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Temperature Cycling Life Prediction of Low-Voltage Transportation Electric Machines Winding: From Lifetime Model Proposal to Applications

  • Xuanming Zhou
  • , Yatai Ji
  • , Paolo Giangrande
  • , Weiduo Zhao*
  • , Michael Galea
  • *Corresponding author for this work

Research output: Journal PublicationArticlepeer-review

Abstract

The rapid electrification of transportation demands compact, high-power-density low-voltage electric machines (EMs), whose winding insulation life limits safety and uptime. Conventional Arrhenius models consider only thermal-chemical aging and often neglect thermal-mechanical (T-M) fatigue resulting from frequent temperature cycling in vehicle duty cycles. Based on mathematical derivation and previous physical models, this article proposed a unified temperature-cycling life model that couples Arrhenius T-C terms with a phenomenological T-M fatigue term driven by cycle amplitude and mean temperature. The life model's parameters are tuned using experimental data collected during accelerated temperature profiles (TPs) cycling tests performed on motorette specimens, while the life model is validated across different TPs. The predicted life outcomes demonstrate higher computational efficiency and yield more conservative results compared to the physical model simulations. As proof of concept, the proposed model is employed at the design stage of an EM meant for automotive applications, in order to achieve a mission profile-based reliability-oriented design. Meanwhile, a real-time life consumption methodology, employing online cycle counting, is implemented to facilitate continuous reliability assessment and monitoring. This integrated approach establishes a systematic framework for evaluating and managing the reliability of EM insulation systems, thereby enhancing the methodological foundation for life prediction under realistic and dynamically varying operating conditions.

Original languageEnglish
Pages (from-to)3239-3252
Number of pages14
JournalIEEE Transactions on Transportation Electrification
Volume12
Issue number2
DOIs
Publication statusPublished - 1 Apr 2026

Free Keywords

  • Electric machine (EM) degradation modeling
  • life prediction
  • online health diagnosis
  • periodic temperature aging
  • physics of failure
  • reliability assessment

ASJC Scopus subject areas

  • Automotive Engineering
  • Transportation
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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