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Air conditioning system is used for various application, in passenger car it gives comfort to the passenger. Now a days huge advancement have been included in the air conditioning system, especially automatic air conditioning system plays a vital role in passenger car. These air conditioning systems are performing well and have the capability of maintaining the temperature for long time with energy consumption. However, in some vehicle the performance of these air conditioning system is not achieved, while some vehicle achieved better performance. In later study it is found that, the structure of vehicle body also influence the performance of air conditioning system. In some structure the air conditioning air-flow a long distance in short time and have the capability to enhance the air conditioning performance. It is also found that the air conditioning performance can be improved by the structure of vehicle body. In this paper, we considered an Indian small budget car. The structure of the car is slightly modified and replaced the position of the air conditioning outlet. Then the residual temperature inside the car is analyzed with and without air conditioning. Here the CFD is used to analysis the temperature inside car at various position.

In both centralized and decentralized air-conditioning systems, the performance, sustainability, and efficiency of the systems in delivering thermal comfort within a specific area are assessed as part of the air thermal management platform evaluation process. The evaluation of air thermal management platforms entails a thorough examination of numerous elements, customized to the unique features of these systems, such as system components, energy efficiency, control systems, maintenance procedures, and environmental concerns. The study considers mathematical modeling of energy-efficient techniques based on meteorological data of cooperative centralized and decentralized air-conditioning systems for external air recirculation treatment. Three systems were considered: an independently functioning central air conditioner, a central system functioning together with a local air conditioner, and a central system operating together with an adiabatic humidifier. Technological aspects of cycle performance are shown to be dependent on the acceptable design capacity of the air cooler and the adiabatic humidifier air wet-bulb temperature limit. Increasing the setting capacities of the air cooler to 0.00786 kg m −2  s −1 and the adiabatic humidifier to 0.03864 kWh, the air flow rate decreases from 0.0072 to 0.004 kg m −2  s −1 , and when the setting capacities of the air cooler are 0.01011 kg m −2  s −1 and the adiabatic humidifier is 0.04831 kWh, the air flow rate decreases to a minimum limit of 0.002 kg m −2  s −1 . Comparing the annual heating, cooling, and humidification load consumption without and with utilization of the second air recirculation, for the heating load 39.48 and 5.01 kWh, the costs increased by a factor of 7.9; for the cooling load 1850 and 1320 kWh, the costs increased 1.4 times; and for the moisture load 331.5 and 1245 kg m −2  s −1 , the costs decreased 3.8 times. The research conducted has led to the development of a methodology that combines the justification of energy-saving modes with formulated climatic tables and a probabilistic-statistical model. This methodology facilitates the selection of subsystem equipment’s AC setting capacities, the calculation of heating, cooling, and moisture load consumption at various times, and the technological scheme for heating and humidity air treatment. The refined AC can operate at peak efficiency and reduce energy loss thanks to this iterative approach. Moreover, this method's progressive design enables it to gradually increase in efficiency over time.

The significant energy consumption systems in the world are air conditioning devices. This issue becomes a crisis when the required energy needs in the world is met by fossil fuels. In this study, conventional and solar air conditioning systems are compared. Real weather data of the city of Baghdad-Iraq were used. Matlab has been used to model the cooling power of electric chillers and solar radiation. Results showed that the use of a solar cooling system with a capacity of 2.5 kW can reduce the energy consumption by 65% compared to conventional air conditioning systems. Reducing energy consumption will reduce customer costs and profitability and reduce environmental emissions to a significant extent, which indicates the effectiveness of the proposed method. The proposed model reduces the daily energy demand, the energy cost, and the amount of CO2 emission as well. This comparison gives a significant indictor to the energy efficiency market.

