IGBT junction temperature real-time decoupling modeling method and system based on dynamic electro-thermal compensation

Abstract

The application discloses an IGBT junction temperature real-time decoupling modeling method and system based on dynamic electrothermal compensation and relates to the technical field of power electronic device state monitoring. At present, the IGBT on-state voltage drop measurement is distorted under a high-voltage environment, and the internal thermal gradient of a chip leads to inaccurate junction temperature estimation. The application comprises: an offline stage, constructing an ideal electrothermal characteristic database of an IGBT, an internal dynamic temperature gradient compensation database of the chip and Foster thermal network model parameters; an online stage, synchronously sampling and preprocessing the operation parameters of the IGBT module; using an adaptive Kalman filter, combining the online real-time parameters with the offline database, iteratively and cooperatively estimating the real-time junction temperature and loss of the IGBT; and finally, outputting and applying the estimated accurate junction temperature and loss data. The technical scheme realizes accurate decoupling of the internal hot spot effect of the chip, improves the junction temperature estimation accuracy and the robustness of online monitoring, and provides core data support for fine thermal management and early fault warning of the flexible DC converter valve.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power electronic device state monitoring, and particularly relates to an IGBT junction temperature real-time decoupling modeling method and system based on dynamic electro-thermal compensation. BACKGROUND

[0002] The modular multilevel converter (MMC) in a flexible direct current transmission system is a key device for realizing high-voltage and large-capacity direct current transmission, and the operating state of the internal core power device insulated gate bipolar transistor (IGBT) of the converter valve is crucial to the reliability and service life of the converter valve. The IGBT generates power loss in the working process, resulting in an increase in the junction temperature. Excessive junction temperature or severe fluctuation under cyclic stress is a major inducement to IGBT thermal fatigue, solder layer aging, and bond wire shedding and other failures. Therefore, accurate, real-time, and online monitoring and modeling of the IGBT junction temperature have irreplaceable value for guaranteeing the safe and reliable operation of the converter valve, prolonging the service life of the device, and realizing predictive maintenance.

[0003] At present, the online estimation method of the IGBT junction temperature mainly relies on the sensitive relationship between the electrical parameters (such as the collector-emitter on-state voltage drop V CE(on) ) of the IGBT and the junction temperature. However, in the high-voltage complex electromagnetic environment of the flexible direct current converter valve, directly online measuring the V CE(on) of the IGBT with high precision faces many challenges: first, the high common-mode voltage and high-frequency noise existing in the converter valve seriously interfere with the measurement of the V CE(on) Such a millivolt-level weak signal acquisition causes serious interference, resulting in a large measurement error, which in turn seriously affects the accuracy of the junction temperature estimation; secondly, in the actual operation process, due to uneven current distribution, thermal resistance path difference, and other factors, the IGBT chip often produces uneven temperature distribution, that is, local hot spots and temperature gradients. This makes the V CE(on) measurement value not simply represent the overall or highest junction temperature of the chip, but is affected by the local temperature, resulting in the fact that the traditional method based on single-point measurement or simple lookup table cannot realize accurate “decoupling” of the junction temperature and cannot accurately reflect the true junction temperature state; in addition, the existing junction temperature estimation model (such as the simplified thermal network model or static lookup table method) often uses static parameters, lacks real-time compensation and adaptive ability for the dynamic electro-thermal coupling characteristics and internal temperature unevenness of the IGBT chip, and thus the estimation accuracy significantly decreases and the robustness is insufficient under complex working conditions, especially when the hot spot effect is intensified, which cannot meet the demand of the high-reliability system for fine junction temperature monitoring.

[0004] In summary, there is an urgent need for an advanced method and system that can overcome the challenges of high-pressure environment measurement, achieve dynamic compensation of chip internal temperature gradient, and provide high-precision, real-time decoupling junction temperature estimation, to effectively improve the operation reliability and intelligent level of flexible direct current transmission system. SUMMARY

[0005] The technical problem to be solved by the present application and the technical task proposed are to perfect and improve the prior art, and to provide an IGBT junction temperature real-time decoupling modeling method and system based on dynamic electro-thermal compensation, to achieve the purpose of high-precision real-time decoupling modeling of IGBT junction temperature. To this end, the present application adopts the following technical solutions.

[0006] An IGBT junction temperature high-precision real-time decoupling modeling method based on dynamic electro-thermal compensation, comprising:

[0007] S1: offline construction of electro-thermal characteristics and compensation database of IGBT module, comprising:

[0008] Construction of ideal electro-thermal characteristic database of IGBT body and antiparallel diode;

[0009] Construction of IGBT chip internal dynamic temperature gradient compensation database;

[0010] Extraction of Foster thermal network model parameters of the IGBT module;

[0011] S2: online real-time high-precision synchronous sampling and preprocessing of IGBT module operating parameters, including high-precision isolation sampling of IGBT collector-emitter on-state voltage drop and multi-channel high-speed synchronous sampling and signal preprocessing of on-state voltage drop, collector current and module shell temperature;

[0012] S3: based on online real-time operating parameters and offline constructed database, performing junction temperature-loss electro-thermal coupling iterative calculation and dynamic compensation;

[0013] S4: outputting and applying the junction temperature and loss data obtained by iterative calculation; the application includes online thermal management, working condition monitoring or fault warning.

[0014] The application realizes high-precision real-time estimation of IGBT junction temperature under complex working conditions by fusing offline modeling and online adaptive filtering technology, effectively decouples the chip internal hot spot effect, significantly improves the accuracy and robustness of the electrical and thermal state monitoring, and provides key data basis for intelligent operation and maintenance and reliability evaluation of the converter valve. Specifically embodied: through high-voltage isolation collection of the collector-emitter on-state voltage drop, the measurement distortion problem caused by the high common-mode voltage and electromagnetic interference of the converter valve is overcome, and reliable data basis is provided for online estimation. The influence of the chip hot spot effect on the on-state voltage drop is quantized in advance, and the measurement deviation is dynamically compensated in the online stage, so that the on-state voltage drop measurement value truly reflects the overall junction temperature rather than the local hot spot temperature. The junction temperature estimation and loss calculation are coupled as a closed-loop system, the model self-consistency is improved through real-time interaction correction, and the error accumulation of the traditional static model under variable working conditions is avoided. The sampling time stamps of the on-state voltage drop, current and shell temperature are aligned to ensure the space-time consistency of the electrical and thermal parameters in the transient process, and the microsecond-level real-time requirement is met.

[0015] As a preferred technical means: the step S1 of constructing the ideal electrical and thermal characteristic database specifically includes: obtaining the on-state voltage drop and current relationship of the IGBT and the antiparallel diode at multiple preset uniform junction temperature points through pulse testing, and establishing a three-dimensional mapping function of the on-state voltage drop changing with the current and the junction temperature by using a segmented polynomial or a logarithmic fitting.

