Power Flow Management in HEV using Adaptive Neuro-Fuzzy Controller

The effective power distribution between electrical and mechanical system is always a challenge for control engineers. This paper presents a controller design based on an Adaptive neural fuzzy inference system (ANFIS) for improving the fuel economy. The Energy Management System (EMS) ensures effective power distribution between Internal Combustion Engine (ICE) and Electric Motor (EM). The ANFIS Controller is trained for controlling the on-off of ICE, EM and generator on the basis of value of speed, SOC and engine rpm. The simulation results show the better fuel economy and the battery's state of charge (SOC), thereby improving the battery life cycle. The EMS showed good regenerative capabilities.