Improved Flow Rate and Pressure ANN Estimators for a Centrifugal Fan with Induction Motor Drive
Year 2024,
Volume: 8 Issue: 3, 130 - 142, 30.09.2024
Cebrail Turkeri
,
Oleh Kiselychnyk
Abstract
Energy saving control algorithms of centrifugal fans/pumps are based on the use of the frequency-controlled induction motor drives and pressure or flow rate sensors, the costs of which are comparable to the cost of the fans/pumps for low-power applications. The paper develops a new and simple estimation approach of the pressure and flow rate, utilising the measured Root Mean Square (RMS) value of the stator current, estimated motor’s input active power, reference stator voltage frequency and feed-forward backpropagation artificial neural network. The error percentage for both flow rate and pressure in experimental and estimated data is within the range of ±5%, which conforms to the ISO 13348 standard. A test rig for the rapid control prototyping of the fan is designed, and necessary design and test procedures are developed. The estimation approach is verified experimentally and demonstrates better estimation accuracy compared to the existing and possible similar simple approaches. The developed algorithm can be easily embedded into the industrial variable frequency drives without any hardware changes.
Supporting Institution
The ministry of National Education of Turkish Government
References
- [1] de Almeida, AT, Fonseca, P, Falkner, H, Bertoldi, P. Market transformation of energy-efficient motor technologies in the EU. Energy Policy 2003; 31: 563-575. DOI: 10.1016/S0301-4215(02)00100-3
- [2] Abdelaziz, EA, Saidur, R, Mekhilef, S. A review on energy saving strategies in industrial sector. Renewable and Sustainable Energy Reviews 2011; 15: 150-168. DOI: 10.1016/j.rser.2010.09.003
- [3] Waide, P, Brunner, CU. Energy-efficiency policy opportunities for electric motor-driven systems. International Energy Agency 2011; na: 132. DOI: 10.1787/5kgg52gb9gjd-en
- [4] Almounajjed, A, Sahoo, AK, Kumar, MK, Assaf, T. Fault diagnosis and investigation techniques for induction motor. International Journal of Ambient Energy 2022; 43: 6341–6361. DOI: 10.1080/01430750.2021.2016483
- [5] Binder A. Potentials for energy saving with modern drive technology-a survey. In: SPEEDAM 2008 Proceedings of 19th International Symposium on Power Electronics, Electrical Drives, Automation and Motion, June 2008: Ischio, Italy: pp. 90-95.
- [6] Ferreira, FJTE, Fong, JAC, de Almeida, AT. Ecoanalysis of variable-speed drives for flow regulation in pumping systems. IEEE Transactions on Industrial Electronics 2011; 58: 2117-2125. DOI: 10.1109/TIE.2010.2057232
- [7] Kiselychnyk, O, Bodson, M, Werner, H. Interactive energy saving control of water supply pump based on pressure measurement. Transactions of Kremenchuk State Polytehnic University 2009; 56: 166-171 <https://ela.kpi.ua/handle/123456789/38238>
- [8] Kiselychnyk O, Bodson M, Werner H. Overview of energy efficient control solutions for water supply systems. In: KSPU 2009 Transactions of Kremenchuk State Polytechnic University 2009; Kremenchuk, Ukraine: pp. 40–45.
- [9] de Almeida, AT, Ferreira, FJTE, Both, D. Technical and economical considerations in the application of variable-speed drives with electric motor systems. IEEE Transactions on Industry Applications 2005; 41: 188-199. DOI: 10.1109/TIA.2004.841022
- [10] Making Sense of Sensorless - Empowering Pumps and Equipment.pdf [Internet]. [cited 2023 Oct. 23]. Available from: https://empoweringpumps.com/making-sense-sensorless.
- [11] Kiselychnyk, O, Bodson, M. Nonsensor control of centrifugal water pump with asynchronous electric-drive motor based on extended Kalman filter. Russian Electrical Engineering 2011; 82: 69-75. DOI: 10.3103/S1068371211020088
- [12] Wu, Q, Shen, Q, Wang, X, Yang, Y. Estimation of centrifugal pump operational state with dual neural network architecture-based model. Neurocomputing 2016; 216: 102–108. DOI: 10.1016/j.neucom.2016.07.035
- [13] Ahonen, T, Tamminen, J, Ahola, J, Viholainen, J, Aranto, N, Kestilä, J. Estimation of pump operational state with model-based methods. Energy Conversion and Management 2010; 51: 1319-1325. DOI: 10.1016/j.enconman.2010.01.009
- [14] Tamminen J, Ahonen T, Ahola J, Kestilä J. Sensorless flow rate estimation in frequency-converter-driven fans. In: EPE 2011 Proceedings of the 2011-14th European Conference on Power Electronics and Applications: Birmingham, United Kingdom: pp. 1-10.
