Battery SOC constraint comparison for predictive energy management of plug-in hybrid electric bus
Gaopeng Li,
Jieli Zhang and
Hongwen He
Applied Energy, 2017, vol. 194, issue C, 578-587
Abstract:
In this paper, model predictive control (MPC) is employed to resolve the energy management problem of a plug-in hybrid electric bus (PHEB). Dynamic programming (DP), as a global optimization method, is inserted at each time step of the MPC, to solve the optimization problem regarding the prediction horizon. A multi-step Markov prediction model is constructed to forecast the near future driving velocities for the MPC. The battery SOC is restrained to fluctuate near a reference trajectory to ensure the global performance of MPC. Three novel restraining methods are proposed and compared in this paper. The resultant fuel economy performance with different SOC constraint methods are evaluated. Simulation results indicate that by restraining the battery SOC adaptively to the control variables gains the best fuel economy performance, and the fuel consumption of MPC is 8.7% less than a ruled based strategy.
Keywords: Plug-in hybrid electric vehicles; Model predictive control; Markov; Energy management; Battery SOC constraint (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (33)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261916313733
Full text for ScienceDirect subscribers only
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:eee:appene:v:194:y:2017:i:c:p:578-587
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic
DOI: 10.1016/j.apenergy.2016.09.071
Access Statistics for this article
Applied Energy is currently edited by J. Yan
More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().