[0016] The on-state voltage drop is measured under extremely short pulse width, the chip self-heating effect is suppressed, the data strictly reflects the intrinsic electrical characteristics under the preset uniform junction temperature, and the temperature rise distortion caused by the traditional direct current test is avoided. For the strong nonlinear characteristics of the IGBT on-state voltage drop changing with the current index and negatively related to the junction temperature, a segmented polynomial or a logarithmic function is used for three-dimensional mapping, which is more consistent with the physical nature of the semiconductor device than the linear interpolation or simple table lookup method, and the function expression accuracy is significantly improved. Through system testing at multiple junction temperature points, a continuous function of current and junction temperature is established, which overcomes the defect that discrete data points cannot represent the intermediate state, and provides a complete mathematical benchmark for online real-time decoupling calculation.

[0017] As a preferred technical means: the step S1 of constructing the dynamic temperature gradient compensation database specifically includes: establishing an IGBT module three-dimensional electro-thermal coupling model by using a multi-physical field finite element simulation software, simulating the chip transient temperature field distribution under different working conditions; extracting the average junction temperature, the maximum junction temperature and the local junction temperature of the measurement point; defining the temperature gradient compensation as the difference between the on-state voltage drop considering the temperature non-uniformity obtained by simulation and the ideal on-state voltage drop in the ideal electrical and thermal characteristic database, and establishing the mapping relationship between the compensation and the current, the average junction temperature and the thermal gradient characteristic quantity.

[0018] Three-dimensional electro-thermal coupling simulation replaces physical probes. Under the constraint that temperature sensors cannot be deployed in chip structures, the transient temperature field distribution is accurately reconstructed using finite element simulation to directly obtain the highest junction temperature and local measurement point temperature that cannot be measured by traditional methods, and to reveal microscopic thermal non-uniformity. The abstract thermal gradient is converted into a quantifiable voltage compensation amount, and a physical causal relationship for compensation is established. The compensation amount is related to the current, average junction temperature, and thermal gradient characteristic quantity to form a compensation rule library, providing a theoretically complete input-output relationship for online dynamic compensation.

[0019] As a preferred technical means: in the Foster thermal network model parameters extracted in step S1, the transient thermal impedance is represented by the combination of N-order thermal resistance and corresponding thermal time constant, where N is the model order.

[0020] Through the combination of multi-order thermal resistance and thermal time constant, the thermal response process under different time scales can be comprehensively covered, providing an accurate heat transfer model basis that conforms to the physical law for online real-time junction temperature estimation, and ensuring the accuracy of the prediction of the dynamic change of the junction temperature.

[0021] As a preferred technical means: in step S2, a high-voltage isolation differential amplification circuit is used to instantaneously collect the collector-emitter on-state voltage drop; the rising edge or falling edge of the IGBT gate drive signal is used as the sampling trigger point, and the on-state voltage drop, collector current, and module shell temperature are synchronously collected by a multi-channel high-speed analog-to-digital converter; digital filtering and timestamp alignment are performed on the collected data to ensure time synchronization.

[0022] The use of a high-voltage isolation differential amplification circuit can effectively resist high-voltage common-mode interference and high-frequency electromagnetic noise during IGBT operation, capture millivolt-level collector-emitter on-state voltage drop instantaneous signals, and solve the problem of insufficient measurement accuracy of weak electrical parameters in a high-voltage environment. Using the rising edge or falling edge of the IGBT gate drive signal as the sampling trigger point can accurately lock the key moments of device turn-on / off, ensuring that the collected on-state voltage drop, collector current, and module shell temperature can truly reflect the device characteristics under the same working state, and avoiding parameter mismatch caused by sampling time deviation. The synchronous collection of the multi-channel high-speed analog-to-digital converter, digital filtering, and timestamp alignment processing can eliminate transient noise and measurement burrs, while strictly ensuring the consistency of the on-state voltage drop, current, and shell temperature in the time dimension, providing high-quality input data for subsequent junction temperature-loss coupling calculation in terms of time synchronization and noise suppression, and laying the foundation for accurate modeling.

[0023] As a preferred technical means: step S3 includes:

[0024] A Kalman filter state space model is constructed, with the junction temperature as the state vector, the Foster thermal network model as the state transition equation, and the on-state voltage drop as the observation value;

[0025] In each sampling period iteration is performed:

[0026] a) State prediction: based on the junction temperature, current and case temperature at the last time, the current junction temperature is predicted by Foster model;

[0027] b) Observation update:

[0028] i. According to the current and the predicted junction temperature, the temperature gradient compensation quantity is obtained from the dynamic temperature gradient compensation database;

[0029] ii. The measurement noise covariance matrix is dynamically adjusted to increase with the increase of the temperature gradient compensation quantity;

[0030] iii. The real-time on-state voltage drop measurement value is subtracted by the sum of the ideal on-state voltage drop and the temperature gradient compensation quantity to obtain the compensated observation value;

[0031] iv. The junction temperature estimate value is updated in combination with the Kalman gain;

[0032] c) Output the dynamically compensated real-time junction temperature and the recalculated loss.

[0033] The sum of the real-time measured on-state voltage drop, the ideal on-state voltage drop and the temperature gradient compensation quantity is subtracted to eliminate the systematic deviation of the chip local hot spot on the measurement, so that the observation value truly reflects the overall junction temperature state. According to the compensation quantity, the measurement noise covariance matrix is adjusted in real time to realize the intelligent balance of the model prediction and the measured value, and the variable working condition adaptability is improved. The output junction temperature is fed back to the loss calculation, and the updated loss is re-input into the Foster model for the next period prediction to form a self-correcting cycle, avoiding error accumulation. Ensure that the junction temperature estimation and the loss calculation can be mutually fed back and corrected in real time, so that the output result can track the dynamic electrical and thermal state of the IGBT in real time, meeting the real-time demand of online monitoring.

[0034] As a preferred technical means: in step S3,

[0035] The dynamic adjustment of the measurement noise covariance matrix includes: querying the dynamic temperature gradient compensation database according to the current and the predicted junction temperature, and linearly or nonlinearly increasing the value of the measurement noise covariance matrix when the absolute value of the temperature gradient compensation quantity increases;

[0036] The loss recalculation includes: based on the updated junction temperature estimate value, in combination with the real-time current and switching frequency, the loss is calculated by the on-state loss formula and the switching energy formula.

[0037] The design of dynamically adjusting the measurement noise covariance matrix can adaptively adjust the trust weight of the on-state voltage drop measurement value according to the actual situation of the chip internal temperature gradient (reflected by the temperature gradient compensation amount). When the absolute value of the temperature gradient compensation amount increases, the measurement noise covariance matrix can be increased linearly or non-linearly, so as to reduce the weight of the measurement value in the junction temperature estimation, reduce the error caused by the interference of the local hot spot on the measurement value, and enhance the stability and anti-interference ability of the junction temperature estimation under complex working conditions.

[0038] The loss is recalculated based on the updated junction temperature estimation value, ensuring real-time matching of the loss and the junction temperature. Since there is a strong coupling relationship between the loss and the junction temperature, the latest junction temperature is used to calculate the loss, so that the loss result is more consistent with the actual working state of the device, and accurate loss data provides reliable input for the next round of junction temperature prediction, forming a dynamic closed-loop correction of the junction temperature and the loss, further improving the consistency and accuracy of the estimation of the two.