The number of people who use airplanes has increased year by year. However, most passengers have a feeling of discomfort during a long-distance flight. One of the factors is the lack of temperature control in the cabin. If air conditioning control can be adjusted to each passenger’s thermal sensation, the whole comfort in the cabin would be improved. Therefore, a personal air conditioning control method is required for airplanes. In order to implement personal air conditioning adapted to individual thermal sensation, this study proposes a seat-type air conditioning system that adjusts the temperature to each part of the body and aims to clarify the appropriate temperature setting in consideration of individual thermal sensation. As a result, the appropriate degree of temperature setting change was clarified based on the thermal sensation index. It was found that changing the temperature setting by 2.5 °C per scale of the thermal sensation improved the passenger’s comfort. Furthermore, people who tend to feel cold were found to be more sensitive to temperature changes. It is concluded that personalized air conditioning is possible based on individual thermal sensitivity characteristics. For prospects, it is desirable to study a system that automatically predicts the thermal sensation taking into account individual thermal sensitivity characteristics.

A large input delay, parametric uncertainties, matched disturbances and mismatched disturbances exist extensively in variable air volume air-conditioning systems, which can deteriorate the control performance of the room temperature and even destabilize the system. To address this problem, an adaptive-gain command filter control framework for the room temperature of variable air volume air-conditioning systems is exploited. Through skillfully designing an auxiliary system, both the filtered error and the input delay can be compensated concurrently, which can attenuate the effect of the filtered error and the input delay on the control performance of the room temperature. Then, a smooth nonlinear term with an adjusted gain is introduced into the control framework to compensate for parametric uncertainties, matched disturbances and mismatched disturbances, which relieves the conservatism of the controller gain selection. With the help of the Lyapunov theory, both the boundedness of all the system signals and the asymptotic tracking performance for the room temperature can be assured with the presented controller. Finally, the contrastive simulation results demonstrate the validity of the developed method.

Water flow rate plays an important role in the modeling prediction, fault detection and diagnosis, and performance optimization of the variable water flow air‐conditioning (VWFAC) system. However, flowmeters employed by the system's terminals have not been widely used in engineering applications for the constraints in installation space and high installation and retrofit costs. Therefore, in this study, a terminal flow rate estimation method is proposed for the VWFAC system to reduce the dependency on flowmeters. The water flow rate estimation model is developed based on the flow resistance characteristics inside the air handling unit (AHU) and was trained and verified at the Monitoring and Control Laboratory established in the Dalian University of Technology. The results indicate that the maximum root‐mean‐square error (RMSE) during the training and validation sessions are 0.038 m3/h and 0.028 m3/h, respectively, while the corresponding mean absolute percentage error (MAPE) are below 1.4% and 6.5%, which is acceptable for engineering applications. To improve the flow rate estimation accuracy of the model, water temperature, water flow rate, and pressure difference are suggested to cover a wide varied range during the training session as much as possible. Systematic error is an important index in determining the demands for sensor's accuracy class. According to the results of water flow rate, the systematic errors of the estimates are ranged between 0.51% and 0.76%, only about 1/4 to 1/3 of the measurements systematic errors. Based on the error propagation theory, the water flow rate estimates would be reliable if the systematic error of the pressure measurements does not over twice that of the water flow rate measurements. This flow rate estimation method can be further applied to other thermal engineering systems to bring considerable economic benefits for engineering applications. The massive use of flowmeters to monitor the terminal (represented by air handling unit, AHU) water flow rate of the variable water flow air‐conditioning system can results in high installation and retrofit costs in engineering applications. To reduce this cost, a new terminal flow rate estimation method is proposed in this paper based on the flow resistance property inside the AHU. The experimental results indicate that water temperature sensors and differential pressure sensors with specified precision class can be used to replace the flowmeter to measure the terminal water flow rate accurately.

Electric utility companies (EUCs) play an intermediary role of retailers between wholesale market and end-users, maximizing their profits. Retail pricing can be well deployed with the support of EUCs to promote demand response (DR) programs for heating, ventilating, and air-conditioning (HVAC) systems in commercial buildings. This paper proposes a pricing strategy to help EUCs and building operators achieve an optimal DR of price-elastic HVAC systems, considering peak load reduction. The proposed strategy is implemented by adopting a bi-level decision model. The nonlinear thermal response of an experimental building room is modeled using piecewise linear equations, which helps convert the bi-level model to the single-level model. The pricing strategy is implemented considering a time-of-use (TOU) pricing scheme, leading to low price volatility. Case studies are conducted for two types of load curves and the results demonstrate that the proposed strategy helps EUC promote the price-based DR of the commercial buildings for conventional load curves. However, EUC cannot reduce the peak load on duck curve caused by the large introduction of photovoltaic generators, even with price-sensitive HVAC systems in commercial building. This will be addressed in future studies by inducing DR participation of HVAC systems in residential buildings.

