Efficient Maximum Torque Per Ampere (MTPA) Control of Interior PMSM Using Sparse Bayesian Based Offline Data-Driven Model With Online Magnet Temperature Compensation-Reference-Cited by-同舟云学术

Efficient Maximum Torque Per Ampere (MTPA) Control of Interior PMSM Using Sparse Bayesian Based Offline Data-Driven Model With Online Magnet Temperature Compensation

Published:2023-04 Issue:4 Volume:38 Page:5192-5203
ISSN:0885-8993
Container-title:IEEE Transactions on Power Electronics
language:
Short-container-title:IEEE Trans. Power Electron.

Author:

Huang Kaide¹^ORCID,Peng Weiwen²^ORCID,Lai Chunyan³^ORCID,Feng Guodong²^ORCID

Affiliation:

1. School of Mathematics and Big Data, Foshan University, Foshan, China

2. School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, China

3. Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, Canada

Funder

National Natural Science Foundation of China

Basic and Applied Basic Research Foundation of Guangdong Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/63/10046180/09991887.pdf?arnumber=9991887

Reference36 articles.

1. Adaptive Maximum Torque per Ampere Control of Synchronous Reluctance Motors by Radial Basis Function Networks

2. Alternative to Extended Block Sparse Bayesian Learning and Its Relation to Pattern-Coupled Sparse Bayesian Learning

3. Maximum Efficiency Per Ampere Control of Permanent-Magnet Synchronous Machines

4. Extension of SBL Algorithms for the Recovery of Block Sparse Signals With Intra-Block Correlation

5. Improved Maximum-Torque-Per-Ampere Algorithm Accounting for Core Saturation, Cross-Coupling Effect, and Temperature for a PMSM Intended for Vehicular Applications

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