[0039] Another technical solution of the application is an IGBT junction temperature high-precision real-time decoupling modeling system based on dynamic electro-thermal compensation, which comprises:

[0040] An offline modeling module is used to construct an electro-thermal characteristic and compensation database of an IGBT module offline, comprising: constructing an ideal electro-thermal characteristic database of an IGBT body and an anti-parallel diode, constructing an IGBT chip internal dynamic temperature gradient compensation database, and extracting Foster thermal network model parameters of the IGBT module;

[0041] An online sampling and preprocessing module is used to perform online real-time high-precision synchronous sampling and preprocessing of IGBT module operating parameters, comprising: high-precision isolated sampling of an IGBT collector-emitter on-state voltage drop; multi-channel high-speed synchronous sampling and signal preprocessing of the on-state voltage drop, the collector current and the module shell temperature;

[0042] An electro-thermal coupling estimation module is connected to the offline modeling module and the online sampling and preprocessing module, and is used to perform junction temperature-loss electro-thermal coupling iterative calculation and dynamic compensation based on online real-time operating parameters and offline constructed databases;

[0043] A data output and application module is used to output and apply the junction temperature and loss data obtained by iterative calculation, and the application includes online thermal management, working condition monitoring or fault warning.

[0044] The system pre-constructs three types of core databases of ideal electro-thermal characteristics of IGBT, dynamic temperature gradient compensation and Foster thermal network model parameters through an offline modeling module, providing comprehensive and accurate offline basic data support for online estimation; the online sampling and preprocessing module is specially designed for parameter measurement in high-voltage environment, realizing high-precision isolated sampling of on-state voltage drop and synchronous preprocessing of multiple parameters, and ensuring the accuracy of input data; the electro-thermal coupling estimation module connects offline data and online parameters, and performs dynamic coupling calculation and compensation; the data output and application module directly meets the actual operation and maintenance requirements, realizes effective application of data, forms a complete closed loop of "offline modeling-online collection-dynamic estimation-actual application", and is strong in systematicness. Through high-precision isolated sampling technology and multi-channel synchronous processing, the online sampling and preprocessing module can accurately capture weak signals such as millivolt on-state voltage drop in high-voltage complex electromagnetic environment, and through signal preprocessing, ensures the strict synchronization of on-state voltage drop, current and shell temperature in time dimension, provides high-quality input data for subsequent estimation, and overcomes the problems of easy interference and insufficient precision in high-voltage environment. The electro-thermal coupling estimation module is based on offline database and online real-time parameters, and through iterative calculation and dynamic compensation, can effectively correct the influence of chip internal temperature gradient on measurement, decouple local hotspot effect, make the estimation of junction temperature and loss more close to the actual working state of IGBT, and improve the estimation accuracy in dynamic working condition. The data output and application module applies accurate junction temperature and loss data to online thermal management, working condition monitoring and fault warning, directly serves the fine operation and maintenance of flexible DC converter valve, and improves the engineering practicability and reliability guarantee capability of the system.

[0045] As a preferred technical means: the offline modeling module includes an industrial computer or workstation equipped with simulation software and data analysis tools for IGBT module characteristic calibration, simulation and database generation.

[0046] The industrial computer or workstation has powerful computing processing capability, can efficiently support the multi-physical field finite element simulation of the fine three-dimensional electro-thermal coupling model of the IGBT module, and the processing and analysis of a large amount of test data, and ensures the efficiency of the offline modeling process and the smooth completion of complex computing tasks. The simulation software (such as a multi-physical field coupling simulation tool) can accurately simulate the electro-thermal characteristics and temperature gradient distribution inside the IGBT chip, and the professional data analysis tool (such as data fitting and regression analysis software) can process the test and simulation data with high precision (such as constructing a three-dimensional mapping function of ideal electro-thermal characteristics, fitting Foster thermal network model parameters), which ensures the accuracy and fine degree of the offline database (ideal electro-thermal characteristic database, dynamic temperature gradient compensation database, etc.). The hardware and software combination is specially designed for the characteristic calibration, simulation and database generation of the IGBT module, can realize the effective fusion and calibration of the test data and simulation data, and ensures that the offline constructed model parameters and database not only conform to the theoretical simulation law, but also fit the actual device characteristics, thereby providing high-quality and high-reliability offline basic data support for subsequent online real-time estimation.

[0047] As a preferred technical means: the online sampling and preprocessing module comprises:

[0048] A high-voltage isolation on-state voltage drop sampling unit is configured to collect the instantaneous collector-emitter on-state voltage drop;

[0049] A current collection unit is configured to measure the instantaneous collector current of the IGBT in real time;

[0050] A module shell temperature collection unit is configured to measure the module shell temperature in real time;

[0051] A high-speed data collection and synchronous processing unit is configured to perform instantaneous synchronous sampling on the on-state voltage drop, collector current and module shell temperature, and perform digital filtering and timestamp alignment;

[0052] The electro-thermal coupling estimation module comprises:

[0053] A Kalman filter core algorithm implementation unit is configured to implement state prediction and observation update of the Kalman filter;

[0054] A loss calculation unit is configured to calculate the conduction loss and switching loss of the IGBT in real time;

[0055] A database interface is configured to interact with the ideal electro-thermal characteristic database and the dynamic temperature gradient compensation database generated by the offline modeling module;

[0056] A Foster thermal network model solver is configured to implement the Foster thermal network model and perform state prediction of the junction temperature;

[0057] The data output and application module comprises:

[0058] a data storage unit for storing historical junction temperature and loss data;

[0059] a communication interface unit for data exchange with a converter valve control system, a SCADA system or a remote monitoring and diagnosis platform;

[0060] a human-computer interaction interface for real-time display of the electro-thermal state of the IGBT;

[0061] a control and protection interface for control of a cooling system or a protection device.

[0062] The high-voltage isolation on-state voltage drop sampling unit is specially designed for instantaneous collection of collector-emitter on-state voltage drop, can accurately capture millivolt-level weak signals in a high-voltage environment, and ensures the measurement accuracy of key electrical parameters; the current collection unit and the module shell temperature collection unit are respectively focused on real-time acquisition of instantaneous current and shell temperature, ensuring that no core operating parameters are missed; the high-speed data collection and synchronous processing unit strictly ensures the consistency of on-state voltage drop, current and shell temperature in the time dimension through instantaneous synchronous sampling, digital filtering and timestamp alignment, effectively eliminates noise interference, and provides high-quality, time-synchronized input data for subsequent electro-thermal coupling calculation. The Kalman filter core algorithm implementation unit ensures efficient execution of the dynamic iteration process of junction temperature estimation, supporting real-time updating of junction temperature; the loss calculation unit is focused on real-time calculation of conduction loss and switching loss, and forms a dynamic coupling with the junction temperature; the database interface ensures effective calling of the ideal electro-thermal characteristic database and the dynamic temperature gradient compensation database constructed offline, providing accurate basis for calculation; the Foster thermal network model solver realizes junction temperature prediction based on physical heat conduction law, ensuring the physical consistency of calculation, and improving the accuracy and dynamic response capability of junction temperature and loss estimation. The data storage unit realizes effective retention of historical junction temperature and loss data, supports trend analysis and backtracking; the communication interface unit is compatible with multiple platforms such as converter valve control systems, SCADA systems, etc., expanding the application range of data; the human-computer interaction interface intuitively displays the electro-thermal state of the IGBT, making it convenient for operation and maintenance personnel to master the equipment situation in real time; the control and protection interface directly interfaces with the cooling system and the protection device, so that the junction temperature and loss data can be directly converted into control instructions, supporting real-time thermal management and protection actions, and improving the engineering practicability and system reliability of the technical scheme.

