A Study on Real Time IGBT Junction Temperature Estimation Using the NTC and Calculation of Power Losses in the Automotive Inverter System

Lim, Heesun; Hwang, Jaeyeob; Kwon, Soonho; Baek, Hyunjun; Uhm, Juneik; Lee, GeunHo

doi:10.3390/s21072454

Cited by 13 publications

(6 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As inverters have been developed to drive induction motors and supply important applications, it has become crucial to understand how to regulate the IGBT junction temperature, which is the power module of an inverter. The IGBTs are often restricted by their junction temperature, and if the junction temperature is not correctly controlled, there is a significant risk of failure due to overheating [8]. The IGBTs are responsible for all power loss; the heat produced by the IGBT is mostly transferred to the substrate, heat sink, and air through heat conduction.…”

Section: Methods 21 Thermal Resistance Modelmentioning

confidence: 99%

Modeling of IGBT junction temperature based on load torque variation in induction motor

Mayyahi

Omar

2023

IJPEDS

View full text Add to dashboard Cite

In order to discuss the effectiveness of inverter performance, it is essential to concentrate on its losses. Thus, knowing the junction temperature (TJ) value of the inverter switches insulated-gate bipolar transistor (IGBTs) under different loading conditions allows determining their reliability and designing the right heat sink. The old methods to calculate the TJ are inaccurate, difficult to implement, and require mathematical analysis. So, in this work, a new approach was used to calculate the TJ in a simplified way, using the SIMSCAPE environment in the MATLAB simulation. The IGBT in the SIMSCAPE environment is of an improved design and has a direct thermal port. The TJ estimation is more accurate and it relies only on the thermal impedance model, so we do not need to compute the power losses as was done in previous studies. This functionality is only accessible in more recent versions of MATLAB (2019-2023). With different motor load torques, the IGBT junction temperature is evaluated, and the effect of the selected heat sink on the value of TJ is evaluated when it is under the effect of natural cooling and air-forced cooling.

show abstract

Section: Methods 21 Thermal Resistance Modelmentioning

confidence: 99%

Modeling of IGBT junction temperature based on load torque variation in induction motor

Mayyahi

Omar

2023

IJPEDS

View full text Add to dashboard Cite

show abstract

“…Li et al [21] established the generalized power loss model of hybrid switch, taking the device size as the continuous input variable and the total power loss and junction temperature as the output. Lim et al [22] was used to calculate the power loss of power semiconductor devices by the Simulink model, and the junction temperature is estimated based on the loss obtained from the model and the thermal impedance model of the inverter systems. A general silicon carbide punch through IGBT structure is realized by adopting appropriate physics based models and parameters by Johannesson et al [23], and it is proved that the switching loss increases with the increase of charge carrier life.…”

Section: Literature Reviewmentioning

confidence: 99%

Enhanced marine predators algorithm optimized support vector machine for IGBT switching power loss estimation

Liu,

Li,

Liu

2023

Meas. Sci. Technol.

View full text Add to dashboard Cite

As the use of renewable energy generation continues to grow, improving power conversion efficiency has become an urgent task. This study aims to propose a high-precision power module loss estimation method, with a focus on predicting the switching losses of Insulated Gate Bipolar Transistor (IGBT) modules, which is crucial for the reliability assessment of IGBT modules. The main objective of this study is to establish a high-precision predictive model for IGBT module switching losses to enhance the reliability and efficiency of these devices. Firstly, a dynamic characteristic test platform was established to acquire relevant data for in-depth analysis of IGBT behavior. Secondly, given the excellent performance of Support Vector Machine (SVM) in handling both strong and small-sized datasets, SVM was chosen as the foundational model for high-precision switching loss estimation. Subsequently, an Enhanced Marine Predatory Algorithm (EMPA), known for its superior convergence precision and speed, was introduced to optimize the random parameters of SVM. Finally, a method based on the Enhanced Marine Predatory Algorithm Optimized Support Vector Machine (EMPA-SVM) was constructed for predicting IGBT switching power losses. The proposed approach was validated using dynamic characteristic test data. And it indicated that the predictive model achieved the value of R2 exceeding 99.8% for switching losses. Additionally, the MAE and RMSE metrics of EMPA-SVM model outperformed other models. Therefore, the research results unambiguously demonstrate the significant benefits of accurately predicting IGBT switching losses in enhancing device performance.

show abstract

“…Different power losses, including conduction, switching, and thermal power losses, introduce temperature cycling during the operation of an IGBT power module [31,32], and this temperature cycling profile weakens the properties of the IGBT module and shortens its useful lifetime. As a result, in the selection process of an IGBT module for a target application, loss modeling and thermal analysis of the IGBT module can be used to predict the module's temperature based on the power losses and heat energy calculation.…”

Section: Introductionmentioning

confidence: 99%

Estimation Technique for IGBT Module Junction Temperature in a High-Power Density Inverter

Okilly,

Choi,

Kwak

et al. 2023

Machines

View full text Add to dashboard Cite

During the last few decades, insulated-gate bipolar transistor (IGBT) power modules have evolved as reliable and useful electronic parts due to the increasing relevance of power inverters in power infrastructure, reliability enhancement, and long-life operation. Excessive temperature stresses caused by excessive power losses frequently cause high-power-density IGBT modules to fail. As a result, module temperature monitoring techniques are critical in designing and selecting IGBT modules for high-power-density applications to guarantee that temperature stresses in the various module components remain within the rated values. In this paper, a module’s different losses were estimated, a heating pipe system for the thermal power cycling technique was proposed, and finite element method (FEM) thermal modeling and module temperature measurement were performed using ANSYS Icepak software version 2022 R1 to determine whether the IGBT module’s temperature rise was within acceptable bounds. To test the proposed technique, a proposed design structure of the practical railway application with a 3.3 MW traction inverter is introduced using commercialized IGBT modules from Semikron company with maximum temperature of about 150 °C. the FEM analysis results showed that the maximum junction temperature is about 109 °C which is in acceptable ranges, confirming the appropriate selection of the employed IGBT module for the target application.

show abstract

A Study on Real Time IGBT Junction Temperature Estimation Using the NTC and Calculation of Power Losses in the Automotive Inverter System

Cited by 13 publications

References 16 publications

Modeling of IGBT junction temperature based on load torque variation in induction motor

Modeling of IGBT junction temperature based on load torque variation in induction motor

Enhanced marine predators algorithm optimized support vector machine for IGBT switching power loss estimation

Estimation Technique for IGBT Module Junction Temperature in a High-Power Density Inverter

Contact Info

Product

Resources

About