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This paper presents an energy-efficient and terrain-information-and-preceding-vehicle-information-incorporated energy management strategy for fully electric vehicles (FEVs) equipped with in-wheel motors. Saving driving energy with terrain preview and preceding vehicle movement prediction are crucial to prolong the driving distance for an FEV. Unlike conducting energy optimization under the assumption...
Limited travelling range is a major concern for fully electric vehicles (FEVs), and enlarging the total driving range is a main research topic of FEVs. Recently, with the development of intelligent transportation systems, traffic information can be available for the vehicle control systems, like terrain profile and velocity and acceleration of preceding vehicles. With such information, energy-efficient...
In this paper, a model predictive controller is designed to control an FEV based on the road terrain grade information and the front vehicles movement prediction. With the vehicle-to-vehicle and vehicle-to-infrastructure wireless communication technologies, two front vehicles movement information are obtained, and a Bayes Network model is applied to predict the movement of the closer preceding vehicle...
In this paper, a temporal multi-objective ant colony optimization (ACO) algorithm is proposed to generate the routing plan for electric vehicles to fulfill the various requirements of drivers under a time-dependent stochastic traffic environment. The algorithm optimizes the route length, traveling time, energy, battery recycling lifetime and cabin temperature integrally, and meets constraints on arrival...
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