@inproceedings{7bb88ffb2220463b901ff6a80407e21b,
title = "Energy management strategy of extended-range hybrid electric vehicle considering time-domain features of optimization targets",
abstract = "An adaptive equivalent fuel consumption minimization strategy (A-ECMS) considering time domain characteristics of the optimization targets is proposed in this paper. Vehicle speed prediction in short time domain is used to adjust the penalty coefficient related to transient conditions, so as to reduce the adverse effects of frequent engine transients. The stored long-time domain historical vehicle speed data is used to adjust the penalty coefficient related to SOC trajectory, so that the SOC can be maintained while ensuring better fuel economy. Comparing the ECMS with the A-ECMS proposed in this paper, the simulation results show that setting up the penalty coefficients of different targets in different time domains can improve the fuel economy and effectively reduce the number of engine starts and stops, thus achieving the purpose of reducing pollutant emissions.",
keywords = "Extended range hybrid electric vehicles, energy management, speed prediction, time domain feature",
author = "Xu Wang and Ying Huang and Yongliang Li",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 5th CAA International Conference on Vehicular Control and Intelligence, CVCI 2021 ; Conference date: 29-10-2021 Through 31-10-2021",
year = "2021",
doi = "10.1109/CVCI54083.2021.9661131",
language = "English",
series = "2021 5th CAA International Conference on Vehicular Control and Intelligence, CVCI 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2021 5th CAA International Conference on Vehicular Control and Intelligence, CVCI 2021",
address = "United States",
}