Frank Willems
To accelerate the transition to climate neutral mobility, the development of self-learning control systems for sustainable powertrains is crucial to guarantee minimal energy consumption and operational costs over lifetime and to minimize development time and costs.
Professorship chair
Self-learning powertrains (Faculty Mechanical Engineering, Control Systems Technology, Eindhoven University of Technology).
Research area
The majority of goods are transported by trucks and ships, which are propelled by heavy-duty powertrains. These powertrains are mainly powered by internal combustion engines. In the coming decades, internal combustion engines will remain the primary power source for these heavy applications. To support the transition to climate neutral mobility, future powertrains will become increasingly complex. This complexity arises from electrification and the introduction of waste heat recovery and highly efficient combustion concepts.
Control systems are the brain of the powertrain. These systems play an essential role in minimizing fuel consumption, in making vehicle performance robust for real-world driving conditions, and in enabling the use of a wide range of sustainable fuels, including green hydrogen. However, the industry is facing a turning point. Conventional control methods will no longer suffice as development time and costs reach unacceptable levels.
Development of self-learning powertrains is crucial to deal with the complexity and diversity of future ultra-clean and efficient vehicles and to minimize development time and costs. This requires integration of energy and emission management strategies at system level. My research concentrates on the development of self-learning control concepts, in which the energy efficiency of the total powertrain is optimized online by the application of smart sensors and route information.
Top publications
- Borth, M., Kupper, F., Mulder, L., & Willems, F. (2025). Risk-Averse Decision Support for Optimal Use of Electric Vehicles. IEEE, https://doi.org/10.1109/ITSC58415.2024.10920082
- Vlaswinkel, M. G., & Willems, F. (2023).Cylinder Pressure Feedback Control for Ideal Thermodynamic Cycle Tracking: Towards Self-learning Engines. IFAC-PapersOnLine, 56(2), 8260-8265.https://doi.org/10.1016/j.ifacol.2023.10.1011
- Garg, P., Silvas, E., & Willems, F. (2023).Systematic hyperparameter selection in Machine Learning-based engine control to minimize calibration effort. Control Engineering Practice,140, 105666. https://doi.org/10.1016/j.conengprac.2023.105666
Helmond - Automotive Campus
Automotive Campus 30
5708 JZ Helmond
The Netherlands
Postal address
P.O. Box 756
5700 AT Helmond
The Netherlands