Temperature-adaptive torque allocation for all wheel drive electric trucks

Ghazali, Mohammad (author), Vukotić, Mario (author), Miljavec, Damijan (author), Hartavi, Ahu Ece (author)

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℃. For the Eskisehir cycle, the proposed method reduces power consumption by up to 2% and 3%, respectively, within operating temperature range of −20℃ to 180℃. 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.

• Language: English
• Keywords: electric machine, thermal model, energy optimization, electrification, heavy duty trucks, torque allocation
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FE - Faculty of Electrical Engineering
• Publication status: Published
• Publication version: Version of Record
• Year: 2025
• Number of pages: 15 str.
• Numbering: Vol. 276, art.126846
• PID: 20.500.12556/RUL-173660
• UDC: 621.313/.314
• ISSN on article: 1873-5606
• DOI: 10.1016/j.applthermaleng.2025.126846
• COBISS.SI-ID: 236302339
• Publication date in RUL: 19.09.2025

Record is a part of a journal

• Title: Applied thermal engineering
• Publisher: Elsevier
• ISSN: 1873-5606
• COBISS.SI-ID: 23195397

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

• Language: Slovenian
• Keywords: električni stroj, termičn model, energijska optimizacija, elektrifikacija, težki tovornjaki, porazdeljevanje navora