Parameter identification of PMSM using EKF with temperature variation tracking in automotive applications

Rachid Kerid, Hicham Bourouina, Réda Yahiaoui


Permanent magnet synchronous machine is widely used for electric vehicles traction because of its high power density and its efficiency on a large flux weakening range. This paper focuses in particular on the estimation of PMSM parameters using EKF, we present a study assessing the temperature variations impact on the behavior of PMSM motor, and therefore we propose to estimate the temperature-dependent parameters. The main contribution in this work is an effective method for estimating parameters or their temperature variation, makes it possible to study and to avoid performance degradation by tracking and adapting the parameters in torque observer in order to find the same performance at any temperature and can be also used for thermal monitoring, which allows for better availability of motor, without causing damage, however, the knowledge of degradation mechanisms also gives insight for the design of this machine. Nowadays, there are essentially maps of reference currents according to the torque and speed that are used by car manufacturers and no account is then given of the parameter variations. The effectiveness of the proposed estimation method verified by both simulation and experiment.


Permanent Magnet Synchronous Machine (PMSM), Modeling, Identification, Extended Kalman Filter (EKF), Torque control, Temperature variation.

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Copyright (c) 2018 Rachid Kerid, Hicham Bourouina

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ISSN: 2303-4521

Digital Object Identifier DOI: 10.21533/pen

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License