Multiobjective Optimal Sizing of Hybrid Energy Storage System for Electric Vehicles

Energy storage system (ESS) is an essential component of electric vehicles, which largely affects their driving performance and manufacturing cost. A hybrid energy storage system (HESS) composed of rechargeable batteries and ultracapacitors shows a significant potential for maximally exploiting their complementary characteristics. This study focuses on optimal HESS sizing of an example electric vehicle using a multi-objective optimization algorithm, with the overarching goal of reducing the ESS cost while prolonging battery life. To this end, a battery state-of-health model is incorporated to quantitatively investigate the impact of component sizing on battery life. The wavelet-transform-based power management algorithm is adopted to realize the power coordination between the batteries and ultracapacitors, in which the ultracapacitors are responsible for handling high-frequency power transients, whereas the batteries deal with average power leveling. The Urban Dynamometer Driving Schedule is used to represent real power demands.