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Sustainability 2018, 10(10), 3644; https://doi.org/10.3390/su10103644

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

1
State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China
2
Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, Hebei University of Technology, Tianjin 300130, China
3
Institute of Innovation and Circular Economy, Asia University, Taichung 41354, Taiwan
4
School of Business, Dalian University of Technology, Panjin 124221, China
*
Authors to whom correspondence should be addressed.
Received: 11 September 2018 / Revised: 30 September 2018 / Accepted: 2 October 2018 / Published: 11 October 2018
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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. View Full-Text
Keywords: Kernel principal component analysis; ageing test; state monitoring; grey model; Insulated gate bipolar transistors module Kernel principal component analysis; ageing test; state monitoring; grey model; Insulated gate bipolar transistors module
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Liu, B.-Y.; Wang, G.-S.; Tseng, M.-L.; Li, Z.-G.; Wu, K.-J. New Energy Empowerment Using Kernel Principal Component Analysis in Insulated Gate Bipolar Transistors Module Monitoring. Sustainability 2018, 10, 3644.

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