IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i20p7679-d945757.html
   My bibliography  Save this article

Optimization Process Applied in the Thermal and Luminous Design of High Power LED Luminaires

Author

Listed:
  • Jose Luiz F. Barbosa

    (Electrical, Mechanical & Computer Engineering School, Federal University of Goias, Goiania 74605-010, Brazil
    Studies and Researches in Science and Technology Group, Federal Institute of Goias, Goiania 74055-110, Brazil)

  • Antonio P. Coimbra

    (Institute of Systems and Robotics, University of Coimbra, 3030-290 Coimbra, Portugal)

  • Dan Simon

    (Department of Electrical Engineering and Computer, Cleveland State University, Cleveland, OH 44115, USA)

  • Wesley P. Calixto

    (Electrical, Mechanical & Computer Engineering School, Federal University of Goias, Goiania 74605-010, Brazil
    Studies and Researches in Science and Technology Group, Federal Institute of Goias, Goiania 74055-110, Brazil
    Institute of Systems and Robotics, University of Coimbra, 3030-290 Coimbra, Portugal)

Abstract

This work proposes the design of an optimization method for high-power LED luminaires with the introduction of new evaluation metrics. A luminaire geometry computational method is deployed to conduct thermal and optical analysis. This current effort novels by designing a tool that enables the analysis of uniformity for individual luminaire over the target plane in accordance with international regulatory standards. Additionally, adequate thermal management is conducted to guarantee nominal operation standard values determined by LED vendors. The results of this optimization method present luminaire models with different geometries that allow the stabilization of the temperature within the safety and uniform illuminance distribution thresholds. The resulting solution proposes the design of a 2 × 2 HP-LED rectangular luminaire. During simulations, the temperature of the LED reaches a maximum value of 73.9 ∘ C in a steady state with a uniform index of 0.228 for its individual luminaire. The overall uniform index identified for two separate and adjacent luminaire points in a pedestrian walk is 0.5413 with a minimal illuminance of 36.95 lx, maximum illuminance of 93.65 lx and average illuminance of 68.27 lx. Overall, we conclude that the currently adopted metric, which takes into consideration only the ratio between the minimum and the average illuminance, is not efficient and it cannot distinguish different luminaire geometry standards according to their uniform illuminance distribution. The metric proposed and designed in this work is capable of evaluating illuminance and thermal threshold criteria, as well as classifying different sorts of luminaries.

