Research Article
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A Control of SynRM using MPPT Algorithm and Effects of Advance Angle on Motor Performance

Year 2020, Volume: 15 Issue: 2, 49 - 60, 24.09.2020

Abstract

Solar-powered irrigation systems are quite important in terms of renewable energy usage. These systems consist of solar panel, boost converter, battery, battery charge management system, motor drive, motor and pump. The installation costs of system increase and the system reliability reduces due to the amount of equipment. Nowadays, low-voltage Permanent Magnet Synchronous Motors (PMSMs) are used to eliminate drawbacks of the boost converter. However, PMSMs have high cost because of the magnets. Synchronous Reluctance Motors (SynRMs) having lower cost than PMSMs can be used in these applications. The proposed system can be operated by using only the solar-panel, SynRM and drive without other devices. Thus, the system cost can be significantly reduced. In addition, durability of the system can be increased due to not using battery and magnets causing problems such as maintenance and low lifespan. A SynRM pump motor which can operate with a lower voltage level generated by the photovoltaic (PV) panel was designed in this paper. This motor has high efficiency because of no-copper losses of the rotor. Effects of advance angle on designed motor performance were analyzed and suitable advance angle was selected for the motor. Additionally, the designed SynRM was controlled by the MPPT algorithm.

Supporting Institution

TUBİTAK

Project Number

116E116

Thanks

The authors would like to thank The Scientific and Technological Research Council of Turkey (TUBITAK) for financial support (Project No: 116E116)

References

  • Referans 1 Kostko JK. Polyphase reaction synchronous motors. J Am Inst Electr Eng 1923;4 2: 1162–1168.
  • Referans 2 Lagerquist R, Boldea I, Miller T.J.E. Sensorless-control of the synchronous reluctance motor. IEEE Trans Ind Appl 1994; 30: 673-682.
  • Referans 3 Xu L, Xu X, Lipo T a., Novotry DW. Vector Control of a Synchronous Reluctance Motor Including Saturation and Iron Loss. IEEE Trans Ind Appl 1991; 27: 977–985.
  • Referans 4 Aydogmus O. Design of a solar motor drive system fed by a direct-connected photovoltaic array. Adv Electr Comput Eng 2012; 12: 53–58.
  • Referans 5 Kumar R, Singh B. Solar photovoltaic array fed water pump driven by brushless DC motor using Landsman converter. IET Renew Power Gener 2016; 10: 474–484.
  • Referans 6 Vagati A. The synchronous reluctance solution: a new alternative in AC drives. Proc IECON’94 - 20th Annu Conf IEEE Ind Electron; 5-9 Sept. 1994; Blogna, Italy. pp. 1–13.
  • Referans 7 Piegari L, Rizzo R. Adaptive perturb and observe algorithm for photovoltaic maximum power point tracking. IET Renew Power Gener 2010; 4: 317-328.
  • Referans 8 Femia N, Petrone G, Spagnuolo G, Vitelli M. Optimizing sampling rate of P&O MPPT technique. PESC Rec. - IEEE Annu. Power Electron. Spec. Conf: 20-25 June 2004; Aachen, Germany. pp. 1945–1949.
  • Referans 9 Esram T, Chapman PL. Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques. IEEE Trans Energy Convers 2007; 22: 439–449.
  • Referans 10 Gao J, Wu X, Huang S, Zhang W, Xiao L. Torque ripple minimisation of permanent magnet synchronous motor using a new proportional resonant controller. IET Power Electron 2017; 10: 208–214.
  • Referans 11 Shukla S, Singh B. Solar powered sensorless induction motor drive with improved efficiency for water pumping. IET Power Electron 2018; 11: 416–426.
  • Referans 12 Hussein KH, Muta I, Hoshino T, Osakada M. Maximum photovoltaic power tracking: an algorithm for rapidly changing atmospheric conditions. Gener Transm Distrib IEE Proceedings- 1995; 142: 59–64.
  • Referans 13 Rahim NA, Che Soh A, Radzi MAM, Zainuri MAAM. Development of adaptive perturb and observe-fuzzy control maximum power point tracking for photovoltaic boost dc–dc converter. IET Renew Power Gener 2014; 8: 183–194.
  • Referans 14 Rizzo SA, Scelba G. ANN based MPPT method for rapidly variable shading conditions. Appl Energy 2015; 145: 124–132.
  • Referans 15 Elobaid LM, Abdelsalam AK, Zakzouk EE. Artificial neural network-based photovoltaic maximum power point tracking techniques: a survey. IET Renew Power Gener 2015; 9: 1043–1063.
  • Referans 16 Noguchi T, Togashi S, Nakamoto R. Short-current pulse-based maximum-power-point tracking method for multiple photovoltaic-and-converter module system. IEEE Trans Ind Electron 2002; 49: 217–223.
  • Referans 17 Staton DA, Miller TJE, Wood SE. Maximising the saliency ratio of the synchronous reluctance motor. IEE Proc B Electr Power Appl 1993; 140: 249-259.
  • Referans 18 Lipo TA. Synchronous reluctance machines-a viable alternative for ac drives? Electr Mach Power Syst 1991; 19: 659–671.
  • Referans 19 Kamper MJ, Van Der Merwe FS, Williamson S. Direct finite element design optimisation of the cageless reluctance synchronous machine. IEEE Trans Energy Convers 1996; 11: 547–553.
  • Referans 20 Taghavi S, Pillay P. A Sizing Methodology of the Synchronous Reluctance Motor for Traction Applications. 2014. Referans 21 Ferrari M, Bianchi N, Doria A, Fornasiero E. Design of Synchronous Reluctance Motor for Hybrid Electric Vehicles. IEEE Trans. Ind. Appl. 2015; 51: 3030-3040.
  • Referans 22 Truong PH, Flieller D, Nguyen NK, Mercklé J, Sturtzer G. Torque ripple minimization in non-sinusoidal synchronous reluctance motors based on artificial neural networks. Electr Power Syst Res 2016; 140: 37–45.
  • Referans 23 Moghaddam RR. Synchronous Reluctance Machine (SynRM) Design. Master Thesis, Royal Institute of Technology, 2007.
Year 2020, Volume: 15 Issue: 2, 49 - 60, 24.09.2020

