Neural network approach on loss minimization control of a PMSM with core resistance estimation

Permanent magnet synchronous motors (PMSMs) are often used in industry for high-performance applications. Their key features are high power density, linear torque control capability, high efficiency, and fast dynamic response. Today, PMSMs are prevalent especially for their use in hybrid electric vehicles. Since operating the motor at high efficiency values is critically important for electric vehicles, as for all other applications, minimum loss control appears to be an inevitable requirement in PMSMs. In this study, a neural network-based intelligent minimum loss control technique is applied to a PMSM. It is shown by means of the results obtained that the total machine losses can be controlled in a way that keeps them at a minimum level. It is worth noting here that this improvement is achieved compared to the case with I d set to zero, where no minimum loss control technique is used. Within this context, hysteresis and eddy current losses are primarily obtained under certain conditions by means of a PMSM finite element model, initially developed by CEDRAT as an educational demo. A comprehensive loss model with a dynamic core resistor estimator is developed using this information. A neural network controller is then applied to this model and comparisons are made with analytical methods such as field weakening and maximum torque per ampere control techniques. Finally, the obtained results are discussed.

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[1] Asaei B, Rahrovi B. Minimum-copper-loss control over full speed range of an IPMSM drive for hybrid electric vehicle application. In: IEEE 2010 Vehicle Power and Propulsion Conference; 13 September 2010; Lille, France. New York, NY, USA: IEEE. pp. 1-6.
[2] Jeong YS, Sul SK, Hiti S, Rahman KM. Online minimum-copper-loss control of an interior permanent-magnet synchronous machine for automotive applications. IEEE T Ind Appl 2006; 42: 1222-1229.
[3] Wu Z, Li G, Zhu Y. Efficient optimization control of permanent magnet synchronous motor using artificial neural network. Adv Inf Sci Serv Sci 2011; 3: 260-267.
[4] Almandoz G, Ugalde G, Poza J, Escalada AJ. MATLAB-Simulink coupling to finite element software for design and analysis of electrical machines. In: Katsikis VN, editor. MATLABA Fundamental Tool for Scientific Computing and Engineering Applications. Rijeka, Croatia: InTech, 2012. pp. 161-184.
[5] Aorith H, Wang J, Lazari P. A new loss minimization algorithm for interior permanent magnet synchronous machine drives. In: IEEE 2013 International Electric Machines and Drives Conference; 1215 May 2013; Chicago, IL, USA. New York, NY, USA: IEEE. pp. 526-533.
[6] Gracia MH, Lange E, Hameyer K. Numerical calculation of iron losses in electrical machines with a modified postprocessing formula. In: Proceedings of the 16th International Symposium on Electromagnetic Fields COMPUMAG; 2428 June 2007; Aachen, Germany. New York, NY, USA: IEEE. pp. 1-2.
[7] Han SH, Soong WL, Jahns TM. An analytical design approach for reducing stator iron losses in interior PM synchronous machines during flux-weakening operation. In: IEEE 2007 Industry Applications Annual Meeting; 2327 September 2007; New Orleans, LA, USA. New York, NY, USA: IEEE. pp. 103- 110.
[8] Ugalde G, Almandoz G, Poza J, Gonzalez A. Computation of iron losses in permanent magnet machines by multidomain simulations. In: 13th European Conference on Power Electronics and Applications; 810 September 2009; Barcelona, Spain. New York, NY, USA: IEEE. pp. 1-10.
[9] Bernal FF, Garefa-Cerrada A, Faure R. Loss-minimization control of synchronous machines with constant excitation. In: IEEE 1998 Annual Power Electronics Specialists Conference; 22 May 1998; Osaka, Japan. New York, NY, USA: IEEE. pp. 132-138.
[10] Cavallaro C, Di Tommaso AO, Miceli R, Raciti A, Galluzzo GR, Trapanese M. Analysis a DSP implementation and experimental validation of a loss minimization algorithm applied to permanent magnet synchronous motor drives. In: 29th Annual Conference of the IEEE Industrial Electronics Society; 26 November 2003; Roanoke, VA, USA. New York, NY, USA: IEEE. pp. 312-317.
