Performance testing and optimization of a split-type air conditioner with evaporatively-cooled condenser

Atmaca, İbrahim; Şenol, Ali; Çağlar, Ahmet

doi:10.1016/j.jestch.2021.09.010

Cited by 21 publications

(8 citation statements)

References 33 publications

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“…While the comparisons of average daily consumed energy-saving between automatic and manual systems using the same computation methods were 1.66 kWh (20.24%), 1.78 kWh (22.14%), and 1.68 kWh (20.44%), respectively. Furthermore, these energy savings were higher than the adaptive model conserved energy, 8.6% [6], stratum ventilation, 6.4% [12], split-type AC evaporative cooling of condenser,4%-12.4% [14], and BEV balance on energy-saving and thermal comfort, 10% [15]. Nevertheless, these energy savings were in ranges to extended utilizing air re-circulation, 11%-30% [7], 15% on lightweight thermoelectric, [9], energy efficiency improvements in three cities, 12.3%, 38.5%, and 221.9% [13], AC included home appliances using a hybrid PV, diesel generator and batteries, 20% [16] and using PCRC, 18% [20].…”

Section: Discussionmentioning

confidence: 92%

“…These values of the energy-saving were lower than that of the dynamic setting temperature, 59%.1% [4], ventilation and variation law, 30% [5], M-cycle evaporative cooling, 38% [8], exhausted air recovering energy, 50% [10], preference map, 57.38% [25], 33%-44% energy saving of the PMV-based temperature control system [27], and remote computer room, 40% [28]. However, these values of percentage energy saving are more significant than that of the adaptive model, 8.6% [6], with stratum ventilation, 6.4% [12], and 4%-12.4% power saving using the condenser evaporative cooling of split-type AC [14]. Nevertheless, these values were in ranges or around utilizing air extended driving range re-circulation, 11%-30% [7], lightweight thermoelectric, 15% [9], 12.3%, 38.5%, and 221.9% energy efficiency improvement [13], IoT for computer rooms, 16.64% [28], IoT prototype in the HVAC system, 20% [29], and 16.4% energy saving utilized chilled water loop and air handling process [32].…”

Section: Automatic Testingmentioning

confidence: 99%

“…It spent 35%-42% more electricity for householders [2], and even HVAC is utilized to provide grid services [3]. Many efforts on energy saving of air conditioning systems have been conducted, such as dynamic setting temperature, 59.1% of energy consumption saving [4], ventilation and variation law of 30% reducing energy consumption [5], 8.6% of conserved energy of adaptive model [6], 11%-30% extended driving range of utilizing air re-circulation [7], 38% reduced electric energy of M-cycle evaporative cooling [8], 15% potential energy saving of lightweight thermoelectric [9], 50% recover energy of exhausted air [10], PCA-GMMs has 99% fault diagnosis correct rates [11], 6.4% reducing energy consumption with stratum ventilation [12], 12.3%, 38.5% and 221.9% energy efficiency improvements in three cities [13], 4%-12.4% decreasing power consumption using a evaporative cooling of condenser of a split-type AC [14], balance on energy saving and thermal comfort on a BEV by 10% slow down, energy gain reached 2.2 kWh [15], and 20% reducing fuel consumption on home appliances (including ACs) using a hybrid PV, diesel generator and batteries [16].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

IoT-Based Air Conditioning Control System for Energy Saving

Waluyo¹,

Widura²,

Hadiatna³

et al. 2023

Int. J. Adv. Sci. Eng. Inf. Technol.

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A high portion of electric consumption is air conditioning in householders or offices, reaching 42%. Therefore, it is necessary to automatically regulate air conditioning operations for energy saving using a control system, usually involving its hardware. As another option, the control system also involves electronic devices and software. This research developed an automatic control system using an ESP32 microcontroller integrated into the Blynk-based internet of things (IoT) for energy-saving air conditioning. The ESP32 was programmed using Arduino IDE and combined with a motion sensor to maximize energy saving. The motion sensor was a trigger to turn on the system. The recorded data were current, voltage, power, temperature, and motion detection. Based on the recorded power, the consumed energy was computed using trapezoidal and Simpson's composite rules of numerical integrations and ordinary methods. The testing was conducted in conventional, manual, and automatic operations. The yielded automatic control system operated adequately. The testing results revealed that the automatic operation saved 1.15 kWh (15.00%),0.99 kWh (13.66%), and 1.14 kWh (14.87%) average daily energy compared to the conventional operation, respectively, by using the ordinary, Simpson's composite rule, and trapezoidal composite rule computations. While the automatic compared to the manualmethodssaved1.68 kWh (20.44%), 1.78 kWh (22.14%), and 1.66 kWh (20.24%), respectively, for the same computations. Thus, the automatic system considerably saved energy compared to conventional and manual operations. Moreover, these energy savings were also higher than some previous research on air conditioning energy savings.

