An Evolutionary Multiobjective Optimization Approach for HEV Energy Management System

Hybrid vehicles have become a promising solution to mitigate the negative effects of pollution and fossil fuel dependency, consequences (among other causes) of an increasing demand on mobility of people and goods. A hybrid vehicle is integrated by many subsystems, where one of the most important is the energy management system, which coordinates when to switch between energy sources to give a desired output. The energy management system needs to take into account several objectives and specifications, most of the times in conflict, to guarantee an acceptable vehicle's performance. This situation makes it a complex system to control and design. In this context, multiobjective optimization could play a significant role as a design tool, since it enables the designer to analyse the tradeoff among design alternatives. In this paper we present a multiobjective optimization design procedure by means of evolutionary multiobjective optimization in order to tune the energy management system of hybrid vehicles. To this aim, new meaningful objectives are stated and optimized. The presented results validate this approach as viable and useful for designers.