Minimizing Costs and CO2 Emissions in Sustainable Electrified Vehicles’ ESS

This research explores and compares the ideal Energy Storage System (ESS) sizing for Battery Electric Vehicles (BEV), Fuel Cell Electric Vehicles (FCEV), and Plug-in Fuel Cell Electric Vehicles (PFCEV) using a multi-objective double connected loop strategy. The study establishes maximum speed and driving range as performance benchmarks and employs the Worldwide Harmonized Light Vehicles Test Procedure (WLTP) for simulations. A battery aging model is used to assess the influence of component sizing on battery lifespan, CO2 emissions, and cost. The SuperCapacitor (SC) is deployed to shield other sources from high currents and provide power during acceleration. A Quadratic Programming (QP) Energy Management System (EMS) algorithm is implemented in the inner loop to minimize driving cost, battery aging, and Fuel Cell (FC) aging. A Genetic Algorithm (GA) is used in the outer loop to identify the feasible optimal solution domain that meets the constraints. The results indicate that ESS hybridization successfully reduces both cost and emissions. It also shows the necessity for green and cost-effective production methods for hydrogen, as conventional hydrogen is the primary contributor to cost and emissions.