Optimal Sizing of the Energy Storage System for a Plug-in Fuel Cell Electric Vehicle: A Multi-Objective Approach

This paper investigates the optimal sizing of the Energy Storage System (ESS) for a Plug-in Fuel Cell Electric Vehicle (PFCEV) using a multi-objective approach. The ESS consists of a battery, proton-exchange membrane fuel cell (FC), and supercapacitor (SC). The study sets maximum speed and driving range as driving performance requirements and uses the Urban Dynamometer Driving Schedule (UDDS) for simulations. A severity factor aging model is employed to analyze the impact of component sizing on battery life, CO2 emissions, and cost. The SC is utilized to protect the other sources from high currents and supply power during acceleration. A Quadratic Programming (QP) Energy Management System (EMS) algorithm minimizes driving cost, battery aging, and FC aging. The study employs a Genetic Algorithm (GA) to explore the feasible optimal solution domain that satisfies the constraints. Based on the findings, It can be inferred that the utilization of hydrogen is the primary contributor to emissions and a significant factor in the cost. This highlights the need for producing hydrogen in a more environmentally-friendly and cost-effective manner. This study provides insights into the optimal sizing of the PFCEV ESS, with potential implications for the design of an eco-friendly and cost-efficient electric vehicle (EV).