EXTENDED KALMAN FILTER DESIGN FOR RAILWAY TRACTION MOTOR

Yıl 2017, Cilt: 5 Sayı: 4, 432 - 444, 01.12.2017

Caglar Uyulan Metin Gokasan

https://doi.org/10.15317/Scitech.2017.103

Öz

Monitoring the adhesion force between a railway wheel and a rail surface is very essential in maintaining high acceleration and braking performance of railway vehicles. Due to the difficulties encountered in direct measurement of friction coefficient, creepage and adhesion force; state observers are used as indirect estimation methods. This paper proposes an effective estimation method, which exploits railway traction motor behaviour to give an assistance for realizing wheel slip and adhesion control in order to be used in railway applications. This method plays an active role in optimizing the use of the existing adhesion and reducing wheel wear by decreasing high creep values. With this method, adhesion force can be indirectly estimated by measuring stator currents, and angular speed of the AC traction motor and using dynamic relationships based on the extended Kalman filter (EKF) simulation model. The re-adhesion controller can be designed to regulate the motor torque command according to the maximum available adhesion depending on the estimated results. To test the proposed method, simulations were performed under different friction coefficients.

Anahtar Kelimeler

Adhesion mode, Extended Kalman filter, Full state estimation, Railway traction

Demiryolu Cer Motorları için Genişletilmiş Kalman Filtresi Tasarımı

Öz

Bir demiryolu tekerleği ile rayı arasında meydana gelen tutunma kuvvetinin izlenmesi, demiryolu araçlarının yüksek hızlanma ve frenleme performansının korunmasında oldukça önemlidir. Sürtünme katsayısı, kayma ve tutunma kuvvetinin doğrudan ölçülmesinde karşılaşılan zorluklardan dolayı, durum gözetleyicilerine dayalı dolaylı tahmin yöntemleri kullanılır. Bu makale, demiryolu uygulamalarında kullanılmak üzere tekerlek kayma ve yeniden tutunma kontrolünü gerçekleştirmek için demiryolu cer motor davranışını kullanan etkili bir tahmin yöntemi önermektedir. Bu yöntem, mevcut tutunmanın kullanımını iyileştirmede ve yüksek kayma değerlerini düşürerek tekerlek aşınmasının azaltılmasında etkin bir rol oynamaktadır. Bu yöntemle, stator akımları ve asenkron cer motorun açısal hızı ölçülerek, genişletilmiş Kalman filtresi (GKF) simülasyon modeline dayanan dinamik ilişkiler kullanılarak tutunma kuvveti dolaylı olarak tahmin edilebilir. Yeniden tutunma kontrolörü, tahmin sonuçlarına bağlı olan maksimum erişilebilir tutunma özelliklerine göre motor moment komutu düzenlenerek tasarlanabilir. Önerilen yöntemi test etmek için, farklı tekerlek-ray sürtünme katsayıları altında simülasyonlar gerçekleştirilmiştir.

Anahtar Kelimeler

Demiryolu Cer sistemi, Genişletilmiş Kalman filtresi, Tam durum kestirimi, Tutunma modeli

