Model Predictive Current Control of Switched Reluctance Motor Drive: An Initial Study

• Type: Article in International Conference Proceedings Book
• Date: 2020

Authors

Pereira, M (Author) Other; Rui Esteves Araújo (Author) FEUP

Conference proceedings International

Title: Technological Innovation for Life Improvement - 11th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2020, Costa de Caparica, Portugal, July 1-3, 2020, Proceedings

Pages: 256-264

11th Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2020

1 July 2020 through 3 July 2020

Indexing

Scopus - 2 Citations

Other information

Authenticus ID: P-00S-337

DOI: 10.1007/978-3-030-45124-0_24

Abstract (EN): A considerable amount of research within the last few decades has been focusing on controllers for switched reluctance motor drives and how they affect the torque ripple. Despite all its potentials, there are still major concerns and obstacles to overcome concerning the dependency of the magnetic characteristic of the switched reluctance motor. This work targets these concerns by proposing an initial study of the fundamentals of a drive scheme using a finite set model predictive control for a switched reluctance motor through an asymmetric bridge converter. The implementation of this scheme is the main contribution of this paper. The method uses the dynamic model of the motor to estimate the future behavior of the current for each converter state. A cost function then evaluates which switching state minimizes the current error and applies it to the motor. Some simulation results illustrate the technique. Simulation results show the good performance of the method with fast and accurate transient response. © IFIP International Federation for Information Processing 2020.

Language: English

Type (Professor's evaluation): Scientific