to the technical field of reactive power compensation of power systems, and discloses a system for harmonic suppression and dynamic compensation of an active filter based on IGBT multi-mode regulation, which comprises a control module, a high-frequency harmonic detection module, an IGBT gate drive compensation circuit and an IGBT junction temperature observer. The high-frequency harmonic detection module is electrically connected to the control module and is configured to detect power grid harmonic signals in real time at a sampling rate of 200 kHz and transmit the signals to the control module. The IGBT gate drive compensation circuit is electrically connected to the control module and a preset IGBT module, and the control module dynamically adjusts the dead time and switching frequency of the IGBT module through the IGBT gate drive compensation circuit. The IGBT junction temperature observer is electrically connected to the IGBT module and the control module and is configured to monitor the junction temperature of the IGBT module in real time. When the junction temperature exceeds 125 DEG C, the control module triggers a derating protection mechanism. Based on the detection signals of the high-frequency harmonic detection module, the control module generates a PWM compensation waveform through a model predictive control algorithm unit, so that the IGBT module performs harmonic compensation through the IGBT gate drive compensation circuit.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of reactive power compensation of power systems, and particularly relates to a harmonic suppression and dynamic compensation system of an active power filter based on IGBT multi-modal regulation. BACKGROUND

[0002] With the wide application of industrial nonlinear loads (such as frequency converters and rectifiers), the problems of power grid harmonic pollution and reactive power imbalance are increasingly serious. Although the traditional active power filter (APF) can realize harmonic compensation, it generally has the following technical bottlenecks: first, the control algorithm mostly adopts PI control or traditional hysteresis control with fixed parameters, which is difficult to dynamically adapt to complex harmonic scenarios, and the total harmonic distortion (THD) suppression precision is insufficient and the switching loss is high; second, the IGBT dead time is fixedly set and not dynamically adjusted in combination with real-time working conditions, which leads to the risk of upper and lower bridge arm short circuit and distortion of compensation waveform; third, the junction temperature monitoring relies on external sensors or simplified models, which cannot accurately evaluate the thermal state of the device, the protection mechanism responds laggingly under high temperature, and lacks fault positioning capability, resulting in high operation and maintenance cost; fourth, the reactive power regulation range is narrow, which is difficult to meet the demand of bidirectional power flow of power grid.

[0003] In the prior art, although model predictive control (MPC) is applied in APF, the coupling influence of IGBT switching characteristics, dead time and junction temperature is not fully considered, and the detection sampling rate is generally lower than 50 kHz, which is difficult to capture high-frequency harmonic components; at the same time, the IGBT driving circuit and the thermal management system are relatively independent, and lack of multi-modal coordinated regulation mechanism, which leads to the difficulty in balancing between high-precision compensation and reliability of the system.

[0004] Therefore, there is an urgent need for a harmonic suppression and dynamic compensation system of an active power filter based on IGBT multi-modal regulation to solve at least one of the above problems. SUMMARY

[0005] The present application provides a harmonic suppression and dynamic compensation system of an active power filter based on IGBT multi-modal regulation, which aims to solve the problems that the traditional active power filter (APF) can realize harmonic compensation, but generally has the following technical bottlenecks: first, the control algorithm mostly adopts PI control or traditional hysteresis control with fixed parameters, which is difficult to dynamically adapt to complex harmonic scenarios, and the total harmonic distortion (THD) suppression precision is insufficient and the switching loss is high; second, the IGBT dead time is fixedly set and not dynamically adjusted in combination with real-time working conditions, which leads to the risk of upper and lower bridge arm short circuit and distortion of compensation waveform; third, the junction temperature monitoring relies on external sensors or simplified models, which cannot accurately evaluate the thermal state of the device, the protection mechanism responds laggingly under high temperature, and lacks fault positioning capability, resulting in high operation and maintenance cost; fourth, the reactive power regulation range is narrow, which is difficult to meet the demand of bidirectional power flow of power grid, and the like.

[0006] In a first aspect, the embodiments of the present application provide an active filter harmonic suppression and dynamic compensation system based on IGBT multi-modal regulation, comprising:

[0007] a control module configured to construct a multi-modal collaborative control architecture, the multi-modal collaborative control architecture comprising a model predictive control algorithm unit that generates a PWM compensation waveform in real time;

[0008] a high-frequency harmonic detection module electrically connected to the control module and configured to detect power grid harmonic signals in real time at a sampling rate of 200 kHz and transmit the signals to the control module;

[0009] an IGBT gate drive compensation circuit electrically connected to the control module and a preset IGBT module, the control module dynamically adjusts the dead time and switching frequency of the IGBT module through the IGBT gate drive compensation circuit;

[0010] an IGBT junction temperature observer electrically connected to the IGBT module and the control module and configured to monitor the junction temperature of the IGBT module in real time, and trigger the control module to start a derating protection mechanism when the junction temperature exceeds 125℃;

[0011] The control module generates the PWM compensation waveform through the model predictive control algorithm unit based on the detection signals of the high-frequency harmonic detection module, drives the IGBT module to perform harmonic compensation through the IGBT gate drive compensation circuit, realizes dynamic compensation of reducing total harmonic distortion rate from 15% to below 3% and bidirectional adjustment of reactive power ±1Mvar, and integrates a fault positioning unit in the IGBT junction temperature observer for fault positioning of the IGBT module.

[0012] In some embodiments, the generation of the PWM compensation waveform through the model predictive control algorithm unit includes constructing a prediction model containing IGBT switching characteristics, dead time effects and power grid harmonic characteristics, performing rolling optimization calculation on harmonic current compensation amount in the next control period based on 200 kHz sampling signals input in real time by the high-frequency harmonic detection module, and generating a PWM drive signal sequence containing dead time compensation and switching frequency dynamic adjustment parameters.

[0013] Exemplarily, the IGBT module is driven by the IGBT gate drive compensation circuit to perform harmonic compensation, so as to reduce the total harmonic distortion rate from 15% to below 3% and realize dynamic compensation of bidirectional adjustable reactive power of ±1 Mvar, including: according to the dead-time adjustment instruction carried in the PWM compensation waveform, the phase difference of the driving signals of the upper and lower bridge arms of the IGBT is corrected in real time through the IGBT gate drive compensation circuit, and the switching frequency is dynamically adjusted according to the reactive power compensation target, so that the IGBT module outputs compensation current with the same amplitude and opposite phase as the harmonic current of the power grid, and the bidirectional power flow control circuit is used to realize the adjustable output of inductive or capacitive reactive power of ±1 Mvar.

[0014] Exemplarily, in the rolling optimization process, the model predictive control algorithm unit introduces an adaptive weight factor to perform multi-objective optimization on THD suppression effect and switching loss, and the weight factor is dynamically adjusted in real time according to the IGBT junction temperature: when the junction temperature is greater than or equal to 100°C, the switching loss weight is automatically increased to above 0.7, and the IGBT heating is preferentially reduced; when the junction temperature is less than 100°C, the weight is inclined to THD suppression, so that the compensation accuracy is increased by 20%.

[0015] In some embodiments, the junction temperature of the IGBT module is monitored in real time, and when the junction temperature exceeds 125°C, the control module is triggered to start the derating protection mechanism, including: the IGBT junction temperature observer constructs a thermal network model based on the IGBT on-state voltage drop, switching loss and heat dissipation parameters, estimates the chip junction temperature in real time, and sends a derating instruction to the control module when the junction temperature exceeds 125°C. The control module reduces the IGBT loss by more than 30% by reducing the switching frequency, limiting the maximum compensation current and switching to a low-loss control mode, and records the time-temperature curve of the abnormal junction temperature through the fault positioning unit for subsequent fault analysis.

[0016] In some embodiments, the power grid harmonic signal is detected in real time at a sampling rate of 200 kHz and transmitted to the control module, including: the high-frequency harmonic detection module integrates an anti-aliasing filter and a synchronous sampling phase-locked loop, and performs 200 kHz synchronous sampling on the power grid voltage and current signals. The amplitude, phase and frequency parameters of 2-50 harmonic components are extracted through fast Fourier transform (FFT), a digital signal sequence containing the characteristics of each harmonic is generated and transmitted to the control module.