Abstract

Project Number

116E116

References

  • Referans 1 Kostko JK. Polyphase reaction synchronous motors. J Am Inst Electr Eng 1923;4 2: 1162–1168.
  • Referans 2 Lagerquist R, Boldea I, Miller T.J.E. Sensorless-control of the synchronous reluctance motor. IEEE Trans Ind Appl 1994; 30: 673-682.
  • Referans 3 Xu L, Xu X, Lipo T a., Novotry DW. Vector Control of a Synchronous Reluctance Motor Including Saturation and Iron Loss. IEEE Trans Ind Appl 1991; 27: 977–985.
  • Referans 4 Aydogmus O. Design of a solar motor drive system fed by a direct-connected photovoltaic array. Adv Electr Comput Eng 2012; 12: 53–58.
  • Referans 5 Kumar R, Singh B. Solar photovoltaic array fed water pump driven by brushless DC motor using Landsman converter. IET Renew Power Gener 2016; 10: 474–484.
  • Referans 6 Vagati A. The synchronous reluctance solution: a new alternative in AC drives. Proc IECON’94 - 20th Annu Conf IEEE Ind Electron; 5-9 Sept. 1994; Blogna, Italy. pp. 1–13.
  • Referans 7 Piegari L, Rizzo R. Adaptive perturb and observe algorithm for photovoltaic maximum power point tracking. IET Renew Power Gener 2010; 4: 317-328.
  • Referans 8 Femia N, Petrone G, Spagnuolo G, Vitelli M. Optimizing sampling rate of P&O MPPT technique. PESC Rec. - IEEE Annu. Power Electron. Spec. Conf: 20-25 June 2004; Aachen, Germany. pp. 1945–1949.
  • Referans 9 Esram T, Chapman PL. Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques. IEEE Trans Energy Convers 2007; 22: 439–449.
  • Referans 10 Gao J, Wu X, Huang S, Zhang W, Xiao L. Torque ripple minimisation of permanent magnet synchronous motor using a new proportional resonant controller. IET Power Electron 2017; 10: 208–214.
  • Referans 11 Shukla S, Singh B. Solar powered sensorless induction motor drive with improved efficiency for water pumping. IET Power Electron 2018; 11: 416–426.
  • Referans 12 Hussein KH, Muta I, Hoshino T, Osakada M. Maximum photovoltaic power tracking: an algorithm for rapidly changing atmospheric conditions. Gener Transm Distrib IEE Proceedings- 1995; 142: 59–64.
  • Referans 13 Rahim NA, Che Soh A, Radzi MAM, Zainuri MAAM. Development of adaptive perturb and observe-fuzzy control maximum power point tracking for photovoltaic boost dc–dc converter. IET Renew Power Gener 2014; 8: 183–194.
  • Referans 14 Rizzo SA, Scelba G. ANN based MPPT method for rapidly variable shading conditions. Appl Energy 2015; 145: 124–132.
  • Referans 15 Elobaid LM, Abdelsalam AK, Zakzouk EE. Artificial neural network-based photovoltaic maximum power point tracking techniques: a survey. IET Renew Power Gener 2015; 9: 1043–1063.
  • Referans 16 Noguchi T, Togashi S, Nakamoto R. Short-current pulse-based maximum-power-point tracking method for multiple photovoltaic-and-converter module system. IEEE Trans Ind Electron 2002; 49: 217–223.
  • Referans 17 Staton DA, Miller TJE, Wood SE. Maximising the saliency ratio of the synchronous reluctance motor. IEE Proc B Electr Power Appl 1993; 140: 249-259.
  • Referans 18 Lipo TA. Synchronous reluctance machines-a viable alternative for ac drives? Electr Mach Power Syst 1991; 19: 659–671.
  • Referans 19 Kamper MJ, Van Der Merwe FS, Williamson S. Direct finite element design optimisation of the cageless reluctance synchronous machine. IEEE Trans Energy Convers 1996; 11: 547–553.
  • Referans 20 Taghavi S, Pillay P. A Sizing Methodology of the Synchronous Reluctance Motor for Traction Applications. 2014. Referans 21 Ferrari M, Bianchi N, Doria A, Fornasiero E. Design of Synchronous Reluctance Motor for Hybrid Electric Vehicles. IEEE Trans. Ind. Appl. 2015; 51: 3030-3040.
  • Referans 22 Truong PH, Flieller D, Nguyen NK, Mercklé J, Sturtzer G. Torque ripple minimization in non-sinusoidal synchronous reluctance motors based on artificial neural networks. Electr Power Syst Res 2016; 140: 37–45.
  • Referans 23 Moghaddam RR. Synchronous Reluctance Machine (SynRM) Design. Master Thesis, Royal Institute of Technology, 2007.
There are 22 citations in total.

