Development of an Energy-Efficient Routing Algorithm for Electric Vehicles

Shifting to electric alternatives in transportation is one of the solutions to lessen the greenhouse gas emissions in the environment. The electric vehicles' acceptance in the mass market is hindered, however, by their short range and the lack of infrastructure in the country. To address the first problem, an energy-efficient route-planner is proposed that takes into consideration the vehicle's regenerative ability and road topography to provide energy-saving routes, thereby maximizing its mileage. This paper presents an optimization approach using Particle Swarm Optimization(PSO), an optimization which trades off solution quality for computational speed. The proposed algorithm's performance is measured by its computation time and its route energy-consumption which are compared with least energy-cost path and the fastest path. The algorithm is tested in different traffic scenarios using the road simulator, Simulation of Urban Mobility(SUMO). The findings present that PSO's route quality is comparable to both the least energy-cost and fastest path. In some cases, however, the energy-efficient algorithms can have larger energy savings compared to the fastest route when the road characteristics allow it.