RESEARCH PAPER
A reliability-oriented method for constructing baseline operating conditions of electric drive systems based on minimum cycle identification
1
School of Mechanical Engineering, University of Shanghai for Science and Technology, China
2
Base for Postdoctoral Innovation and Practice of Yuxin Electronic Technology Group Co., Ltd., China
3
Central Research Institute for Product R&D, JianglingMotorsCo.,Ltd, China
4
School of Mechanical and Automotive Engineering, South China University of Technology, China
5
Dongfeng Liuzhou MOTOR Co.,Ltd, China
A – Conceptualization; B – Methodology; C – Software; D – Validation; E – Formal analysis; F – Investigation; G – Resources; H – Data curation; I – Writing – original draft; J – Writing – review & editing; K – Visualization; L – Supervision; M – Project administration; N – Funding acquisition
Submission date: 2026-03-12
Final revision date: 2026-04-25
Acceptance date: 2026-08-14
Online publication date: 2026-09-10
Corresponding author
Li-Hui Zhao
School of Mechanical Engineering, University of Shanghai for Science and Technology, China
School of Mechanical Engineering, University of Shanghai for Science and Technology, China
KEYWORDS
reliability evaluationelectric drive systembaseline operating conditionsminimum cycle periodbig data of users
TOPICS
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.
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