Hybrid Energy Dual Storage Systems for EV Powertrain with Enhanced Algorithm GOA and GA

Abstract

Although EV offers several advantages such as being terrain friendly, producing less noise, and reducing dependency on reactive powers, it also has significant drawbacks. High power and high energy force systems for EVs will be obtained concurrently through the integration of batteries and ultra-capacitors. As a result, ultra-capacitors manage short-term power demands, while batteries provide long-term mobility for the vehicle. A novel algorithm, cold-thoroughbred GOA-GA, is proposed by combining the GOA and GA. The proposed hybrid GOA-GA has a strong eventuality to escape original optima while achieving the convergence. The proposed crossbred algorithm is used to perform a multi-objective function optimization to drop the HESS mass as well as increase the vehicle's operating range. By exercising the MATLAB/ Goad software, the entire frame was erected with the FTP-75, US06 (maximum speed as well as demanded acceleration) and HWFET driving cycles. When compared to an equivalent EV posted with a single HESS unit, the proposed binary-HESS armature has increased driving range while lowering the HESS mass.