[0063] Advantages:

[0064] 1. Significantly improve the accuracy of junction temperature estimation: through the innovative high-precision on-state voltage drop V CE(on)The transient sampling technology overcomes the challenge of measuring electrical parameters in a high-voltage environment. By combining an offline constructed dynamic temperature gradient compensation database and an online adaptive Kalman filter, the chip internal hotspot effect on the measured value can be dynamically compensated, thereby decoupling a more true and representative IGBT junction temperature, and reducing the estimation error to a very low level. V CE(on) The influence of the measured value is decoupled to a more true and representative IGBT junction temperature, and the estimation error is reduced to a very low level.

[0065] 2. Realize the electric-thermal coupling co-estimation of junction temperature and loss: A junction temperature-loss iterative closed loop with a Kalman filter as the core is established, which tightly couples the junction temperature estimation and loss calculation, so that they correct each other and converge cooperatively, the estimation result is more in line with the actual electric-thermal coupling characteristics of IGBT, and the physical self-consistency and accuracy of the model are improved.

[0066] 3. Improve the robustness and adaptability of online monitoring: The adaptive Kalman filter can effectively suppress measurement noise and model uncertainty, and adjust its filtering strategy according to the dynamic temperature gradient changes caused by electric-thermal coupling, so that the method can maintain high precision and high robustness under complex and variable operating conditions (such as load fluctuation, environmental temperature change, etc.).

[0067] 4. Provide core data for fine thermal management of flexible DC converter valve: The obtained high-precision real-time junction temperature and loss data can be directly used to implement accurate overheat protection, optimize cooling strategy, evaluate device thermal stress accumulation, and perform early fault warning, which can effectively support the development of smart and highly reliable operation and maintenance of flexible DC transmission system, prolong the service life of equipment, and reduce operation and maintenance cost. BRIEF DESCRIPTION OF DRAWINGS

[0068] Figure 1 is the general block diagram of the present application;

[0069] Figure 2 is the schematic diagram of the offline test bench of the present application;

[0070] Figure 3 is the construction flowchart of the dynamic temperature gradient compensation database in the chip of the present application;

[0071] Figure 4 is the online running parameter sampling circuit module block diagram of the present application;

[0072] Figure 5 is the Kalman filtering flowchart of the present application. DETAILED DESCRIPTION

[0073] The technical solutions of the present application will be further described in detail in combination with the drawings of the specification.

[0074] The technical solutions of the embodiments of the present application will be described clearly and completely in combination with the drawings of the embodiments of the present application.

[0075] Embodiment one:

[0076] As Figure 1 indicated, the application provides an IGBT junction temperature high-precision real-time decoupling modeling method based on dynamic electro-thermal compensation, including the following steps:

[0077] S1: Offline electro-thermal characteristic and compensation database construction for IGBT module. This step is carried out in a controlled laboratory environment, aiming to provide accurate electro-thermal characteristic model and compensation database for online real-time estimation.

[0078] S1.1 Construct the ideal electro-thermal characteristic database of IGBT body and antiparallel diode.

[0079] Specifically, the application uses high-precision test equipment to perform pulse testing on the IGBT module to obtain its electrical characteristics under uniform junction temperature. The test bench (which can refer to Figure 2 ) mainly includes:

[0080] High-power pulse power supply: provides controllable, short pulse large current (for example, the pulse current peak can reach 2 times the rated current of the module, and the pulse width can be adjusted in the range of 10 µs to 100 µs), which is used to drive the IGBT to turn on. The pulse width is short enough to ensure that the self-heating effect of the device during measurement can be ignored, so that the junction temperature remains uniform with the shell temperature.

[0081] Precise temperature control box (constant temperature oil bath or TEC temperature control system): used to accurately control the temperature of the substrate or heat sink of the IGBT module being tested. Its temperature control accuracy needs to reach within ±0.1℃ to ensure the uniformity and stability of the junction temperature of the IGBT chip during the measurement process. The test temperature points can be selected at multiple representative temperatures, such as 25℃, 75℃, 125℃, 150℃, etc.

[0082] High-speed oscilloscope: with high bandwidth (for example, more than 1GHz), high sampling rate (for example, more than 5GS / s) and high vertical resolution (for example, 12 bits or higher), used to synchronously capture the instantaneous collector current (IGBT collector current I C or antiparallel diode forward current I F ) waveform and collector-emitter on-state voltage drop (IGBT collector-emitter on-state voltage drop V CE(on) or antiparallel diode forward voltage V F) waveforms. Current measurement is usually achieved by high-bandwidth current probes or precision shunts, while voltage measurement employs four-wire Kelvin connection, connecting the voltage measurement points directly to the emitter and collector pins of the IGBT chip to eliminate the influence of lead and test fixture resistance on V CE(on) the measurement accuracy.

[0083] Data acquisition and processing system: responsible for synchronizing the pulse power supply and oscilloscope, and storing and analyzing the collected waveform data. Data processing includes extracting the stable conduction platform from the pulse waveform I C and V CE(on) the instantaneous value, averaging multiple measurement results to further reduce random noise.

[0084] Performing mathematical fitting on the collected multiple sets of V CE(on) - I C and V F - I F data. The fitting method can use piecewise polynomial fitting or logarithmic fitting, etc. For example, under each fixed junction temperature T j , the relationship between I C and V CE(on) is fitted to obtain coefficients A ( T j ), B ( T j ), C ( T j ); the relationship between I F and V F is fitted to obtain coefficients D ( T j ), E ( T j ), F ( T j ). These coefficients are themselves fitted as a function of junction temperature T j , for example Ultimately, a three-dimensional mapping function or multi-dimensional lookup table is formed that can accurately describe the ideal electrical characteristics of IGBTs and anti-parallel diodes under uniform junction temperature conditions.

[0085] Subsequent applications: This "ideal electrothermal characteristic database" is used in this invention to calculate ideal... V CE(on),ideal ( I C , T j The basis of this is also the dynamic temperature gradient compensation amount Δ. V CE(on),comp The calculation benchmark is used to compare actual measurements with ideal conditions, thereby quantifying the impact of temperature non-uniformity.

[0086] S1.2 Construct a dynamic temperature gradient compensation database for the chip's internal environment.

[0087] Specifically, this invention utilizes specialized multiphysics finite element simulation software, such as COMSOL Multiphysics. COMSOL Multiphysics was chosen because of its powerful bidirectional coupling simulation capabilities, which can simultaneously solve the electric, current, and temperature field problems within power electronic devices, accurately simulating the generation, transfer, and distribution of heat, rather than simply performing heat conduction calculations. (For details, refer to...) Figure 3 (Flowchart shown)

[0088] Model building methods:

[0089] 3D Geometric Model Reconstruction: Based on detailed structural drawings or X-ray tomographic data of the IGBT module, accurately reconstruct the 3D geometric model of the IGBT module in COMSOL. This model should include all critical layers, such as: the IGBT chip, anti-parallel diode chip, chip solder layers (e.g., silver sintering layer, soft solder layer), ceramic copper-clad laminate (DBC), copper substrate, bonding wires, package casing, and connecting heat sink. The geometric dimensions of each layer must be precisely modeled according to the actual device.

