Authors: Teresa Donateo, Lorenzo Serrao, Giorgio Rizzoni
Addresses: Dipartimento di Ingegneria dell'Innovazione, Universita del Salento, via per Arnesano, 73100, Lecce, Italy. ' CAR, Center for Automotive Research, The Ohio State University, Columbus, OH, USA. ' CAR, Center for Automotive Research, The Ohio State University, Columbus, OH, USA
Abstract: In the present investigation an innovative procedure to design a hybrid electric vehicle (HEV) is proposed, based on two steps: optimisation and decision-making. Both steps require a multi-objective approach due to the many goals to be taken into account in the design of a complex system like an HEV. The method has been applied to the preliminary design of the powertrain and tuning of the control strategy of a series hybrid vehicle, simulated with a Matlab-Simulink code. The hardware parameters included the number of axles in the vehicle, number of electric motors per axle, and type and quantity of energy storage system devices (batteries and/or electrochemical capacitors). The control parameters are related to fuel economy conversion factors and the maximum and minimum state of charge allowed to the secondary energy storage systems. Several attributes of performance and fuel consumption evaluated with respect to seven driving cycles were considered as optimisation goals.
Keywords: genetic algorithms; GAs; hybrid powertrain; multi-criteria decision making; MCDM; multi-objective optimisation; hybrid electric vehicles; HEV design; tuning; control strategy; vehicle performance; fuel consumption.
International Journal of Electric and Hybrid Vehicles, 2008 Vol.1 No.2, pp.142 - 165
Published online: 18 Apr 2008 *Full-text access for editors Access for subscribers Purchase this article Comment on this article