Dynamic Negotiation-Based Distributed EMPC With Varying Consensus Speeds of Heterogeneous Electric Vehicle Platoons

This work addresses the issue of optimizing energy consumption and coordination of heterogeneous electric vehicle (EV) platoons. To achieve this, we propose a novel approach called dynamic negotiation (DN)-based distributed economic model predictive control (DEMPC) for the platoon. This method is tailored to the heterogeneous characteristics and coordination requirements of EVs, dynamically optimizing consensus speed trajectories through online negotiation of a multiobjective utopia point. Considering factors such as electricity consumption and travel time, the optimization yields an optimal accessible speed for the platoon. To ensure the EVs cooperatively follow the optimal accessible speed while minimizing their self-interested economical cost (i.e., energy savings), we design the local EMPC of each EV, incorporating contractive constraints. The simulation results demonstrate the advantages of the proposed method in electricity savings and battery lifespan extension.