[0090] Material property definition: Define the temperature-dependent thermophysical parameters (such as thermal conductivity) for each material in the model (e.g., Si chip, Ag sintering, Cu, Al2O3 ceramic, Si3N4 ceramic, etc.). k ( T ), specific heat capacity C p ( T ),density p ( T )) and electrical parameters (such as resistivity) p e (T Temperature dependency is the key to accurately capture the electro-thermal coupling effect.

[0091] Physical field coupling setup: Establish the "current-heat transfer" multi-physical field interface.

[0092] Set up the current field in the AC / DC module, calculate the Joule heat loss density within the IGBT chip and bonding wire through the current density distribution (as the heat source term).

[0093] Set up the temperature field in the heat conduction module, input the loss calculated by the current field as the heat source into the heat conduction equation.

[0094] Set up the two-way coupling: the loss calculated by the current field as the heat source; at the same time, the calculation result (junction temperature) of the temperature field will be fed back to the update of the electrical parameters (such as chip resistivity, bonding wire resistance), affecting the loss calculation at the next moment.

[0095] Boundary conditions and meshing: Set up the actual heat dissipation conditions, such as the convective heat transfer coefficient h between the bottom of the heat sink and the cooling liquid (considering the flow rate, temperature influence), or the natural convection and radiation heat transfer with the ambient air. Local mesh refinement is performed on key areas such as IGBT chip, solder layer and bonding wire (for example, tetrahedral or hexahedral mesh is used, and boundary layer meshing is performed on key heat flow paths) to accurately capture the small temperature gradient and hot spots in these areas.

[0096] Transient simulation setup: Simulate the transient electro-thermal coupling behavior of IGBT under different operating currents (such as from light load to heavy load), switching frequency, duty cycle and transient thermal shock (for example, short-time overload). The simulation time step should be small enough to capture the rapid dynamic changes of the junction temperature.

[0097] Data extraction and compensation parameter construction: Post-process the simulation results. For each simulation condition and time step, extract the instantaneous three-dimensional temperature field distribution of the IGBT chip. Based on this, accurately calculate: the average junction temperature of the chip ( T j avg,sim ), the highest junction temperature inside the chip ( T j max,sim ), and the local junction temperature corresponding to the measurement point position in S2 ( V CE(on) T j local,sim ). By setting a virtual voltage measurement point in the simulation model, obtain the V CE(on) value considering the influence of temperature non-uniformity inside the chip ( V ​CE(on),simulated ).

[0098] Subsequently, this invention defines the temperature gradient compensation amount Δ V CE(on),comp The calculation formula is as follows:

[0099]

[0100] Among them, "thermal gradient characteristics" are parameters used to quantify the temperature non-uniformity inside the chip, such as the difference between the chip's highest temperature and average temperature (ΔT). T j grad = T j max,sim - T j avg,sim Or, more complex spatial temperature gradient feature vectors (such as temperature differences at multiple key points). By performing nonlinear regression fitting or machine learning training (such as radial basis function neural networks or support vector regression machines) on these simulation data, a Δ... V CE(on),comp and I C , T j avg,sim The complex mapping relationship between thermal gradient characteristics is stored in the form of a mathematical model or a multidimensional lookup table, forming a "dynamic temperature gradient compensation database".

[0101] Subsequent applications: This database is an implementation of the present invention. V CE(on) The key to dynamic compensation and junction temperature decoupling. FEM simulation provides internal details that are difficult to obtain with traditional testing, enabling us to accurately quantify the impact of temperature non-uniformity on... V CE(on) The influence of this is incorporated into the online estimation model, thereby improving the accuracy of online estimation.

[0102] S1.3 Extract the parameters of the Foster thermal network model of the IGBT module.

[0103] Specifically, this invention obtains the transient thermal resistance characteristic curve of the IGBT module by consulting the datasheet provided by the manufacturer. Z thjc ( t Alternatively, experimental measurements can be performed using thermal transient testing equipment (e.g., the Mentor Graphics T3Ster thermal tester). This equipment can measure the IGBT's thermal transient response after a power pulse is applied. V CE(on)transient variation, deduce the transient response of junction temperature, and then get the accurate Z thjc ( t ) curve.

[0104] Then, use the curve fitting algorithm (for example, a nonlinear optimization algorithm based on least squares or particle swarm optimization algorithm) to fit the measured or data book curve into the form of the Foster thermal network model:

[0105]

[0106] where, N is the order of the model (usually 3 to 5 orders according to the fitting accuracy and calculation efficiency), R i is the thermal resistance of the i order, t i is the thermal time constant of the i order. This parameter set { R i , t i} will be used for online real-time dynamic estimation of junction temperature as the core component of the state transition equation in the Kalman filter.

[0107] Subsequent application: the Foster thermal network model provides an accurate physical model basis for online junction temperature estimation, ensuring the accuracy of the dynamic response of the junction temperature.

[0108] S2: Online real-time high-precision synchronous sampling and preprocessing of IGBT module operating parameters. This step aims to obtain high-quality electrical and thermal parameter inputs in the actual operation field of the flexible DC converter valve.

[0109] S2.1 V CE(on) high-precision isolated sampling.

[0110] Specifically, the present application deploys a specially designed high-voltage isolated, high common-mode rejection ratio differential amplifier circuit at the Collector and Emitter pins of each IGBT module. This circuit uses a precision differential operational amplifier (such as ADI's AD8479) combined with a high-speed analog isolator (such as Analog Devices' ADuM7420 or Texas Instruments' ISO224) to withstand the transient common-mode voltage of up to several thousand volts during the operation of the converter valve and ensure electrical isolation between the measurement circuit and the control circuit. The differential amplifier uses a design with high bandwidth, low input bias current, and high common-mode rejection ratio (CMRR usually requires more than 80 dB @ 100 kHz) to ensure that the VCE(on) During the signal acquisition process, high-frequency noise and common-mode interference are effectively suppressed. The bandwidth of the sampling circuit needs to match the switching speed of the IGBT, usually requiring several MHz to several tens of MHz. (For specific processes, refer to Figure 4 the circuit module block diagram shown)

[0111] S2.2 Multi-channel high-speed synchronous sampling and signal preprocessing.

[0112] Specifically, the present application adopts a high-performance, multi-channel, high-speed analog-to-digital converter (ADC) system. This system can be composed of a high-performance digital signal processor (DSP) integrated high-speed ADC chip (for example, TI's ADS8688 series, providing 16-bit resolution, single-channel sampling rate up to 500 kSPS to 1 MSPS, or higher-speed analog-to-digital converter ADC). The ADC system receives analog signals from the above-mentioned V CE(on) isolated sampling circuit, high-precision Hall effect current sensor (such as LEM's LA series, used to measure I C IGBT module housing or heat sink substrate (used to measure module shell temperature T C ).

