Montalto, Lorenzo (Chalmers), Murgovski, Nikolce (Chalmers University of Technology), Fredriksson, Jonas (Chalmers University of Technology)

Electrical Vehicles Charging: An Optimal Control Approach Via Pontryagin's Maximum Principle

Scheduled for presentation during the Regular Session "S35b-Optimization, Control, and Learning for Efficient and Resilient ITS" (FR-EA-T35), Friday, November 21, 2025, 14:50−14:50, Surfers Paradise 2

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 October 18, 2025

Abstract

This study provides a semi-analytical solution to the charging optimization problem for electric vehicles, using Pontryagin's Maximum Principle (PMP) to derive explicit expressions for optimal control and costate trajectories. Such expressions enable much faster trajectory computation than numerical optimization, making this method suitable for larger trip-planning problems. In addition, these explicit expressions reveal the fundamental structure of the optimal solution and how all the parameters and variables affect it, leading to more interpretable results and deeper theoretical insights than fully numerical or black-box methods allow. The method nearly eliminates online computation, while having an average difference with a benchmark solution of about 2.74%.