Human thermal comfort in passenger vehicles using an organic phase change material- an experimental investigation, neural network modelling, and optimization

In this research, an attempt is made to maintain human thermal comfort by regulating temperature and relative humidity inside the automobile cabin by impregnating an organics phase change material (PCM)-coconut oil-underneath the rooftop of the vehicle and vacant spaces in door interior. Temperature and relative humidity inside the vehicle cabin with and without PCM are discussed. In the next phase of this study, multiple feed forward back propagation (MBP) artificial neural network modelling for regression is carried out. Later, variable effects and optimization was performed using response surface methodology (RSM). The results show that the interior temperature of the automobile cabin is decreased by 13 degrees C on an average with an average increase in relative humidity of 8.6%. This method is a simple and feasible solution to prevent undesirable heating and steep humidity decrease in automobile cabins when parked under sunlight which guarantee energy saving, safety and enhanced quality of car interior. The developed MBP model can be used easily for prediction of thermal comfort factors. From the response surface analysis the strong association between ambient temperature and temperature with PCM and humidity inside cabin without PCM and humidity with PCM is established.