Abstract
Proper functioning of heating, ventilation, and air conditioning (HVAC) systems is important for efficient thermal management, as well as operational costs. Most of these systems use nonlinear time variances to handle disturbances, along with controllers that try to balance rise times and stability. The latest generation of fuzzy logic controllers (FLC) is algorithm-based and is used to control indoor temperatures, CO2 concentrations in air handling units (AHUs), and fan speeds. These types of controllers work through the manipulation of dampers, fans, and valves to adjust flow rates of water and air. In this paper, modulating equal percentage globe valves, fans speed, and dampers position have been modeled according to exact flow rates of hot water and air into the building, and a new approach to adapting FLC through the modification of fuzzy rules surface is presented. The novel system is a redesign of an FLC using MATLAB/Simulink, with the results showing an enhancement in thermal comfort levels.
Highlights
Ventilation, and air conditioning (HVAC) systems are installed in millions of commercial and noncommercial buildings as a means to provide the desired thermal comfort standards at an affordable cost and with minimal maintenance requirements
Due to the potential these systems have for future energy needs, this paper proposes identifying advanced novel HVAC system models that employ intelligent control algorithms to produce energy savings without sacrificing comfort levels
Control signals are obtained from fuzzy logic controllers (FLC) to reduce error as well as error change
Summary
Ventilation, and air conditioning (HVAC) systems are installed in millions of commercial and noncommercial buildings as a means to provide the desired thermal comfort standards at an affordable cost and with minimal maintenance requirements. Energy saving is a key feature of HVAC systems and is increasing in importance [2, 3]. As the housing and business needs of the developed world generally include buildings that require HVAC systems, the percentage contribution of the total energy consumption of these buildings has increased from 20% to 40% in Western countries [4, 5]. Recent research indicates that intelligent control might be a viable method of achieving optimal comfort levels at high energy efficiency. Due to the potential these systems have for future energy needs, this paper proposes identifying advanced novel HVAC system models that employ intelligent control algorithms to produce energy savings without sacrificing comfort levels. Modeling HVAC systems and components mathematically has been demonstrated in the literature to be a viable approach for designing controls and detecting faults
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