Optimal sizing and sensitivity analysis of a battery-supercapacitor energy storage system for electric vehicles

This paper presents a sizing method with sensitivity analysis for battery-supercapacitor hybrid energy storage systems (HESSs) to minimize vehicle-lifetime costs. An optimization framework is proposed to solve joint energy management-sizing optimization. Sensitivity analysis is performed using eight parameters of the vehicle, HESS system and components as sensitive factors. We explain why HESS sizing is sensitive to each factor by discussing the change of optimal HESS size and costs with varying factor values. The relative importance of each factor in practical engineering is quantified and compared. Results show that battery degradation accounts for around 89% of HESS costs; among eight sensitive factors, vehicle driving range has the biggest impact on HESS costs with a calculated impact degree of 1.243. By analyzing comprehensive factors in optimization of HESS sizing, it is expected to provide general a sizing guide applicable to various application scenarios of HESS in electric vehicles. (c) 2021 Elsevier Ltd. All rights reserved.

Automated summary

This paper introduces a sizing method with sensitivity analysis for battery-supercapacitor hybrid energy storage systems to minimize vehicle-lifetime costs. By performing sensitivity analysis on eight parameters, the relative importance of each factor in practical engineering is quantified and compared. Results show that battery degradation accounts for around 89% of HESS costs, with vehicle driving range having the biggest impact on HESS costs.