Details

Primary Language English
Journal Section TJST
Authors

Güllü Boztaş 0000-0002-1720-1285

Ömür Aydoğmuş 0000-0001-8142-1146

Hanifi Güldemir 0000-0003-0491-8348

Project Number 116E116
Publication Date September 24, 2020
Submission Date March 28, 2020
Published in Issue Year 2020 Volume: 15 Issue: 2

Cite

APA Boztaş, G., Aydoğmuş, Ö., & Güldemir, H. (2020). A Control of SynRM using MPPT Algorithm and Effects of Advance Angle on Motor Performance. Turkish Journal of Science and Technology, 15(2), 49-60.
AMA Boztaş G, Aydoğmuş Ö, Güldemir H. A Control of SynRM using MPPT Algorithm and Effects of Advance Angle on Motor Performance. TJST. September 2020;15(2):49-60.
Chicago Boztaş, Güllü, Ömür Aydoğmuş, and Hanifi Güldemir. “A Control of SynRM Using MPPT Algorithm and Effects of Advance Angle on Motor Performance”. Turkish Journal of Science and Technology 15, no. 2 (September 2020): 49-60.
EndNote Boztaş G, Aydoğmuş Ö, Güldemir H (September 1, 2020) A Control of SynRM using MPPT Algorithm and Effects of Advance Angle on Motor Performance. Turkish Journal of Science and Technology 15 2 49–60.
IEEE G. Boztaş, Ö. Aydoğmuş, and H. Güldemir, “A Control of SynRM using MPPT Algorithm and Effects of Advance Angle on Motor Performance”, TJST, vol. 15, no. 2, pp. 49–60, 2020.
ISNAD Boztaş, Güllü et al. “A Control of SynRM Using MPPT Algorithm and Effects of Advance Angle on Motor Performance”. Turkish Journal of Science and Technology 15/2 (September 2020), 49-60.
JAMA Boztaş G, Aydoğmuş Ö, Güldemir H. A Control of SynRM using MPPT Algorithm and Effects of Advance Angle on Motor Performance. TJST. 2020;15:49–60.
MLA Boztaş, Güllü et al. “A Control of SynRM Using MPPT Algorithm and Effects of Advance Angle on Motor Performance”. Turkish Journal of Science and Technology, vol. 15, no. 2, 2020, pp. 49-60.
Vancouver Boztaş G, Aydoğmuş Ö, Güldemir H. A Control of SynRM using MPPT Algorithm and Effects of Advance Angle on Motor Performance. TJST. 2020;15(2):49-60.