TY - GEN
T1 - Improved Two-Vector-Based Model Predictive Current Control with Online Parameter Identification for Doubly Salient Electromagnetic Machine
AU - Zhou, Xingwei
AU - Zhan, Minhui
AU - Guo, Yaowu
AU - Niu, Shuangxia
AU - Dai, Shangjian
AU - Zhang, Li
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023/12/14
Y1 - 2023/12/14
N2 - The traditional finite control set model predictive control (MPC) suffers from the problems of large current ripple and high system parameter dependence. To overcome these, an improved two-vector-based model predictive current control (TV-MPCC) with online parameters identification is proposed for doubly salient electromagnetic machine (DSEM). At first, the voltage vector combinations are localized and shortlisted based on the principle of differential-free beat current control, thus avoiding the complex computation of traditional traversal algorithms. Then, the impact of parameters mismatch is studied in depth, and the sensitivity of different parameters is obtained. Afterwards, an online identification based on MRAS is put forward to eliminate the influence of key parameters mismatch of self-inductance as well as the mutual inductance between armature and excitation windings. Finally, the validity and feasibility of the proposed strategies are verified by simulations under multiple operating conditions.
AB - The traditional finite control set model predictive control (MPC) suffers from the problems of large current ripple and high system parameter dependence. To overcome these, an improved two-vector-based model predictive current control (TV-MPCC) with online parameters identification is proposed for doubly salient electromagnetic machine (DSEM). At first, the voltage vector combinations are localized and shortlisted based on the principle of differential-free beat current control, thus avoiding the complex computation of traditional traversal algorithms. Then, the impact of parameters mismatch is studied in depth, and the sensitivity of different parameters is obtained. Afterwards, an online identification based on MRAS is put forward to eliminate the influence of key parameters mismatch of self-inductance as well as the mutual inductance between armature and excitation windings. Finally, the validity and feasibility of the proposed strategies are verified by simulations under multiple operating conditions.
KW - doubly salient electromagnetic machine (DSEM)
KW - model predictive control (MPC)
KW - online parameter identification
UR - http://www.scopus.com/inward/record.url?scp=85182314078&partnerID=8YFLogxK
U2 - 10.1109/ICEMS59686.2023.10344470
DO - 10.1109/ICEMS59686.2023.10344470
M3 - Conference article published in proceeding or book
AN - SCOPUS:85182314078
T3 - 2023 26th International Conference on Electrical Machines and Systems, ICEMS 2023
SP - 3048
EP - 3053
BT - 2023 26th International Conference on Electrical Machines and Systems, ICEMS 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 26th International Conference on Electrical Machines and Systems, ICEMS 2023
Y2 - 5 November 2023 through 8 November 2023
ER -