- [15] Pechenik, M, Kiselychnyk, O, Buryan, S, Petukhova, D. Sensorless control of water supply pump based on neural network estimation. Electrotechnic and Computer Systems 2011; 3: 462-466 <https://eltecs.op.edu.ua/index.php/journal/article/view/790
- [16] Bose, BK. Expert system, fuzzy logic, and neural network applications in power electronics and motion control. In Proceedings of the IEEE 1994; 82: 1303-1323. DOI: 10.1109/5.301690
- [17] Lee, HY, Lee, JL, Kwon, SO, Lee, SW. Performance estimation of induction motor using artificial neural network. In: IWSSIP 2018 25th International Conference on Systems, Signals and Image Processing 2018; Ohrid, North Macedonia: pp. 1-3.
- [18] Ebrahim, OS, Badr, MA, Elgendy, AS, Jain, PK. ANN-based optimal energy control of induction motor drive in pumping applications. IEEE Transactions on Energy Conversion 2010; 25: 652-660. DOI: 10.1109/TEC.2010.2041352
- [19] Wlas, M, Krzeminski, A, Guzinski, J, Abu-Rub, H, Toliyat, HA. Artificial-neural-network-based sensorless nonlinear control of induction motors. IEEE Transactions on Energy Conversion 2005; 20: 520-528. DOI: 10.1109/TEC.2005.847984
- [20] Tamminen, J, Viholainen, J, Ahonen, T, Ahola, J, Hammo, S, Vakkilainen, E. Comparison of model-based flow rate estimation methods in frequency-converter-driven pumps and fans. Energy Efficiency 2014; 7: 493–505. DOI: 10.1007/s12053-013-9234-6
- [21] Altivar Machine ATV320 Variable Speed Drives for Asynchronous and Synchronous Motors Installation Manual.pdf [Internet]. [cited 2023 Oct. 22]. Available from: https://download.schneider-electric.com.
- [22] ACS550 User’s Manual ACS550-01 Drives (0.75…160 kW) ACS550-U1 Drives (1…200 hp).pdf [Internet]. [cited 2023 Oct 22]. Available from: https://library.e.abb.com.
- [23] Barbarelli, S, Amelio, M, Florio, G. Predictive model estimating the performances of centrifugal pumps used as turbines. Energy Jul. 2016; 107: 103–121. DOI: 10.1016/J.energy.2016.03.122.
- [24] Ahonen, T, Kortelainen, JT, Tamminen, JK, Ahola, J. Centrifugal pump operation monitoring with motor phase current measurement. International Journal of Electrical Power Energy Systems 2012; 42: 188-195. DOI: 10.1016/j.ijepes.2012.04.013.
Year 2024,
Volume: 8 Issue: 3, 130 - 142, 30.09.2024
Cebrail Turkeri
,
Oleh Kiselychnyk
References
- [1] de Almeida, AT, Fonseca, P, Falkner, H, Bertoldi, P. Market transformation of energy-efficient motor technologies in the EU. Energy Policy 2003; 31: 563-575. DOI: 10.1016/S0301-4215(02)00100-3
- [2] Abdelaziz, EA, Saidur, R, Mekhilef, S. A review on energy saving strategies in industrial sector. Renewable and Sustainable Energy Reviews 2011; 15: 150-168. DOI: 10.1016/j.rser.2010.09.003
- [3] Waide, P, Brunner, CU. Energy-efficiency policy opportunities for electric motor-driven systems. International Energy Agency 2011; na: 132. DOI: 10.1787/5kgg52gb9gjd-en
- [4] Almounajjed, A, Sahoo, AK, Kumar, MK, Assaf, T. Fault diagnosis and investigation techniques for induction motor. International Journal of Ambient Energy 2022; 43: 6341–6361. DOI: 10.1080/01430750.2021.2016483
- [5] Binder A. Potentials for energy saving with modern drive technology-a survey. In: SPEEDAM 2008 Proceedings of 19th International Symposium on Power Electronics, Electrical Drives, Automation and Motion, June 2008: Ischio, Italy: pp. 90-95.