[0017] In some embodiments, the dynamic adjustment of the dead time and switching frequency of the IGBT module by the IGBT gate drive compensation circuit includes: the IGBT gate drive compensation circuit integrates an adjustable delay unit and a frequency control module, the control module dynamically adjusts the dead time and switching frequency according to the current harmonic compensation accuracy and IGBT junction temperature state through a fuzzy adaptive algorithm, and in a high harmonic content scenario, the switching frequency is increased to enhance the compensation accuracy, and in a high temperature scenario, the dead time is reduced to reduce the switching loss; the adjustment step corresponding to the dead time is ≤100 ns; the adjustment range corresponding to the switching frequency is 10 kHz-50 kHz.

[0018] In some embodiments, the fault positioning of the IGBT module includes: the fault positioning unit constructs a fault feature database based on the IGBT gate drive voltage waveform, the collector current abnormal fluctuation signal and the junction temperature mutation data, performs pattern recognition on fault types such as overcurrent, short circuit and drive circuit failure through a support vector machine algorithm, and combines the dead time and switching frequency adjustment parameters when the fault occurs to position the fault to a specific IGBT chip or drive circuit element.

[0019] In some embodiments, the multi-modal collaborative control architecture integrates an IGBT aging prediction module based on a long short-term memory network, the IGBT aging prediction module predicts the remaining life of the IGBT module and dynamically adjusts the control strategy by learning historical junction temperature fluctuations, switching times and fault data: when the predicted remaining life <20%, automatically switch to a conservative control mode, reduce the switching frequency by 25% and expand the dead time safety margin, and prolong the service period of the device.

[0020] In some embodiments, the model predictive control algorithm unit embeds a harmonic current prediction model based on Kalman filtering when generating the PWM compensation waveform, the model combines power grid load change trends and historical harmonic data to predict and compensate harmonic components within 200 μs in the future, so that the dynamic response time is shortened to 50 μs.

[0021] The embodiment of the application provides a kind of active filter harmonic suppression and dynamic compensation system based on IGBT multimodal regulation, comprising: control module: the architecture containing model predictive control (MPC) algorithm unit is constructed, real-time generates PWM compensation waveform, realizes multi-objective optimization (THD suppression and switch loss balance);High-frequency harmonic detection module: with 200kHz high sampling rate real-time detection power grid harmonic signal (2-50 times component), provide accurate input for control module;IGBT gate drive compensation circuit: dynamically adjust IGBT dead time (step ≤100ns) and switching frequency (10kHz-50kHz), correct driving signal phase difference and adapt to working condition change;IGBT junction temperature observer: based on thermal network model estimates junction temperature, triggers derating protection (reduces loss by more than 30%) when more than 125 DEG C, and integrates fault positioning unit to realize device-level fault diagnosis;

[0022] THD is reduced from 15% to below 3% by rolling optimization of harmonic compensation amount by MPC algorithm, and PWM sequence containing dead zone / frequency parameters is generated by combining high-frequency detection signal to drive IGBT to output inverse compensation current, realize the dynamic compensation of reactive power ±1Mvar bidirectional adjustable.

[0023] The provided system has at least the following beneficial effects:

[0024] High-precision harmonic suppression: 200kHz high-frequency detection combined with model predictive control, accurately capture high-frequency harmonic characteristics, THD suppression ability increased by more than 5 times, meet the stringent power quality standards;

[0025] Strong dynamic adaptability: dynamically adjust dead time and switching frequency according to real-time working condition, improve compensation accuracy in high harmonic scenario, reduce loss in high temperature scenario, balance performance and reliability;

[0026] Intelligent thermal management and fault protection: junction temperature observer real-time evaluates device state, derating protection mechanism effectively avoids overheating failure, fault positioning unit realizes rapid operation and maintenance, reduces downtime;

[0027] Bidirectional reactive power regulation capability: support ±1Mvar reactive power dynamic output, adapt to complex power grid scenarios such as new energy access, improve system flexibility;

[0028] Multi-modal collaborative optimization: through adaptive weight factor and aging prediction module, realize control strategy self-adjustment, prolong IGBT service period and reduce long-term operation and maintenance cost.

[0029] The above technical scheme breaks through the limitations of traditional active filter in precision, reliability and adaptability through multi-module cooperation and dynamic regulation of key parameters, and has significant technical progress and industrial application value.

[0030] It should be understood that the general description and detailed description of the foregoing are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF DRAWINGS

[0031] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0032] Figure 1 is a structural schematic block diagram of an active filter harmonic suppression and dynamic compensation system based on IGBT multi-modal regulation provided by an embodiment of the present application.

[0033] It should be understood that the general description and detailed description of the foregoing are only exemplary and explanatory, and cannot limit the present application. DETAILED DESCRIPTION

[0034] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are some embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0035] The flowcharts shown in the drawings are only exemplary descriptions, and do not necessarily include all the contents and operations / steps, and do not necessarily be executed in the described order. For example, some operations / steps can be decomposed, combined or partially merged, so that the actual execution order can be changed according to the actual situation.

[0036] It should be understood that, in order to clearly describe the technical solutions of the embodiments of the present application, in the embodiments of the present application, the same items or similar items with basically the same functions and effects are distinguished by using "first", "second" and the like. Those skilled in the art can understand that "first", "second" and the like do not limit the quantity and execution order, and "first", "second" and the like do not necessarily mean different.

[0037] It should be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and do not intend to limit the present application. As used in the present application specification and the appended claims, unless otherwise clearly indicated by the context, the singular form "a", "an" and "the" are intended to include the plural form.

[0038] It should also be understood that the term "and / or" as used herein refers to any one of the associated listed items, or a combination of any of the associated listed items, and all possible combinations, and includes these combinations.

[0039] Some embodiments of the present application will be described in detail with reference to the drawings. The following examples and features in the examples can be combined with each other in the case of no conflict.

[0040] With the wide application of industrial nonlinear loads such as frequency converters and rectifiers, the problems of power grid harmonic pollution and reactive power imbalance are becoming increasingly serious. Although the traditional active power filter (APF) can achieve harmonic compensation, it generally has the following technical bottlenecks: first, the control algorithm mostly uses PI control or traditional hysteresis control with fixed parameters, which is difficult to dynamically adapt to complex harmonic scenarios, and the total harmonic distortion (THD) suppression precision is insufficient and the switching loss is high; second, the IGBT dead time is fixedly set and not dynamically adjusted in combination with real-time working conditions, resulting in the risk of upper and lower bridge arm short circuit and compensation waveform distortion; third, the junction temperature monitoring relies on external sensors or simplified models, which cannot accurately assess the thermal state of the device, the protection mechanism responds laggingly under high temperature, and lacks fault positioning capability, resulting in high operation and maintenance cost; fourth, the range of reactive power regulation is narrow, which is difficult to meet the demand of bidirectional power flow of power grid.

[0041] In the prior art, model predictive control (MPC) has been applied in APF, but the coupling effects of IGBT switching characteristics, dead time and junction temperature have not been fully considered, and the detection sampling rate is generally lower than 50kHz, which is difficult to capture high-frequency harmonic components; at the same time, the IGBT drive circuit and the thermal management system are relatively independent, and lack of multi-modal coordinated control mechanism, resulting in difficulty in balancing between high-precision compensation and reliability of the system.

[0042] Therefore, there is an urgent need for an active filter harmonic suppression and dynamic compensation system based on IGBT multi-modal regulation to solve at least one of the above problems.

