Xiao, Shunyuan (Nanjing University of Posts and Telecommunications), Ni, Shuang (Nanjing University of Posts and Telecommunications), Ding, Lei (Swinburne University of Technology), Ye, Maojiao (Nanjing University of Science and Technology)

Event-Based Predictive Control of EV Platoons with Energy Economy and Resource Efficiency

Scheduled for presentation during the Video Session "On-Demand Video Presentations" (VP-VP), Saturday, November 22, 2025, 08:00−18:00, On-Demand Platform

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on April 2, 2026

Abstract

This paper proposes a distributed event-based two-level model predictive control (EMPC-2L) strategy for heterogeneous electric vehicle (EV) platoons, enhancing both energy economy and communication resource efficiency. First, a two-level architecture is developed, where the upper level performs receding-horizon optimization at the leader vehicle to minimize the total energy consumption of the platoon, while the lower level enables follower vehicles to cooperatively perform local predictive control based on the leader's trajectory. Second, an event-triggered mechanism is designed to jointly determine the triggering of communication and optimization computation for follower vehicles, adapting dynamically to real-time resource occupancy to reduce unnecessary updates. Third, an event-based predictive control scheme is formulated to ensure the platoon stability and control performance with enhanced energy economy and resource efficiency. Comparative simulation results validates that the proposed EMPC-2L strategy significantly improves energy efficiency, reduces communication and computation load while enhances ride comfort in EV platoon driving.