Abstract Today, as people are spending increasing amounts of time in their cars, they have come to recognize that the car should function as a “residential” space. An eco-friendly indoor environment that provides comfort in terms of visual, tactile, and auditory senses is needed for the driver and the passengers. The quality of the car’s indoor environment was evaluated on various factors, such as indoor thermal comfort, indoor air quality, smell, and noise. For the indoor air quality, the typical pollutants that degrade the air quality are $ CO_{2} $, volatile organic compounds, and exhaust gases. Especially, $ CO_{2} $ has a direct relationship with drowsy driving which leads to traffic accidents. There have been many experimental and analytical studies to reduce the level of $ CO_{2} $ in a short time, but analyses of parameters that affect indoor $ CO_{2} $ concentration are insufficient and comprehensive standards for evaluating the car indoor $ CO_{2} $ concentration do not yet exist. In this study, several parameters were selected that can influence the reduction rate of $ CO_{2} $ concentration, and a series of computational analyses were conducted to study the results of these parameters in $ CO_{2} $ reduction. Based on this study, a prediction equation for $ CO_{2} $ concentration was derived. For this, a general full factorial design was used to evaluate the $ CO_{2} $ reduction characteristic based on various parameters (ventilation mode, boarding condition, vent angle, mass flow rate, and operation mode), and then their effects were analyzed to obtain an evaluation database of indoor air quality. From that, a prediction equation was derived to estimate the indoor air quality, enabling us to evaluate the $ CO_{2} $ concentration quickly that actually influences the human body without carrying out time-consuming CFD analyses for $ CO_{2} $ concentration. This study will be useful in designing HVAC systems and establishing the control logic for effective improvement of the car’s indoor air quality in the future.
Numerical study to evaluate the characteristics Of HVAC-related Parameters to reduce $ CO_{2} $ concentrations in cars
2016
Aufsatz (Zeitschrift)
Englisch
BKL: | 55.20$jStraßenfahrzeugtechnik / 55.20 Straßenfahrzeugtechnik |
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