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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.
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Zhang et al. (2017) studied this question.
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