Heuts, Y.J.J. (Eindhoven University of Technology), Smit, Nick Andreas (Eindhoven University of Technology), Wouters, Joey (VDL Enabling Transport Solutions), Velpari, Ranjith (Eindhoven University of Technology), Hulsebos, Oswin (VLD ETS), Donkers, M.C.F. (Tijs) (Eindhoven University of Technology)

A Convex Optimization Eco-Driving Assistance System Applied on a Battery-Electric Heavy-Duty Vehicle

Scheduled for presentation during the Regular Session "Optimization and control for eco-driving and racing" (MoA2), Monday, June 16, 2025, 12:00−12:20, 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

In this work, an overview is given of ongoing work towards an Eco-Driving Assistance System (EDAS) for a battery-electric heavy-duty vehicle. The objective of the EDAS is to provide the driver with a recommendation on the vehicle’s optimal speed trajectory that minimizes its energy consumption over the entire trip. This requires solving a receding-horizon optimal~ control problem, which, in this case, consists of a convex optimization problem and can be solved as a second-order cone program. Simulations were used to explore different prediction horizon lengths and move-blocking strategies of the underlying receding horizon optimal control problem, aiming to strike a balance between numerical complexity and energy savings. Finally, the method is implemented on a battery-electric heavy-duty vehicle where an augmented speedometer is presented to the driver. Multiple tests with and without EDAS have been performed, which demonstrated a reduction of 6.5% to 12% in energy consumption compared to the situation when the driver was not assisted by the EDAS. The energy saving potential can be increased by 6% by also taking into account the corners along the route.