A vacant unit, once used by a Portuguese Deli, was converted to a bar/music room in Toronto. The unit was divided into two spaces along its north-south axis. The western portion was designed as a music room that would provide a performance space from a solo artist to a Jazz combo to a small rock band. The eastern part was designed as a regular bar/dining area. The plan also called for a microbrewery unit at the back of the unit. The bar music can be loud, while the music room can be pianissimo to forte depending on the type of performance. The acoustical design aspects are critical for the music room. In addition, the acoustical separation between the two spaces is equally important. The music room/bar is currently in use. The design results are compared to actual field measurements. The results showed that the music venue performed satisfactorily. The acoustical separation between the music venue and the bar/restaurant was better than expected other than an installation deficiency of the south side sound lock doors. The background sound along the northern portion was NC-35 or less. However, the southern portion’s background sound exceeded NC-35 due to the hissing of the return air grille. The acoustical design and the performance results of the music venue-bar/restaurant are presented in this paper.

Over the past two decades, extensive research has elucidated the significant contributions of various nanomaterial such as metals, metal oxides, carbon nanotubes (single, double, and multi-wall), nanowires, and graphene in improving the tribological and thermal properties of AC & R systems used in both industrial and domestic settings. A recent research paper has specifically focused on the performance enhancement of AAC through the use of Nano-oxides, namely CuO, ZnO, and TiO2, employing mathematical modeling. This study investigates how dispersed Nano-oxides of CuO, ZnO, and TiO2, when added to a base of POE lubricant and HFC-R134a refrigerant, influence the performance of automobile air conditioning systems. The primary focus is on viscosity, heat transfer rate, and thermal conductivity of the working medium. The experimental results are compared with tested data, and further analysis is conducted using TK Solver 6.0 and Origin Lab software. The findings demonstrate that the incorporation of these Nano-oxides has a positive impact on thermal-physical properties (k-Thermal conductivity, ρ-viscosity, ρ-density and Cp-specific-heat) and heat transfer characteristics compared to systems without Nano-materials. Furthermore, there is a notable increase in Coefficient of Performance (COP) ranging from 23–29% with varying volume concentrations of Nano-oxides (0.5% to 2.5%) under atmospheric temperature conditions. Consequently, the combination of copper oxide, Zinc Oxide, and Titania nanoparticles with HFC-R134a as well as R1234ze (E) proves to be an effective approach for optimizing refrigerant properties and improving the performance of automobile air conditioning systems. Thus, Nano-oxides dispersion offer a promising solution for enhancing energy efficiency and reducing the reliance on conventional energy sources in thermal systems.

The efficient management of Heating Ventilation and Air Conditioning (HVAC) systems in smart buildings is one of the main applications of the Internet of Things (IoT) paradigm. In this paper we propose an IoT based architecture for the implementation of Model Predictive Control (MPC) of HVAC systems in real environments. The considered MPC algorithm optimizes on line, in a closed-loop control fashion, both the indoor thermal comfort and the related energy consumption for a single zone environment. Thanks to the proposed IoT based architecture, the sensing, control, and actuating subsystems are all connected to the Internet, and a remote interface with the HVAC control system is guaranteed to end-users. In particular, sensors and actuators communicate with a remote database server and a control unit, which provides the control actions to be actuated in the HVAC system; users can set remotely the control mode and related set-points of the system; while comfort and environmental indices are transferred via the Internet and displayed on the end-users’ interface. The proposed IoT based control architecture is implemented and tested in a campus building at the Polytechnic of Bari (Italy) in a proof of concept perspective. The effectiveness of the proposed control algorithm is assessed in the real environment evaluating both the thermal comfort results and the energy savings with respect to a classical thermostat regulation approach.