Journals / Acta Materialia Turcica / 2017 / Cilt: 1 - Sayı: 1

Increasing Energy Efficiency of Electric Motors by Post-Integration Parameter Calibration

Pages
27–30
Publication Date
2017-12-28
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

At the end of the studies, a more effective system is obtained by checking the resistance and the inductance values.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, in order to optimize the energy efficiency of a brushless DC motor (BLDC), a post-integration parameter calibration scheme is proposed and tested.
📊
Key Findings & Data:The controller gains are calculated in the model using the motor parameters directly.
💡
Conclusion & Impact:At the end of the studies, a more effective system is obtained by checking the resistance and the inductance values.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:energy efficiency · electric motor · motor parameter calibration

Abstract

In this study, in order to optimize the energy efficiency of a brushless DC motor (BLDC), a post-integration parameter calibration scheme is proposed and tested. The controller gains are calculated in the model using the motor parameters directly. A self-calibration algorithm is implemented, the change in parameters is logged and the resulting efficiency change is calculated and presented. At the end of the studies, a more effective system is obtained by checking the resistance and the inductance values.

🔖

Cite This Article

Esen, Z. İ., Şahin, M., Çakıroğlu, S., Külünk, Z. (2017). Increasing Energy Efficiency of Electric Motors by Post-Integration Parameter Calibration. Acta Materialia Turcica, Cilt: 1 - Sayı: 1, 27–30. https://ajindex.com/articles/727661

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (3)

  1. P. Waide, C. U. Brunner, “Energy‐efficiency policy opportunities for electric motor‐driven systems”, IEA Energy Efficiency Series, (2011
  2. D. Wilson, “Teaching Your PI Controller To Behave”, Motor Drive & Control Blog,Texas Instruments, (2015
  3. W. Wu, “DC motor identification using speed step responses”, American Control Conference (ACC), 2010 4. AA Bature, M. Muhammad, A. M. Abdullahi, “Identification and Real Time Control of a DC Motor”, IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE) e-ISSN: 2278-1676,p-ISSN: 2320-3331, Volume 7, Issue 4, 2013 5. P. Huynh, H. Zhu, D. Aliprantis, “Parameter estimation for single-phase induction motors using test measurement data”, North American Power Symposium (NAPS), 2016 6. A. M. El-Sawy, Y. S. Mohamed and A. A. Zaki, “Stator Resistance and Speed Estimation for Induction Motor Drives As Influenced by Saturation”, The Online Journal on Electronics and Electrical Engineering (OJEEE) Vol. (3) – No. (2), 2011 7. P. Blaha, P. Vaclavek, “AC Induction Motor Stator Resistance Estimation Algorithm”, 7th WSEAS International Conference on Electric Power Systems, High Voltages, Electric Machines, 2007 8. C.M.F.S.Reza, S. Mekhilef, “Online Stator Resistance Estimation Using Artificial Neural Network for Direct Torque Controlled Induction Motor Drive”, 2013 IEEE 8th Conference on Industrial Electronics and Applications (ICIEA), 2013.