Bayesian Experimental Design for LEDs using Gaussian Processes

被引：0

作者：

Forster, Peter ^{[1
]}

Schoeps, Sebastian ^{[2
]}

Schilders, Wil ^{[1
]}

Boeckhorst, Stephan ^{[3
]}

Mevenkamp, Maximilian ^{[3
]}

机构：

[1] Eindhoven Univ Technol, Eindhoven, Netherlands

[2] Tech Univ Darmstadt, Darmstadt, Germany

[3] Hella GmbH & Co KGaA, Lippstadt, Germany

来源：

2023 29TH INTERNATIONAL WORKSHOP ON THERMAL INVESTIGATIONS OF ICS AND SYSTEMS, THERMINIC | 2023年

基金：

欧盟地平线“2020”;

关键词：

experimental design; LEDs; Gaussian processes; spectral power distribution;

D O I：

10.1109/THERMINIC60375.2023.10325903

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

We present a novel design of experiments approach for LEDs based on Gaussian processes. The method aims to decrease the measurement effort associated with characterizing LEDs based on their spectral power distribution (SPD) and derived quantities of interest (QOIs), such as the luminous flux or color coordinates. It is both easy to implement and based on open source software. We showcase the approach on an example taken from automotive applications. For the considered example, we are able to decrease the total number of measurements by over 75 %, while the model is able to predict the SPD and derived QOIs with relative errors of less than 5 %.

引用

页数：6

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