[0043] To solve the above problems, please refer to Figure 1The embodiment of the application provides a kind of active filter harmonic suppression and dynamic compensation system based on IGBT multimodal regulation, the system includes: control module, configured to build multi-modal collaborative control architecture, the multi-modal collaborative control architecture includes model predictive control algorithm unit, the model predictive control algorithm unit generates PWM compensation waveform in real time;High-frequency harmonic detection module is electrically connected with the control module, and is configured to detect power grid harmonic signal in real time with 200kHz sampling rate and transmit to the control module;IGBT gate drive compensation circuit is electrically connected with the control module and preset IGBT module, and the control module dynamically adjusts the dead time and switching frequency of the IGBT module by the IGBT gate drive compensation circuit;IGBT junction temperature observer is electrically connected with the IGBT module and the control module, and is configured to monitor the junction temperature of the IGBT module in real time, and triggers the control module to start the derating protection mechanism when the junction temperature exceeds 125 DEG C;Wherein, the control module generates the PWM compensation waveform by the model predictive control algorithm unit based on the detection signal of the high-frequency harmonic detection module, to drive the IGBT module to execute harmonic compensation by the IGBT gate drive compensation circuit, realize that total harmonic distortion rate is reduced from 15% to below 3% and the dynamic compensation of reactive power ±1Mvar bidirectional adjustable;The IGBT junction temperature observer integrates fault positioning unit, for fault positioning of the IGBT module.

[0044] Specifically, the model predictive control algorithm unit (MPC) is distinguished from the traditional fixed parameter PI control or hysteresis control, and adopts the model predictive control algorithm to predict the coupling relationship between power grid harmonic state and IGBT switching behavior in real time. The algorithm integrates IGBT switching characteristics (such as on-resistance, switching delay), dead time dynamic adjustment logic and junction temperature thermal model, and generates optimal PWM compensation waveform in real time by rolling optimization objective function (such as minimizing THD, switching loss, junction temperature fluctuation).

[0045] Multi-modal collaborative mechanism: establish the collaborative regulation link of control module, drive circuit and thermal management system, dynamically switch control strategy (such as high-frequency compensation mode, energy-saving mode, derating protection mode) according to real-time working condition (such as load harmonic frequency, IGBT junction temperature, power grid reactive power demand), realize the balance of high-precision compensation and device reliability.

[0046] The high-frequency harmonic detection module adopts 200kHz ultra-high frequency sampling rate to collect power grid voltage and current signals in real time. Compared with the traditional sampling rate below 50kHz, it can accurately capture high-frequency harmonic components (such as carrier harmonics generated by frequency converter) above 20kHz, provide high-resolution harmonic feature data (including harmonic amplitude, phase, frequency) for the control module, and support the dynamic adaptation of MPC algorithm to complex harmonic scenes.

[0047] The IGBT gate drive compensation circuit is integrated with a dynamic dead-time adjustment module and a switching frequency adaptive module. The dead-time is dynamically adjusted according to the current junction temperature of the IGBT, bus voltage and switching frequency, and the optimal dead-time is calculated in real time (instead of the traditional fixed dead-time setting), which avoids the risk of upper and lower bridge arm shoot-through (such as increasing the dead-time when the junction temperature rises to compensate for the switching delay difference of the device), and reduces the distortion of the compensation waveform caused by fixed dead-time.

[0048] The switching frequency is adaptively adjusted in combination with the PWM waveform output by the MPC algorithm (such as increasing the switching frequency in high-frequency harmonic scenarios to improve compensation accuracy, and reducing the frequency in low-load scenarios to reduce loss), which realizes the optimal balance between switching loss and compensation effect.

[0049] The IGBT junction temperature observer uses non-contact junction temperature monitoring. It discards external sensors or simplifies the thermal model, uses a real-time observation algorithm based on the nonlinear mapping relationship between IGBT on-state voltage (V CE(on)) and junction temperature, and combines the thermal resistance model of the device junction to the shell (considering the real-time heat dissipation efficiency of the heat sink) to accurately calculate the junction temperature (error ≤ ±2℃).

[0050] Fault positioning unit: integrated multi-sensor data fusion (such as drive circuit voltage, IGBT current, temperature gradient), through fault feature library matching (such as junction temperature mutation, switching waveform anomaly), realize the accurate positioning of IGBT module fault (such as solder layer falling off, gate drive failure) (positioning accuracy to single tube IGBT), solve the problem that traditional protection mechanism can only respond to high temperature but cannot locate the fault point.

[0051] MPC algorithm coupled with IGBT characteristics modeling: Introduce the influence function of IGBT switching delay time and dead-time on PWM waveform in the prediction model, and the temperature characteristic parameters of junction temperature on device switching speed (such as temperature rise leading to increased switching loss), so that the control algorithm directly senses the physical state change of the device, and improves the real-time and robustness of the control strategy.

[0052] By optimizing the objective function of the MPC algorithm, the reactive power regulation range is expanded to ±1Mvar (traditional APF is usually ≤±0.5Mvar), supporting bidirectional dynamic compensation of grid capacitive / inductive reactive power, adapting to new energy grid connection and other bidirectional power flow scenarios.

[0053] The high-frequency harmonic detection module collects three-phase voltage ua, ub, uc and current ia, ib, ic at a rate of 200kHz, extracts each harmonic component (focuses on 5th, 7th, 11th, etc. high-frequency harmonics) through fast Fourier transform (FFT), and generates a harmonic feature vector (amplitude, phase, frequency) to transmit to the control module.

[0054] The model predictive control unit receives the harmonic feature vector, combines the junction temperature Tj fed back in real time by the IGBT junction temperature observer, the current dead time tdead of the drive circuit, and the switching frequency fs, and constructs a prediction model: state variables: grid harmonic current ih, APF compensation current ic, and IGBT junction temperature Tj; control variables: PWM duty cycle d, dead time tdead, and switching frequency fs; objective function: J = λ1||ih-ic|| + λ2fs + λ3(Tj-Tnom) 2 2 ; wherein λ1, λ2, and λ3 are weight coefficients that balance harmonic suppression accuracy, switching loss, and junction temperature stability. The optimal control variables in the next 2-3 switching periods are solved by rolling optimization, and the PWM compensation waveform is generated and output to the IGBT gate drive compensation circuit.

[0055] The drive circuit dynamically adjusts: according to the PWM signal output by the control module and the real-time dead time tdead, a drive pulse with dead zone compensation is generated to ensure that the upper and lower bridge arm switching signals do not overlap (eliminate the risk of shoot-through), and the IGBT switching process is optimized through dynamic switching of the gate resistance (such as reducing the resistance to reduce the switching delay when the switching speed is high).

[0056] The junction temperature observer calculates Tj in real time. When Tj≥125℃ (IGBT safe working temperature threshold), a derating signal is sent to the control module to trigger the following actions: reduce the switching frequency to the safe range (such as from 20kHz to 15kHz) to reduce switching loss; increase the dead time to compensate for the slow switching speed of IGBT at high temperature; the fault positioning unit synchronously collects the drive voltage and current waveform, and matches the preset fault characteristics (such as abnormal rise of on-state voltage of IGBT in a certain phase) through a neural network model to locate the faulty device and report to the operation and maintenance system.

[0057] The control module adjusts the phase and amplitude of the compensation current based on the grid reactive power detection result (inductive reactive power is positive, capacitive reactive power is negative) through the MPC algorithm to make the APF work in rectifier or inverter mode: when the grid is inductive (reactive power Q>0), the APF outputs capacitive reactive power (current leads voltage); when the grid is capacitive (Q<0), the APF absorbs capacitive reactive power (current lags voltage), achieving continuous adjustment within ±1Mvar.

[0058] Traditional APF is limited by fixed parameter control and low sampling rate, and the THD suppression capability is usually 5%-10%. The system reduces THD from 15% to below 3% (meets the strict harmonic standard of IEEE 519-2014) through 200kHz high-frequency detection and MPC algorithm dynamic optimization, especially for the suppression of high-frequency harmonics above 20kHz, which improves the suppression effect by 60%, solving the problem of high-frequency pollution of nonlinear loads (such as frequency converters). ​

[0059] Dead-time dynamic adjustment eliminates the risk of upper and lower bridge arm shoot-through, compared with the traditional fixed dead-time design, the shoot-through failure rate is reduced by 80%; the accuracy of junction temperature observation is improved, the high temperature protection response time is shortened from 50ms of the traditional scheme to less than 10ms, avoiding the desaturation failure of IGBT due to overheating; the fault positioning unit realizes the IGBT module level fault diagnosis (such as distinguishing single tube damage and drive circuit fault), the operation and maintenance personnel can directly locate the fault device, reducing the troubleshooting time by more than 70%, reducing the operation and maintenance cost.

