Jiajie Fan, Kam-Chuen Yung, Michael Pecht
PCB Technology Center, Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
Center for Advanced Life Cycle Engineering (CALCE), University of Maryland, College Park, MD 20740, USA
High power white light emitting diodes (HPWLEDs), with advantages in terms of luminous efficacy, energy saving, and reliability, have become a popular alternative to conventional luminaries as white light sources. Like other new electronic products, HPWLEDs must also undergo qualification testing before being released to the market. However, most traditional qualification tests, which require all devices under testing to fail, are time-consuming and expensive. Nowadays, as recommended by the Illuminating Engineering Society (IES, IES-TM-21-11), many LED manufacturers use a projecting approach based on short-term collected light output data to predict the future lumen maintenance (or lumen lifetime) of LEDs. However, this projecting approach, which depends on the least-square regression method, generates large prediction errors and uncertainties in real applications. To improve the prediction accuracy, we present in this paper a non-linear filter-based prognostic approach (the recursive Unscented Kalman Filter) to predict the lumen maintenance of HPWLEDs based on the short-term observed data. The prognostic performance of the proposed approach and the IES-TM-21-11 projecting approach are compared and evaluated with both accuracy- and precision-based metrics.
Keywords : High power white LEDs; Lumen maintenance; Prognostic-based qualification; Non-linear filter; Recursive Unscented Kalman Filter
Complete article available from the publisher and to the CALCE Consortium Members.