Prognostic System for Power Modules in Converter Systems Using Structure Function

Aliyu, Attahir Murtala; Castellazzi, Alberto

Abstract

This paper proposes an on-board methodology for monitoring the health of power converter modules in drive systems, using vector control heating and structure function to check for degradation. It puts forward a system that is used on-board to measure the cooling curve and derive the structure function during idle times for maintenance purposes. The structure function is good tool for tracking the magnitude and location of degradation in power modules. The ability to keep regular track of the actual degradation level of the modules enables the adoption of preventive maintenance, reducing or even eliminating altogether the appearance of failures during operation, significantly improving the availability of the power devices. The novelty in this work is the complete system that is used to achieve degradation monitoring; combining the heating technique and the measurement without additional power components except the measurement circuit which can be integrated into the gate drive board and the challenges encountered. Experimental results obtained from this show that it is possible to implement an on-board health monitoring system in converters which measures the degradation on power modules.

Citation

Aliyu, A. M., & Castellazzi, A. (2018). Prognostic System for Power Modules in Converter Systems Using Structure Function. IEEE Transactions on Power Electronics, 33(1), 595-605. https://doi.org/10.1109/TPEL.2017.2672823

• Journal Article Type: Article
• Acceptance Date: Feb 8, 2017
• Online Publication Date: Feb 22, 2017
• Publication Date: Jan 1, 2018
• Deposit Date: Nov 20, 2017
• Publicly Available Date: Nov 20, 2017
• Journal: IEEE Transactions on Power Electronics
• Print ISSN: 0885-8993
• Electronic ISSN: 1941-0107
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 33
• Issue: 1
• Pages: 595-605
• DOI: https://doi.org/10.1109/TPEL.2017.2672823
• Public URL: https://nottingham-repository.worktribe.com/output/963117
• Publisher URL: http://ieeexplore.ieee.org/document/7862288/
• Additional Information: ©2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.