[0113] The sampling trigger uses the rising edge or falling edge of the IGBT gate drive signal as the precise synchronization trigger point, controlled by the high-precision timer inside the FPGA, ensuring V CE(on) , I C and T C strict synchronization in the time dimension. During the extremely short platform period of IGBT conduction (usually 1-2 microseconds), the ADC system performs high-density instantaneous sampling to obtain the V CE(on) instantaneous value that best represents the device conduction state.

[0114] The collected raw digital data stream is subjected to real-time digital filtering (for example, using a median filter to eliminate sharp noise, or a low-pass filter to smooth high-frequency noise). Then, the precise timestamp alignment algorithm is implemented, and through interpolation or resampling technology, the strict consistency of all acquisition parameters in the time dimension is ensured, providing clean, synchronized, and high-precision data stream for subsequent electro-thermal coupling estimation.

[0115] Subsequent application: high-quality online measurement data is the basis of the whole high-precision junction temperature estimation, overcoming the difficulties of traditional measurement in high-pressure environment, providing reliable observation values for subsequent Kalman filtering.

[0116] S3: Based on online real-time operating parameters and offline constructed database, junction temperature-loss electric heat coupling iterative calculation and dynamic compensation are carried out. This step is the core intelligent processing part of the application, which is usually run in real time on high-performance embedded controllers (such as DSP, FPGA) or industrial PCs.

[0117] S3.1 Construct the state space model of Kalman filter.

[0118] System state vector x k : defined as the instantaneous junction temperature of IGBT, that is, x k =[ T j ] k T .

[0119] State transition equation: established based on the Foster thermal network model extracted in S1.3 and the IGBT loss calculation model. In each real-time sampling period Δ t s , the dynamic change of junction temperature can be approximately expressed as:

[0120]

[0121] Where, T j (k) is the junction temperature at the current time, T C (k) is the module case temperature measured in real time in S2, is the total loss of IGBT (including conduction loss and switching loss) estimated at the last time, Z thjc (Δ t s ) is the response of the transient thermal impedance calculated according to the Foster model parameters (S1.3) in the Δ t s time step, w k is the process noise representing model uncertainty or unmodeled dynamics, which is usually modeled as zero-mean Gaussian white noise.

[0122] The calculation of depends on the junction temperature at the last time and the current current, which is obtained through the "ideal electro-thermal characteristic database" of S1.1 and the loss calculation formula:

[0123]

[0124] wherein, P cond is the conduction loss, P sw is the switching loss, V bus is the DC bus voltage, f sw is the switching frequency. The conduction loss is usually calculated according to I C and V CE(on) The switching loss is calculated according to the switching energy E on, E off (these also depend on I C , V bus, T j ) and the switching frequency.

[0125] Observation equation: the high-precision sampled in S2 is taken as the observation value, and the relationship with the junction temperature is established:

[0126]

[0127] wherein, V CE(on),ideal provided by the "ideal electrothermal characteristic database" of S1.1, I C (k) is the current collected in real time by S2, v k is the measurement noise (residual white noise). Δ V CE(on),comp is a key dynamic temperature gradient compensation term, which is queried or calculated according to the current I C and the junction temperature predicted by the Kalman filter (or the prior estimate ) of S1.2 "dynamic temperature gradient compensation database".

[0128] S3.2 Iterative calculation process based on adaptive Kalman filter.

[0129] In each real-time sampling period, the following Kalman filter iteration steps are performed (the Kalman filter flowchart shown in Figure 5 ), to realize the cooperative estimation and dynamic compensation of the junction temperature and the loss:

[0130] Initialization: at the beginning of each sampling period, the current real-time IC (k) 、 T C (k) and . Set the initial state estimate and error covariance matrix P k-1 If it is the first run, can be set to T C (0) .

[0131] State prediction step:

[0132] Predict junction temperature: Estimate the junction temperature at the previous time step and the current I C (k) , T C (k) First, use the "ideal electro-thermal characteristic database" and the loss calculation formula of S1.1 to calculate the loss at the previous time step . Then, use the Foster thermal network model of S1.3 to predict the prior estimate of the junction temperature at the current time step .

[0133] Predict error covariance: Update the prior error covariance matrix:

[0134]

[0135] where, A k is the state transition matrix derived based on the state transition equation, Q k is the process noise covariance matrix, which reflects the uncertainty of the model itself and the unmodeled dynamics.

[0136] Observation update and dynamic compensation:

[0137] Calculate the Kalman gain K k :

[0138]

[0139] where, H k is the observation matrix derived based on the observation equation (i.e. V CE(on) the partial derivative of T j ). R k is the dynamically adjusted measurement noise covariance matrix. Rk The value is adjusted in real time based on information provided by the dynamic temperature gradient compensation database constructed in S1.2. Specifically, it is adjusted according to the current. I C (k) and predicted junction temperature Query or calculate the corresponding Δ from the database. V CE(on),comp When the internal temperature gradient of the chip is larger (Δ V CE(on),comp The larger the absolute value), the better. R k The larger the value of Δ, the stronger the Δ V CE(on) When the "reliability" or "representativeness" of the measurement decreases, the Kalman filter will rely more on the model predictions. Conversely, when the temperature gradient is small, R k The smaller the value, the more the filter depends on the measured value. This dynamic adjustment allows the filter to adaptively cope with measurement errors and non-uniformity caused by electrothermal coupling, enhancing the filter's robustness. State update (junction temperature decoupling): Using the calculated Kalman gain, combined with the high-precision real-time data acquired in S2... and model predictions V CE(on) Update the junction temperature estimate:

[0140]

[0141] right By performing "calibration" or "compensation," the coupling is achieved. V CE(on) The measurement was affected by the uneven temperature inside the chip. It can more accurately reflect the junction temperature of the IGBT as a whole or in a critical area, rather than just the temperature of a local measurement point affected by hot spots.

[0142] Update the posterior error covariance matrix:

[0143]

[0144] Loss recalculation and output: using the latest and most accurate junction temperature estimates. Recalculate the precise loss at the current moment. Outputs the current IGBT junction temperature with high precision and dynamic compensation. and precise loss This process is performed in real time during each sampling cycle, forming a closed loop and continuously providing updated electrothermal status information.

[0145] S4: output and apply the accurate junction temperature and loss data obtained by iterative calculation. This step aims to use the real-time estimated IGBT accurate junction temperature and loss data to guide the fine operation management and reliability improvement of the flexible DC converter valve.

[0146] Specifically, the accurate junction temperature and loss data can be directly applied to the following aspects:

[0147] Online thermal management and heat dissipation optimization: Based on the real-time feedback of the IGBT accurate junction temperature, the control system of the converter valve can intelligently adjust the cooling system (for example, adjust the cooling liquid flow, control the fan speed, switch the heat dissipation mode), to ensure that the IGBT always operates within the safe working area, and avoid performance degradation or damage caused by overheating.

[0148] Device working condition fine monitoring: Real-time monitoring of IGBT actual loss and junction temperature data, and comparison with design value, historical health data or preset threshold. Once there is abnormal fluctuation or deviation, the system can timely issue an alarm to help operation and maintenance personnel find potential operation abnormalities or early signs of failure.

