SmartCar: Smart charging and driving control for electric vehicles in the smart grid

Abstract

Electric vehicle (EV) is the next-generation vehicle powered by electricity. Keeping EVs charged and ready to go will require a tight integration and coordination of an infrastructure of equipment connected to the power grid for vehicle charging and a new IT management system for monitoring, analyzing and controlling the vehicle charging. Smart grid technologies have brought opportunities to solve challenges in the EV ecosystem. Both academia and industry have been seeking technologies and applications to optimize an EV driver's driving cost. However, it still remains an open problem of how to handle the driving demand uncertainty and the electricity price uncertainty for EV charging. To address this challenge, we model the driving cost minimization problem and formulate it as an optimization problem. While the driver demand and the electricity price are varying with time, we leverage the Model Predictive Control (MPC) based method to design a dynamic charging (controlling when to charge and how much to charge) and driving (controlling the switching between electric driven mode and gasoline driven mode during the driving process) control scheme. Performance evaluation results demonstrate the effectiveness and cost efficiency of our approach.