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

Abstract

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. In addition, 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 article. The proposed method relies on the modeling of the EESM stator and rotor and utilizes the stator current measurements and parameter information that are already available in the current controller. Hence, this method is easy to implement and requires no additional sensors or parameter calibration work. The experimental results show that, by 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.