Secondments – SustainablePowerTrains

Chalmers secondment at McMaster University – Thermal modelling

Condition Monitoring and Reliability of Power-Electronic Systems

Abdelaali Fargi (National Engineering School of Monastir) – on secondment at Aalborg University to Contribute to the optimization parameters of DC-DC converters using Physics Informed Machine Learning Models in Electric Vehicles.

Physics-Informed Machine Learning for State of Health Estimation of Li-ion Batteries through the Federated Learning Paradigm

Machine Learning algorithms for RUL prediction

Exploring Structural Health Monitoring (SHM) of Composite Structures in EV Powertrains

Implementing Thermal Models within Pack level architecture

DFN parameter identification under with thermal controller using PyBaMM

Degradation-aware fast-charging control using feedback from pressure sensors

Visit and meeting to AAU Energy

Modeling SiC MOSFETs drift parameters for predictive maintenance of power converters

Ilya Kuangaliyev (Chalmers University of Technology) on a secondment at the Institute for Power Electronics and Electrical Drives, RWTH Aachen, to collaborate on Control and Machine Learning for Sustainable Battery Recycling

AI-Based Balancing Control for Electric Vehicle Battery Packs

Battery modelling for field data

Developing a life cycle assessment model for sodium-ion batteries

Advancing EV Battery Management with AI : A Research Stay at the University of Ottawa

Life Cycle Analysis and links to Digital Product Passport

Teaming Secondment at Chalmers University of Technology, Sweden

Adaptive Control Strategies for Efficient EV Traction Systems

Mark Blyth (University of Bristol) on secondment at CEA to develop battery thermal modelling techniques

Enhancing Predictive Maintenance with Semantic AI Frameworks in Electrified Automotive Systems

Youssof Fassi (CEA) on secondment at AAU to develop Physics-informed machine learning-based predictive maintenance techniques for power electronics

Vincent Heiries (CEA) on secondment at University of Ottawa to develop Deep Learning based solution for EV driver habits forecasting and prediction of EV battery required energy

Chadha Jenzeri ( National Engineering School of Monastir) – on secondment at AI4SEC to develop a predictive maintenance interface and algorithms on Coral Dev and Grafana

Alper Kanak (ERARGE, Ergünler R&D Co. Ltd, R&D Director) on secondment at AI4SEC OÖ (Estonia) to semantically model the Predictive Maintenance (PdM) in the electrified automotive domain

ACKOWLEDGEMENTS

Funded by the European Union under
Grant Agreement n° 101131278

© 2026 SustainablePowerTrains.