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Energetic Macroscopic Representation and Optimal Fuzzy Logic Energy Management Strategy of a Hybrid Electric Locomotive with experimental characterization of Nickel-Cadmium battery cells

Abstract The simulation of a Hybrid Electric Locomotive (HEL) using the Energetic Macroscopic Representation (EMR) is suggested in this paper. Firstly, on-board primary (diesel driven generator set) and secondary sources’ (batteries and Electric Double-Layer Capacitors) dynamical models are developed. EMR is a graphical tool using interconnected blocks where components are described according to the physical causality. Secondly, Nickel-Cadmium battery cells’ experimental characterization, for different working temperatures, is presented. Experiments aim at determining the behavior of such a technology at extreme temperatures and different States Of Charge (SOC). Then, based on the dynamical models and the experimental results, the paper presents the implementation of a real time Energy Management Strategy (EMS) based on Type-2 Fuzzy Logic. The EMS does not necessitate prior knowledge of the driving cycle and the fuzzy logic controller design is performed using a genetic algorithm. It also takes into account the intrinsic characteristics of the on-board sources (response time, reversibility, power and energy density…). Results show the efficiency of this EMS regarding the diesel engine use.