A reliability-oriented method for constructing baseline operating conditions of electric drive systems based on minimum cycle identification

Abstract

Electric drive systems in new energy vehicles operate under complex and time-varying conditions that accelerate component degradation and affect system reliability. Constructing representative operating conditions is therefore essential for reliability evaluation. This study proposes a method for constructing baseline operating conditions based on minimum cycle identification and category-based sampling. Multiscale load data are segmented using a variable sliding-window method, and indicators from time, frequency and damage domains are used to determine the minimum representative cycle through a relative recurrence index. Operating-condition segments are then clustered according to damage-rate characteristics and sampled within categories to maintain statistical consistency with the overall dataset. A case study based on operational data from 30 vehicles shows that 90% of users have minimum cycle periods shorter than 11,587 km. The difference in damage-rate means is below 1%, while the joint probability distribution error is lower than 0.001.