TY - GEN
T1 - A Low-Computational-Complexity Modulated Model Predictive for Starting Control of HighPower PM Starter-Generator
AU - Deng, Hongjing
AU - Jia, Shaofeng
AU - Xia, Yonghong
AU - Liang, Deliang
AU - Huang, Zhen
N1 - Publisher Copyright:
© 2025 Korean Institute of Electrical Engineers Electrical Machinery and Energy Conversion Systems Society.
PY - 2025
Y1 - 2025
N2 - This paper proposes a dual-vector model predictive control (MPC) strategy with significantly low computational complexity. This paper describes the structure of the permanent magnet starter-generator system and the requirements for its starting mode. The MPC was introduced due to its compatibility with the starting mode. The principle of conventional MPC introduced. Based on that, A low-computational-complexity MPC is proposed. The proposed method achieved through optimized voltage vector traversal logic and streamlined duty cycle calculation methods. Simulation studies conducted in MATLAB/Simulink demonstrate that the proposed low-complexity MPC outperforms conventional MPC in both dynamic response and steady-state performance, exhibiting faster transient response and lower current total harmonic distortion (THD).
AB - This paper proposes a dual-vector model predictive control (MPC) strategy with significantly low computational complexity. This paper describes the structure of the permanent magnet starter-generator system and the requirements for its starting mode. The MPC was introduced due to its compatibility with the starting mode. The principle of conventional MPC introduced. Based on that, A low-computational-complexity MPC is proposed. The proposed method achieved through optimized voltage vector traversal logic and streamlined duty cycle calculation methods. Simulation studies conducted in MATLAB/Simulink demonstrate that the proposed low-complexity MPC outperforms conventional MPC in both dynamic response and steady-state performance, exhibiting faster transient response and lower current total harmonic distortion (THD).
KW - low-computational-complexity
KW - model predictive control
KW - PM starter-generator
UR - https://www.scopus.com/pages/publications/105032903847
U2 - 10.23919/ICEMS66262.2025.11317313
DO - 10.23919/ICEMS66262.2025.11317313
M3 - 会议稿件
AN - SCOPUS:105032903847
T3 - ICEMS 2025 - 28th International Conference on Electrical Machines and Systems
SP - 2039
EP - 2044
BT - ICEMS 2025 - 28th International Conference on Electrical Machines and Systems
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 28th International Conference on Electrical Machines and Systems, ICEMS 2025
Y2 - 16 November 2025 through 19 November 2025
ER -