[11] Cavallaro C, Di Tommaso AO, Miceli R, Raciti A, Galluzzo GR, Trapanese M. Efficiency enhancement of permanentmagnet synchronous motor drives by online loss minimization approaches. IEEE T Ind Electron 2005; 52: 1153-1160.
[12] Erdo˘gan H, G¨um¨u¸s B, Ozdemir M. Minimum loss control of permanent magnet synchronous motor. In: Elektrik, ¨ Elektronik, Bilgisayar ve Biyomedikal M¨uhendisli˘gi Sempozyumu ve Sergisi; 2729 November 2014; Bursa, Turkey. Ankara, Turkey: TMMOB. pp. 27-29 (in Turkish with abstract in English).
[13] K¨uttler S, Benkara KEK, Friedrich G, Vangraefsch`epe F, Abdelli A. Impact of the flux weakening on the iron losses in an internal permanent magnet synchronous machine. In: IEEE 2014 Energy Conversion Congress and Exposition; 1418 September 2014; Pittsburgh, PA, USA. New York, NY, USA: IEEE. pp. 4188-4195.
[14] Morimoto S, Tong Y, Takeda Y, Hirasa T. Loss minimization control of permanent magnet synchronous motor drives. IEEE T Ind Electron 1994; 41: 511-517.
[15] Uddin MN, Member S, Zou H, Azevedo F. Online loss minimization based adaptive flux observer for direct torque and flux control of PMSM drive. In: IEEE 2014 Industry Applications Society Annual Meeting; 59 October 2014; Vancouver, BC, Canada. New York, NY, USA: IEEE. pp. 1-7.
[16] Watanabe Y, Kim TW, Mushi A, Kawamura A. Research on overall efficiency improvement of electric vehicles by MTHDPAM control method. In: IEEE 2012 15th International Power Electronics and Motion Control Conference; 46 September 2012; Novi Sad, Serbia. New York, NY, USA: IEEE. pp. LS5c.21-LS5c.26.
[17] Krings A, Nategh S, Wallmark O, Soulard J. Local iron loss identification by thermal measurements on an outerrotor permanent magnet synchronous machine. In: IEEE 2012 15th International Conference on Electrical Machines and Systems; 2124 October 2012; Sapporo, Japan. New York, NY, USA: IEEE. pp. 1-5.
[18] Dutta R, Chong L, Rahman FM. Analysis and experimental verification of losses in a concentrated wound interior permanent magnet machine. Pr Electromagn Res B 2013; 48: 221-248.
[19] Shchur I, Rusek A, Makarchuk O, Mandzyuk M. Definition of parameters of mathematical model of pmsm for electric vehicles on the basis of computer and experimental research. Maszyny Elektryczne Zeszyty Problemowe 2014; 1: 147-152.
[20] Soulard J. Modeling of iron losses in permanent magnet synchronous motors with field-weakening capability for electric vehicles. Int J Auto Tech 2003; 4: 87-94.
[21] Lee JY, Lee SH, Lee GH, Hong JP, Hur J. Determination of parameters considering magnetic nonlinearity in an interior permanent magnet synchronous motor. IEEE T Magn 2006; 42: 1303-1306.
[22] Lee BH, Kwon SO, Sun T, Hong JP, Lee GH, Hur J. Modeling of core loss resistance for d-q equivalent circuit analysis of IPMSM considering harmonic linkage flux. IEEE T Magn 2011; 47: 1066-1069.
[23] Vaez S, John VI. Minimum loss operation of PM motor drives. In: IEEE 1995 Canadian Conference on Electrical and Computer Engineering; 58 September 1995; Montreal, QC, Canada. New York, NY, USA: IEEE. pp. 284-287.
