Temperature-adaptive torque allocation for all wheel drive electric trucks
• Dynamic torque distribution strategy predicated on variable operating temperatures. • Baseline and changing temperatures’ criticality in electric vehicle efficiency. • Demonstrated key benefits of a new torque allocation strategy for electric trucks. • Notable reduction of power consumption with the potential to increase savings to 7 %. Electrification of heavy-duty trucks is of great interest since it would bring substantial benefits in terms of reduce emissions ( > 80 % of road transport) and noise pollution. This study investigates energy-optimized torque allocation for a 370 kW all-wheel-drive electric truck under variable temperatures. The novel approach incorporates electric machine temperature dynamics into the modelling process, recognizing that the electric machine temperature varies with load and speed. A high-fidelity, multi-physical model of the permanent magnet synchronous machine is developed enabling analysis of electric, magnetic, mechanical, and thermal phenomena, including their cross-influence. The model dynamically updates electric machines’ characteristics and component loss rates as a function of temperature and integrates this information into a control strategy that adaptively allocates torque between axles. To the best of the authors’ knowledge, this temperature-adaptive torque control represents a novel contribution. Therefore, the novel strategy optimally distributed torque between axles based on the temperature-dependent loss characteristics of each motor to minimize overall energy consumption. The result is compared with two conventional techniques: (1) fixed torque ratio distribution, and (2) fixed-temperature optimal torque allocation using efficiency maps generated at −20℃ and + 50 ° C . For the Eskisehir cycle, the proposed method reduces power consumption by up to 2 % and 3 % , respectively, within operating temperature range of - 20 ° C to 180 ° C . Further analysis of a hypothetical cycle indicates that energy savings may increase to 3 % and 7 % , demonstrating the drive cycle’s decisive effect. This work advances the integration of thermal dynamics into vehicle level control, offering practical pathways to improve efficiency up to 7 % , in electric heavy duty vehicles.
Authors
- Mario Vukotić (ORCID: https://orcid.org/0000-0002-1421-1277)
- Damijan Miljavec (ORCID: https://orcid.org/0000-0001-8466-176X)
- Ahu Ece Hartavi
- Mohammad Ghazali
Institutions
- University of Ljubljana (SI)
- ASV (United Kingdom) (GB)
Publication Details
- Journal
- Applied Thermal Engineering
- Published
- 2025-05-17
- DOI
- https://doi.org/10.1016/j.applthermaleng.2025.126846
- Citations
- 3
- Primary Topic
- Electric and Hybrid Vehicle Technologies
- Type
- article
- Field-Weighted Citation Impact
- 2.05