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Optimization Design of the BLDC Motor Using Backtracking Search Algorithm


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DOI: https://doi.org/10.15866/iree.v16i2.17411

Abstract


The use of fossil energy has a negative impact on the climate and on the environment. For this reasons, the electric vehicles present an attractive and interesting solution to protect the Earth. However, the high cost of manufacture and the limited autonomy are the major problems of electric vehicles today. In order to solve these problems, the authors have chosen to act directly on the electric motor, which represents the heart of the traction system of electric vehicles. In this paper, the authors have been interested to optimize the design of an in-wheel BLDC motor presented by an analytical model consisting of a set of mathematical equations that describe several physical phenomena. Two in-wheel BLDC motor optimization problems have been presented and BSA has been chosen to do the optimization in order to evaluate its ability and its efficiency to solve similar complex optimization problems to use it in future research work.
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Keywords


BSA; Electric Vehicles; in-Wheel BLDC Motor; Optimization Problem

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References


D. Fodorean, L. Idoumghar and L. Szabo, Motorization for an Electric Scooter by Using Permanent-Magnet Machines Optimized Based on a Hybrid Metaheuristic Algorithm, in IEEE Transactions on Vehicular Technology, vol. 62, no. 1, pp. 39-49, Jan. 2013.
https://doi.org/10.1109/tvt.2012.2215970

Y. Yang and R. Guan, Hybrid fuel cell powertrain for a powered wheelchair driven by rim motors, 2011 International Conference on Power Engineering, Energy and Electrical Drives, Malaga, Spain, 2011, pp. 1-6.
https://doi.org/10.1109/powereng.2011.6036540

L. Rambaldi, E. Bocci, and F. Orecchini, Preliminary experimental evaluation of a four wheel motors , batteries plus ultracapacitors and series hybrid powertrain, Appl. Energy, vol. 88, no. 2, pp. 442–448, 2011.
https://doi.org/10.1016/j.apenergy.2010.08.008

R. Wang, Y. Chen, D. Feng, X. Huang, and J. Wang, Development and performance characterization of an electric ground vehicle with independently actuated in-wheel motors, J. Power Sources, vol. 196, no. 8, pp. 3962–3971, 2011.
https://doi.org/10.1016/j.jpowsour.2010.11.160

Y. Hung and C. Wu, A combined optimal sizing and energy management approach for hybrid in-wheel motors of EVs, Appl. Energy, vol. 139, pp. 260–271, 2015.
https://doi.org/10.1016/j.apenergy.2014.11.028

Yee-Pien Yang, Yih-Ping Luh and Cheng-Huei Cheung, Design and control of axial-flux brushless DC wheel motors for electric Vehicles-part I: multiobjective optimal design and analysis, in IEEE Transactions on Magnetics, vol. 40, no. 4, pp. 1873-1882, July 2004.
https://doi.org/10.1109/isie.2003.1267324

Z. Q. Zhu, D. Howe and C. C. Chan, Improved analytical model for predicting the magnetic field distribution in brushless permanent-magnet machines, in IEEE Transactions on Magnetics, vol. 38, no. 1, pp. 229-238, Jan. 2002.
https://doi.org/10.1109/20.990112

Z. Q. Zhu, D. Howe, E. Bolte and B. Ackermann, "Instantaneous magnetic field distribution in brushless permanent magnet DC motors. I. Open-circuit field," in IEEE Transactions on Magnetics, vol. 29, no. 1, pp. 124-135, Jan. 1993.
https://doi.org/10.1109/20.195557

L. Xu, C. David, J. Li, M. Ouyang, and Z. Hu, Multi-objective component sizing based on optimal energy management strategy of fuel cell electric vehicles q, Appl. Energy, 2015.
https://doi.org/10.1016/j.apenergy.2015.02.017

L. Xu, M. Ouyang, J. Li, F. Yang, L. Lu, and J. Hua, Optimal sizing of plug-in fuel cell electric vehicles using models of vehicle performance and system cost, Appl. Energy, vol. 103, no. 2013, pp. 477–487, 2015.
https://doi.org/10.1016/j.apenergy.2012.10.010

F. Lei, Y. Bai, W. Zhu, and J. Liu, A novel approach for electric powertrain optimization considering vehicle power performance , energy consumption and ride comfort, Energy, vol. 167, pp. 1040–1050, 2019.
https://doi.org/10.1016/j.energy.2018.11.052

S. Brisset and P. Brochet, Analytical model for the optimal design of a brushless DC wheel motor, COMPEL - Int. J. Comput. Math. Electr. Electron. Eng., vol. 24, no. 3, pp. 829–848, 2005.
https://doi.org/10.1108/03321640510612952

F. Lei, B. Du, X. Liu, X. Xie, and T. Chai, Optimization of an implicit constrained multi-physics system for motor wheels of electric vehicle, Energy, vol. 113, pp. 980–990, 2016.
https://doi.org/10.1016/j.energy.2016.07.139

