Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Electrical Engineering
Erschienen in: Electrical Engineering 1/2021

06.10.2020 | Original Paper

Pulse injection-based sensorless switched reluctance motor driver model with machine learning algorithms

verfasst von: Ferhat Daldaban, Mehmet Akif Buzpinar

Erschienen in: Electrical Engineering | Ausgabe 1/2021

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

In this study relationships of pulse injected idle phase currents are used to predict rotor position with tuned fine tree and ensemble bagged tree algorithm in MATLAB. Different classifier algorithms trained, tested, and the best accurate results are obtained via ensemble bagged tree classifier using idle phase currents. Three-phase 6/4 switched reluctance motor (SRM) with optical position sensors diagnosis pulses has been injected into idle phases and operated at constant load and speed. The measured idle phase currents were rearranged using the time series method and trained with supervised machine learning algorithms. These unprocessed idle phase currents reduce processing time and contribute to the real-time operation of the system. This study proves that SRM can be driven by predicting the active phase to be triggered by trained ensemble bagged tree and tuned fine tree machine learning algorithms from real-time measured idle phase current data.
Vorheriger Artikel Developed analytical expression for current harmonic distortion of the PV system’s inverter in relation to the solar irradiance and temperature
Nächster Artikel A novel regression method in forecasting short-term grid electricity load in buildings that were connected to the smart grid