[0060] Multi-modal collaborative control makes the system automatically switch control strategies in complex scenarios such as industrial variable frequency load (harmonic frequency 10-30kHz), rectifier (mainly low-order harmonic), etc., and quickly compensates when the load suddenly changes (response time ≤50μs); the reactive power regulation range is expanded to ±1Mvar, meeting the reactive power compensation needs of bidirectional power flow scenarios such as new energy grid connection and electric vehicle charging, and improving the traditional APF regulation range by 100%.

[0061] Through adaptive adjustment of switching frequency and precise matching of dead-time by MPC algorithm, the system switching loss is reduced by more than 40% compared with traditional hysteresis control, and the efficiency is improved to 98.5% under rated load, meeting the industrial energy saving needs.

[0062] Through the whole-link technology innovation of "high-frequency detection-model prediction-multi-modal driving-accurate thermal management", the system breaks through the bottleneck of traditional APF in control accuracy, reliability and adaptability, realizes the deep collaboration of harmonic suppression, reactive power compensation and device protection, and provides a high-performance solution for industrial power grid harmonic suppression, especially suitable for intelligent manufacturing, new energy and other fields with high harmonic pollution and high reliability requirements.

[0063] In some embodiments, the generating the PWM compensation waveform by the model predictive control algorithm unit comprises: constructing a prediction model containing IGBT switching characteristics, dead-time influence and power grid harmonic characteristics, based on the 200kHz sampling signal input by the high-frequency harmonic detection module in real time, the harmonic current compensation amount in the next control period is calculated by rolling optimization, and the PWM driving signal sequence containing dead-time compensation and switching frequency dynamic adjustment parameters is generated.

[0064] A state space model containing three characteristics is established: IGBT switching characteristics: extract IGBT on-resistance Ron, switching delay time td(on) / td(off), gate charge Qg and other parameters, and construct the influence function of PWM waveform in switching process (such as the phase deviation of compensation current caused by conduction delay).

[0065] Dead-time effect: Taking the dead-time tdead as a controllable variable, the mathematical relationship between the risk of shoot-through and the dead-time is established (e.g., tdead≥td(on)max-td(off)min+Δt, where Δt is a safety margin), and the influence of the dead-time on the compensation current waveform distortion is quantified (e.g., the mapping relationship between the fundamental component attenuation rate and the dead-time).

[0066] Grid harmonic characteristics: Based on the 200 kHz sampling signal output by the high-frequency detection module, the harmonic current state equation ih(k+1) = A * ih(k) + B * uc(k) is constructed, where A is the harmonic state transition matrix, B is the compensation voltage influence matrix, and uc is the APF output voltage.

[0067] Model input: Current harmonic current amplitude / phase, IGBT junction temperature Tj, bus voltage Vdc.

[0068] Rolling optimization calculation: The control period is set to 5 μs (corresponding to a 200 kHz control frequency), and the harmonic current trajectory for the next 3 control periods (15 μs) is predicted in each period. The objective function includes three optimization objectives: J = α||ihref-ic||2+βfs+γtdead; where α, β, γ are weight coefficients, ihref is the expected compensated harmonic current (ideal value is 0), fs is the switching frequency, and tdead is the dead-time. 2 +βfs 2 +γtdead; where α, β, γ are weight coefficients, ihref is the expected compensated harmonic current (ideal value is 0), fs is the switching frequency, and tdead is the dead-time.

[0069] Real-time optimization using quadratic programming (QP) solver, outputting the optimal control quantity for the next period: including dead-time compensation value (such as safe dead-time under current junction temperature), switching frequency fs, PWM duty cycle d.

[0070] PWM drive signal generation: According to the optimization results, the PWM signal sequence including dead-time compensation is generated, for example: for the upper bridge arm drive signal Vgup and the lower bridge arm signal Vgdown, based on the traditional complementary signal, the dynamic dead-time tdead is inserted (e.g., Vgup is turned off and then turned on after a delay of tdead Vgdown), and precise timing control is achieved through the hardware delay unit of the gate drive circuit.

[0071] The prediction model fuses the physical characteristics of IGBT and the harmonic characteristics of the power grid, so that the control algorithm no longer relies on fixed parameters and can respond to load changes (such as frequency fluctuation of the inverter carrier) in real time, solving the problems of "parameter tuning difficulty" and "slow dynamic response" of traditional PI control, and especially improving the compensation accuracy of high-frequency harmonics above 30 times by 50%. The dead time and switching frequency are included in the optimization variables to avoid the distortion of the compensation waveform caused by the fixed dead time in traditional schemes (such as the 5th harmonic amplitude error reduced from 12% to less than 3% caused by the traditional dead time setting), and at the same time, through dynamic adjustment of the switching frequency, low switching loss can still be maintained in high harmonic scenarios (such as THD = 15%) (35% lower than traditional hysteresis control).

[0072] For example, the IGBT module driven by the IGBT gate drive compensation circuit performs harmonic compensation, realizes dynamic compensation of total harmonic distortion from 15% to less than 3% and bidirectional adjustable reactive power ±1Mvar, including: according to the dead time adjustment instruction carried in the PWM compensation waveform, the IGBT gate drive compensation circuit adjusts the phase difference of the drive signals of the upper and lower bridge arms in real time, and according to the dynamic adjustment of the switching frequency according to the reactive power compensation target, the IGBT module outputs a compensation current with the same amplitude and opposite phase as the grid harmonic current, and realizes the output of ±1Mvar adjustable inductive or capacitive reactive power through the bidirectional power flow control circuit.

[0073] The PWM compensation waveform output by the control module carries real-time dead time adjustment instructions (such as the current calculated safe dead time of 400ns), and the adjustable delay unit of the compensation circuit adjusts the phase difference of the upper and lower bridge arm drive signals according to the instructions.

[0074] The hardware implementation uses programmable logic devices (CPLD) to generate drive signals, and writes dead time parameters in real time through registers, for example: when the upper bridge arm off signal is triggered, the CPLD forcibly blocks the lower bridge arm on signal for tdead time, ensuring that the two bridge arms are not turned on at the same time.

[0075] Switching frequency adaptive adjustment: according to the reactive power compensation target (such as the current need to compensate-0.8Mvar capacitive reactive power), the control module calculates the required optimal switching frequency (such as increasing the switching frequency to 30kHz under capacitive load to enhance the high-frequency current tracking ability), and adjusts the carrier period of the PWM signal through the frequency control module.

[0076] Bidirectional power flow control circuit: integrated bidirectional DC-AC converter topology (such as H-bridge structure), by controlling the conduction sequence of IGBT, APF can not only output compensation current (absorb inductive reactive power), but also absorb grid current (output capacitive reactive power), cooperate with current sensor real-time feedback, form closed-loop control.

[0077] Compensation current generation: IGBT module outputs compensation current ic according to the driving signal, and injects into the power grid through the LCL filter to filter out the switching ripple, so that ic is equal in amplitude and opposite in phase to the harmonic current ih of the power grid (error ≤2%), and finally realizes THD≤3%.

[0078] Through dynamic correction of dead time, the distortion of compensation current caused by traditional fixed dead time is eliminated (for example, the 3rd harmonic residual in the traditional scheme is reduced from 5% to less than 0.5% due to insufficient dead time setting), and the system's suppression ability to harmonics above 20 kHz is improved by 70% with the cooperation of 200 kHz high-frequency detection, meeting the stringent requirements of precision electronic equipment on power grid purity. The combination of bidirectional power flow control circuit and adaptive switching frequency realizes continuous regulation of reactive power from-1 Mvar (capacitive) to +1 Mvar (inductive), especially suitable for new energy grid-connected scenarios (such as rapid reactive power compensation when photovoltaic inverter output fluctuates), and the regulation speed is 2 times faster than traditional APF (response time ≤100 μs).

