Convex Optimization for the Energy Management of Hybrid Electric Vehicles Considering Engine Start and Gearshift Costs

Tobias Nüesch, Philipp Elbert, Michael Flankl, Christopher Onder and Lino Guzzella
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Tobias Nüesch: Institute for Dynamic Systems and Control, ETH Zurich, Sonneggstrasse 3, Zurich 8092, Switzerland
Philipp Elbert: Institute for Dynamic Systems and Control, ETH Zurich, Sonneggstrasse 3, Zurich 8092, Switzerland
Michael Flankl: Institute for Dynamic Systems and Control, ETH Zurich, Sonneggstrasse 3, Zurich 8092, Switzerland
Christopher Onder: Institute for Dynamic Systems and Control, ETH Zurich, Sonneggstrasse 3, Zurich 8092, Switzerland
Lino Guzzella: Institute for Dynamic Systems and Control, ETH Zurich, Sonneggstrasse 3, Zurich 8092, Switzerland

Energies, 2014, vol. 7, issue 2, 1-23

Abstract: This paper presents a novel method to solve the energy management problem for hybrid electric vehicles (HEVs) with engine start and gearshift costs. The method is based on a combination of deterministic dynamic programming (DP) and convex optimization. As demonstrated in a case study, the method yields globally optimal results while returning the solution in much less time than the conventional DP method. In addition, the proposed method handles state constraints, which allows for the application to scenarios where the battery state of charge (SOC) reaches its boundaries.

Keywords: HEV; energy management; convex optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (25)

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