Energy-Saving Driving Assistance System Integrated With Predictive Cruise Control for Electric Vehicles

A novel energy-saving driving assistance system (DAS) for electric vehicles (EVs) integrated with predictive cruise control (PCC) is proposed in this paper to extend the driving range while guaranteeing travelling safety. Firstly, the energy-efficient driving task is formulated as the optimal control problem (OCP) with multiple constraints under the model predictive control (MPC) scheme and is solved by using Pontryagin's maximum principle. Then, considering the difference between the optimal and driver's action, and the real-time implementation of the control strategy, a novel energy-saving DAS is proposed, in which a quadratic form OCP is further formulated to find the optimal torque distribution. Furthermore, to achieve a better interaction between the system and the driver, a human machine interface (HMI) hardware is developed to provide drivers with visual and auditory prompts, meanwhile, the driver's demanding torque is adjusted dynamically for eco-driving. Finally, the energy-saving DAS is deployed on an EV, and on-road experiments demonstrate that the proposed system can help save an average of 5.19% energy compared to normal driving by improving the efficiency of the driving motor and the regenerative braking energy (RBE).