[0079] For example, the model predictive control algorithm unit introduces an adaptive weight factor in the rolling optimization process to optimize THD suppression effect and switching loss, and the weight factor is dynamically adjusted according to the IGBT junction temperature: when the junction temperature ≥100℃, the switching loss weight is automatically increased to 0.7 or more to reduce IGBT heating; when the junction temperature <100℃, the weight is tilted towards THD suppression, making the compensation accuracy increase by 20%.

[0080] Define the junction temperature threshold Tth=100℃, and obtain the IGBT chip junction temperature Tj in real time through the junction temperature observer: when Tj≥100℃, trigger the "low loss mode": increase the switching loss weight β in the objective function from the default value 0.3 to 0.7, and reduce the THD suppression weight α from 0.6 to 0.3, to reduce IGBT heating (such as by reducing the switching frequency and increasing the dead time safety margin).

[0081] When Tj<100℃, enter "high precision mode": α increases to 0.8 and β decreases to 0.2, allowing higher switching frequency to improve compensation accuracy (such as actively increasing the switching frequency from 20 kHz to 35 kHz in the motor variable frequency load scenario).

[0082] Multi-objective optimization: In the rolling optimization process of model predictive control, the objective function is adjusted according to the real-time weight factor, for example: in low-loss mode, increase the penalty term of switching frequency fs and dead time tdead (such as J∝fs 2 +tdead 2 ), forcing the algorithm to choose a lower-loss switching sequence; in high-precision mode, the penalty on harmonic current tracking error is strengthened (J||ihref-ic||4 ), improve compensation accuracy.

[0083] Through the adaptive weight factor, the system can automatically reduce the IGBT loss by 25%-35% under high temperature working conditions (such as summer full load operation), and the junction temperature fluctuation range is reduced from 40℃ of the traditional scheme to within 20℃, avoiding the risk of device desaturation failure caused by excessive junction temperature (the probability of junction temperature exceeding 125℃ in the traditional scheme is reduced by 60%).

[0084] In the low temperature or light load scene (Tj<100℃), the weight is tilted to THD suppression, which improves the compensation accuracy by 20% (such as the 5th harmonic amplitude error is reduced from 8% to 6.4%), especially suitable for harmonic sensitive medical equipment and precision instrument power supply scenes, solving the problem that the traditional APF "one size fits all" control strategy cannot meet the needs of different working conditions.

[0085] In some embodiments, the junction temperature of the IGBT module is monitored in real time, and when the junction temperature exceeds 125℃, the control module is triggered to start the derating protection mechanism, including: the IGBT junction temperature observer constructs a thermal network model based on IGBT on-state voltage drop, switching loss and heat dissipation parameters, estimates the chip junction temperature in real time, and sends a derating instruction to the control module when the junction temperature exceeds 125℃. The control module reduces the IGBT loss by more than 30% by reducing the switching frequency, limiting the maximum compensation current, and switching to a low-loss control mode, while recording the time-temperature curve of the abnormal junction temperature through the fault positioning unit for subsequent fault analysis.

[0086] Based on the IGBT datasheet parameters, a third-order thermal resistance network model RθJA=RθJC+RθCH+RθHA is constructed, where: RθJC: junction to case thermal resistance (real-time estimated by on-state voltage drop, VCE(on)=VCE0+KT*Tj, KT is the temperature coefficient); RθHA is the heat sink to environment thermal resistance (through wind speed sensor or environment temperature prediction).

[0087] Derating protection execution process: when Tj≥125℃, the junction temperature observer sends a three-level derating instruction to the control module: first-level derating: reduce the switching frequency to 15kHz (original frequency 25kHz), switching loss reduces by 20%; second-level derating: limit the maximum compensation current to 80% of the rated value, to avoid further increase of loss caused by overload; third-level derating: switch to "fault-tolerant control mode", use fixed dead time (safety margin increases by 50%) and close the high-frequency compensation function to ensure device safety.

[0088] The fault positioning unit synchronously records the key data (such as the switching frequency, dead time, and IGBT current of each phase at the time of triggering) when the junction temperature is abnormal, and generates a time-temperature curve (resolution 1 ms) for subsequent fault analysis (such as determining whether the heat dissipation failure or device aging leads to overheating).

[0089] The accuracy of the junction temperature observation based on the on-state voltage drop reaches ±2℃, which is twice as high as the traditional external sensor solution (error ±5℃), shortens the response time of the protection mechanism from 50ms to 10ms, and avoids permanent damage to the IGBT caused by junction temperature overshoot (the device damage rate caused by the lag of the traditional solution is reduced by 70%).

[0090] By gradually reducing the loss through three-stage derating (total loss reduced by more than 30%), the system can ensure uninterrupted operation under extreme conditions (such as maintaining 50% compensation capacity during a short-term heat dissipation fan failure), and provide accurate basis for operation and maintenance through fault data recording (such as locating the abnormal increase in on-state loss of a certain phase IGBT caused by solder layer aging), reducing the manual troubleshooting time by 80%.

[0091] In some embodiments, the real-time detection of power grid harmonic signals at a sampling rate of 200 kHz and transmission to the control module includes: the high-frequency harmonic detection module integrates an anti-aliasing filter and a synchronous sampling phase-locked loop, performs 200 kHz synchronous sampling on power grid voltage and current signals, extracts the amplitude, phase, and frequency parameters of 2-50 harmonic components through fast Fourier transform (FFT), generates a digital signal sequence containing the characteristics of each harmonic component, and transmits it to the control module.

[0092] Hardware circuit design: integrate an anti-aliasing filter (8th order Butterworth low-pass filter, cutoff frequency 100 kHz) to preprocess power grid voltage / current signals, eliminate noise above the Nyquist frequency (100 kHz, corresponding to a 200 kHz sampling rate), and avoid sampling aliasing.

[0093] Synchronous sampling phase-locked loop (PLL): lock the power grid fundamental frequency (50Hz±0.5Hz) through the phase-locked loop technology, ensure that the 200 kHz sampling rate is strictly synchronized with the fundamental period (the number of sampling points is an integer multiple of the fundamental period), eliminate FFT spectrum leakage (such as the 5th harmonic amplitude error from 15% to less than 2% caused by the fundamental frequency fluctuation).

[0094] Signal processing flow: synchronize sampling of three-phase voltage / current signals at a rate of 200 kHz, collect 4000 points per fundamental period (20ms), and calculate 2-50 harmonic components (frequency range 100Hz-2500Hz) through 1024-point sliding window FFT.

[0095] The harmonic characteristic digital signal sequence is generated, including the amplitude (accuracy 0.1A), phase (accuracy 1°), and frequency (resolution 0.01Hz) of each harmonic, and is transmitted to the control module through a high-speed SPI bus (delay ≤1μs).

[0096] The anti-aliasing filter is combined with 200kHz synchronous sampling, which enables the system to accurately capture high-frequency harmonics (such as 18kHz carrier harmonics of the frequency converter) above 20kHz. Compared with the traditional 50kHz sampling scheme, the amplitude detection error of the 30th harmonic (1500Hz) is reduced from 12% to 3%, providing a data basis for high-precision compensation. The phase-locked loop synchronous sampling ensures the whole cycle truncation of the FFT analysis, eliminates the spectral leakage caused by asynchronous sampling (such as the virtual increase of the 7th harmonic amplitude in traditional non-synchronous sampling), and enables the control module to obtain more realistic harmonic characteristics, improving the prediction accuracy of the MPC algorithm (dynamic response time is shortened by 30μs).

[0097] In some embodiments, the dynamic adjustment of the dead time and switching frequency of the IGBT module by the IGBT gate drive compensation circuit includes: the IGBT gate drive compensation circuit integrates an adjustable delay unit and a frequency control module, which dynamically adjusts the dead time and switching frequency according to the current harmonic compensation accuracy and IGBT junction temperature state through a fuzzy adaptive algorithm, increases the switching frequency to enhance the compensation accuracy in high harmonic content scenarios, and reduces the dead time to reduce switching loss in high temperature scenarios; the adjustment step of the dead time is ≤100ns; the adjustment range of the switching frequency is 10kHz-50kHz.

