Abstract
The optimized design method of the traditional forced air cooling system is highly professional and low in efficiency. In this paper, firstly, the fan curve, physical parameters, friction factor, local flow resistance and other functions are fitted into functions, and the operating point of the forced air cooling system is obtained by iterative calculation. Then, starting from the heat transfer mechanism of the forced air cooling system, the calculation results of the temperature, air volume and pressure of the air cooling system are calculated and deduced. Then, taking the temperature and weight of the radiator as the objective function, the air-cooling system is optimized by genetic algorithm, and the optimal geometric parameters of the radiator meeting the constraints are obtained. Finally, the comparison with commercial software and experimental tests verifies the applicability of the algorithm. This article combines this set of calculation methods to develop a set of programs for the design and optimization of forced air cooling systems, which improves the efficiency of traditional simulation calculations by more than thousands of times. This program has certain application value for improving the design ability of forced air cooling system and improving the research efficiency of new products.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Fu, G., Gao, Z., Zou, H.: Thermal design of power devices and optimal design of heat sink. Semiconductor Technol. 29(5), 78–80 (2004)
Lv, Y., Yang, S.: Thermal design and thermal testing technology of electronic equipment and its latest developments. Electron. Mech. Eng. 23(1), 5–10 (2007)
Su, H., Qin, B.: Optimal design of heat sinks based on genetic algorithms. J. Eng. Des. 14(1), 31–34 (2007)
Huang, M.: Thermal design of a forced air-cooled cabinet. Electron. Mech. Eng. 22(2), 12–13 (2006)
Zhang, L., Zhu, T.: Development of calculation program for thermal performance of ORC system. J. Eng. Therm. Energy Power 29(1), 41–45 (2006)
Zhao, D.: Thermal Design of Electronic Equipment. Publishing House of Electronics Industry, Beijing (2009)
Min, X., Liu, G.: Application of artificial neural network combined with genetic algorithm in modeling and optimization. Appl. Res. Comput. 1(1), 79–80 (2002)
Wu, Y.: Optimal Design of Micro-Channel Heat Sink Based on Genetic Algorithm. University of Electronic Science and Technology of China, Chengdu (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 Science Press
About this paper
Cite this paper
Ge, J., Jin, D., Zhang, J. (2022). Program Design of Forced Air Cooling System Based on Genetic Algorithm. In: Duan, B., Umeda, K., Kim, Cw. (eds) Proceedings of the Eighth Asia International Symposium on Mechatronics. Lecture Notes in Electrical Engineering, vol 885. Springer, Singapore. https://doi.org/10.1007/978-981-19-1309-9_132
Download citation
DOI: https://doi.org/10.1007/978-981-19-1309-9_132
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-1308-2
Online ISBN: 978-981-19-1309-9
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)