A multi-level energy management system for multi-source electric vehicles – An integrated rule-based meta-heuristic approach

João P. Trovão, Paulo G. Pereirinha, Humberto M. Jorge and Carlos Henggeler Antunes

Applied Energy, 2013, vol. 105, issue C, 304-318

Abstract: In this paper, an integrated rule-based meta-heuristic optimization approach is used to deal with a multi-level energy management system for a multi-source electric vehicle for sharing energy and power between two sources with different characteristics, namely one with high specific energy (battery) and other with high specific power (SuperCapacitors). A first (long-term) management level dynamically restricts the search space based on a set of rules (strategic decisions). A second (short-term) management level implements the optimization strategy based on a meta-heuristic technique (tactical decisions). The solutions to the optimal power sharing problem are be used to generate the power references for a lower (operational) level DC–DC converters controller. The Simulated Annealing meta-heuristic is used to define an optimized energy and power share without prior knowledge of power demand. The proposed scheme has been simulated in Matlab®, with models of energy sources for several driving cycles. Illustrative results show the effectiveness of this multi-level energy management system allowing to fulfill the requested performance with better source usage and much lower installed capacities.

Keywords: Electric vehicle; Multiple energy sources; Battery; SuperCapacitors; Energy management system; Simulated Annealing (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (64)

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DOI: 10.1016/j.apenergy.2012.12.081

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