- [6] Ferreira, FJTE, Fong, JAC, de Almeida, AT. Ecoanalysis of variable-speed drives for flow regulation in pumping systems. IEEE Transactions on Industrial Electronics 2011; 58: 2117-2125. DOI: 10.1109/TIE.2010.2057232
- [7] Kiselychnyk, O, Bodson, M, Werner, H. Interactive energy saving control of water supply pump based on pressure measurement. Transactions of Kremenchuk State Polytehnic University 2009; 56: 166-171 <https://ela.kpi.ua/handle/123456789/38238>
- [8] Kiselychnyk O, Bodson M, Werner H. Overview of energy efficient control solutions for water supply systems. In: KSPU 2009 Transactions of Kremenchuk State Polytechnic University 2009; Kremenchuk, Ukraine: pp. 40–45.
- [9] de Almeida, AT, Ferreira, FJTE, Both, D. Technical and economical considerations in the application of variable-speed drives with electric motor systems. IEEE Transactions on Industry Applications 2005; 41: 188-199. DOI: 10.1109/TIA.2004.841022
- [10] Making Sense of Sensorless - Empowering Pumps and Equipment.pdf [Internet]. [cited 2023 Oct. 23]. Available from: https://empoweringpumps.com/making-sense-sensorless.
- [11] Kiselychnyk, O, Bodson, M. Nonsensor control of centrifugal water pump with asynchronous electric-drive motor based on extended Kalman filter. Russian Electrical Engineering 2011; 82: 69-75. DOI: 10.3103/S1068371211020088
- [12] Wu, Q, Shen, Q, Wang, X, Yang, Y. Estimation of centrifugal pump operational state with dual neural network architecture-based model. Neurocomputing 2016; 216: 102–108. DOI: 10.1016/j.neucom.2016.07.035
- [13] Ahonen, T, Tamminen, J, Ahola, J, Viholainen, J, Aranto, N, Kestilä, J. Estimation of pump operational state with model-based methods. Energy Conversion and Management 2010; 51: 1319-1325. DOI: 10.1016/j.enconman.2010.01.009
- [14] Tamminen J, Ahonen T, Ahola J, Kestilä J. Sensorless flow rate estimation in frequency-converter-driven fans. In: EPE 2011 Proceedings of the 2011-14th European Conference on Power Electronics and Applications: Birmingham, United Kingdom: pp. 1-10.
- [15] Pechenik, M, Kiselychnyk, O, Buryan, S, Petukhova, D. Sensorless control of water supply pump based on neural network estimation. Electrotechnic and Computer Systems 2011; 3: 462-466 <https://eltecs.op.edu.ua/index.php/journal/article/view/790
- [16] Bose, BK. Expert system, fuzzy logic, and neural network applications in power electronics and motion control. In Proceedings of the IEEE 1994; 82: 1303-1323. DOI: 10.1109/5.301690
- [17] Lee, HY, Lee, JL, Kwon, SO, Lee, SW. Performance estimation of induction motor using artificial neural network. In: IWSSIP 2018 25th International Conference on Systems, Signals and Image Processing 2018; Ohrid, North Macedonia: pp. 1-3.
- [18] Ebrahim, OS, Badr, MA, Elgendy, AS, Jain, PK. ANN-based optimal energy control of induction motor drive in pumping applications. IEEE Transactions on Energy Conversion 2010; 25: 652-660. DOI: 10.1109/TEC.2010.2041352
- [19] Wlas, M, Krzeminski, A, Guzinski, J, Abu-Rub, H, Toliyat, HA. Artificial-neural-network-based sensorless nonlinear control of induction motors. IEEE Transactions on Energy Conversion 2005; 20: 520-528. DOI: 10.1109/TEC.2005.847984
- [20] Tamminen, J, Viholainen, J, Ahonen, T, Ahola, J, Hammo, S, Vakkilainen, E. Comparison of model-based flow rate estimation methods in frequency-converter-driven pumps and fans. Energy Efficiency 2014; 7: 493–505. DOI: 10.1007/s12053-013-9234-6
- [21] Altivar Machine ATV320 Variable Speed Drives for Asynchronous and Synchronous Motors Installation Manual.pdf [Internet]. [cited 2023 Oct. 22]. Available from: https://download.schneider-electric.com.
- [22] ACS550 User’s Manual ACS550-01 Drives (0.75…160 kW) ACS550-U1 Drives (1…200 hp).pdf [Internet]. [cited 2023 Oct 22]. Available from: https://library.e.abb.com.
- [23] Barbarelli, S, Amelio, M, Florio, G. Predictive model estimating the performances of centrifugal pumps used as turbines. Energy Jul. 2016; 107: 103–121. DOI: 10.1016/J.energy.2016.03.122.
- [24] Ahonen, T, Kortelainen, JT, Tamminen, JK, Ahola, J. Centrifugal pump operation monitoring with motor phase current measurement. International Journal of Electrical Power Energy Systems 2012; 42: 188-195. DOI: 10.1016/j.ijepes.2012.04.013.