A multi-level energy management system for multi-source electric vehicles – An integrated rule-based meta-heuristic approach João P. Trovão a,c,⇑ , Paulo G. Pereirinha a,c,d , Humberto M. Jorge b,c , Carlos Henggeler Antunes b,c a Department of Electrical Engineering, Polytechnic Institute of Coimbra, Rua Pedro Nunes, 3030-199 Coimbra, Portugal b Department of Electrical Engineering and Computers, University of Coimbra, Polo II, 3030-290 Coimbra, Portugal c R&D Unit INESC Coimbra, Rua Antero de Quental 199, 3000-033 Coimbra, Portugal d Portuguese Electric Vehicle Association, Av. Rovisco Pais, 1, 1049-001 Lisbon, Portugal highlights " An integrated rule-based meta-heuristic approach for energy management is presented. " An energy level and a power level are implemented as an optimization problem. " We develop energy level with rule-sets and power level with Simulated Annealing. " We model and simulate the approach for several cycles for EV with battery and SCs. " The proposed approach is validated with different initial SCs’ SoC. article info Article history: Received 28 July 2012 Received in revised form 14 December 2012 Accepted 31 December 2012 Available online 7 February 2013 Keywords: Electric vehicle Multiple energy sources Battery SuperCapacitors Energy management system Simulated Annealing 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 Ò , with models of energy sources for several driving cycles. Illustra- tive 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. Ó 2013 Elsevier Ltd. All rights reserved. 1. Introduction The development of modern societies is closely linked to people and goods mobility. However, economic, ecological and geopoliti- cal aspects related with energy availability impose difficult chal- lenges to achieve sustainable mobility. Due to its very high efficiency and much smaller local/global emission levels compara- tively to internal combustion engines vehicles, electric traction has a fundamental place in sustainable mobility, especially road elec- tric vehicles (EVs) [1,2]. Nevertheless, EVs still have a major draw- back: energy storage. For massive deployment of EVs the driving range, charging time and lifetime problems must be solved. Typi- cally, an EV stores energy in batteries that are bulky, heavy and expensive. Due to this problem, with current battery technology, it is very difficult to make a general purpose EV that effectively competes with ICE cars. At present and in the foreseeable future, the viable EV energy sources are batteries, fuel cells, SuperCapacitors (SCs) and ultra- high-speed flywheels. Batteries are the most mature source for EV application but currently they offer either high specific energy (HSE) or high specific power (HSP). Fuel cells are expensive and less mature for EV application. They can offer exceptionally HSE, but with very low specific power. Such low specific power almost rules out their standalone application in EVs that require a high acceleration rate or hill climbing capability, and they are incapable of accepting the regenerative energy during EV braking or downhill 0306-2619/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.apenergy.2012.12.081 ⇑ Corresponding author at: Department of Electrical Engineering, Polytechnic Institute of Coimbra, Rua Pedro Nunes, 3030-199 Coimbra, Portugal. Tel.: +351 239 720 200; fax: +351 239 720 201. E-mail address: jtrovao@isec.pt (J.P. Trovão). Applied Energy 105 (2013) 304–318 Contents lists available at SciVerse ScienceDirect Applied Energy journal homepage: www.elsevier.com/locate/apenergy