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Literatur
1.
Krishnan R (2001) Switched reluctance motor drives: modeling, simulation, analysis, design, and applications. CRC Press, London
2.
Miller TJE (2001) Electronic control of switched reluctance machines. Newnes, Australia
3.
Fard G (2009) Sensorless speed control of switched reluctance motor drive using the binary observer with online flux-linkage estimation. Iran J Electr Electron Eng 5(2):143–150MathSciNet
4.
Echenique E, Dixon J, Cárdenas R, Peña R (2009) Sensorless control for a switched reluctance wind generator, based on current slopes and neural networks. IEEE Trans Ind Electron 56(3):817–825CrossRef
5.
Fahimi B, Emadi A, Sepe RB (2005) Four-quadrant position sensorless control in SRM drives over the entire speed range. IEEE Trans Power Electron 20(1):154–163CrossRef
6.
Bateman CJ, Mecrow BC, Clothier AC, Acarnley PP, Tuftnell ND (2010) Sensorless operation of an ultra-high-speed witched reluctance machine. IEEE Trans Ind Appl 46(6):2329–2337CrossRef
7.
Khalil A et al (2007) Four-quadrant pulse injection and sliding-mode-observer-based sensorless operation of a switched reluctance machine over entire speed range including zero speed. IEEE Trans Ind Appl 43(3):714–723CrossRef
8.
Pasquesoone G, Mikail R, Husain I (2011) Position estimation at starting and lower speed in three-phase switched reluctance machines using pulse injection and two thresholds. IEEE Trans Ind Appl 47(4):1724–1731CrossRef
9.
Hu KW, Chen YY, Liaw CM (2015) A reversible position sensorless controlled switched-reluctance motor drive with adaptive and intuitive commutation tunings. IEEE Trans Power Electron 30(7):3781–3793CrossRef
10.
Ofori E, Husain T, Sozer Y, Husain I (2015) A pulse-injection-based sensorless position estimation method for a switched reluctance machine over a wide speed range. IEEE Trans Ind Appl 51(5):3867–3876CrossRef
11.
Paramasivam S, Vijayan S, Vasudevan M, Arumugam R, Krishnan R (2007) Real-time verification of AI based rotor position estimation techniques for a 6/4 pole switched reluctance motor drive. IEEE Trans Magn 43(7):3209–3222CrossRef
12.
Gan C, Wu J, Yang S, Hu Y (2015) Phase current reconstruction of switched reluctance motors from DC-link current under double high-frequency pulses injection. IEEE Trans Ind Electron 62(5):3265–3276CrossRef
13.
Hossain S, Husain I, Klode H, Omekanda A, Gopalakrishan S (2002) Four quadrant and zero speed sensorless control of a switched reluctance motor. In: 37th IAS annual meeting conference record of the 2002 IEEE industry applications conference (Cat. No. 02CH37344), vol 3, pp 1641–1646
14.
Khalil A et al (2005) A hybrid sensorless SRM drive with eight- and six-switch converter topologies. IEEE Trans Ind Appl 41(6):1647–1655CrossRef
15.
Chen KH, Sun YK, Li TB (2016) Sensorless control of switched reluctance motor. Dianji yu Kongzhi Xuebao/Electric Mach Control 20(3):85–89
16.
Gao H, Salmasi FR, Ehsani M (2004) Inductance model-based sensorless control of the switched reluctance motor drive at low speed. IEEE Trans Power Electron 19(6):1568–1573CrossRef
17.
Krishnamurthy M, Edrington CS, Fahimi B (2004) Prediction of rotor position at standstill and flying shaft conditions in switched reluctance machines. In: Nineteenth annual IEEE applied power electronics conference and exposition, 2004. APEC’04, vol 1, pp 537–544. IEEE
18.
Cai J, Deng Z (2012) Sensorless control of switched reluctance motor based on dynamic thresholds of phase inductance. Electr Power Compon Syst 40(8):915–934CrossRef
19.
Chang YT, Cheng KWE, Ho SL (2015) Type-V exponential regression for online sensorless position estimation of switched reluctance motor. IEEE/ASME Trans Mechatron 20(3):1351–1359CrossRef
20.
Cai Jun, Deng Zhiquan (2011) Sensorless control of switched reluctance motor based on phase inductance vectors. IEEE Trans Power Electron 27(7):3410–3423
21.
Thompson KR, Acarnley PP, French C (2000) Rotor position estimation in a switched reluctance drive using recursive least squares. IEEE Trans Ind Electron 47(2):368–379CrossRef
22.
Ha K, Kim RY, Ramu R (2011) Position estimation in switched reluctance motor drives using the first switching harmonics through fourier series. IEEE Trans Ind Electron 58(12):5352–5360CrossRef
23.
Zhang X, Li M, Zong XZhu, Cheng D (2017) Learning k for kNN classification. ACM Trans Intell Syst Technol 8(3):1–19
24.
Cai J, Deng Z (2015) Initial rotor position estimation and sensorless control of SRM based on coordinate transformation. IEEE Trans Instrum Meas 64(4):1004–1018CrossRef
25.
Kozak J (2019) Evolutionary computing techniques in data mining. In: Studies in computational intelligence. Springer, Berlin, vol 781, pp 29–44
26.
Bontempi G, Ben Taieb S, Le Borgne YA (2013) Machine learning strategies for time series forecasting. In: Lecture notes in business information processing, LNBIP, vol 138, pp 62–77
27.
Al-Bahadly IH (2008) Examination of a sensorless rotor-position-measurement method for switched reluctance drive. IEEE Trans Ind Electron 55(1):288–295CrossRef
Metadaten
Titel
Pulse injection-based sensorless switched reluctance motor driver model with machine learning algorithms
verfasst von
Ferhat Daldaban
Mehmet Akif Buzpinar
Publikationsdatum
06.10.2020
Verlag
Springer Berlin Heidelberg
Erschienen in
Electrical Engineering / Ausgabe 1/2021
Print ISSN: 0948-7921
Elektronische ISSN: 1432-0487
DOI
https://doi.org/10.1007/s00202-020-01111-6

Weitere Artikel der Ausgabe 1/2021

Electrical Engineering 1/2021 Zur Ausgabe

Original Paper

Monte Carlo simulation of electric vehicle loads respect to return home from work and impacts to the low voltage side of distribution network

Original Paper

A modified carrier-based PWM technique for minimization of leakage current in transformer less single-phase grid-tied PV system

Original Paper

Fault tolerant-based virtual actuator design for wide-area damping control in power system

Original Paper

Enhancing power system loadability and optimal load shedding based on TCSC allocation using improved moth flame optimization algorithm

Original Paper

Design, analysis, and testing of I-type electromagnetic actuator used in single-coil active magnetic bearing

Original Paper

An efficient model predictive control based on Lyapunov function for doubly fed induction generator fed by a T-type inverter

Neuer Inhalt

    Bildnachweise