Kaynakça

• Alonge, F., D'ippolito, F., 2010, “Extended Kalman Filter for Sensorless Control of Induction Motors”, First Symposium on Sensorless Control for Electrical Drives, Padova, Italy, 9-10 July 2010.
• Alsofyani, I. M., Idris, N., Sutikno, T., Alamri, Y. A., 2012, “An optimized Extended Kalman Filter for Speed Sensorless Direct Troque Control of An İnduction Motor”, IEEE International Conference on Power and Energy, Kota Kinabalu, Malaysia, 2-5 December 2012.
• Barut, M., Bogosyan, O., Gokasan, M., 2002, “EKF Based Estimation for Direct Vector Control of Induction Motors”, IEEE 28th Annual Conference of the Industrial Electronics Society, Sevilla, Spain, 5-8 November 2002.
• Barut, M., Bogosyan, S., Gokasan, M., “EKF Based Sensorless Direct Torque Control of IMs in The Low Speed Range”, Proceedings of the IEEE International Symposium on Industrial Electronics, 2005, ISIE 2005, Dubrovnik, Croatia, 20-23 June 2005.
• Barut, M., Bogosyan, S., Gokasan, M., 2007, “Speed-Sensorless Estimation for Induction Motors Using Extended Kalman Filters”, IEEE Transactions on Industrial Electronics, Vol. 54(1), pp. 272-280.
• Barut, M., Gokasan, M., Bogosyan, O., 2003, “An extended Kalman Filter Based Sensorless Direct Vector Control of Induction Motors”, IECON'03. 29th Annual Conference of the IEEE Industrial Electronics Society (IEEE Cat. No.03CH37468), Roanoke, VA, USA, 2-6 November 2003.
• Bogosyan, S., Barut, M., Gokasan, M., 2007, “Braided Extended Kalman Filters for Sensorless Estimation In İnduction Motors at High-Low/Zero Speed”, IET Control Theory & Application, Vol. 1(4), pp. 987-998.
• Cai, L., Zhang, Y., Zhang, Z., Liu, C., Lu, Z., 2003, “Application of Genetic Algorithms in EKF for Speed Estimation of an Inducion Motor”, Proc. on IEEE Power Electronics Specialist Conference, Acapulco, Mexico, Vol. 1, pp. 345-349, 15-19 June 2003.
• Charles, G., Goodall, R., 2006, “Low Adhesion Estimation”, IET International Conference on Railway Condition Monitoring, Birmingham, UK 29-30 Nov. 2006
• Gaspar, P., Szabo, Z., Bokor, J., 2006, “Observer Based Estimation of The Wheel-Rail Friction Coefficient”, IEEE Conference on Computer Aided Control System Design. Munich, Germany 4-6 Oct. 2006
• Hussain, I., Mei, T. X., Ritchings, R. T., 2013, “Estimation of Wheel–Rail Contact Conditions and Adhesion Using The Multiple Model Approach”, Vehicle System Dynamics, Vol. 51(1), pp. 32-53.
• Iwnicki, S., 2003, “Simulation of Wheel-Rail Contact Forces”, Fatigue Fracture of Engineering Materials and Structures, Vol. 26(10), pp. 887-900.
• Kalker, J., 1968, “On The Rolling Contact of Two Elastic Bodies in The Presence of Dry Friction”, Wear, Vol. 11(4), pp. 303.
• Kawamura, A., Takeuchi, K., Furuya, T., Cao, M., Takaoka, Y., Yoshimoto, K., 2003, “Measurement of Tractive Force and the New Maximum Tractive Force Control by the Newly Developed Tractive Force Measurement Equipment”, IEEJ Transactions on Industry Applications, Vol. 123(8), pp. 885-893.
• Matsumoto, Y., Eguchi, N., Kawamura, A., 2001, “Novel Re-Adhesion Control for Train Traction System of The "Shinkansen" with The Estimation of Wheel-to-Rail Adhesive Force”, IECON'01, 27th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.37243), Denver, CO, USA, Vol. 2, pp. 1207-1212 29 Nov.-2 Dec. 2001
• Mei, T., Hussain, I., 2010, “Detection of Wheel-Rail Conditions for Improved Traction Control”, IET Conference on Railway Traction Systems, Birmingham, UK 13-15 April 2010
• Polach, O., 1999, “A Fast Wheel-Rail Forces Calculation Computer”, Veh. Syst. Dyn. Suppl, 1999, Vol. 33, pp. 728–739.
• Radionov, I. A., Mushenko, A. S., 2015, “The method of estimation of adhesion at “wheel-railway” contact point”, 2015 International Siberian Conference on Control and Communications (SIBCON), Omsk, Russia, 21-23 May 2015.
• Rizzo, R., Iannuzzi, D., 2002, “Indirect Friction Force Identification for Application in Traction Electric Drives”, Mathematics and Computers in Simulation, Vol. 60(3-5), pp.379-387.
• Shi, K., Chan, T., Wong, Y., Ho, S., 2002, Speed Estimation of An İnduction Motor Drive Using an Optimized Extended Kalman Filter”, IEEE Transactions on Industrial Electronics, Vol. 49(1), pp.124-133.
• Singh, K., Singh, M., 2013, “Design of Kalman Filter for Induction Motor Drive” Students Conference on Engineering and Systems (SCES), Allahabad, India, 12-14 April 2013.
• Wang, S., Xiao, J., Huang, J., Sheng, H., 2016, “Locomotive Wheel Slip Detection Based on Multi-Rate State İdentification of Motor Load Torque”, Journal of the Franklin Institute, 2016, Vol. 353(2), pp. 521-540.
• Ward, C. P., Goodall, R. M., Dixon, R., 2011, “Contact Force Estimation in the Railway Vehicle Wheel-Rail Interface”, IFAC Proceedings Volumes, Vol. 44(1), pp. 4398-4403.
• Ward, C., Goodall, R., Dixon, R., Charles, G., 2012, “Detection of Low Adhesion in The Railway Vehicle Wheel/Rail İnterface: Assessment of Multi-Bodied Simulation Data, Proceedings of 2012 UKACC International Conference on Control, Cardiff, UK, 3-5 September 2012.
• Zhao, Y., Liang, B., 2013, “Re-adhesion Control for A Railway Single Wheelset Test Rig Based on The Behaviour of The Traction Motor”, Vehicle System Dynamics, Vol. 51(8), pp. 1173-1185.
• Zhao, Y., Liang, B., Iwnicki, S., 2012, “Estimation of the Friction Coefficient Between Wheel and Rail Surface Using Traction Motor Behaviour”, Journal of Physics: Conference Series, 2012, Vol. 364, 012004.
• Zhao, Y., Liang, B., Iwnicki, S., 2014, “Friction Coefficient Estimation Using an Unscented Kalman Filter”, Vehicle System Dynamics, Vol. 52(Sup1), pp. 220-234.