The evolution of IC engines in the automobile industry has increased the range and convenience of personal travel. It provides faster means of travel, which has permitted large sections of the urban population to travel far distant places for work and other activities. Vehicles have become a necessary part of everyday life, so much so that an average person travels about 45 km every day and spends at least 5% of daily time traveling. In this context, air conditioning in automobiles has become more a necessity than a luxury. The World Health Organization (WHO) defines health as a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity. A person’s health is dependent on the quality of the environment, and a significant aspect of it is the thermal characteristics of the occupied space. A poorly conditioned environment inside an automobile cabin is found to increase fatigue and loss in the cognitive abilities of the driver. Due to these reasons, occupant thermal comfort has always been a subject of interest for the automotive industry. In the field of automobile air conditioning, there are many issues that still require much research attention. These issues include real-time thermal comfort assessment in automobile cabins, intelligent automation of control parameters, and optimization of the HVAC system by considering external climatic conditions and fuel consumption.
Three-dimensional unsteady cooling simulations are carried out to simulate the flow inside an automobile cabin under the effects of solar radiation. Results indicate that non-homogeneity in flow and thermal distribution is the defining characteristic of in-cabin microclimate. Therefore, the present study shows the significance of local air temperature and velocity on occupant thermal comfort. This is achieved by comparing the thermal comfort indicated by Equivalent Temperature (ET) with Effective Draft Temperature (EDT). The application of EDT for the assessment of thermal comfort in automobile cabins has not been studied so far. The EDT model is only dependent on the local air temperature and velocity; thus, its comparison with ET brings out the role of local temperature and velocity on cabin thermal comfort. The present study also elaborates the flow and thermal characteristics inside the automobile cabin for different vertical guide vane angles.
The present study also investigates the influence of ambient climatic conditions on a parked car soaked under direct sunlight. The climatic conditions are incorporated into the CFD simulations through three parameters: ambient temperature, solar flux, and wind speed (which influences the heat transfer coefficient between the surface of the automobile cabin and the surrounding air). The effects of these parameters on the Mean Radiant Temperature (MRT) at the driver’s location inside the car are analyzed by considering a rich parametric space of the variables of influence. Results from high-fidelity CFD simulations are combined with versatile machine learning algorithms to provide best-fit predictions of MRT for different climatic conditions. This methodology enables the estimation of MRT without having to rely on experiments or CFD simulations.