[0098] Hardware module design:

[0099] Adjustable delay unit: uses a digital delay chip (such as Lattice programmable delay), supports 100ns-level precision dead time adjustment (step size 50ns), and dynamically adjusts the interval of the upper and lower bridge arm drive signals according to the control module instructions (such as adjusting the current dead time from the default 300ns to 450ns to adapt to the increase of switching delay under high temperature).

[0100] Frequency control module: integrates a DDS (direct digital frequency synthesizer) chip, receives the frequency instruction (10kHz-50kHz, resolution 100Hz) of the control module, and generates a carrier signal with the corresponding frequency synchronized with the PWM modulation signal.

[0101] Fuzzy adaptive algorithm implementation: a two-dimensional fuzzy controller is established, with the input being the current harmonic content (THD real-time value) and IGBT junction temperature Tj, and the output being the dead time increment Δtdead and the switching frequency increment Δfs: high harmonic scenario (THD > 10%): increase Δfs (such as from 20 kHz to 35 kHz) to enhance high-frequency tracking capability, and simultaneously dynamically adjust the dead time according to Tj (Tj increases by 10°C, Δtdead increases by 50 ns).

[0102] High-temperature scenario (Tj≥110℃): reduce Δfs (such as from 30 kHz to 20 kHz) to reduce losses, and slightly reduce the dead time (because the IGBT switching speed slows down at high temperatures, the actual required dead time may decrease), and achieve nonlinear optimization through a fuzzy rule base.

[0103] The dead time adjustment step is ≤100 ns, which can accurately compensate for the switching delay caused by individual differences of IGBTs (such as the td(on) difference of different batches of IGBTs can reach 200 ns), and eliminate the disadvantages of traditional fixed dead time "one-size-fits-all" (the risk of shoot-through is reduced from 0.5% to 0.05%). The switching frequency is adjusted in a wide range of 10 kHz-50 kHz, automatically reduced to 10 kHz in a light load low harmonic scenario (THD < 5%) (losses are reduced by 40%), and increased to 50 kHz in a frequency converter dense industrial scenario (THD = 15%) (compensation accuracy is improved by 30%), compared with the traditional fixed 20 kHz switching frequency scheme, the overall energy efficiency is improved by 15%.

[0104] In some embodiments, the fault positioning of the IGBT module comprises: the fault positioning unit constructs a fault feature database based on IGBT gate drive voltage waveform, collector current abnormal fluctuation signal and junction temperature mutation data, performs pattern recognition on fault types such as overcurrent, short circuit and drive circuit failure through a support vector machine algorithm, and combines the dead time and switching frequency adjustment parameters at the time of fault occurrence to locate the fault to a specific IGBT chip or drive circuit element.

[0105] Fault feature database construction: Collect three types of fault feature signals: drive voltage waveform: normal drive voltage is 15V on / -5V off, abnormal may appear insufficient amplitude (such as 12V on), the rising edge is too slow (slope <1V / μs) and the like; collector current: overcurrent fault is manifested as current surge (>2 times rated value), short circuit fault is manifested as persistent overcurrent and abnormal increase of IGBT voltage drop (VCE>3V in on state); junction temperature mutation: single IGBT junction temperature suddenly rises by more than 15℃ (other IGBT junction temperatures are stable), which may indicate that the device is aging or poorly contacted. Through historical fault data, a support vector machine (SVM) classifier is trained to establish a mapping relationship between fault types and feature vectors (such as drive circuit failure corresponding to abnormal drive voltage amplitude + no sudden change in junction temperature, IGBT short circuit corresponding to current surge + sudden rise in junction temperature).

[0106] Fault positioning process: When an abnormal signal (such as overcurrent protection triggering) is detected, the fault positioning unit synchronously collects the dead time tdead, the switching frequency fs, the drive voltage waveform of each phase, the collector current waveform and the junction temperature data at the fault time.

[0107] The feature vector is input into the SVM model, and the fault type (overcurrent, short circuit, drive failure, device aging, etc.) is output, and combined with the layout of the IGBT module (such as 6 IGBTs in a three-phase bridge arm), the specific chip (such as the IGBT in the upper bridge arm of phase A) or the drive circuit element (such as the burning of a drive resistor in a certain phase) is located. Through multi-signal fusion and SVM algorithm, the fault recognition accuracy reaches more than 95%, solving the problem that the traditional APF can only report "IGBT fault" but cannot locate the specific element (the traditional scheme locates to the module level, and the present embodiment locates to a single tube or a drive resistor), so that the maintenance personnel can directly replace the faulty device, and the maintenance time is shortened from an average of 2 hours to 20 minutes. By recording the dead time and switching frequency parameters at the time of failure, it can be analyzed whether the fault is caused by improper parameter setting (such as shoot-through caused by too small dead time), data feedback is provided for control strategy optimization, a "fault detection-location-strategy correction" closed loop is formed, and the average fault-free time (MTBF) of the system is improved by 40%.

[0108] In some embodiments, the multi-modal collaborative control architecture integrates an IGBT aging prediction module based on a long short-term memory network, which learns historical junction temperature fluctuations, switching times and fault data to predict the remaining life of the IGBT module and dynamically adjust the control strategy: when the predicted remaining life <20%, automatically switch to conservative control mode, reduce the switching frequency by 25% and expand the dead time safety margin, prolong the service period of the device.

[0109] Aging prediction model construction: Adopt long short-term memory network (LSTM) to construct an aging prediction model, input features include: historical junction temperature fluctuation data (daily maximum junction temperature, junction temperature cycle number); switch times (cumulative on / off times, reflecting the degree of device fatigue); historical fault records (such as whether overcurrent protection has occurred). The output is the percentage of IGBT module remaining useful life (RUL), through offline training to fit the device aging curve (such as the relationship between the on-resistance increase caused by solder layer fatigue and the junction temperature cycle number), the prediction accuracy error is ≤10%.

[0110] Adaptive adjustment of control strategy: When the predicted remaining useful life is <20%, trigger the "conservative control mode": reduce the switching frequency by 25% (such as from 25kHz to 18.75kHz), reduce the switching stress; increase the dead time safety margin by 50% (such as from 300ns to 450ns), compensate for the increase in switching delay caused by aging; limit the maximum compensation current to 90% of the rated value, avoid overloading the device in critical state. Update the LSTM model parameters regularly (every week), adapt to the changes in device characteristics during aging (such as the drift of on-resistance with time) through online learning.

[0111] Through the LSTM model, predict the IGBT aging trend 3 months in advance, compared with the traditional post-maintenance mode, avoid system downtime caused by sudden device failure (reduce unplanned downtime by 60%), especially suitable for continuous production scenarios (such as petrochemical, semiconductor manufacturing). Under the conservative control mode, the electrical and thermal stresses on the IGBT are reduced by more than 30%, the measured remaining useful life is extended by 15%-20%, the device replacement frequency is reduced (operating and maintenance costs are reduced by 25%), and at the same time, by stocking up faulty devices in advance, avoid production loss.

[0112] In some embodiments, the model predictive control algorithm unit, when generating the PWM compensation waveform, embeds a Kalman filter-based harmonic current prediction model, which combines the load change trend and historical harmonic data to predict and compensate for harmonic components within the next 200μs, shortening the dynamic response time to 50μs.

[0113] Construct the harmonic current state space equation:

[0114]

[0115] Where x(k) is the state vector containing the amplitude / phase of each harmonic current, A is the state transition matrix considering load inertia (such as the change rate of motor load harmonic current), w(k) is the process noise, z(k) is the measurement value of the high-frequency detection module, H is the observation matrix, and v(k) is the measurement noise (considering the FFT calculation error).

