Multi-Objective Optimization Analysis of Motor Cooling System in Articulated Dump Truck

Abstract:

Article Preview

In order to ensure the reliable and safe operation of the electric driving motor of the articulated dump truck, water cooling system is installed for each motor. For the best performance of the water cooling system, not only the heat transfer should be enhanced to maintain the motor in relatively low temperature, but also the pressure drop in the water cooling system should be reduced to save energy by reducing the power consumption of the pump. In this paper, the numerical simulation of the cooling progress is completed and the temperature and pressure field distribution are obtained. The multi-objective optimization model is established which involves the cooling system structure, temperature field distribution and pressure field distribution. To improve the computational efficiency, the surrogate model of the simulation about the cooling process is established based on the Response Surface Methodology (RSM). After the multi-objective optimization, the Pareto optimal set is obtained. The proper design point, which could make the average temperature and pressure drop of the cooling system relative desirable, is chosen from the Pareto optimal set.

Info:

Periodical:

Advanced Materials Research (Volumes 383-390)

Edited by:

Wu Fan

Pages:

4715-4720

DOI:

10.4028/www.scientific.net/AMR.383-390.4715

Citation:

Y. Zhang et al., "Multi-Objective Optimization Analysis of Motor Cooling System in Articulated Dump Truck", Advanced Materials Research, Vols. 383-390, pp. 4715-4720, 2012

Online since:

November 2011

Export:

Price:

$35.00

[1] Liwei Song, Zijian Li, Jingyi Gao, Qingchu Zeng, and Fuping Wang, 3D Thermal Analysis of Water Cooling Induction Motor used for HEV, Proc. IEEE Symp. Electrical Machines and Systems, 2008. ICEMS 2008, IEEE Press, Otc. 2008, pp.534-537.

DOI: 10.1109/vppc.2008.4677805

[2] Yan Zhang, Yanhua Shen, and Wenming Zhang, Optimized Design of the Cooling System for an Articulated Dump Truck's Electric Drive System, Proc. SAE Symp. SAE 2010 World Congress & Exhibition, SAE Press, Apr. 2010, doi: 10. 4271/2010-01-0504.

DOI: 10.4271/2010-01-0504

[3] Kleijnen J. P. C, Response surface methodology for constrained simulation optimization: an overview, Simulation Modelling Practice and Theory, vol. 16, p.50–64, Jan. (2008).

DOI: 10.1016/j.simpat.2007.10.001

[4] R. Rikards, H. Abramovich, J. Auzins, A. Korjakins, O. Ozolinsh, K. Kalnins, and T. Green, Surrogate Models for Optimum Design of Stiffened Composite Shells, Composite Structures, vol. 63, p.243–251, (2004).

DOI: 10.1016/s0263-8223(03)00171-5

[5] Xue Guan Song, Ji Hoon Jung, Hwan Jung Son, Joon Hong Park, Kwon Hee Lee, and Young Chul, Metamodel-based Optimization of a Control Arm Considering Strength and Durability Performance, Computers and Mathematics with Applications, in press.

DOI: 10.1016/j.camwa.2010.03.019

[6] Tushar Goel, Rajkumar Vaidyanathan, Raphael T. Haftka, Wei Shyy, Nestor V. Queipo, and Kevin Tucker, Response surface approximation of Pareto optimal front in multi-objective optimization, Comput. Methods Appl. Mech. Engrg, vol. 196, p.879–893, Jul. (2006).

DOI: 10.2514/6.2004-4501

[7] N. Amanifard, N. Nariman-Zadeh, M. Borji, A. Khalkhali, and A. Habibdoust, Modelling and Pareto optimization of heat transfer and flow coefficients in microchannels using GMDH type neural networks and genetic algorithms, Energy Conversion and Management, vol. 49, 2008, pp.311-329.

DOI: 10.1016/j.enconman.2007.06.002

[8] V.S. Summanwar, V.K. Jayaraman, B.D. Kulkarni, H.S. Kusumakar, and K. Gupta, J. Rajesh , Solution of constrained optimization problems by multi-objective genetic algorithm, Computers and Chemical Engineering, vol. 26, p.1481–1492, (2002).

DOI: 10.1016/s0098-1354(02)00125-4

[9] Victor Pereyra, Fast computation of equispaced Pareto manifolds and Pareto fronts for multiobjective optimization problems, Mathematics and Computers in Simulation, vol. 79, p.1935–1947, (2009).

DOI: 10.1016/j.matcom.2007.02.007

[10] Shinya Watanabe, Tomoyuki Hiroyasu, and Mitsunori Miki, NCGA : Neighborhood Cultivation Genetic Algorithm for Multi-Objective Optimization Problems, Proc. Genetic and Evolutionary Computation Conference, 2002, p.458–465.

DOI: 10.1007/1-84628-137-7_9

In order to see related information, you need to Login.