Minimal Energy Transient Motion Control of Electrical Connected Vehicles

Abstract

Vehicle transient motion control plays an important role in reducing energy consumption for both hybrid and electric vehicles since vehicle acceleration and deceleration can be optimized based on driving environment. In this article, nonlinear quadratic tracking (NQT) control is used for optimal acceleration and minimal principle is applied to deceleration to optimize energy recovery, where acceleration control generates the propulsion torque based on the current powertrain status and the error between vehicle speed and given reference provided by the connected system based on the surrounding traffic; and the deceleration (braking) control optimizes regenerative brake to maximize the recovered energy while obeying speed and braking distance constraints. Both control strategies are designed for real-time applications and updated online to respond to the rapid changing traffic environment. Cosimulation models, consisting of SUMO traffic and Simulink control models, are developed for validating the proposed control strategies through computer-in-the-loop (CIL) and hardware-in-the-loop (HIL) simulations. CIL simulation results show that in the eco-acceleration mode, the proposed strategy can save 6.8% energy over the rapid acceleration and brake control recovers 50.8% more energy than the vehicle driven by SUMO simulated human driver. HIL simulations further confirm reduction of energy consumption and adaptability to a changing traffic environment in real-time.