Hybrid Controlled Multi-Input DC/DC Converter for Electric Vehicle Application

Abstract

The use of energy sources for electric vehicle (EV) applications relies heavily on the power electronic interlinking and its successful control mechanism. A hybrid adaptive neuro-fuzzy inference system (ANFIS) proportional-integral (PI) based control strategy for a multi-input DC-DC converter is investigated in-depth for this purpose. At steady state, the proposed hybrid ANFIS PI controller uses the standard PI controller, and during the transient state, the ANFIS PI control strategy is used. Furthermore, the proposed control scheme aids in the tracing of a predetermined speed pattern in order to achieve total EV. A detailed simulation analysis of the proposed control strategy is carried out and its performace was compared with traditional controllers. The result indicated that the designed control strategy is reliable since it offers bidirectional power management, high gain with quick reaction, and low steady-state error. It enables rapid tracking and achieves improved dynamic response through increased flexibility and energy efficiency. The proposed scheme reduces component stress, as demonstrated by a reliability assessment using the MIL-HDBK-217F military handbook. At nominal power, the converter achieves 96.954% efficiency. An 80 W converter prototype was created and tested in the laboratory to monitor the real-time system’s response time.