Numerical thermal analysis and optimization of multi-chip LED module using response surface methodology and genetic algorithm

Tang, H.; Ye, Huai-Yu; Chen, Xian-Ping; Qian, Cheng; Fan, Xue-Jun; Zhang, Kouchi

doi:10.1109/ACCESS.2017.2737638

Numerical thermal analysis and optimization of multi-chip LED module using response surface methodology and genetic algorithm

Title

Numerical thermal analysis and optimization of multi-chip LED module using response surface methodology and genetic algorithm

Author

Tang, H. (TU Delft Electronic Components, Technology and Materials)
Ye, Huai-Yu (Chongqing University)
Chen, Xian-Ping (Chongqing University)
Qian, Cheng (Chinese Academy of Sciences; Changzhou Institute of Technology Research for Solid State Lighting)
Fan, Xue-Jun (Lamar University)
Zhang, Kouchi (TU Delft Electronic Components, Technology and Materials)

Date

2017-08-09

Abstract

In this paper, the heat transfer performance of the multi-chip (MC) LED module is investigated numerically by using a general analytical solution. The configuration of the module is optimized with genetic algorithm (GA) combined with a response surface methodology. The space between chips, the thickness of the metal core printed circuit board (MCPCB), and the thickness of the base plate are considered as three optimal parameters, while the total thermal resistance (R_tot) is considered as a single objective function. After optimizing objectives with GA, the optimal design parameters of three types of MC LED modules are determined. The results show that the thickness of MCPCB has a stronger influence on the total thermal resistance than other parameters. In addition, the sensitivity analysis is performed based on the optimum data. It reveals thatR_tot increases with the increased thickness of MCPCB, and reduces as the space between chips increases. The effect of the thickness of base plate is far less than that of the thickness of MCPCB. After optimization, three types of MC LED modules obtain lower T_j andR_tot. Moreover, the optimized modules can emit large luminous energy under high-power input conditions. Therefore, the optimization results are of great significance in the selection of configuration parameters to improve the performance of the MC LED module.

Subject

genetic algorithm
Multi-chip LED module
optimization
response surface methodology
thermal resistance
OA-Fund TU Delft

To reference this document use:

http://resolver.tudelft.nl/uuid:1397c49e-4df9-4ff2-84d7-6a8511757062

DOI

https://doi.org/10.1109/ACCESS.2017.2737638

ISSN

2169-3536

Source

IEEE Access, 5, 16459-16468

Part of collection

Institutional Repository