Model Identification and Wall-Plug Efficiency Measurement of White LED Modules
Ahmed Zurfi1 & Jing Zhang1 Show affiliations
- University of Arkansas at Little Rock, United States
American Journal of Engineering and Applied Sciences, Volume 9, Issue 2, pp. 412–419 · doi.org/10.3844/ajeassp.2016.412.419
Abstract
In this study, an experimental method is developed to measure the Wall-Plug efficiency of white LED modules without using any apparatus or sensors to measure the intensity of light. The tested LED module consists of a white LED chip-on-board affixed on a heatsink. The proposed method is mainly based on thermal and electrical models of the LED module. Measurements of thermal and electrical power are implemented instead of optical power. The presented method is not intended to replace the existing conventional techniques used to obtain optical and thermal characteristics of LEDs, but it provides a simplified way to evaluate the Wall-Plug efficiency of white LED modules under pragmatic operational conditions. In this method, the parameters of the wall-plug efficiency model of an LED-heatsink module are identified. Then, the model is applied to evaluate the efficiency at operating conditions of different heatsink temperature and input current. A 9 W Cree© XLamp white LED was tested at an ambient temperature of 23°C±1. Experimental results revealed that the parameters of the efficiency model can be extracted using the proposed method without measurement of optical power.
Licence and reuse
Open access. This article is licensed under a Creative Commons Attribution 3.0 Licence (CC BY 3.0), as printed on the article, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original authors and the source. No permission is needed.
How to reuse this articleResponses (0)
About this article
Zurfi, A. & Zhang, J. (2016). Model Identification and Wall-Plug Efficiency Measurement of White LED Modules. American Journal of Engineering and Applied Sciences, 9(2), 412–419. https://doi.org/10.3844/ajeassp.2016.412.419
- Licence
- CC BY 3.0
- Issue
- Volume 9, Issue 2
- Policies
- Editorial independenceUse of generative AIData availabilityAppeals and complaints
- Version
- Version of record
