A New Energy Management Strategy for Electric Vehicles Based on Optimal Adaptive State Machine Control

In this paper, an optimal energy management system (EMS) for an electric vehicle (EV)microgrid made of a battery-supercapacitor hybrid power system is proposed. Through bidirectional DC-DC converters, the storage systems are coupled in parallel to the DC-bus and fed via an inverter, a synchronous reluctance motor (SynRM). The driving factor behind the suggested EMS is using the complementing properties of two techniques: the Slap Swarm optimization Algorithm (SSA) and State Machine Control (SMC). The SSA's fast optimization method makes real-time adaption of the SMC improvements possible, maximizing system performance. The primary objective of the proposed EMS is to provide DC-bus stability, respect source dynamics, and meet SynRM motor power requirements. Additionally, the algorithm lessens the impact of the motor's harmonics, hence improving battery lifetime. To test the control design and assess the efficacy of the proposed EMS, extensive simulations of the advocated optimal EMS of the hybrid power system of an EV are carried out in a Matlab/Simulink environment.