[0149] Converter valve operation efficiency evaluation: Accurate calculation of power loss of each IGBT module is crucial for evaluating the operation efficiency of the entire converter valve and even the flexible DC power transmission system. Based on accurate loss data, the scheduling strategy of the system can be optimized to improve the overall energy conversion efficiency.

[0150] Early fault warning and predictive maintenance: Monitor the long-term trend of junction temperature and loss, such as abnormal increase in junction temperature fluctuation and continuous increase in loss under the same working condition. These changes can be used as early warning signals for internal aging of IGBT (such as bond wire fatigue and expansion of solder layer voids leading to increased thermal resistance), thereby achieving predictive maintenance of the device, avoiding sudden failure, reducing operation and maintenance costs and improving system availability.

[0151] Embodiment two:

[0152] The embodiment of the application also provides an IGBT junction temperature high-precision real-time decoupling modeling system based on dynamic electro-thermal compensation. The system can realize all processes of the above method.

[0153] Please refer to the accompanying drawings. The IGBT junction temperature high-precision real-time decoupling modeling system based on dynamic electro-thermal compensation comprises:

[0154] Offline modeling module: used for performing the above-mentioned S1 offline electro-thermal characteristic and compensation database construction. The module is a high-precision test and simulation integrated platform, usually composed of high-performance industrial computers or special workstations, equipped with:

[0155] High-precision pulse test unit: including high-power pulse power supply, precision temperature control box, high-speed oscilloscope and data acquisition card, used to perform S1.1, ideal electrical and thermal characteristic calibration test of IGBT body and anti-parallel diode.

[0156] Multi-physics simulation workstation: equipped with professional multi-physics finite element simulation software such as COMSOL Multiphysics and its related modules (such as AC / DC module, heat conduction module), used to perform simulation calculations required for S1.2 chip internal dynamic temperature gradient compensation database construction.

[0157] Data analysis and database management unit: integrated with MATLAB, Python and other data analysis tools and database management systems, used for mathematical fitting, regression analysis or machine learning training of test and simulation data, finally generating and managing "ideal electrical and thermal characteristic database" and "dynamic temperature gradient compensation database", and storing Foster thermal network model parameters.

[0158] Online sampling and preprocessing module: used to perform S2 above to conduct online real-time high-precision synchronous sampling and preprocessing of IGBT module operating parameters. This module is physically deployed near the IGBT module of the flexible DC converter valve, mainly including:

[0159] High-voltage isolation on-state voltage drop sampling unit: containing high-voltage isolation, high common-mode rejection ratio differential amplification circuit, directly connected to the collector and emitter of IGBT, transmitting signals to the main processing unit through optical fiber or high-speed digital isolator, achieving millivolt-level V CE(on) Safe and accurate collection of signals in high-voltage environment.

[0160] Current acquisition unit: using high-bandwidth, high-precision Hall effect current sensor or Rogowski coil, used to measure the instantaneous current of IGBT in real time I C .

[0161] Module shell temperature acquisition unit: using platinum resistance (RTD) sensor or optical fiber temperature sensor, installed on the surface of IGBT module shell or heat sink base plate, used to measure module shell temperature in real time and stably T C .

[0162] High-speed data acquisition and synchronous processing unit: usually implemented by FPGA or DSP, integrated with multi-channel high-speed ADC chip, capable of triggering synchronously with IGBT gate drive signal, with high precision of microseconds or even nanoseconds, to V CE(on) 、 I C and T CThe instantaneous synchronous sampling is performed. The unit also has a built-in digital filtering algorithm and timestamp alignment algorithm to preprocess the collected raw data and output clean and synchronous digital signal stream.

[0163] The electric-thermal coupling estimation module is used to perform the junction temperature-loss electric-thermal coupling iterative calculation and dynamic compensation based on the online real-time running parameters and the offline constructed database. The module is the core intelligent operation unit of the whole system, and is usually implemented by a high-performance digital signal processor (DSP, such as TIC2000 series) or an industrial-grade embedded computer (with a multi-core processor), and has strong floating-point operation capability and real-time operating system (RTOS) support. The functional logic inside the module includes:

[0164] The Kalman filter core algorithm implementation unit is used to program the state prediction and observation update of the Kalman filter to perform real-time and dynamic estimation of the IGBT junction temperature.

[0165] The loss calculation unit receives the junction temperature estimated by the module and the real-time current provided by the online sampling and preprocessing module, and calculates the conduction loss and switching loss of the IGBT in real time according to the "ideal electric-thermal characteristic database" constructed in S1.1.

[0166] The database interface and access logic provides an efficient access mechanism for the "ideal electric-thermal characteristic database" and "dynamic temperature gradient compensation database" constructed in S1 to obtain the required characteristic parameters and compensation quantities.

[0167] The Foster thermal network model solver is used to implement the Foster thermal network model extracted in S1.3 for state prediction of the junction temperature in the Kalman filter.

[0168] The dynamic compensation logic is a core component in the observation update of the Kalman filter. According to the current and the predicted junction temperature, the logic obtains the corresponding Δ V CE(on),comp from the "dynamic temperature gradient compensation database", and dynamically adjusts the value of the measurement noise covariance matrix R k in the Kalman filter, and performs compensation correction of the measurement value in the observation update formula, so as to realize the "decoupling" accurate estimation of the junction temperature. V CE(on)

[0169] The data output and application module is used to perform the output and application of the accurate junction temperature and loss data obtained by the iterative calculation in S4. The module is responsible for managing and interfacing the output data (accurate junction temperature, accurate loss) of the electric-thermal coupling estimation module, and usually includes:

[0170] ​Data storage unit: high-speed and large-capacity non-volatile memory (such as SSD or NAND Flash) is used for long-term storage of real-time calculation junction temperature and loss data, supporting historical trend analysis, data backtracking and fault diagnosis.

[0171] Communication interface unit: support multiple standard industrial communication protocols (such as Modbus TCP / RTU, IEC 61850, CANbus, Ethernet / IP), realize real-time data exchange with converter valve station-level control system, SCADA system, remote monitoring and diagnosis platform.

[0172] Human-machine interface (HMI): provides a visual interface to display the current junction temperature, loss, operating status, alarm information and historical trend chart of IGBT in real time, making it easy for operation and maintenance personnel to intuitively understand the health status of the equipment.

[0173] Control and protection interface (optional): provides a direct control interface with the cooling system or protection system, such as digital output or analog output, to realize accurate overheat protection action or active thermal management control based on real-time junction temperature.

[0174] In specific implementation, the working principle, control process and technical effect of the IGBT junction temperature high-precision real-time decoupling modeling system based on dynamic electro-thermal compensation provided by the embodiment of the present application correspond to the same as the IGBT junction temperature high-precision real-time decoupling modeling method based on dynamic electro-thermal compensation in the above embodiment, and will not be repeated here.

[0175] The IGBT junction temperature real-time decoupling modeling method and system based on dynamic electro-thermal compensation shown above are specific embodiments of the present application, which have embodied the substantial characteristics and progress of the present application. According to actual use needs, equivalent modifications can be made under the inspiration of the present application, which are all within the protection scope of the present application.

