Module Junction Temperature Research Articles

Research on junction temperature monitoring technology of IGBT modules

Modular Multilevel Converter (MMC) is widely used in flexible HVDC transmission systems, IGBT module as its core power device, its failure process seriously affects the operation reliability of MMC. The high junction temperature is an important reason for the failure of the IGBT module, so monitoring the junction temperature of IGBT module is an important means to ensure the stable operation of the system. According to the topological structure of IGBT module, the current junction temperature monitoring methods of IGBT module are summarized and compared. According to the shortcomings of the current research and the current research status, the research direction of IGBT module junction temperature monitoring is prospected.

Electrothermal-Control Co-Design of an All Silicon Carbide 2×250 kW Dual Inverter for Heavy-Duty Traction Applications

This article presents the design and demonstration of an all silicon carbide (SiC) 2×250 kW dual inverter for heavy-duty traction applications. Through the use of a formal electrothermal-control co-design approach, the maximum power density of the proposed inverter system is 60 kW/L, which is accomplished by. More specifically, to analyze the thermal performance of the inverter, a lumped thermal model is developed based on the characteristics of the power modules and the cold plate. To analyze the complicated interaction between the power losses and module junction temperatures, a closed-loop iterative estimation scheme is proposed to estimate the inverter power loss and module junction temperature. Based on the proposed thermal model and estimation scheme, a detailed optimization procedure on the selection of switching frequency and dc-link capacitor is presented to maximize power density. Furthermore, design optimization of the busbar was conducted to minimize the stray inductance, thus reducing the voltage overshoot during switching transients. Comprehensive experimental studies were performed on a physical converter prototype built based on the optimization results, which validate both the effectiveness of the presented design approach.

Electro-Thermal Control on Power Electronic Converters: A Finite Control Set Model Predictive Control Approach

<div class="section abstract"><div class="htmlview paragraph">With the increasing attention towards electric vehicles (EV), power electronics technology has become more prominent on vehicular systems. EV requires compact energy conversion and control technology to improve system efficiency and optimize the sizing of power components. Therefore, it is important to reduce thermal losses, while supplying an adequate amount of power to different EV devices. Silicon carbide (SiC)-based power semiconductors provide performance improvements such as lower power losses, higher junction temperature and higher switching frequency compared to the conventional silicon (Si)-based switching devices. High-frequency switching is preferred for power converters to minimize the necessity of passive filters; however, high-frequency switching causes additional thermal stress on semiconductor switches due to the increase in switching losses. The degradation of switching devices in power converters are primarily related to the junction temperature. One method to improve the lifetime of semiconductors is to control the module junction temperature by controlling switching losses in the switching state, while providing power quality in the required limits and maintaining voltage stability. This concept is referred to as active thermal management. This paper illustrates the Finite Control Set Model Predictive Control (FCS-MPC) approach on how electrical performance can be preserved while providing electro-thermal management for the SiC-based switching devices on three-level three-phase power converter to improve system efficiency and reliability.</div></div>

Combined electro-thermal model for PV panels

AbstractThis paper presents a combined electro-thermal model to serve the aim of accurate output power prediction of photovoltaic systems, based on the concept of the thermal energy balance. The electrical sub-model is built based on fitting a surface to the current-voltage curves collected under wide range temperatures and irradiances. For this purpose, the current-voltage characteristic curves are reproduced using two different methods. The thermal sub-model considers all the effective heat transfer mechanisms to estimate the photovoltaic module junction temperature. The Newton-Raphson iterative method is used as a solving algorithm to calculate the photovoltaic junction temperature. The collected results prove the applicability of the model under a wide range of environmental conditions.

Research on IGBT junction temperature model based on united-parameters

The insulated gate bipolar transistor (IGBT) is the most expensive central component in the converter interior, but it is also one of the most vulnerable to failure. The failure of power electronic system is mainly due to temperature change. Therefore, the accurate extraction of IGBT module junction temperature is the basis of life prediction and reliability evaluation of high-power power conversion equipment. There is a great advantage in the non-invasive process of obtaining junction temperature through the dynamic temperature sensitive electrical parameter method; However, the measurement results are easily interfered with by a single dynamic temperature sensitive electrical parameter method. In this paper, a high-precision IGBT online junction temperature model based on united-parameters is proposed. The single dynamic thermosensitive electrical parameter only considers the change of a certain capacitance or inductance, which leads to the inaccurate measurement. A large number of effective temperature sensitive electrical parameters can be added to the model in order to reduce other disturbances and improve the accuracy and reliability of junction temperature prediction. Firstly, the limitations of each temperature sensitive electrical parameter were determined by comparing the existing temperature sensitive parameter method. Secondly, the appropriate united-parameters can be determined by theoretical analysis and practical verification. Finally, a junction temperature extraction model based on united-parameters was established by multiple linear regression method. Compared with the single dynamic TSEP-junction temperature, the proposed method has advantages in on-line temperature extraction and high precision monitoring.

