This study proposes an algorithm to save driving energy in an autonomous vehicle based on vehicle-to-vehicle technology. Saving the vehicular driving energy can be realized by reducing unnecessary deceleration and acceleration occurred in road congestion and by reducing the resistance caused by the internal factors of the vehicle. The algorithm proposed in this study defines cornering resistance, one of the internal resistance factors of a vehicle while driving, in terms of steering angle. Thereafter, the control inputs of a vehicle are adjusted to reduce the cornering resistance. In particular, because the target vehicle is to be a four-wheel independent drive vehicle, there are many control input values such as steering angle and yaw moment. To simultaneously obtain the desired driving performance and the minimized driving energy in such a vehicle environment, the control input values are optimally distributed by leveraging model predictive control (MPC). Moreover, a weighting factor for the MPC to yield appropriate control inputs is selected by considering the predefined cornering resistance. A simulation setup linked with CarSim-Simulink is established to verify the reduction of driving energy through the proposed algorithm. The simulation results evaluate the driving performance, driving safety, and energy-efficient driving in various driving scenarios. Author