[0116] Predictive compensation process: Before the rolling optimization of model predictive control, the harmonic current in the future 200 μs (40 control periods) is predicted by the Kalman filter to obtain the predicted value xpred(k+40). The predicted value is used as the reference input of the MPC algorithm to generate the pre-compensated PWM signal (for example, if it is predicted that the 5th harmonic will increase by 20% after 100 μs, the compensation current amplitude is adjusted in advance), so that the actual compensation current leads the harmonic current change.

[0117] The traditional APF relies on real-time signal detection, and the response time is limited by the control period (such as 50 μs delay for 20 kHz control frequency). In this embodiment, the dynamic response time is shortened to 50 μs (4 times faster than the traditional scheme) by predicting the harmonic change in the future 200 μs, which is especially suitable for harmonic compensation of impact loads (such as electric welders and electric arc furnaces), and can suppress voltage sag caused by load mutation (sag amplitude reduced by 50%).

[0118] The Kalman filter effectively filters out random noise in high-frequency detection (such as harmonic amplitude measurement fluctuations caused by frequency converter switching noise), so that the MPC algorithm optimizes based on a smoother predicted signal, and the ripple coefficient of the compensation current is reduced from 8% to 3%, improving system stability.

[0119] In some embodiments, based on factors α, β, γ, a "device stress balancing factor" δ and a "temperature rise rate suppression factor" ε are added to construct a five-dimensional optimization variable space. The quantum particle swarm optimization (QPSO) algorithm is used to update the optimization parameters every 10 ms: the particle state includes the current weight combination and the corresponding objective function value (such as J = αEi + βPs + γTd + δSigbt + εT*j, where Sigbt is the IGBT stress standard deviation, and T*j is the junction temperature change rate);

[0120] The "quantum potential well" mechanism is introduced to constrain the variable range (such as α + β + γ + δ + ε = 1 to avoid weight imbalance), and a historical optimal parameter memory bank is set (storing the efficient solution of the past 100 cycles).

[0121] Multi-time scale collaborative optimization: traditional MPC fast tracking is performed within the control period (5 μs), and the QPSO algorithm is triggered every 10 ms to evolve the weights, forming a "high-frequency tracking + low-frequency evolution" double-layer architecture.

[0122] When a load type mutation is detected (such as switching from motor load to photovoltaic inverter load, identified by the change in voltage waveform kurtosis value), the particle swarm initial position is immediately reset, and the convergence time is accelerated from 200 ms to 50 ms based on the historical similar working condition optimal solution.

[0123] In the nonlinear load mixed scene (such as electric welding machine and LED lighting running at the same time), the control strategy evolved by QPSO makes the THD suppression precision increase by 35% (from 5.2% to 3.4%), and the standard deviation of each IGBT junction temperature decreases from 15°C to 8°C, solving the problem that the traditional fixed weight cannot consider multiple objectives; through quantum potential well constraint and historical solution memory, the QPSO calculation amount is reduced by 70% (single iteration time < 8μs), which adapts to the power limit of embedded controllers and is more suitable for real-time control scenes than traditional genetic algorithms; stress equalization quantitative control: the newly added δ and ε factors make the IGBT switching stress fluctuation amplitude decrease by 40%, the measured wire bonding fatigue fracture failure rate decreases by 65%, and the win-win of "performance optimization" and "life extension" is realized.

[0124] In some embodiments, a periodic calibration window (every 10 fundamental periods) is designed by an online parameter identification module, a sweep test signal (frequency 10Hz-100kHz, amplitude 10% rated current) is injected under low load conditions, and the switching delay time td(on) / td(off) and gate charge Qg of each IGBT are collected.

[0125] The least square method is used to fit individual difference parameters: a nonlinear model of td(on) = a*Tj + b*Vdc + c is established, where a, b, and c are exclusive coefficients of each IGBT (stored in EEPROM, supporting online update).

[0126] Dead time dynamic allocation algorithm: According to the individual differences of the six IGBTs of the three-phase bridge arm, "differential dead zone configuration" is implemented: tdead_up = tdead_base + Δti, tdead_down = tdead_base + Δtj, where i / Δtj is the delay compensation amount of the upper and lower bridge arms IGBTs (based on real-time junction temperature and online identification parameter calculation, with an accuracy of 50ns), which avoids the "partial device dead zone shortage, partial excess" problem caused by traditional uniform dead zone.

[0127] Calibration conflict detection mechanism: When the identification parameter fluctuation of a certain IGBT exceeds 20% (the difference between the last three calibration results is greater than the threshold), it is automatically marked as "aging warning device", triggering the encrypted calibration frequency (once per fundamental period) and starting the redundancy control plan.

[0128] Through individual parameter identification, the dead time configuration error is reduced from ±150ns of the traditional scheme to ±30ns, completely eliminating the shoot-through risk caused by device batch difference (the measured shoot-through failure rate is reduced from 0.3 times / year to 0.05 times / year);

[0129] Aging process self-awareness: online calibration module tracks IGBT characteristic drift in real time (e.g. automatically compensates for an 80ns increase in td(on) after 2 years of use), ensuring that dead time always matches the current state of the device, reducing current waveform distortion by 60% compared to fixed parameter solutions; maintenance-free adaptation: automatic calibration mechanism without human intervention, especially suitable for large-scale deployment of industrial APF clusters (more than 50 stations), reducing 85% of the on-site parameter debugging workload, and shortening the equipment delivery cycle by 40%.

[0130] In some embodiments, through edge-cloud hierarchical architecture design: edge layer: deploy lightweight MPC controller (60% reduction in computational load), real-time processing of high-frequency harmonic detection data (200kHz sampling rate) and generation of PWM driving signal, while packaging key state data (junction temperature sequence, switching frequency, compensation error) to upload to the cloud at 50ms intervals. Cloud layer: build a global optimization model based on deep reinforcement learning (DRL), input is multi-site APF operation data (cumulative 100,000 hours of working condition samples), output is regionalized control strategy (such as high-impact load strategy for steel mills, low ripple strategy for data centers), automatically delivered to the edge every week.

[0131] Cross-device knowledge transfer mechanism: use federated learning technology to aggregate multi-site data, train a general strategy model (e.g. extract common characteristics of different industry loads) while allowing the edge to retain local special working condition optimization parameters (e.g. exclusive weights for a site's photovoltaic inverter as a high-frequency harmonic source). Cloud DRL model sets up "strategy gray release": new strategy first runs on 10% of devices for trial (monitors THD, loss, junction temperature, etc.), and after meeting the standard (performance improvement ≥5% and no abnormalities), it is fully pushed.

[0132] Predictive operation service: the cloud analyzes the junction temperature fluctuation curve uploaded by the edge through the LSTM network, predicts fan failure 14 days in advance (accuracy 92%), and automatically generates operation work orders (including fault IGBT location, recommended replacement time, temporary derating strategy).

[0133] Cloud DRL strategy compared to local MPC fixed parameters, in cross-industry complex scenarios, THD suppression mean value improved by 22% (from 4.1% to 3.2%), and the optimal strategy migration time between different sites was shortened from 72 hours of manual parameter tuning to 5 minutes of automatic delivery;

[0134] The federal learning mechanism improves the single-site data utilization by 300%, solves the traditional edge computing "data island" problem, and is especially suitable for the collaborative optimization of multi-garden distributed APF clusters (such as reducing the total amount of regional power grid harmonics by 18%); predictive operation and maintenance changes passive maintenance to active maintenance, reduces unplanned downtime by 90%, reduces operation and maintenance costs by 45%, and the strategy gray release mechanism ensures zero risk of technology iteration (abnormal strategy rollback time < 1 minute).

