  As the deployment of low carbon transportation technologies, specifically
electric vehicles (EVs), is increasing, the concept of their eco-driving is
gaining significant attention. Contrary to the eco-driving techniques used in
conventional internal combustion engine vehicles that do not have the
capability of regenerative braking, this paper proposes a genetic algorithm
(GA)-based eco-driving technique for EVs considering regenerative braking. In
the proposed approach, the optimal or near-optimal combination of variables in
the driving cycle of EVs is searched using GA. The proposed approach starts by
generating an initial population of chromosomes, where all variables under
consideration are encoded in each chromosome. This population of chromosomes is
passed through crossover, mutation, and elitist-based selection over a certain
number of generations, which results in a driving cycle with the least energy
consumption. The proposed method is verified using two case studies. The
results of the case studies show the capability of the proposed method in
computing the minimum energy driving cycle.
