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Optimal energy management of fuel cell hybrid electric vehicle based on model predictive control and on-line mass estimation

Authors :
Weiwei Xin
Enyong Xu
Weiguang Zheng
Haibo Feng
Jirong Qin
Source :
Energy Reports, Vol 8, Iss , Pp 4964-4974 (2022)
Publication Year :
2022
Publisher :
Elsevier, 2022.

Abstract

Energy management strategies with prediction message show great potential in optimizing control objectives for fuel cell hybrid vehicles. This paper presents a novelty model-predictive-control based energy management framework for fuel cell commercial vehicle, in which the vehicle mass is firstly introduced as a variable parameter for controller. A vehicle mass identification model is established and embed in the framework based on recursive least square algorithm, and the influence of variable algorithm parameters on estimator is evaluated. Then the effects of mass varying on vehicle performance is talked about in detail. In addition, the performance for different drive cycles on different loaded is also given. The simulation results show that the fuel consumption is positively correlated with the mass identification error, and the designed controller can reduce the additional fuel consumption to around 0.1%, which is much batter to the deterministic parameters scheme. Finally, the shortcomings of the designed controller are given. This paper provides a reliable theoretical basis to address varying-mass vehicle energy management problems.

Details

Language :
English
ISSN :
23524847
Volume :
8
Issue :
4964-4974
Database :
Directory of Open Access Journals
Journal :
Energy Reports
Publication Type :
Academic Journal
Accession number :
edsdoj.27c501747bb046a2a1843611ebc3c398
Document Type :
article
Full Text :
https://doi.org/10.1016/j.egyr.2022.03.194