Efficient energy management strategies for hybrid electric vehicles using shuffled frog-leaping algorithm

Abstract

This paper proposes two novel approaches for the problem of energy management in hybrid electric vehicles. Shuffled frog-leaping algorithm (SFLA) is a recently proposed population-based optimization algorithm. This paper first formulates energy management as an optimization problem and optimizes the problem using SFLA. Then the paper makes use of SFLA as a training algorithm to train artificial neural network (ANN) and this SFLA-trained ANN is used for energy management. Interestingly, the proposed approaches of this paper are found to be robust and more efficient than contemporary approaches.