Enhancing Energy Efficiency in Air Handling Units Through AI Driven Optimization

Year : 2024 | Volume : 02 | Issue : 02 | Page : 19 28
    By

    Dhanush M,

  • Shivashankar Hiremath,

  • Subramanya R. Prabhu B,

  1. Student, Department of Mechatronics, Manipal Institute of Technology, Manipal Academy Higher Education (MAHE), Manipal, Karnataka, India
  2. Professor, Department of Mechatronics, Manipal Institute of Technology, Manipal Academy Higher Education (MAHE), Manipal, Karnataka, India
  3. Professor, Department of Mechatronics, Manipal Institute of Technology, Manipal Academy Higher Education (MAHE), Manipal, Karnataka, India

Abstract

This research explores the implementation of artificial intelligence (AI) in enhancing the energy efficiency of Air Handling Units (AHUs) in manufacturing facilities. The study proposes a comprehensive solution architecture that incorporates temperature and humidity sensors within AHUs, utilizing RS485 for data communication. The collected data undergoes exploratory analysis, which informs the training of a decision tree algorithm, chosen for its accuracy and compatibility with edge gateways. The algorithm’s predictions enable real-time adjustments to the duty cycle of variable frequency drives (VFDs), effectively optimizing energy usage. In a comparative analysis, the project showcases the transition from traditional belt-driven fans with a 60% efficiency to advanced direct-driven energy-efficient axial flow fans boasting a 90% efficiency. This upgrade results in substantial energy savings of up to 35%, significantly reducing operational costs and minimizing environmental impact. The AI model classifies temperature trends into nine distinct classes, with corresponding actions that the system takes to maintain optimal performance. The implementation of the decision tree model not only enhances energy efficiency but also contributes to a remarkable decrease in CO2 emissions, aligning with sustainability goals. This research emphasizes the importance of AI in HVAC systems, demonstrating how intelligent decision-making can lead to improved performance, cost savings, and environmental benefits. Furthermore, the findings serve as a foundation for future advancements in energy management within industrial settings, underscoring the critical role of AI in driving sustainable practices.

 

Keywords: Energy efficiency, air handling units (AHUs), artificial intelligence (AI), decision tree algorithm, variable frequency drive (VFD), sustainable manufacturing

[This article belongs to International Journal of Industrial and Product Design Engineering ]

How to cite this article:
Dhanush M, Shivashankar Hiremath, Subramanya R. Prabhu B. Enhancing Energy Efficiency in Air Handling Units Through AI Driven Optimization. International Journal of Industrial and Product Design Engineering. 2024; 02(02):19-28.
How to cite this URL:
Dhanush M, Shivashankar Hiremath, Subramanya R. Prabhu B. Enhancing Energy Efficiency in Air Handling Units Through AI Driven Optimization. International Journal of Industrial and Product Design Engineering. 2024; 02(02):19-28. Available from: https://journals.stmjournals.com/ijipde/article=2024/view=192166


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Regular Issue Subscription Original Research
Volume 02
Issue 02
Received 28/10/2024
Accepted 20/11/2024
Published 30/11/2024
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