Phosphor-converted LED modeling using near-field chromatic luminance data.

A new method of creating a source model of a phosphor-converted white LED is demonstrated. It is based on a simple phosphor model, of which some key parameters have been obtained from measuring the near-field chromatic and luminance characteristics of a complete LED. The accuracy of the model is verified by measurements and simulations on an LED with a ball lens as primary optic.

Implementing dynamic daylight spectra with light-emitting diodes.

Algorithms for selecting LEDs to imitate a group of daylight spectra, instead of fixed-spectrum lighting, are based on minimizing two indices. The first index related to the LEDs only is minimized for determining LED candidates. Minimizing the second index obtained by applying the daylight spectra to the candidates achieves a minimax solution. The sum of the second indices of the daylight spectra can be well approximated by that of the average spectrum of the daylight spectra and is treated as a target spectrum for the LED selection. A pruning process is followed to delete redundant LEDs.

Optimal selection of commercial sensors for linear model representation of daylight spectra.

The average spectral power distribution of a set of measured daylight spectra, E(av)(lambda), is used for preliminary screening to select optimal sensor sets for daylight recovery. Spectra quite different from E(av)(lambda) are applied to the screened sets to obtain minimum total spectral error, which is closely related to recovery metrics but not to the coefficient of error. All basis functions should be utilized to make these two errors equal, to predict precisely the best sensor set, and to extend a set of few sensors to a set of many sensors. These are not acquirable by an exhaustive full search method.