KPI-related monitoring approach for powertrain system in hybrid electric vehicles

Hao, Weichen; Wang, Yue; Wang, Yonghui; Lu, Shan; Lou, Zhijiang; Lan, Yungang; Hou, Weifeng

doi:10.1016/j.egyr.2024.02.058

Energy Reports

2024

DOI: 10.1016/j.egyr.2024.02.058

|View full text |Cite

KPI-related monitoring approach for powertrain system in hybrid electric vehicles

Weichen Hao,

Yue Wang,

Yonghui Wang

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Macro- and micro-spacetime feature-preference gated recurrent unit for remaining useful life prediction of electric motor in multiple working conditions

Sun,

Zhou,

et al. 2024

SIViP

View full text Add to dashboard Cite

Macro- and micro-spacetime feature-preference gated recurrent unit for remaining useful life prediction of electric motor in multiple working conditions

Sun,

Zhou,

et al. 2024

SIViP

View full text Add to dashboard Cite

Process monitoring in hybrid electric vehicles based on dynamic nonlinear method

Wang,

Deprizon,

Kit

et al. 2024

J Appl Eng Science

View full text Add to dashboard Cite

Highway third-level faults can significantly deteriorate the reliability and performance of hybrid electric vehicle (HEV) powertrains. This study presents a novel process monitoring method aimed at addressing this issue. We propose a multivariate statistical method based on dynamic nonlinear improvement, namely dynamic neural component analysis (DNCA). This method does not require the establishment of precise analytical models; instead, it only necessitates acquiring data from HEV powertrains. Through numerical simulation and real HEV experiments, we demonstrate the effectiveness of this approach in monitoring highway third-level faults. The testing outcomes demonstrate that DNCA outperforms traditional dynamic methods like dynamic principal component analysis (DPCA), conventional nonlinear methods such as kernel PCA (KPCA) and NCA, as well as traditional dynamic nonlinear methods like DKPCA.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

KPI-related monitoring approach for powertrain system in hybrid electric vehicles

Cited by 2 publications

References 41 publications

Macro- and micro-spacetime feature-preference gated recurrent unit for remaining useful life prediction of electric motor in multiple working conditions

Macro- and micro-spacetime feature-preference gated recurrent unit for remaining useful life prediction of electric motor in multiple working conditions

Process monitoring in hybrid electric vehicles based on dynamic nonlinear method

Contact Info

Product

Resources

About