Suggested Citation

  • Jose Luiz F. Barbosa & Antonio P. Coimbra & Dan Simon & Wesley P. Calixto, 2022. "Optimization Process Applied in the Thermal and Luminous Design of High Power LED Luminaires," Energies, MDPI, vol. 15(20), pages 1-28, October.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:20:p:7679-:d:945757
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/20/7679/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/20/7679/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jose Luiz F. Barbosa & Dan Simon & Wesley P. Calixto, 2017. "Design Optimization of a High Power LED Matrix Luminaire," Energies, MDPI, vol. 10(5), pages 1-18, May.
    2. H. Christopher Frey & Sumeet R. Patil, 2002. "Identification and Review of Sensitivity Analysis Methods," Risk Analysis, John Wiley & Sons, vol. 22(3), pages 553-578, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Makam, Vaishno Devi & Millossovich, Pietro & Tsanakas, Andreas, 2021. "Sensitivity analysis with χ2-divergences," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 372-383.
    2. S. Cucurachi & E. Borgonovo & R. Heijungs, 2016. "A Protocol for the Global Sensitivity Analysis of Impact Assessment Models in Life Cycle Assessment," Risk Analysis, John Wiley & Sons, vol. 36(2), pages 357-377, February.
    3. Emanuele Borgonovo, 2006. "Measuring Uncertainty Importance: Investigation and Comparison of Alternative Approaches," Risk Analysis, John Wiley & Sons, vol. 26(5), pages 1349-1361, October.
    4. Carla L. Simões & Ricardo Simoes & Ana Sofia Gonçalves & Leonel J. R. Nunes, 2023. "Environmental Analysis of the Valorization of Woody Biomass Residues: A Comparative Study with Vine Pruning Leftovers in Portugal," Sustainability, MDPI, vol. 15(20), pages 1-16, October.
    5. Retno Agustarini & Yetti Heryati & Yelin Adalina & Wahyu Catur Adinugroho & Dhany Yuniati & Rizki Ary Fambayun & Gerhard Eli Sabastian & Asep Hidayat & Hesti Lestari Tata & William Ingram & Aulia Perd, 2022. "The Development of Indigofera spp. as a Source of Natural Dyes to Increase Community Incomes on Timor Island, Indonesia," Economies, MDPI, vol. 10(2), pages 1-30, February.
    6. Sumeet R. Patil & H. Christopher Frey, 2004. "Comparison of Sensitivity Analysis Methods Based on Applications to a Food Safety Risk Assessment Model," Risk Analysis, John Wiley & Sons, vol. 24(3), pages 573-585, June.
    7. Mohammad Reza KHALEGHI & Jamal GHODUSI & Hassan AHMADI, 2014. "Regional analysis using the Geomorphologic Instantaneous Unit Hydrograph (GIUH) method," Soil and Water Research, Czech Academy of Agricultural Sciences, vol. 9(1), pages 25-30.
    8. Abdo Abdullah Ahmed Gassar & Choongwan Koo & Tae Wan Kim & Seung Hyun Cha, 2021. "Performance Optimization Studies on Heating, Cooling and Lighting Energy Systems of Buildings during the Design Stage: A Review," Sustainability, MDPI, vol. 13(17), pages 1-47, September.
    9. Layimar Cegarra & Andrea Colins & Ziomara P Gerdtzen & Marco T Nuñez & J Cristian Salgado, 2019. "Mathematical modeling of the relocation of the divalent metal transporter DMT1 in the intestinal iron absorption process," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-26, June.
    10. Luigi Dolores & Maria Macchiaroli & Gianluigi De Mare, 2022. "Financial Impacts of the Energy Transition in Housing," Sustainability, MDPI, vol. 14(9), pages 1-17, April.
    11. Mariem Ellouze & Jean‐Pierre Gauchi & Jean‐Christophe Augustin, 2010. "Global Sensitivity Analysis Applied to a Contamination Assessment Model of Listeria monocytogenes in Cold Smoked Salmon at Consumption," Risk Analysis, John Wiley & Sons, vol. 30(5), pages 841-852, May.
    12. Sinan Xiao & Zhenzhou Lu & Pan Wang, 2018. "Multivariate Global Sensitivity Analysis Based on Distance Components Decomposition," Risk Analysis, John Wiley & Sons, vol. 38(12), pages 2703-2721, December.
    13. Andreas Binder & Onkar Jadhav & Volker Mehrmann, 2021. "Error Analysis of a Model Order Reduction Framework for Financial Risk Analysis," Papers 2110.00774, arXiv.org.
    14. Babak Jafarizadeh, 2022. "Forecasts of Prices and Informed Sensitivity Analysis: Applications in Project Valuations," Decision Analysis, INFORMS, vol. 19(3), pages 205-219, September.
    15. João Delgado & Simon Pollard & Kerry Pearn & Emma L. Snary & Edgar Black & George Prpich & Phil Longhurst, 2017. "U.K. Foot and Mouth Disease: A Systemic Risk Assessment of Existing Controls," Risk Analysis, John Wiley & Sons, vol. 37(9), pages 1768-1782, September.
    16. Zhou, Yuekuan & Zheng, Siqian & Zhang, Guoqiang, 2020. "Machine-learning based study on the on-site renewable electrical performance of an optimal hybrid PCMs integrated renewable system with high-level parameters’ uncertainties," Renewable Energy, Elsevier, vol. 151(C), pages 403-418.
    17. Andreas Tsanakas & Pietro Millossovich, 2016. "Sensitivity Analysis Using Risk Measures," Risk Analysis, John Wiley & Sons, vol. 36(1), pages 30-48, January.
    18. Marco Aurélio de Oliveira & Antonio Schalata Pacheco & André Hideto Futami & Luiz Veriano Oliveira Dalla Valentina & Carlos Alberto Flesch, 2023. "Self‐organizing maps and Bayesian networks in organizational modelling: A case study in innovation projects management," Systems Research and Behavioral Science, Wiley Blackwell, vol. 40(1), pages 61-87, January.
    19. Jonas Hülsmann & Julia Barbosa & Florian Steinke, 2023. "Local Interpretable Explanations of Energy System Designs," Energies, MDPI, vol. 16(5), pages 1-17, February.
    20. Ye Cao & H. Christopher Frey, 2011. "Assessment of Interindividual and Geographic Variability in Human Exposure to Fine Particulate Matter in Environmental Tobacco Smoke," Risk Analysis, John Wiley & Sons, vol. 31(4), pages 578-591, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:20:p:7679-:d:945757. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.