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Section: Discussionmentioning

confidence: 92%

Section: Automatic Testingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

IoT-Based Air Conditioning Control System for Energy Saving

Waluyo¹,

Widura²,

Hadiatna³

et al. 2023

Int. J. Adv. Sci. Eng. Inf. Technol.

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show abstract

“…Figure 1 shows the schematic diagram and block diagram of the split-type of air conditioner in which the main components are a compressor, condenser, evaporator, and expansion valve. The vapor compression refrigeration cycle [18]- [20] can be seen in the pressure-enthalpy diagram in Figure 1(a). Consider the equation of vapor compression from Figure 1(b) at the state points as follows.…”

Section: Methods 21 System Description and Equationmentioning

confidence: 99%

Experimental study of compressor electric current detection for a split-type air conditioner affects energy savings

Saengchandr

Sukontanakarn

Waiyagan

2023

IJECE

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The paper presents an experimental study that aims to measure the compressor electric current of a split-type air conditioner for analyzing the various abnormal condition of the R-32 refrigerant pressure, especially for detecting compressor electric current while occurring dirt in the evaporator coil and condenser coil. The method was to install sensor devices to measure the temperature and humidity of inlet air and outlet air, and the velocity of the air outlet of the evaporator unit. In condenser unit was to measure the electric current compressor and electric power input. All data from sensors send to the Arduino board and using Parallax Data Acquisition (PLX-DAQ) Excel Macro for the record. The results show physical behavior and the changing of compressor electric current according to the abnormal condition of the refrigerant system, blocking of condenser and evaporator coil.

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“…As a result, the effect of outdoor air temperature and relative humidity on the amount of useful heat recovery will be analysed, and the effect of temperature and humidity on HRV devices will be examined. In addition, the result of which temperature and humidity value affects which HRV device will be examined [ 16 ].…”

Section: Methodsmentioning

confidence: 99%

Analysis of direct expansion heat recovery ventilation devices by orthogonal optimization method

Coskun

YALIN

Atmaca

2023

J Therm Anal Calorim

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Heat recovery ventilation devices include rectangular plate cross-flow, hexagonal plate combined counter and cross-flow, rotary wheel sensible, sorption rotor hybrid sensible and latent heat exchanger. Currently, existing studies have produced no clear findings on which climatic conditions latent heat recovery would be optimal, and therefore sought to determine in which climatic conditions it would be suitable to use devices that perform latent heat recovery. This study analysed the performance of different heat recovery devices in different climatic conditions in a ventilation project of a sample hotel building. In the case study, while there is a useful heat recovery between 44.01 and 58.68 kW at low outdoor temperatures in devices with only sensible heat transfer, this value increases up to 158.42 kW, as the outdoor temperature rises. In the heat recovery device providing latent heat transfer, the amount of useful heat recovery varies between 51.34 and 352.16 kW at low outdoor temperatures, depending on the outdoor relative humidity, while this amount increases to 411.26 from 773.25 kW at high outdoor temperatures. Outdoor temperature and humidity levels required for latent heat recovery was also determined by orthogonal optimization method. By using the orthogonal optimization, the study found that under conditions of high temperature that exceeds 35 °C in outdoor ambient temperature, and high humidity that exceeds 60% relative humidity, usage of latent heat recovery devices caused significant differences in total heat recovery ratio. Analysis also concludes that these devices can be used under these conditions.

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Performance testing and optimization of a split-type air conditioner with evaporatively-cooled condenser

Cited by 21 publications

References 33 publications

IoT-Based Air Conditioning Control System for Energy Saving

IoT-Based Air Conditioning Control System for Energy Saving

Experimental study of compressor electric current detection for a split-type air conditioner affects energy savings

Analysis of direct expansion heat recovery ventilation devices by orthogonal optimization method

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