Modeling of IGBT Using Temperature Prediction Method

نویسندگان

  • Amit Thakur
  • Y S Thakur
چکیده

A temperature prediction method of Insulated Gate Bipolar Transistor (IGBT) module based on autoregressive moving average model is proposed. Historical and current temperature datum of IGBT module is indispensable to the ARMA method, temperature time series is obtained by uniform sampling, and autoregressive (AR) model is constructed. Temperature time series prediction of IGBT module is realized by employing optimal prediction theory of autoregressive moving average (ARMA) module. Experiments results show the effectiveness and the satisfactory precision of the prediction method. KeywordsAutoregressive Model; Insulated Gate Bipolar Transistor; Optimal Prediction; Time Series Analysis Introduction

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Junction Temperature Prediction of IGBT Power Module Based on BP Neural Network

In this paper, the artificial neural network is used to predict the junction temperature of the IGBT power module, by measuring the temperature sensitive electrical parameters (TSEP) of the module. An experiment circuit is built to measure saturation voltage drop and collector current under different temperature. In order to solve the nonlinear problem of TSEP approach as a junction temperature...

متن کامل

Quantitative Modeling for Prediction of Critical Temperature of Refrigerant Compounds

The quantitative structure-property relationship (QSPR) method is used to develop the correlation between structures of refrigerants (198 compounds) and their critical temperature. Molecular descriptors calculated from structure alone were used to represent molecular structures. A subset of the calculated descriptors selected using a genetic algorithm (GA) was used in the QSPR model development...

متن کامل

Numerical Prediction of Solder Fatigue Life in a High Power IGBT Module Using Ribbon Bonding

This study focused on predicting the fatigue life of an insulated gate bipolar transistor (IGBT) power module for electric locomotives. The effects of different wiring technologies, including aluminum wires, copper wires, aluminum ribbons, and copper ribbons, on solder fatigue life were investigated to meet the high power requirement of the IGBT module. The module’s temperature distribution and...

متن کامل

Thermal conductivity of Water-based nanofluids: Prediction and comparison of models using machine learning

Statistical methods, and especially machine learning, have been increasingly used in nanofluid modeling. This paper presents some of the interesting and applicable methods for thermal conductivity prediction and compares them with each other according to results and errors that are defined. The thermal conductivity of nanofluids increases with the volume fraction and temperature. Machine learni...

متن کامل

Thermal conductivity of Water-based nanofluids: Prediction and comparison of models using machine learning

Statistical methods, and especially machine learning, have been increasingly used in nanofluid modeling. This paper presents some of the interesting and applicable methods for thermal conductivity prediction and compares them with each other according to results and errors that are defined. The thermal conductivity of nanofluids increases with the volume fraction and temperature. Machine learni...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2013