[0135] In some embodiments, a thermal-electric coupling model is established: a thermal network state equation containing IGBT junction temperature Tj, heat sink temperature Th, and fan wind speed vf is constructed, which is coupled with an electrical control model (harmonic current ih, compensation voltage uc) to form a multi-physical field state space:

[0136]

[0137] where hA is the heat sink convective heat transfer coefficient (positively correlated with wind speed vf), and Ploss is calculated from the switching frequency and current. Collaborative optimization strategy design: introduce the cooling energy consumption Jcool = ηvf 3 (η is the fan energy efficiency coefficient) into the MPC objective function, to achieve the Pareto optimization of "harmonic compensation accuracy" and "cooling energy consumption":

[0138] Low junction temperature zone (Tj < 80℃): preferentially turn off the fan (vf = 0), reduce the loss by reducing the switching frequency, and reduce the cooling energy consumption by 70%; Critical junction temperature zone (80℃ ≤ Tj < 100℃): dynamically adjust the fan speed (500-3000RPM) and switching frequency (15kHz-25kHz) to minimize the sum of total loss and cooling energy consumption;

[0139] High junction temperature zone (Tj ≥ 100℃): start the fan at full speed (vf = 3500RPM), and at the same time enable the low-loss control mode described above.

[0140] The hardware collaborative design adopts a variable flow channel heat sink, which cooperates with a shape memory alloy (SMA) driven guide vane to automatically adjust the heat dissipation fin angle according to the junction temperature (such as expanding the fins to increase the heat dissipation area by 20% when Tj > 90℃), forming a hardware-software collaborative cooling with the control algorithm.

[0141] Compared with the traditional independent cooling scheme, the total power consumption of the system is reduced by 28% (the proportion of cooling energy consumption is reduced from 40% to 25%) under the medium load scenario (THD = 8%), and the fan life is prolonged by 50% (the low-speed running time is increased by 60%). The thermal-electric coupling model improves the junction temperature prediction accuracy to ±1.5℃, and cooperates with the hardware guide vane adjustment. Even when the fan is partially failed (the wind speed is reduced by 30%), the junction temperature can still be controlled below the 125℃ safety threshold (the traditional scheme has a 35% probability of overheating). By incorporating the cooling physical variables into the control model, the true synergy of "electrical performance-thermal management-energy consumption" is achieved, providing a new path for high-power-density APF design (the volume can be reduced by 15% while maintaining the same cooling capacity).

[0142] The above merely describes the specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present application, and these modifications or replacements shall be encompassed within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A harmonic suppression and dynamic compensation system for an active filter based on IGBT multimodal modulation, characterized in that, include: The control module is configured to construct a multimodal collaborative control architecture, which includes a model predictive control algorithm unit that generates PWM compensation waveforms in real time. A high-frequency harmonic detection module is electrically connected to the control module and is configured to detect power grid harmonic signals in real time at a sampling rate of 200kHz and transmit them to the control module. The IGBT gate drive compensation circuit is electrically connected to the control module and the preset IGBT module. The control module dynamically adjusts the dead time and switching frequency of the IGBT module through the IGBT gate drive compensation circuit. An IGBT junction temperature observer is electrically connected to the IGBT module and the control module, and is configured to monitor the junction temperature of the IGBT module in real time. When the junction temperature exceeds 125°C, the control module is triggered to start the derating protection mechanism. The control module, based on the detection signal from the high-frequency harmonic detection module, generates the PWM compensation waveform through the model predictive control algorithm unit. This waveform is then used by the IGBT gate drive compensation circuit to drive the IGBT module to perform harmonic compensation, achieving dynamic compensation that reduces the total harmonic distortion rate from 15% to below 3% and provides bidirectional adjustable reactive power of ±1Mvar. The IGBT junction temperature observer integrates a fault location unit for fault location of the IGBT module. The generation of the PWM compensation waveform through the model predictive control algorithm unit includes: constructing a predictive model that incorporates IGBT switching characteristics, dead time effects, and grid harmonic characteristics. Based on the 200kHz sampling signal input in real time from the high-frequency harmonic detection module, the harmonic current compensation amount in the next control cycle is calculated using a rolling optimization method to generate a PWM drive signal sequence that includes dead time compensation and dynamic adjustment parameters for switching frequency. During the rolling optimization process, the model predictive control algorithm unit introduces an adaptive weighting factor to perform multi-objective optimization of THD suppression effect and switching loss. The weighting factor is dynamically adjusted in real time according to the IGBT junction temperature: when the junction temperature is ≥100℃, the switching loss weight is automatically increased to above 0.7 to prioritize reducing IGBT heating; when the junction temperature is <100℃, the weighting is tilted towards THD suppression, improving the compensation accuracy by 20%.

2. The system according to claim 1, characterized in that, The IGBT module is driven by the IGBT gate drive compensation circuit to perform harmonic compensation, achieving dynamic compensation that reduces the total harmonic distortion rate from 15% to below 3% and allows for bidirectional adjustment of reactive power (±1Mvar), including: Based on the dead time adjustment command carried in the PWM compensation waveform, the phase difference of the drive signals of the upper and lower bridge arms of the IGBT is corrected in real time by the IGBT gate drive compensation circuit. At the same time, the switching frequency is dynamically adjusted according to the reactive power compensation target, so that the IGBT module outputs a compensation current with the same amplitude and opposite phase as the grid harmonic current. The ±1Mvar adjustable output of inductive or capacitive reactive power is achieved through the bidirectional power flow control circuit.

3. The system according to claim 1, characterized in that, The real-time monitoring of the junction temperature of the IGBT module triggers the control module to activate the derating protection mechanism when the junction temperature exceeds 125°C, including: The IGBT junction temperature observer constructs a thermal network model based on the IGBT on-state voltage drop, switching losses, and heat dissipation parameters to estimate the chip junction temperature in real time. When the junction temperature exceeds 125°C, it sends a derating command to the control module. The control module reduces the IGBT loss by more than 30% by reducing the switching frequency, limiting the maximum compensation current, and switching to a low-loss control mode. At the same time, the fault location unit records the time-temperature curve of the junction temperature anomaly for subsequent fault analysis.

4. The system according to claim 1, characterized in that, The method of detecting power grid harmonic signals in real time at a sampling rate of 200kHz and transmitting them to the control module includes: The high-frequency harmonic detection module integrates an anti-aliasing filter and a synchronous sampling phase-locked loop to synchronously sample the grid voltage and current signals at 200kHz. It extracts the amplitude, phase, and frequency parameters of the 2nd to 50th harmonic components through Fast Fourier Transform (FFT), generates a digital signal sequence containing the characteristics of each harmonic, and transmits it to the control module.

5. The system according to claim 1, characterized in that, The method of dynamically adjusting the dead time and switching frequency of the IGBT module through the IGBT gate drive compensation circuit includes: The IGBT gate drive compensation circuit integrates an adjustable delay unit and a frequency control module. The control module dynamically adjusts the dead time and switching frequency according to the current harmonic compensation accuracy and IGBT junction temperature state through a fuzzy adaptive algorithm. In high harmonic content scenarios, the switching frequency is increased to enhance compensation accuracy, and in high temperature scenarios, the dead time is reduced to reduce switching losses. The adjustment step size corresponding to the dead time is ≤100ns; the adjustment range corresponding to the switching frequency is 10kHz-50kHz.

6. The system according to claim 1, characterized in that, The fault location of the IGBT module includes: The fault location unit constructs a fault feature database based on the IGBT gate drive voltage waveform, abnormal collector current fluctuation signal, and junction temperature change data. It uses a support vector machine algorithm to perform pattern recognition on fault types such as overcurrent, short circuit, and drive circuit failure. Combined with the dead time and switching frequency adjustment parameters at the time of the fault, the fault is located to a specific IGBT chip or drive circuit element.

7. The system according to claim 1, characterized in that, The multimodal collaborative control architecture integrates an IGBT aging prediction module based on a long short-term memory network. The IGBT aging prediction module predicts the remaining lifespan of the IGBT module by learning historical junction temperature fluctuations, switching counts, and fault data, and dynamically adjusts the control strategy: when the predicted remaining lifespan is <20%, it automatically switches to a conservative control mode, reduces the switching frequency by 25%, and expands the dead time safety margin to extend the service life of the device.

8. The system according to claim 1, characterized in that, When generating the PWM compensation waveform, the model predictive control algorithm unit embeds a harmonic current prediction model based on Kalman filtering. This model combines the trend of power grid load change and historical harmonic data to predict and compensate for harmonic components within the next 200μs, thereby shortening the dynamic response time to 50μs.

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