Impact Factor:7.847

DOI number:10.1109/JAS.2022.106010

Teaching and Research Group:Lin, M., Chen, S., Wang, W., & Wu, J.

Journal:IEEE/CAA Journal of Automatica Sinica

Abstract:This letter presents a multi-feature fusion-based method for estimating the instantaneous energy consumption of electric buses. More specifically, to improve the accuracy of instantaneous energy consumption estimation of electric buses, we propose a new energy consumption estimation method based on random forest regression (RFR) with multi-feature fusion. The multi-feature includes driving behavior, vehicle status, and external environment. The experimental results show that the absolute mean average percentage error (MAPE) value of the method proposed in this paper is 7.10%, which has a higher estimation accuracy than several state-of-the-art methods.

Indexed by:Journal paper

Discipline:Engineering

Document Type:J

Volume:10

Issue:10

Page Number:2035–2037

Translation or Not:no

Date of Publication:2023-10-01

Included Journals:SCI

Links to published journals:https://www.ieee-jas.net/en/article/doi/10.1109/JAS.2022.106010