Numerical junction temperature calculation method for reliability evaluation of power semiconductors in power electronics converters

The junction temperature of power semiconductors is a critical parameter during reliability evaluation. The incorporation of long-term mission profiles, such as power loadings and ambient temperature, into lifetime and reliability evaluations of power semiconductors increases the computational burden. Thus, there is an urgent need for a more accurate method for junction temperature acquisition. Current methods for junction temperature calculation are computationally inefficient and do not comprehensively incorporate long-term factors into junction temperature calculation and power semiconductor reliability evaluation. Here, a junction temperature calculation method is proposed that enables reliability evaluation for insulated gate bipolar transistor (IGBT) power semiconductors. This approach calculates the IGBT module junction temperature on the basis of an electro-thermal analogy using Gauss–Seidel iteration. When compared with electrical–thermal simulation and other numerical calculation methods, the proposed method guarantees accuracy, while greatly reducing the computational time and load. A performance comparison between the proposed method, electro-thermal simulation based on a Fuji IGBT simulator, and experimental results was carried out using a three-phase DC/AC inverter as a case study.

Research on on-line monitoring technology of IGBT module junction temperature based on Kalman filter

IGBT is the core device of energy conversion and transmission, commonly known as the CPU of power electronic devices. However, with the continuous improvement of IGBT power density, its reliability is increasingly concerned by industry and academia. The failure of IGBT module is mainly related to the average junction temperature and the amplitude of junction temperature fluctuation, and with the increase of the amplitude of junction temperature fluctuation, the number of failure cycles of IGBT module will sharply decrease. It can be seen that the change of junction temperature in power module is the key to affect its fatigue life. In this paper, an on-line junction temperature monitoring method based on Kalman filter is proposed, which combines the actual temperature measured by IGBT module with the junction temperature obtained by RC thermal network, so it has the advantages of high reliability and real-time on-line monitoring. The simulation results show the effectiveness of the method.

Distributed Systematic Grid-Connected Inverter Using IGBT Junction Temperature Predictive Control Method: An Optimization Approach

Distributed systematic grid-connected inverter practice needs to improve insulated gate bipolar transistor (IGBT) stability to ensure the safe operation. This study is to ensure the safety and reliability operation of the IGBT module in symmetry to meet the reliable and stable distributed systematic grid-connected inverter practice and the junction temperature is a parameter to assess its operating state. It is difficult to accurately acquire the IGBT junction temperature to be solved by a single method of combining the test and the modeling. The saturation voltage drop or collector current and module junction temperature data under different power cycles are measured by the power cycle test and the single pulse test. The improved chicken swarm optimization increases the chickens diversity and self-learning ability. The prediction model of the improved chicken swarm optimization-support vector machine is proposed to forecast the module junction temperature. The result showed to compare with the particle swarm optimization-support vector machine model and chicken swarm optimization-support vector machine model and showed the coincidence degree between the proposed model prediction value and the true value is higher. The mean absolute error ratio indicates the proposed model has a smaller error and a better prediction performance. The proposed model has a positive impact on improving the distributed systematic grid-connected inverter industrial development and promotes the new energy usage.

A High Precision On-Line Detection Method for IGBT Junction Temperature Based on Stepwise Regression Algorithm

The insulated gate bipolar transistor (IGBT), one of the most vulnerable component, is one of the most precious central component in the converter interior. High junction temperature will lead to device failure, which is the main reason of failure of power electronic system. Therefore, on-line high precision measurement of IGBT module junction temperature is the basis of life prediction and reliability evaluation of high-power power conversion equipment. In this paper, the principle of IGBT junction temperature extraction and the latest development of related technologies are summarized. In particular, the working principle and shortcomings of temperature sensitive electrical parameter (TSEP) method are summarized. The change of junction temperature will affect the inter-electrode capacitance in the internal structure of IGBT, which will cause the change of temperature sensitive electrical parameters. The single temperature sensitive electrical parameter method is easily affected by IGBT structure and inter-electrode capacitance. This paper presents an algorithm for high precision on-line detection of IGBT junction temperature. The parameter types are optimized by stepwise regression and the model is established accordingly. In this paper, IGBT: FF50R12RT4 is used as the experimental equipment. By comparing the junction temperature model established based on multiple linear stepwise regression algorithm with the junction temperature model based on traditional temperature sensitive electrical parameters, it is proved that the algorithm has better fitting degree and precision, and the algorithm can be used for high precision online extraction of junction temperature.

Power converter junction temperature measurement using infra‐red sensors

Studies demonstrate that the power converter has one of the highest failure rates in a wind turbine, with a key failure driver being the power module junction temperature ( T j ). This paper details an experimental setup for simplified emulation of wind turbine conditions on a power converter with infra-red sensing of IGBT T j . Results are compared to previous simulation work for a PMSG wind turbine, with the same trend of increasing mean T j with wind speed found, and the need to use an equivalent generator reactance in highlighted. A commercial-scale prototype for more accurate wind turbine converter emulation is also detailed.

