Energy-Optimal Adaptive Cruise Control based on Model Predictive Control

In this paper an approach for an energy-optimal adaptive cruise control based on model predictive control (MPC) is presented. The approach uses the knowledge of the given route to precalculate a position-dependent energy-optimal speed trajectory using dynamic programming while taking additional information like speed limits, road slope and travel time into account during the optimization. The model predictive controller is used to control the traction force of the host vehicle such that the vehicle speed follows the optimal speed trajectory as good as possible while ensuring constraints like distance to a preceding vehicle or speed limits. To show the benefits of the approach, a comparison of the energy consumption between the controlled vehicle and the preceding vehicle on the same route is performed. For the speed profile of the preceding vehicle, data of real test drives is used. Simulations show that the approach leads to a significant reduction of the energy consumption compared to the preceding vehicle on the same route. Furthermore the simulations indicate that the approach achieves high energy savings even with a poor prediction model for the preceding car. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.