Energy-Optimal Adaptive Cruise Control based on Hybrid Model Predictive Control with Mixed-Integer Quadratic Programming

This paper presents a novel design of energyoptimal adaptive cruise control (EACC) for internal combustion engine (ICE) vehicles based on hybrid model predictive control (HMPC), which optimally plans the vehicle speed trajectory for higher energy efficiency through taking both traffic and road information ahead into account. HMPC is proposed in this work to cope with the discrete control variable for switching the ICE on and off. HMPC is formulated as a mixed-integer quadratically constrained quadratic programming problem (MIQCQP), which is recast as a mixed-integer second order cone programming (MISOCP) problem. The performance of HMPC-based EACC is evaluated in real driving conditions and compared with linear MPC, as well as with receding horizon dynamic programming (RHDP).