Load Spectrum Compilation Method of Hybrid Electric Vehicle Reducers Based on Multi-Criteria Decision Making

Jie Li, Chongyang Han, Weibin Wu, Ting Tang, Xiao Ran, Zefeng Zheng and Shunli Sun
Additional contact information
Jie Li: Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China
Chongyang Han: Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China
Weibin Wu: Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China
Ting Tang: Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China
Xiao Ran: College of Engineering, South China Agricultural University, Guangzhou 510642, China
Zefeng Zheng: Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China
Shunli Sun: Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China

Energies, 2022, vol. 15, issue 9, 1-18

Abstract: This article proposes a method for compiling the load spectra of reducers for hybrid electric vehicles. Selecting typical working conditions for real vehicle data collection, the load data under each typical working condition were divided into five categories according to the state of the power source and the data were preprocessed. The optimal sample loads for compiling load spectra were obtained based on a multi-criteria decision-making method, rainflow counting for optimal sample loads was performed according to different power source output patterns, non-parametric extrapolation was performed to obtain the full-life two-dimensional load spectrum after dimensionality reduction, and a full-life eight-level programmed load spectrum that could be used for bench tests was obtained. Using the programmed load spectrum and the extracted sample load as the load input, a fatigue life prediction simulation of the reducer gear of a hybrid electric vehicle was carried out. The reducer gear fatigue life from the programmed load spectrum was compared to the gear fatigue life under actual load. The fatigue life of the reducer gear when the programmed load spectrum was used as the input was 1.412 × 10 3 . When the actual load was used as the input load, the fatigue life of the reducer gear was 1.933 × 10 3 . The relative error between the two is only 26%, which is in the normal range. The results show that the programmed load spectrum is effective and reliable and that the load spectrum compilation method provides a basis for accurately evaluating the reliability of the hybrid electric vehicle reducer.

Keywords: hybrid electric vehicle; reducer; load spectrum; multi-criteria decision making; rainflow counting; fatigue life prediction (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/9/3293/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/9/3293/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2022:i:9:p:3293-:d:806650

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().