Rule based energy management strategy for a series–parallel plug-in hybrid electric bus optimized by dynamic programming

Jiankun Peng, Hongwen He and Rui Xiong

Applied Energy, 2017, vol. 185, issue P2, 1633-1643

Abstract: An appropriate energy management strategy is able to further improve the fuel economy of PHEVs. The rule-based energy management algorithms are dominated in industry due to their fast computation and ease of establishment potentials, however, their performance differ a lot from improper setting of parameters and control actions. This paper employs the dynamic programming (DP) to locate the optimal actions for the engine in PHEVs, and more importantly, proposes a recalibration method to improve the performance of the rule-based energy management through the results calculated by DP algorithm. Eventually, an optimization-based rule development procedure is presented and further validated by hardware-in-loop (HIL) simulation experiments. The HIL simulation results show that, the improved rule-based energy management strategy reduces fuel consumption per 100km from 25.46L diesel to 22.80L diesel. The main contribution of this study is to explore a novel way to calibrate the existed heuristic control strategy with the global optimization result through advanced intelligent algorithms.

Keywords: Energy management strategy; Dynamic programming; Rule-based; Plug-in hybrid electric bus; Hardware-in-loop (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (136)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261915016049
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:185:y:2017:i:p2:p:1633-1643

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.2015.12.031

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 ().