Audio Synthesis and Sound Quality of Automotive Air-Conditioning Systems

2017 ◽  
Author(s):  
Antoine Minard ◽  
Christophe Lambourg ◽  
Patrick Boussard ◽  
Olivier Cheriaux
Keyword(s):  
Air Conditioning ◽  
Sound Quality ◽  
Automotive Air Conditioning ◽  
Air Conditioning Systems

A Semantic Differential for Evaluating the Sound Quality of Fan Systems

2017 ◽  
Author(s):  
Carolin Feldmann ◽  
Thomas Carolus ◽  
Marc Schneider
Keyword(s):  
Principal Component ◽  
Semantic Differential ◽  
Sound Quality ◽  
Heat Pumps ◽  
First Case ◽  
Objective Metrics ◽  
Main Components ◽  
Air Conditioning Systems ◽  
The University

Fans are main components e.g. in heating, ventilating and air conditioning systems for vehicles or buildings, cooling units of engines and electronic circuits, and household appliances such as kitchen exhaust hoods or vacuum cleaners. End-users increasingly demand a high sound quality of their system or device. The overall objective of a recent research project at the University of Siegen is a multidimensional assessment of fan sound quality. In a first step an advanced novel semantic differential for the assessment of fan-related sounds is established with the aid of carefully designed jury tests. Eventually, this semantic differential is employed for sound quality jury tests of fans in kitchen exhaust hoods, heat pumps and air purifiers as a first case. Finally, a prediction model is suggested, which relates the outcome from the jury tests to objective metrics. A principal component analysis is carried out and yields five main assessment criteria with 23 relevant adjective scales. The results show that the perceived sound quality of fan systems is mainly determined by the loudness and tonality of the sound. The spectral content (represented by the sharpness) as well as the time structure (represented by the roughness) have no significant impact on perceived sound quality of the fan systems investigated.

scholarly journals Refrigerating fluid with a low global warming potential for automotive air conditioning systems in summer

2021 ◽  
pp. 45-45
Author(s):  
Zhaofeng Meng ◽  
Yin Liu ◽  
Dingbiao Wang ◽  
Long Gao ◽  
Junhai Yan
Keyword(s):  
Global Warming ◽  
Global Warming Potential ◽  
Air Conditioning ◽  
Cooling Capacity ◽  
Automotive Air Conditioning ◽  
Discharge Temperature ◽  
Air Conditioning Systems ◽  
Low Global Warming Potential ◽  
Lower Discharge

Refrigerants with low global warming potential (GWP) are much needed in automotive air conditioning systems. This paper compares two refrigerants, R134a (GWP=1300) and R513A (GWP=573) experimentally. The results show that the latter has lower cooling capacity, lower COP and lower discharge temperature than the former, revealing that R513A is a promising replacement of its high GWP partner.

scholarly journals Data Analysis and Modeling of Chilled Water Loops in Air Conditioning Systems

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Zhida Zhao ◽  
Nanyang Yu ◽  
Tao Yu ◽  
Haofei Zhang
Keyword(s):  
Air Conditioning ◽  
Training Data ◽  
Local Optimum ◽  
Ann Model ◽  
Nonlinear Variation ◽  
Mean Squared Errors ◽  
Chilled Water ◽  
Air Conditioning Systems ◽  
Speed Simulation

Artificial neural network has been widely used in air conditioning systems as an effective method for predicting parameters, and the accuracy of ANN model relies on training data and network structure. In order to increase the quality of chilled water loops model, this paper develops an optimal data processing algorithm combining Kalman filtering with particle swarm optimization to compensate for uncertain factors and disturbances of collected data from the case building and establishes the nonlinear variation trend database. Based on Elman and BP neural networks, this paper proposes the improved network structures to avoid the local optimum predicted value of chilled water loops and increase data training speed. Simulation results show that this algorithm improves the data accuracy of current percentage (CP) of chillers and chilled water temperatures 12% and 9%. Compared with Elman and BP models, mean absolute errors of CP improved models are improved 24.1% and 10.3%, and mean squared errors of water temperature improved models are improved 5.2% and 4.8%. For the purpose of energy conservation control in air conditioning systems, this work has an application value and can be used for predicting other parameters of buildings.

scholarly journals The Experimental Assessment of R134a and Its Lower GWP Alternative R1234yf in an Automobile Air Conditioning System

2019 ◽  
Vol 25 (12) ◽  
pp. 1-14
Author(s):  
Rafah Hussain ◽  
Issam Mohammed Ali
Keyword(s):  
Ambient Temperature ◽  
Air Conditioning ◽  
Cooling Capacity ◽  
Air Conditioning System ◽  
Automotive Air Conditioning ◽  
Nominal Capacity ◽  
Automotive Air Conditioning System ◽  
And Performance ◽  
Air Conditioning Systems ◽  
Main Operating

Reducing global warming potential (GWP) of refrigerants is needed to the decrease of ozone-depleting of refrigeration systems leakages. Refrigerant R1234yf is now used to substitute R134a inside mobile air conditioning systems. Thermodynamic properties of R1234yf are similar to R134a. Also, it has a very low GWP of 4, compared to 1430 for R134a, making it a proper choice for future automobile refrigerants. The purpose of this research is to represent the main operating and performance differences between R1234yf and R134a. Experimental analysis was carried out on the automotive air conditioning system (AACS) with 3 kW nominal capacity, to test and compare the performance of R134a with R1234yf. Experiments were accomplished for both refrigerants in almost the same working conditions and procedure with a range of ambient temperature varied from 26oC to 50oC. Parameters studied were ambient temperature, type of refrigerant in the system at compressor speed 1450 rpm, and internal thermal loads of passenger room. The performance characteristics of the system, including COP and cooling capacity, were studied by changing different parameters. The results show that COP of R134a is higher than R1234yf by 12.6%, while the refrigeration effect of R134a is higher than R1234yf by 25%. This shows that R1234yf is a suitable and good candidate for drop-in replacement of R134a in AACS.

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