Claims

1. An IGBT junction temperature high-precision real-time decoupling modeling method based on dynamic electrothermal compensation, characterized in that, The method comprises the steps of: S1: offline constructing an electrical-thermal characteristic and compensation database of the IGBT module, comprising: constructing an ideal electrical-thermal characteristic database of the IGBT body and the anti-parallel diode; constructing an IGBT chip internal dynamic temperature gradient compensation database, wherein a three-dimensional electrical-thermal coupling model of the IGBT module is established by using a multi-physical field finite element simulation software, the chip transient temperature field distribution under different working conditions is simulated, the average junction temperature, the maximum junction temperature and the local junction temperature of the measuring point of the chip are extracted, the temperature gradient compensation quantity is defined as the difference between the on-state voltage drop obtained by simulation and the ideal on-state voltage drop in the ideal electrical-thermal characteristic database, and the mapping relationship between the compensation quantity and the current, the average junction temperature and the thermal gradient characteristic quantity is established; extracting the Foster thermal network model parameters of the IGBT module; S2: online real-time high-precision synchronous sampling and preprocessing the operating parameters of the IGBT module, comprising high-precision isolated sampling of the on-state voltage drop of the IGBT collector-emitter, and multi-channel high-speed synchronous sampling and signal preprocessing of the on-state voltage drop, the collector current and the module shell temperature; S3: based on the online real-time operating parameters and the offline constructed database, performing junction temperature-loss electrical-thermal coupling iterative calculation and dynamic compensation, comprising: constructing a Kalman filter state space model, taking the junction temperature as the state vector, the Foster thermal network model as the state transition equation and the on-state voltage drop as the observation value; iteratively performing the following in each sampling period: a) state prediction: predicting the current junction temperature based on the junction temperature, the current and the shell temperature at the last moment by the Foster model; b) observation update: i. according to the current and the predicted junction temperature, obtaining the temperature gradient compensation quantity from the dynamic temperature gradient compensation database; ii. dynamically adjusting the measurement noise covariance matrix, so that the measurement noise covariance matrix increases with the increase of the temperature gradient compensation quantity; including: querying the dynamic temperature gradient compensation database according to the current and the predicted junction temperature, and linearly or nonlinearly increasing the value of the measurement noise covariance matrix when the absolute value of the temperature gradient compensation quantity increases; iii. subtracting the sum of the ideal on-state voltage drop and the temperature gradient compensation quantity from the real-time on-state voltage drop measurement value to obtain the compensated observation value; iv. updating the junction temperature estimation value in combination with the Kalman gain; c) outputting the real-time junction temperature after dynamic compensation and recalculating the loss; the loss recalculating comprises: based on the updated junction temperature estimation value, combining the real-time current and the switching frequency, and calculating the loss by the on-state loss formula and the switching energy formula; S4: outputting and applying the junction temperature and the loss data obtained by iterative calculation; the application comprises working condition monitoring or fault warning.

2. The IGBT junction temperature high-precision real-time decoupling modeling method based on dynamic electrothermal compensation according to claim 1, characterized in that, In step S1, the ideal electrical-thermal characteristic database is constructed by acquiring the on-state voltage drop and the current relationship of the IGBT and the anti-parallel diode at multiple preset uniform junction temperature points through pulse testing, and a three-dimensional mapping function of the on-state voltage drop changing with the current and the junction temperature is established by using a segmented polynomial or a logarithmic fitting.

3. The IGBT junction temperature high-precision real-time decoupling modeling method based on dynamic electrothermal compensation according to claim 1, characterized in that, In the Foster thermal network model parameters extracted in step S1, the transient thermal impedance is represented by the combination of an N-order thermal resistance and a corresponding thermal time constant, wherein N is the model order.

4. The IGBT junction temperature high-precision real-time decoupling modeling method based on dynamic electrothermal compensation according to claim 1, characterized in that, In step S2, the high-voltage isolated differential amplification circuit is used to collect the collector-emitter on-state voltage drop instantaneously; the rising edge or falling edge of the IGBT gate drive signal is used as the sampling trigger point, and the on-state voltage drop, collector current and module shell temperature are synchronously collected by a multi-channel high-speed analog-to-digital converter; the collected data is digitally filtered and time-stamped to ensure time synchronization.

5. An IGBT junction temperature high-precision real-time decoupling modeling system based on dynamic electrothermal compensation, characterized in that, The system for performing the IGBT junction temperature high-precision real-time decoupling modeling method based on dynamic electro-thermal compensation of any one of claims 1-4, the system comprises: An offline modeling module for offline constructing an electro-thermal characteristic and compensation database of an IGBT module, comprising: constructing an ideal electro-thermal characteristic database of an IGBT body and an anti-parallel diode, constructing an IGBT chip internal dynamic temperature gradient compensation database, and extracting a Foster thermal network model parameter of the IGBT module; An online sampling and preprocessing module for online real-time high-precision synchronous sampling and preprocessing of IGBT module operating parameters, comprising: high-precision isolated sampling of the IGBT collector-emitter on-state voltage drop; multi-channel high-speed synchronous sampling and signal preprocessing of the on-state voltage drop, collector current and module shell temperature; An electro-thermal coupling estimation module connected to the offline modeling module and the online sampling and preprocessing module, for performing junction temperature-loss electro-thermal coupling iterative calculation and dynamic compensation based on online real-time operating parameters and the offline constructed database; A data output and application module for outputting and applying the junction temperature and loss data obtained by iterative calculation, the application comprising online thermal management, operating condition monitoring or fault warning.

6. The IGBT junction temperature high-precision real-time decoupling modeling system according to claim 5, characterized in that, The offline modeling module comprises an industrial computer or workstation equipped with simulation software and data analysis tools for IGBT module characteristic calibration, simulation and database generation.

7. The IGBT junction temperature high-precision real-time decoupling modeling system according to claim 5, characterized in that, The online sampling and preprocessing module comprises: A high-voltage isolated on-state voltage drop sampling unit for collecting instantaneous collector-emitter on-state voltage drop; A current collection unit for real-time measurement of instantaneous collector current of the IGBT; A module shell temperature collection unit for real-time measurement of module shell temperature; A high-speed data collection and synchronous processing unit for instantaneous synchronous sampling of the on-state voltage drop, collector current and module shell temperature, and digital filtering and time stamp alignment.

8. The IGBT junction temperature high-precision real-time decoupling modeling system according to claim 5, characterized in that, The electro-thermal coupling estimation module comprises: A Kalman filter core algorithm implementation unit for implementing state prediction and observation update of the Kalman filter; A loss calculation unit for real-time calculation of the conduction loss and switching loss of the IGBT; A database interface for data interaction with the ideal electro-thermal characteristic database and dynamic temperature gradient compensation database generated by the offline modeling module; A Foster thermal network model solver for implementing the Foster thermal network model for state prediction of the junction temperature.

9. The IGBT junction temperature high-precision real-time decoupling modeling system according to claim 5, characterized in that, The data output and application module comprises: A data storage unit for storing historical junction temperature and loss data; A communication interface unit for data exchange with a converter valve control system, a SCADA system or a remote monitoring and diagnosis platform; A human-computer interaction interface for real-time display of the electro-thermal state of the IGBT. Control and protection interface for controlling the cooling system or protection device.

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