New Energy Empowerment Using Kernel Principal Component Analysis in Insulated Gate Bipolar Transistors Module Monitoring

Bo-Ying Liu,Kuo-Jui Wu,Gao-Sheng Wang,Ming-Lang Tseng,Zhi-Gang Li

doi:10.3390/su10103644

Abstract

At present, energy exhausted and environmental pollution are important issues, vigorously promoting new energy and improving the utilization efficiency and management level of new energy is an important way to achieve sustainable social development. Insulated gate bipolar transistors are important components in power converters and are widely used in new energy generation, new energy vehicles, high-speed rail and industrial production. However, the power module’s age is related to all aspects of its performance change, precluding the use of a single parameter to fully and accurately express the aging state. To monitor this state and evaluate the aging state, this study presents a method to analyze and process the state data of Insulated gate bipolar transistors power module aging tests using kernel principal component analysis and establishes a multi-dimensional grey model to evaluate the power module aging state. Using the temperature cycle aging test platform, the 7000 temperature cycling tests are implemented to accelerate the age of the power module to failure, the dynamic parameters of the power modules are measured after every 1000 cycles. During the accelerated aging process, the case temperature change rate, collector-emitter voltage drop Vce(SAT) and Miller platform of the gate signal of Vge are found to exhibit different variation trends at different aging stages. The result showed that multiple parameters are combined into integrated attributes to enable more accurate implementation of the state monitoring of power modules using the proposed method, which improves the status monitoring level of Insulated gate bipolar transistors modules. The proposed method is beneficial to improve the utilization efficiency and new energy source management level.

Highlights

With the development of science and technology, the application of power electronics technology is extensive, and the insufficient energy supply and environmental pollution are becoming serious
This study is necessary to measure the external characteristics of the power module without measuring the junction temperature, the package of the power module does not have to be destroyed; the accuracy of the state monitoring is improved and the cost is reduced
(2) This paper uses kernel principal component analysis (KPCA) to reduce the dimensionality of multiple variables, which improves the visualization of Insulated Gate Bipolar Transistor (IGBT) power module status monitoring data

Summary

Introduction

With the development of science and technology, the application of power electronics technology is extensive, and the insufficient energy supply and environmental pollution are becoming serious. The new energy sources mainly include wind energy and solar energy. These energy resources are extensive and have little environmental pollution. Replacing non-renewable energy with new energy sources can reduce environmental pollution, and better realize the sustainable development of human society. New energy industries such as wind and solar energy are developing rapidly, and their application range is increasing; it is important to improve the level of new energy management. Improving the reliability and stability of new energy power generation systems will further expand the application scale of new energy sources, which can help to manage the global ecological crisis, improve people’s quality of life and promote the sustainable development of society [1,2]

Methods

Results

Conclusion