Sustain-Deplete approach for State-of-charge management in e-vehicles

Abstract

The battery life of an electric vehicle is usually affected by its accumulated heat, rapid usage, and overall energy efficiency. In the electric vehicle, adding an ultracapacitor to the battery provides improved flexibility in running and using the battery more adequately. The overall system performance and its efficiency are determined by the energy management scheme in the dual-energy storage systems. In order to drive the electric motor, they utilize the energy which is stored in the rechargeable batteries when it is plugged in to a charge point. In this research, to manage the state of charge (SOC), sustain BeC-Artificial Neural Network (BeC-ANN) controller and deplete-BeC-ANN controller are proposed, which manages the energy charging and discharging phenomenon. The main aim of this developed method is to balance the amount of energy when it is driving during an extended period. Depending on the vehicle velocity while driving mode, the remaining energy in the battery and SOC is evaluated using the proposed approach. Controlling of SOC in battery and ultracapacitor is achieved by the two-stage artificial neural network dependent scheme named sustain-BeC-ANN controller and deplete-BeC-ANN controller, which is developed through the integration of the BeC algorithm with the classifier for optimal controller-tuning. The battery and ultracapacitor energy efficiency and its vehicle velocity are considered as measures for evaluation. The Energy storage system in an electric vehicle that the battery achieves better energy efficiency and increased lifetime in this newly developed approach. Eventually, the experimental results reveal the applicability of the developed method.