Predictive Cruise Control Algorithm Design for Commercial Vehicle Energy Saving Based on Mixed Integer Programming

In this paper, an energy-efficient predictive cruise control (PCC) algorithm for commercial vehicles that can optimize vehicle speed in real time is proposed. The predictive cruise problem for commercial vehicles is described as a mixed integer programming (MIP) problem in the model predictive control (MPC) framework and a vehicle controller is designed. The objective function is quadratic, and the system dynamics and performance requirements are transformed into linear constraints by relaxation and introduction of auxiliary variables. The road ahead information is acquired through V2X technology and the cruise speed can be set by the driver. The predictive cruise algorithm is validated under highway conditions with slope variations. The fuel consumption can be reduced by 1.778% compared to normal cruise control. The proposed algorithm can be extended to other more complex traffic conditions by simply adding different constraints or weights to the state or control variables.