Realization of prototype hardware model with a novel control technique used in electric vehicle application

Abstract

Battery and ultra-capacitor (UCp) combination forms the multiple energy storage model (MESM), which provides the optimum benefit to hybrid electric vehicles/electric vehicles (EVs) for its successful operation. The inherent high power density characteristic of UCp is used during starting and momentary periods of EV. On the other hand, the battery provides the average power to the EV, during the steady-state periods. The development of the supervisory energy management strategy, corresponding to the EV dynamics is one of the key issues. In this paper, a new control technique is proposed to attain a smooth and automatic transition between energy sources in MESM according to the EV requirement. A speed condition-based (SCB) controller is designed with four individual math functions, corresponding to the speed of the electric motor (EM). A combination of the SCB controller and the artificial neural network (ANN) formed a SCBANN hybrid controller (SCBANNHC). To identify the proper power split between energy sources, the proposed SCBANNHC is applied to the main circuit in four different case studies corresponding to the load on the EM. Four different case study circuit models are realized in the MATLAB/Simulink environment along with a prototype hardware model for validation of the proposed control technique.