Sizing a battery-supercapacitor energy storage system with battery degradation consideration for high-performance electric vehicles. (1st October 2020)

• Record Type: Journal Article
• Authors: Zhu, Tao; Lot, Roberto; Wills, Richard G.A.; Yan, Xingda
• Is Part Of: Energy. Volume 208(2020)
• Publication Date: 2020-10-01
• Subjects: Electric vehicle -- Hybrid energy storage system -- Battery degradation -- Sizing -- Energy management; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2020.118336
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: This paper presents sizing guides and energy management (EM) benchmarks of battery-supercapacitor (SC) hybrid energy storage system (HESS) in electric vehicle (EV) applications. We explain how to optimize the HESS size in order to minimize battery degradation and financial costs in EVs. We also illustrate the optimal EM benchmarks that can minimize battery degradation with whatever EM technique implemented. By decoupling the EM problem from the sizing one, we reveal the general trends of battery degradation with HESS size, which are irrelevant to design parameters of EVs and specifications of batteries and SCs. The vehicle-lifetime battery replacements and HESS costs are discussed with HESS sizing method. The efficacy of the proposed sizing guides and EM benchmarks is tested in the case study of a sports EV. Results show that the optimally sized HESS can extend battery lifetime by 37% as compared with the battery-only energy storage system and can reduce vehicle-lifetime HESS costs by up to 39% as compared with the unoptimized HESS designs, respectively. Highlights: Battery degradation can be reduced by lowering fluctuation of battery operating power. HESSs with same sized SC packs have almost the same optimal power split strategies. A larger battery pack lowers battery replacements but increases financial costs. A larger SC pack lowers battery replacements but not always lowers financial costs. The optimal HESS design to minimize financial costs is worked out for the case study.