Online incremental inductance identification for reluctance synchronous motors

Matteo Berto; Luigi Alberti; Floran Martin; Marko Hinkkanen

doi:10.1109/IECON48115.2021.9589537

Online incremental inductance identification for reluctance synchronous motors

Matteo Berto^*, Luigi Alberti, Floran Martin, Marko Hinkkanen

^*Tämän työn vastaava kirjoittaja

University of Padova

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussa › Conference article in proceedings › Scientific › vertaisarvioitu

2 Sitaatiot (Scopus)

252 Lataukset (Pure)

Abstrakti

The paper deals with the online incremental inductances estimation of a synchronous motor at low speeds using a high-frequency voltage injection. The control scheme is analogous to that used in position estimation algorithms, with the difference that the current control and the rotating voltage injection operate on the real dq axes. Thus a position sensor is required to apply this method. The corresponding current response is measured, filtered, and processed with an ellipse fitting technique. The estimated ellipse coefficients are then used to retrieve the incremental inductances online without the need of any post processing. A novel formulation to express the estimation error valid for other conventional signal injection techniques is presented. The method has been validated experimentally on a reluctance synchronous motor at locked rotor and during load and speed transients.

Alkuperäiskieli	Englanti
Otsikko	IECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society
Kustantaja	IEEE
Sivumäärä	6
ISBN (elektroninen)	978-1-6654-3554-3
ISBN (painettu)	978-1-6654-0256-9
DOI - pysyväislinkit	https://doi.org/10.1109/IECON48115.2021.9589537
Tila	Julkaistu - 13 marrask. 2021
OKM-julkaisutyyppi	A4 Artikkeli konferenssijulkaisussa
Tapahtuma	Annual Conference of the IEEE Industrial Electronics Society - Virtual, online, Toronto, Kanada Kesto: 13 lokak. 2021 → 16 lokak. 2021 Konferenssinumero: 47 https://ieeeiecon.org/

Julkaisusarja

Nimi	Proceedings of the Annual Conference of the IEEE Industrial Electronics Society
ISSN (elektroninen)	2577-1647

Conference

Conference	Annual Conference of the IEEE Industrial Electronics Society
Lyhennettä	IECON
Maa/Alue	Kanada
Kaupunki	Toronto
Ajanjakso	13/10/2021 → 16/10/2021
www-osoite	https://ieeeiecon.org/

Pääsy asiakirjaan

10.1109/IECON48115.2021.9589537

ELEC_Berto_etal_Online_Incremental_Inductance_Identification_IEEE_IECON_2021Accepted author manuscript, 1,78 MB

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Linkki julkaisuun Scopuksessa

Matteo Berto
Hinkkanen, M. (Host)
1 lokak. 2020 → 31 tammik. 2021
Aktiviteetti: Isännöity akateeminen vierailu Aalto-yliopistossa

Siteeraa tätä

@inproceedings{fc08eb5d163745808a5fce0fe8823b43,

title = "Online incremental inductance identification for reluctance synchronous motors",

abstract = "The paper deals with the online incremental inductances estimation of a synchronous motor at low speeds using a high-frequency voltage injection. The control scheme is analogous to that used in position estimation algorithms, with the difference that the current control and the rotating voltage injection operate on the real dq axes. Thus a position sensor is required to apply this method. The corresponding current response is measured, filtered, and processed with an ellipse fitting technique. The estimated ellipse coefficients are then used to retrieve the incremental inductances online without the need of any post processing. A novel formulation to express the estimation error valid for other conventional signal injection techniques is presented. The method has been validated experimentally on a reluctance synchronous motor at locked rotor and during load and speed transients.",

author = "Matteo Berto and Luigi Alberti and Floran Martin and Marko Hinkkanen",

year = "2021",

month = nov,

day = "13",

doi = "10.1109/IECON48115.2021.9589537",

language = "English",

isbn = "978-1-6654-0256-9",

series = "Proceedings of the Annual Conference of the IEEE Industrial Electronics Society",

publisher = "IEEE",

booktitle = "IECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society",

address = "United States",

note = "Annual Conference of the IEEE Industrial Electronics Society, IECON ; Conference date: 13-10-2021 Through 16-10-2021",

url = "https://ieeeiecon.org/",

}

Berto, M, Alberti, L, Martin, F & Hinkkanen, M 2021, Online incremental inductance identification for reluctance synchronous motors. julkaisussa IECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society. Proceedings of the Annual Conference of the IEEE Industrial Electronics Society, IEEE, Annual Conference of the IEEE Industrial Electronics Society, Toronto, Ontario, Kanada, 13/10/2021. https://doi.org/10.1109/IECON48115.2021.9589537

Online incremental inductance identification for reluctance synchronous motors. / Berto, Matteo; Alberti, Luigi; Martin, Floran et al.
IECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2021. (Proceedings of the Annual Conference of the IEEE Industrial Electronics Society).

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussa › Conference article in proceedings › Scientific › vertaisarvioitu

TY - GEN

T1 - Online incremental inductance identification for reluctance synchronous motors

AU - Berto, Matteo

AU - Alberti, Luigi

AU - Martin, Floran

AU - Hinkkanen, Marko

N1 - Conference code: 47

PY - 2021/11/13

Y1 - 2021/11/13

N2 - The paper deals with the online incremental inductances estimation of a synchronous motor at low speeds using a high-frequency voltage injection. The control scheme is analogous to that used in position estimation algorithms, with the difference that the current control and the rotating voltage injection operate on the real dq axes. Thus a position sensor is required to apply this method. The corresponding current response is measured, filtered, and processed with an ellipse fitting technique. The estimated ellipse coefficients are then used to retrieve the incremental inductances online without the need of any post processing. A novel formulation to express the estimation error valid for other conventional signal injection techniques is presented. The method has been validated experimentally on a reluctance synchronous motor at locked rotor and during load and speed transients.

AB - The paper deals with the online incremental inductances estimation of a synchronous motor at low speeds using a high-frequency voltage injection. The control scheme is analogous to that used in position estimation algorithms, with the difference that the current control and the rotating voltage injection operate on the real dq axes. Thus a position sensor is required to apply this method. The corresponding current response is measured, filtered, and processed with an ellipse fitting technique. The estimated ellipse coefficients are then used to retrieve the incremental inductances online without the need of any post processing. A novel formulation to express the estimation error valid for other conventional signal injection techniques is presented. The method has been validated experimentally on a reluctance synchronous motor at locked rotor and during load and speed transients.

UR - http://www.scopus.com/inward/record.url?scp=85119484251&partnerID=8YFLogxK

U2 - 10.1109/IECON48115.2021.9589537

DO - 10.1109/IECON48115.2021.9589537

M3 - Conference article in proceedings

SN - 978-1-6654-0256-9

T3 - Proceedings of the Annual Conference of the IEEE Industrial Electronics Society

BT - IECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society

PB - IEEE

T2 - Annual Conference of the IEEE Industrial Electronics Society

Y2 - 13 October 2021 through 16 October 2021

ER -

Online incremental inductance identification for reluctance synchronous motors

Abstrakti

Julkaisusarja

Conference

Pääsy asiakirjaan

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Sormenjälki

Aktiviteetit

Matteo Berto

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