Design and Analysis of a Fuel Cell and Batteries in Energy Production for Electric Vehicle

The world’s most economically developed countries are facing an energy crisis caused by geopolitical instability, rising energy costs, global stock disruptions, and a shift towards low-carbon energy sources that has yet to be fully realized. Electrification of the transportation industry offers the advantages of increased energy efficiency and reduced local pollutants. Electric Vehicles (EVs) are environmentally friendly because they reduce fossil fuels usage even zero consumption, need fewer maintenance requirements, and lower operating costs than the vehicles powered by gasoline or diesel. However, this study focuses on comparing various energy management strategies (EMS) for a backup energy supply system for EVs. The hybrid power system (HPS) considered in this study includes DC-DC and DC-AC synchronous converters, as well as supercapacitors, batteries, and fuel cells. The EMS analyzed includes state machine control, classical proportional-integral control, equivalent consumption minimization, frequency decoupling, rule-based fuzzy logic, and fuzzy logic control. The HPS’s efficiency, hydrogen fuel, supercapacitor or battery state of charge levels, and overall performance are evaluated as primary efficiency criteria. Additionally, the HPS not only increases system energy but also reduces the number of pack batteries required. This study designs and constructs the combined power systems to enhance EV power schemes with rechargeable battery power supplies. The results show that a 6-kW fuel cell hybrid increases the power system capacity to 408 kWh. Moreover, a novel method based on wavelet transforms of the instantaneous power of each energy source is used to quantify the stressors on each energy source that impact its life cycle. To validate all analyses and performance, a simulation model and an experimental test bench are created. Finally, simulation results demonstrate a synchronous converter with a 6-kW output power and 96% efficiency, validating the optimization results.