F. Lei, K. Gu, B. Du, and X. Xie, State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, 2017.

T. C. Bora, L. D. S. Coelho, and L. Lebensztajn, Bat-inspired optimization approach for the brushless DC wheel motor problem, IEEE Trans. Magn., vol. 48, no. 2, pp. 947–950, 2012.
https://doi.org/10.1109/tmag.2011.2176108

F. Moussouni, S. Brisset, and P. Brochet, Some results on the design of brushless DC wheel motor using SQP and GA, Int. J. Appl. Electromagn. Mech., vol. 26, no. 3–4, pp. 233–241, 2018.
https://doi.org/10.3233/jae-2007-913

L. Dos Santos Coelho, L. Z. Barbosa, and L. Lebensztajn, Multiobjective particle swarm approach for the design of a brushless DC wheel motor, IEEE Trans. Magn., vol. 46, no. 8, pp. 2994–2997, 2010.
https://doi.org/10.1109/tmag.2010.2044145

M. d. A. Costa e Silva, L. d. S. Coelho and L. Lebensztajn, Multiobjective Biogeography-Based Optimization Based on Predator-Prey Approach, in IEEE Transactions on Magnetics, vol. 48, no. 2, pp. 951-954, Feb. 2012.
https://doi.org/10.1109/tmag.2011.2174205

H. X. Qiu and H. Bin Duan, Multi-objective pigeon-inspired optimization for brushless direct current motor parameter design, Sci. China Technol. Sci., vol. 58, no. 11, pp. 1915–1923, 2015.
https://doi.org/10.1007/s11431-015-5860-x

Tevfik Yigit, Hakan Celik, Speed controlling of the PEM fuel cell powered BLDC motor with FOPI optimized by MSA, International Journal of Hydrogen Energy, Volume 45, Issue 60, 2020, Pages 35097-35107.
https://doi.org/10.1016/j.ijhydene.2020.04.091

D. Potnuru, K. A. Mary, and C. Sai, Experimental implementation of Flower Pollination Algorithm for speed controller of a BLDC motor, Ain Shams Eng. J., vol. 10, no. 2, pp. 287–295, 2019.
https://doi.org/10.1016/j.asej.2018.07.005

P. Civicioglu, Backtracking Search Optimization Algorithm for numerical optimization problems, Appl. Math. Comput., vol. 219, no. 15, pp. 8121–8144, 2013.
https://doi.org/10.1016/j.amc.2013.02.017

M. Modiri-delshad, S. H. Aghay, E. Taslimi-renani, and N. Abd, Backtracking search algorithm for solving economic dispatch problems with valve-point effects and multiple fuel options, Energy, vol. 116, pp. 637–649, 2016.
https://doi.org/10.1016/j.energy.2016.09.140

D. Chen, F. Zou, R. Lu, and S. Li, PT, Inf. Sci. (Ny)., 2018.

M. Brévilliers, O. Abdelkafi, and L. Idoumghar, Sequential and Parallel BSA Algorithm, 16ème congrès annuel de la Société française de recherche opérationnelle et d'aide à la décision (ROADEF), pp. 1–30, 2015.

A. Zendehboudi, A. Mota-babiloni, P. Makhnatch, R. Saidur, and S. M. Sait, Modeling and multi-objective optimization of an R450A vapor compression refrigeration system [Modélisation et optimisation multi-objectifs d’un système frigorifique à compression de vapeur au R450A], Int. J. Refrig., vol. 100, pp. 141–155, 2019.
https://doi.org/10.1016/j.ijrefrig.2019.01.008

Y. Zhang, Z. Jin, X. Zhao, and Q. Yang, Backtracking search algorithm with Lévy flight for estimating parameters of photovoltaic models, Energy Convers. Manag., vol. 208, no. September 2019, p. 112615, 2020.
https://doi.org/10.1016/j.enconman.2020.112615

Gatto, G., Cimino, V.I., Marongiu, I., Meo, S., Perfetto, A., Interleaved ZVS active-clamped bidirectional DC-DC converter for hybrid-electric vehicles, (2011) International Review of Electrical Engineering (IREE), 6 (5), pp. 2188-2197.
https://doi.org/10.15866/iree.v6i5.8483

Esposito, F., Isastia, V., Meo, S., PSO based energy management strategy for pure electric vehicles with dual energy storage systems, (2010) International Review of Electrical Engineering (IREE), 5 (5), pp. 1862-1871.

Del Pizzo, A., Meo, S., Brando, G., Dannier, A., Ciancetta, F., An Energy Management Strategy for Fuel-cell Hybrid Electric Vehicles via Particle Swarm Optimization Approach, (2014) International Review on Modelling and Simulations (IREMOS), 7 (4), pp. 543-553.
https://doi.org/10.15866/iremos.v7i4.4227

Meo, S., Nonlinear convex optimization of the energy management for hybrid electric vehicles, (2014) Engineering Letters, 22 (4), pp. 170-182.


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