Computation of the Speed of Four In-Wheel Motors of an Electric Vehicle Using a Radial Basis Neural Network
Abstract
This paper presents design and speed estimation for an Electric Vehicle (EV) with four in-wheel motors using Radial Basis Neural Network (RBNN). According to the steering angle and the speed of EV, the speeds of all wheels are calculated by equations derived from the Ackermann-Jeantand model using CoDeSys Software Package. The Electronic Differential System (EDS) is also simulated by Matlab/Simulink using the mathematical equations. RBNN is used for the estimation of the wheel speeds based on the steering angle and EV speed. Further, different levels of noise are added to the steering angle and the EV speed. The speeds of front wheels calculated by CoDeSys are sent to two Induction Motor (IM) drives via a Controller Area Network-Bus (CAN-Bus). These speed values are measured experimentally by a tachometer changing the steering angle and EV speed. RBNN results are verified by CoDeSys, Simulink, and experimental results. As a result, it is observed that RBNN is a good estimator for EDS of an EV with in-wheel motor due to its robustness to different levels of sensor noise.
Keywords:
electric vehicle, electronic differential system, in-wheel motor, radial basis neural network, speed estimationDownloads
References
J. S. Lee, Y. J. Ryoo, Y. C. Lim, P. Freere, T. G. Kim, S. J. Son, E. S. Kim, “A neural network model of electric differential system for electric vehicle”, IEEE 26th Annual Conference of the Industrial Electronics Society (IECON), Vol. 1, pp. 83-88, 2000
T. Ma, A. M. Osama, “Optimal charging of plug-in electric vehicles for a car-park infrastructure”, IEEE Transactions on Industry Applications, Vol. 50, No. 4, pp. 2323-2330. 2014 DOI: https://doi.org/10.1109/TIA.2013.2296620
M. Yildirim, M. Polat, H. Kurum, “A survey on comparison of electric motor types and drives used for electric vehicles”, IEEE 16th International Power Electronics and Motion Control Conference and Exposition (PEMC), pp. 218-223, 2014 DOI: https://doi.org/10.1109/EPEPEMC.2014.6980715
Y. E. Zhao, J. W. Zhang, X. Q. Guan, “Modelling and simulation of the electronic differential system for an electric vehicle with two-motor-wheel drive”, International Journal of Vehicle Systems Modelling and Testing, Vol. 4, No. 1-2, pp. 1209-1214, 2009 DOI: https://doi.org/10.1504/IJVSMT.2009.029180
J. L. Febin Daya, P. Sanjeevikumar, F. Blaabjerg, P. W. Wheeler, J. O. Ojo, “Implementation of wavelet-based robust differential control for electric vehicle application”, IEEE Transactions on Power Electronics, Vol. 30, No. 12, pp. 6510-6513, 2015 DOI: https://doi.org/10.1109/TPEL.2015.2440297
Y. Zhou, S. Li, X. Zhou, Z. Fang, “The control strategy of electronic differential for EV with four in-wheel motors”, IEEE Control and Decision Conference (CCDC), pp. 4190-4195, 2010 DOI: https://doi.org/10.1109/CCDC.2010.5498381
L. Zhai, S. Dong, “Electronic differential speed steering control for four in-wheel motors independent drive vehicle”, 9th World Congress on Intelligent Control and Automation (WCICA), pp. 780-783, June 2011 DOI: https://doi.org/10.1109/WCICA.2011.5970621
H. Kahveci, H. I. Okumus, M. Ekici, “An electronic differential system using fuzzy logic speed controlled in-wheel brushless DC motors”, IEEE Fourth International Conference on Power Engineering, Energy and Electrical Drives (POWERENG), pp. 881-885, May 2013 DOI: https://doi.org/10.1109/PowerEng.2013.6635726
R. Wan, G. Liu, D. Zhang, W. Gong, “A fault-tolerant electronic differential system of electric vehicles”, in IEEE Vehicle Power and Propulsion Conference (VPPC), pp. 1-5, Oct. 2013 DOI: https://doi.org/10.1109/VPPC.2013.6671654
S. Sharma, R. Pegu, P. Barman, “Electronic differential for electric vehicle with single wheel reference”, IEEE 1st Conference on Power, Dielectric and Energy Management at NERIST (ICPDEN), pp. 1-5, Jan. 2015 DOI: https://doi.org/10.1109/ICPDEN.2015.7084489
A. Haddoun, M. E. H. Benbouzid, D. Diallo, R. Abdessemed, J. Ghouili, K. Srairi, “Modeling, analysis, and neural network control of an EV electrical differential”, IEEE Transactions on Industrial Electronics, Vol. 55, No. 6, pp. 2286-2294, 2008 DOI: https://doi.org/10.1109/TIE.2008.918392
D. Foito, G. Manuel, V. F. Pires, “Road motion control electric vehicle with speed and torque observer”, IEEE International Conference on New Concepts in Smart Cities: Fostering Public and Private Alliances (SmartMILE), pp. 1-6, 2013 DOI: https://doi.org/10.1109/SmartMILE.2013.6708210
M. Yildirim, E. Oksuztepe, B. Tanyeri, H. Kurum, “Electronic differential system for an electric vehicle with in-wheel motor”, in 9th International Conference on Electrical and Electronics Engineering (ELECO), pp. 1048-1052, 26-28 Nov. 2015 DOI: https://doi.org/10.1109/ELECO.2015.7394567
M. J. L. Orr, Introduction to radial basis function networks, Technical Report, Center for Cognitive Science, University of Edinburgh, 1996.
T. Bow, Pattern recognition and image preprocessing, CRC Press, Sing, 2002. DOI: https://doi.org/10.1201/9780203903896
C. M. Bishop, Neural networks for pattern recognition, Oxford university press, 1995. DOI: https://doi.org/10.1201/9781420050646.ptb6
A. Rubaai, M. D. Kankam, “Adaptive tracking controller for induction motor drives using online training of neural networks”, IEEE Transactions on Industry Applications, Vol. 36, No. 5, pp. 1285-1294, 2000 DOI: https://doi.org/10.1109/28.871276
K. Du, NS Madisetti, Neural networks in a softcomputing framework, Springer Science & Business Media, 2006
S. Stergiopoulos, Advanced signal processing: theory and implementation for sonar, radar, and non-invasive medical diagnostic systems, CRC Press, 2009 DOI: https://doi.org/10.1201/9781420062410
M. Yildirim, E. Oksuztepe, B. Tanyeri, H. Kurum, Design of electronic differential system for an electric vehicle with in-wheel motor, IEEE Power and Energy Conference at Illinois (PECI), pp. 1-5, 2016 DOI: https://doi.org/10.1109/PECI.2016.7459238
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