van den Eshof, Erik (Eindhoven University of Technology), van Kampen, Jorn (Eindhoven University of Technology), Salazar, Mauro (Eindhoven University of Technology)

Human-In-The-Loop Energy and Thermal Management for Electric Racing Cars through Optimization-Based Control

Scheduled for presentation during the Regular Session "Optimization and control for eco-driving and racing" (MoA2), Monday, June 16, 2025, 11:20−11:40, Jos

AAC 2025 11th IFAC International Symposium on Advances in Automotive Control, June 15-18, 2025, Eindhoven, Netherlands

This information is tentative and subject to change. Compiled on May 31, 2025

Abstract

This paper presents an energy and thermal management system for electric race cars, where we tune a lift-off-throttle signal for the driver in real-time to respect energy budgets and thermal constraints. First, we compute the globally optimal state trajectories in a real-time capable solving time, optimizing a 47-kilometer horizon in 2.5 seconds. Next, for safe operation with a human driver, we simplify it to a maximum-power-or-coast operation in full-throttle regions (straights). We define the coasting sections with a threshold on the costate trajectory of the kinetic energy from the optimal solution, and we tune this threshold with an online implementable bisection algorithm and PI feedback loop. Finally, we validate the proposed approach for an electric endurance race car and compare two variants. Our results show that, under typical racing disturbances, our energy management can achieve stint times ranging from less than 0.056% to 0.172% slower compared to offline optimization with a priori knowledge of disturbances, paving the way for on-board implementations and testing.