Recruitment

Post-Doc Proposal, Ampère/Renault-Centrale Nantes chair, 2026

Hybrid Thermal Estimation (Physics + AI) for Electric Machines and Powertrains of Electric Vehicles

Context and objectives:

The transition to sustainable mobility places electric vehicles (EVs) at the heart of industrial strategies. The performance, reliability, and durability of the electric powertrain (EPU), including the electric motor, converters, battery, and auxiliary components, depend heavily on their thermal behavior.

Temperature drifts significantly influence the vehicle's efficiency, range, lifespan, and safety. Furthermore, the prioritization of thermal processes (heating, battery or motor cooling, etc.) can significantly impact the overall efficiency of the EV.

In this context, the work conducted within the Renault–Centrale Nantes Chair (projects E7A, 6AK, HV95, INW) has demonstrated the value of hybrid Physics + AI approaches for online estimation of stator, rotor, and permanent magnet temperatures. These estimations must be robust, fast, inexpensive, and suitable for embedded deployment.

The proposed postdoctoral position aims to optimize an existing hybrid strategy, integrating it into a comprehensive approach to thermal estimation and monitoring of the entire powertrain, including motors, power modules, and battery. The ultimate goal is to improve observer accuracy, reduce computational complexity (CPU), and eliminate the use of sensors (NTC) while maintaining a very high level of reliability.

Required skills:

• Control/Estimation with a solid foundation in stability and robustness testing
• Machines, converters
• Knowledge of AI
• Design/Analysis of electrical machines
• Control of power converters
• Signal processing
• Matlab/Simulink, rapid prototyping

Candidate Profile:

• PhD in Automation or/and Electrical Engineering.
• Motivation for work combining physical modeling, AI, and real-time implementation.
• Excellent communication skills (good level of English).

Contacts:

Prof. Malek GHANES
Chairholder – Ampère/Renault–Centrale Nantes,
Ecole Centrale Nantes (CN), LS2N, CNRS UMR 6004, Nantes, France
Phone: +33 2 40 37 69 13 — Email: Malek.Ghanes@ec-nantes.fr

Salary: Based on experience. Funded by the Ampère/Renault–CN Chair.
Duration: 12 months (renewable once). Starting in March 2026.

Application Process:

Please send your application via the link: https://jobs.ec-nantes.fr/o/post-doctorat-physique-ia-estimation-thermique-des-systemes-de-traction-electrique-hf-ref-1069

References:

• [1] Previati, G., Mastinu, G., & Gobbi, M. (2022). Thermal Management of Electrified Vehicles—A Review. Energies, 15(4), 1326. https://doi.org/10.3390/en15041326.
• [2] Wang, X., Li, B., Gerada, D., Huang, K., Stone, I., Worrall, S., & Yan, Y. (2022). A critical review on thermal management technologies for motors in electric cars. Applied thermal engineering, 201, 117758.
• [3] Schaut, S., Arnold, E., & Sawodny, O. (2021). Predictive thermal management for an electric vehicle powertrain. IEEE Transactions on Intelligent Vehicles, 8(2), 1957-1970.
• [4] Joshi, H., Burkhardt, Y., Seilmeier, M., & Hofmann, W. (2020, August). Error compensation in initial temperature estimation of electric motors using a kalman filter. In 2020 International Conference on Electrical Machines (ICEM) (Vol. 1, pp. 840-846). IEEE.
• [5] Erazo, D. E. G., Wallscheid, O., & Böcker, J. (2019). Improved fusion of permanent magnet temperature estimation techniques for synchronous motors using a Kalman filter. IEEE Transactions on Industrial Electronics, 67(3), 1708-1717.
• [6] D. Reigosa, D. Fernández, M. Martínez, J. M. Guerrero, A. B. Diez and F. Briz, (2019). Magnet Temperature Estimation in Permanent Magnet Synchronous Machines Using the High Frequency Inductance. In IEEE Transactions on Industry Applications, vol. 55, no. 3, pp. 2750-2757, doi: 10.1109/

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