Optimal Energy Management of Electric Vehicles Supplied by Battery and Supercapacitors: A Multi-Objective Approach
Bảo-Huy Nguyễn () and
João Pedro F. Trovão ()
Additional contact information
Bảo-Huy Nguyễn: University of Sherbrooke
João Pedro F. Trovão: University of Sherbrooke
A chapter in Intelligent Control and Smart Energy Management, 2022, pp 317-341 from Springer
Abstract:
Abstract Excluding passive topology, hybrid energy storage system (HESS) requires energy management strategy (EMS) which is traditionally developed by mono-objective approach. Meanwhile, energy management of HESS can be considered as multi-objective problems. Recently, multi-objective EMS has been studied; however, there is a lack of a proper benchmark for performance evaluation and/or EMS tuning. This chapter proposes a methodology for multi-objective global optimal EMS generating a Pareto front benchmark. The optimization process is organized in the form of a hierarchical structure, whereas the optimal solutions are obtained by using dynamic programming (DP) algorithm. Filtering strategy is used as an example of a rule-based strategy for performance evaluation using the generated benchmark. Numerical validations are carried out based on a real electric vehicle (EV) platform of our laboratory. The results confirm the advantages of the proposed approach for multi-objective benchmarking the real-time EMS performance by comparing to the generated Pareto front. Representative solutions in accordance with the typical weighting factor values are also reported to demonstrate the advanced EMS behaviors with different priorities given to the considered objectives. The proposed EMS can therefore be insightful to design and/or to tune the real-time strategies.
Date: 2022
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
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:spr:spochp:978-3-030-84474-5_11
Ordering information: This item can be ordered from
http://www.springer.com/9783030844745
DOI: 10.1007/978-3-030-84474-5_11
Access Statistics for this chapter
More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().