[24] Zarei AH, Abbaszadeh K, Safari K. The analytical analysis of the rotor losses in the PMSM motors. In: Proceedings of the World Congress on Engineering and Computer Science; 2426 October 2012; San Francisco, CA, USA. New York, NY, USA: IEEE. pp. 1044-1048.
[25] Chen JJ, Chin KP. Minimum copper loss flux-weakening control of surface mounted permanent magnet synchronous motors. IEEE T Power Electr 2003; 18: 929-936.
[26] Solomon O, Famouri P. Control and efficiency optimization strategy for permanent magnet brushless AC motors. In: 2009 IEEE International Symposium on Industrial Electronics; 58 July 2009; Seoul, South Korea. New York, NY, USA: IEEE. pp. 505-512.
[27] Sue SM, Hung TW, Liaw JH, Li YF, Sun CY. A new MTPA control strategy for sensorless V/f controlled PMSM drives. In: IEEE 2011 Conference on Industrial Electronics and Applications; 21 23 June 2011; Beijing, China. New York, NY, USA: IEEE. pp. 1840-1844.
[28] Wang W, Fahimi B, Kiani M. Maximum torque per ampere control of permanent magnet synchronous machines. In: IEEE 2012 International Conference on Electrical Machines; 25 September 2012. New York, NY, USA: IEEE. pp. 1013-1020.
[29] Liaw JH, Liao YH, Tung CW, Sue SM, Huang YS. A robust field-weakening control strategy for IPMSM drives. In: IEEE 2010 International Power Electronics Conference; 2124 June 2010; Sapporo, Japan. New York, NY, USA: IEEE. pp. 605-611.
[30] Bolognani S, Calligaro S, Petrella R, Pogni F. Flux-weakening in IPM motor drives: comparison of state-of-art algorithms and a novel proposal for controller design. In: IEEE 2011 European Conference on Power Electronics and Applications; 30 August1 September 2011; Birmingham, UK. New York, NY, USA: IEEE. pp. 1-11.
[31] Pan CT, Liaw JH. A robust field-weakening control strategy for surface-mounted permanent-magnet motor drives. IEEE T Energy Conver 2005; 20: 701-709.
[32] Toosi S, Mehrjou MR, Karami M, Zare MR. Increase performance of IPMSM by combination of maximum torque per ampere and flux-weakening methods. ISRN Power Eng 2013; 2013: 1-11.
[33] Sergaki ES, Georgilakis PS, Kladas a. G, Stavrakakis GS. Fuzzy logic based online electromagnetic loss minimization of permanent magnet synchronous motor drives. In: IEEE 2008 International Conference on Electrical Machines; 69 September 2008; Vilamoura, Portugal. New York, NY, USA: IEEE. pp. 1-7.
[34] Butt CB, Hoque MA, Rahman MA. Simplified fuzzy-logic-based MTPA speed control of IPMSM drive. IEEE T Ind Appl 2004; 40: 1529-1535.
[35] Ducar I, Marinescu C. The PMSM efficiency at variable speed for pumping applications. In: IEEE 2014 International Conference and Exposition on Electrical and Power Engineering; 1618 October 2014; Iasi, Romania. New York, NY, USA: IEEE. pp. 16-18.
[36] Fernandez-Bernal F, Garcia-Cerrada A, Faure R. Determination of parameters in interior permanent magnet synchronous motors with iron losses without torque measurement. IEEE T Ind Appl 2001; 37: 1265-1272.
[37] Finken T, Hameyer K. Computation of iron and eddy-current losses in IPM motors depending on the field weakening angle and current waveform. In: IEEE 2009 International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering; 1719 September 2009; Arras, France. New York, NY, USA: IEEE. pp. 123-128.
[38] Blair JC. Book reviews. B Med Libr Assoc 1980; 68: 250.
[39] Valˇci´c M, Antoni´c R, Tomas V. ANFIS based model for ship speed prediction. Brodogradnja 2011; 62: 373-382.
[40] Jang JSR. ANFIS: adaptive-network-based fuzzy inference system. IEEE T Syst Man Cyb 1993; 23: 665-685.