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

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.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Transportation Electrification
Published
2024-10-08
DOI
https://doi.org/10.1109/tte.2024.3476161
Citations
7
Primary Topic
Electric Motor Design and Analysis
Type
article
Field-Weighted Citation Impact
1.46
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Yujing Liu, Junfei Tang, Bowen Jiang
7 citations
IEEE Transactions on Transportation Electrification
Electric Motor Design and Analysis
1.46
article

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

Yujing Liu, Junfei Tang, Bowen Jiang
article en
7 citations

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.

IEEE Transactions on Transportation ElectrificationVol. 11(1)
Chalmers University of Technology (SE)
Affordable and clean energy
Openalex Percentile: Top 17%
Electric Motor Design and Analysis
1.46
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.