A prognostics framework for power semiconductor IGBT modules through monitoring of the on-state voltage

3Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.

Abstract

This paper presents a literature review and an overview of original contributions on diagnostic and prognostic technologies for IGBT power modules based on the monitoring of the on-state voltage (Von). First, different kinds of Von sensing circuits are discussed in terms of specifications, implementation, performance and cost. A low-cost and practical circuit is experimentally demonstrated. Then, a method is presented and evaluated for estimating wire-bond degradation. Wire-bond lift-off is the most observable wear-out mechanism for industrial power semiconductor IGBT modules subject to active power cycling (Lutz et al., 2011). It is effectively detected by measuring Von at the Zero Temperature Coefficient (ZTC) current value. Next, a method is presented to estimate the die temperature. Knowing the die temperature allows estimating the thermo-mechanical stress imposed to the wire-bonds. It is demonstrated to be feasible with ±3°C accuracy/precision using after careful calibration of Von as a Temperature Sensitive Electrical Parameter (TSEP). Finally, an algorithm is presented to process the information generated from the monitoring of Von and estimate the Remaining Useful Life (RUL). It considers Von evolution prior the first wire-bond lift-off and it combines both condition-based and damage accumulation based predictions. The major contribution of this paper is to present, for the first time, a complete framework for diagnostics and prognostics of power semi-conductor IGBT modules.

Cite

CITATION STYLE

APA

Degrenne, N., Kawahara, C., & Mollov, S. (2019). A prognostics framework for power semiconductor IGBT modules through monitoring of the on-state voltage. In Proceedings of the Annual Conference of the Prognostics and Health Management Society, PHM (Vol. 11). Prognostics and Health Management Society. https://doi.org/10.36001/phmconf.2019.v11i1.829

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free