Performance Analysis of Hybrid Powered Electric Vehicle by Adapting Different MPPT Techniques with Energy Management System

Abstract

The concept of electric vehicles has become an emerging trend for the last few years owing to their hefty returns. This research is a part of the emerging electric vehicle technology replacing the conventional fuel-based vehicle. This work presents the illustration of the hybrid electric vehicle employing the solar and fuel cell as the sources of electric vehicle. It is also involved in the proposal of Maximum Power Point Technique (MPPT) for controlling the output of the sources. In this proposed work, a High Gain Interleaved Boost Converter (HGIBC) is used to extract the maximum power from the PV array and fuel cell along with MPPT techniques. To optimize the maximum power, a single MPPT system has been applied to both the fuel cell stack and solar panel. A Brushless DC Motor (BLDC) is used in this work to evaluate the performance of the electric vehicle. A BLDC motor has been designed to coerce the hybrid electric vehicle using a three-phase inverter. The performance characteristics of the system have been analyzed in terms of rise time, peak overshoot and efficiency. newlineIn order to extract maximum power from PV panel and fuel cell stack the different types of controllers such as Proportional Integral Derivative Controller (PID), Fuzzy Logic Controller (FLC) and Neural Network (NN) based Maximum Power Point Techniques (MPPTs) for attaining static and dynamic performance from the system. The performance assessment of different controllers based MPPTs in terms of voltage, current, power, response time, torque ripples and efficiency of the system. Also, comparative analysis has been made in between Incremental Conductance (INC) and perturband Observe (PandO) based MPPTs system. newlineFurthermore, a Radial Basis Function Network (RBFN) controlled Sensor less Hybrid Electric Vehicle (HEV) using a Brushless DC Motor (BLDC) is proposed. In this context, newline