Online Junction Temperature Estimation Method for SiC Modules With Built-in NTC Sensor

Silicon carbide (SiC) devices characterized by high efficiency, high power density and wide bandgap, have great potential in many advanced applications, such as electric automotive, aviation and military. Thermal management, condition monitoring and life estimation of SiC modules are essential to achieve high reliability. These control techniques require realtime monitoring or estimation of the module's junction temperature. This paper proposed a thermal model based on an integrated negative thermal coefficient (NTC) thermistor in SiC modules. The Finite Element Methods simulation results showed that the parameters of the thermal model are invariant under different heat dissipation conditions and ambient temperatures. The combination of the proposed thermal model with the reading of NTC sensor realized the online estimation of the junction temperature. The accuracy of the thermal model and the independence of thermal impedance were verified by simulation and experimental results.

Analytical and Experimental Investigation on A Dynamic Thermo-Sensitive Electrical Parameter With Maximum $dI_{C}/dt$ During Turn-off for High Power Trench Gate/Field-Stop IGBT Modules

In this paper, a dynamic thermo-sensitive electrical parameter (DTSEP) for extracting the junction temperature of the trench gate/field-stop insulated gate bipolar transistor (IGBT) modules by using the maximum collector current falling rate is proposed. First, a theoretical model of the transient collector current during turn- off process is developed in terms of the behavior characteristics of the inside storage carriers. Then, the inherent linear relationship between the maximum collector current falling rate $dI_{C}/dt$ and junction temperature $T_{j}$ is demonstrated and investigated. Fortunately, benefitting from the presence of the intrinsic parasitic inductance $L_{\rm eE}$ between the Kelvin and power emitters of IGBT modules, the maximum $dI_{C}/dt$ can be easily measured to validate the theoretical analysis. Consequently, the maximum $dI_{C}/dt$ during turn- off process is a promising DTSEP for IGBT module junction temperature estimation. Moreover, the physical device parameters that affect the temperature sensitivity of the maximum $dI_{C}/dt$ are also discussed with the derived transient collector current falling model.

Performance Investigation of Air Velocity Effects on PV Modules under Controlled Conditions

Junction temperature of PV modules is one of the key parameters on which the performance of PV modules depends. In the present work, an experimental investigation was carried out to analyze the effects of air velocity on the performance of two PV modules, that is, monocrystalline silicon and polycrystalline silicon under the controlled conditions of a wind tunnel in the presence of an artificial solar simulator. The parameters investigated include the surface temperature variation, power output, and efficiency of PV modules under varying air velocity from near zero (indoor lab. conditions) to 15 m/s. Additionally, the results were also determined at two different module angular positions: at 0° angle, that is, parallel to air direction and at 10° angle with the direction of coming air to consider the effects of tilt angles. Afterwards, the thermal analysis of the modules was performed using Ansys-Fluent in which junction temperature and heat flux of modules were determined by applying appropriate boundary conditions, such as air velocity, heat flux, and solar radiation. Finally, the numerical results are compared with the experiment in terms of junction temperatures of modules and good agreement was found. Additionally, the results showed that the maximum module temperature drops by 17.2°C and the module efficiency and power output increased from 10 to 12% with increasing air velocity.

Thermal Assessment of RF-Integrated LTCC Front End Modules

The thermal performance of front end module (FEM) incorporating low-temperature cofired ceramic (LTCC) substrate is investigated. An infrared microscope system was used to measure device surface temperature with both RF and dc power. Various duty cycles (25% to 100%) were applied to characterize the thermal performance of the device for different power densities. The maximum junction temperature occurs at the second stage: under dc powering at 100% duty cycle, it reaches 134/spl deg/C. The comparison between numerical and experimental data indicates good agreement, with less than 10% difference in the peak temperature values. When replacing the common 2-layer organic substrate with a 14-layer LTCC substrate and silver paste metallization, the peak junction temperature reaches 130.1/spl deg/C, /spl sim/51% higher compared to the baseline case using a 2-layer organic substrate with copper metallization. However, by increasing the silver paste thermal conductivity from 90 to 350 W/mK, a significant drop in peak temperatures occurs, indicating the impact on the module's overall thermal performance. For the case with 350 W/mK, the peak temperature reaches 82.9/spl deg/C, almost 3% lower than the baseline case with 2-layer organic substrate. The top metal layer thickness (10 versus 30 /spl mu/s) contributed only to 5%-8% change in the peak junction temperature. An improved FEM design incorporates a higher thermal conductivity silver paste material (300 W/mK) and a new thermal via array structure (25 vias, 150 /spl mu/s in diameter each) in the LTCC substrate. The module junction temperature reaches 96/spl deg/C (based on 25/spl deg/C reference temperature and 100% duty cycle), corresponding to a junction-to-substrate (R/sub js/) thermal resistance of 14/spl deg/C/W. Further study reveals that 20% voiding placed at the die center has no impact on FEM thermal performance, while the voiding placed at the die corner (under the heat dissipating stages) increases the stage peak temperature by more than 40/spl deg/C. The last part of this paper focuses on several designs to reduce the manufacturing and assembly costs, while maintaining reasonable FEM thermal performance. Analyses suggest that two particular designs provide the optimal thermal performance when reducing the thermal via number/costs by almost 40%.