Extended-Kalman-Filter Based Field Current Estimation for Brushless Electrically Excited Synchronous Machines Using Stator Current Measurements
Journal article, 2024

Electrically excited synchronous machines (EESMs) are becoming more prevalent in electric vehicles (EVs) due to their high power density and independence of rear-earth materials. Additionally, the use of brushless excitation systems can further improve the efficiency and reliability of EESMs. However, the brushless design also makes the field current not directly measurable. Therefore, a new Extended-Kalman-Filter (EKF) based field current estimation method is proposed in this paper. The proposed method relies on the modelling of the EESM stator and rotor, and utilizes the stator current measurements and parameter information which are already available in the current controller. Hence, this method is easy to implement and requires no additional sensors or parameter calibration work. Experimental results show that, through using the proposed method, the EESM field current can be accurately estimated in both steady states and transients. In addition, the estimation converges fast even with significant initial state errors.

electrically excited synchronous machines (EESMs)

field current estimation

Extended-Kalman-Filter (EKF)

Electric vehicles (EVs)

Author

Bowen Jiang

Chalmers, Electrical Engineering, Electric Power Engineering

Junfei Tang

Chalmers, Electrical Engineering, Electric Power Engineering

Yujing Liu

Chalmers, Electrical Engineering, Electric Power Engineering

IEEE Transactions on Transportation Electrification

2332-7782 (eISSN)

Vol. In Press

Subject Categories

Control Engineering

Other Electrical Engineering, Electronic Engineering, Information Engineering

DOI

10.1109/TTE.2024.3476161

More information

Latest update

11/6/2024