An economic model predictive cruise controller for electric vehicles using Gaussian Process prediction

Recent political decisions in most developed countries urge car manufacturers to reduce vehicle emissions and fuel consumptions, essentially through development of hybrid and battery electric vehicles. Alongside with transfer to electro mobility, many OEMs promote research in car2x communication and cloud services as such connectivity features offer new opportunities to vehicular technology. This work presents a framework for an economic cruise controller for electric vehicles (EVs) utilizing traffic speed data obtained from a cloud server and aiming for real time applicability. Within the scope of this research, an economic model predictive cruise controller based on leading vehicle speed prediction is designed. Novelty of this approach is to utilize real time traffic speed data which significantly improves leading vehicle speed prediction. Error in speed prediction is compared to existing approaches and computed energy consumption using model predictive control is analyzed and discussed for different approaches of leading vehicle speed prediction. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.