A Simple Recursive Least Squares Approach for Off-line Parameter Identification of FOC Permanent Magnet Synchronous Machine Drive
| dc.authorscopusid | 58070564000 | |
| dc.authorscopusid | 58070564100 | |
| dc.authorscopusid | 55780618800 | |
| dc.contributor.author | Calik,R. | |
| dc.contributor.author | Simsek,R.O. | |
| dc.contributor.author | Kivanc,O.C. | |
| dc.date.accessioned | 2024-05-25T12:34:40Z | |
| dc.date.available | 2024-05-25T12:34:40Z | |
| dc.date.issued | 2022 | |
| dc.department | Okan University | en_US |
| dc.department-temp | Calik R., Power Electronics WAT Motor, RandD Department, Istanbul, Turkey; Simsek R.O., Power Electronics WAT Motor, RandD Department, Istanbul, Turkey; Kivanc O.C., Istanbul Okan University, Electrical and Electronics Engineering Department, Istanbul, Turkey | en_US |
| dc.description | Batman University and Batman Energy Coordination Center (EKOM) | en_US |
| dc.description.abstract | A simple and efficient parameter identification algorithm for a permanent magnet synchronous motor (PMSM) drive system is proposed using a recursive least square (RLS) algorithm without any additional sensor. Servo motor control system requires parameter identification due to aging, parameter changes, and mechanical components for driving the reliability and performance of PMSMs. Regarding industrial applications, model-based prediction algorithms are generally expected to be developed. The most important reason is that complex mathematical operations and advanced digital filters are unsuitable for low-cost processors. In this study, all motor parameters (stator resistance, stator inductance, flux linkage, viscous friction, and inertia) are identified using the RLS method as offline. The proposed parameter estimation method for PMSM has been implemented by using the RLS algorithm. Experimental results demonstrate the feasibility and effectiveness of the proposed method. © 2022 IEEE. | en_US |
| dc.identifier.citationcount | 1 | |
| dc.identifier.doi | 10.1109/GEC55014.2022.9986582 | |
| dc.identifier.endpage | 344 | en_US |
| dc.identifier.isbn | 978-166549751-0 | |
| dc.identifier.scopus | 2-s2.0-85146497243 | |
| dc.identifier.startpage | 340 | en_US |
| dc.identifier.uri | https://doi.org/10.1109/GEC55014.2022.9986582 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14517/2602 | |
| dc.language.iso | en | |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
| dc.relation.ispartof | IEEE Global Energy Conference, GEC 2022 -- 2022 IEEE Global Energy Conference, GEC 2022 -- 26 October 2022 through 29 October 2022 -- Batman -- 185674 | en_US |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.scopus.citedbyCount | 3 | |
| dc.subject | FOC | en_US |
| dc.subject | industrial servo drive systems | en_US |
| dc.subject | parameter identification | en_US |
| dc.subject | PMSM | en_US |
| dc.subject | RLS | en_US |
| dc.title | A Simple Recursive Least Squares Approach for Off-line Parameter Identification of FOC Permanent Magnet Synchronous Machine Drive | en_US |
| dc.type | Conference Object | en_US |