Abstract

Electric vehicle (EV) batteries tend to have accelerated degradation due to high peak power and harsh charging/ discharging cycles during acceleration and deceleration periods, particularly in Urban driving conditions. Oversized energy storage system (ESS) meets the high power demand; however, in tradeoff with increased ESS size, volume, and cost. In order to reduce overall ESS size and extend battery cycle life, battery/ultracapacitor (UC) hybrid ESS (HESS) has been considered as a solution in which UCs act as a power buffer to charging/discharging peak power. In this paper, a multiobjective optimization problem is formulated to minimize the overall ESS size, while maximizing the battery cycle life according to the assigned penalty functions. An integrated framework for HESS sizing and battery cycle life optimization applied in a midsize EV, using an Autonomie simulation model, is described and illustrated in this paper. This multidimensional optimization is realized by a sample-based global search oriented DIviding RECTangles (DIRECT) algorithm. The optimization results under Urban Dynamometer Driving Schedule (UDDS) are compared with the battery-only ESS results, which demonstrate significant battery cycle life extension of 76% achieved by the optimized HESS with 72 UC cells.

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