ABSTRACT
Hybrid Electric Vehicles (HEVs) with multiple energy sources can provide better and smoother vehicle performance, as well as contribute to fuel saving and emission reduction. With proper power control, HEVs can intelligently and adaptively provide better power conversion as well as save on fuel costs and improve battery health. Unlike many other control strategies, we focus on multiple conflicting challenges of minimizing the difference between power demand and supplied power as well as other challenges like minimizing fuel consumption while considering the health of the battery used in a hybrid vehicle. This paper uses a Genetic Algorithm (GA) in rule-based energy management whose important aspect of introduction is its ability to optimize multiple objectives. Here, we consider a battery-fuel cell hybrid vehicle. A given severity index is used to quantify the extent of the damage caused by various drive patterns on the battery. By prioritizing the battery life or battery fuel economy, is is not possible to model best the fuel consumption and vice versa. However, depending on the drive cycle there must be an intelligent optimization which considers low fuel consumption as well as better battery fuel economy while maintaining proper vehicle performance.
