Abstract 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 °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.

中文翻译：

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使用有机相变材料的乘用车人体热舒适性——实验研究、神经网络建模和优化

摘要 本研究试图通过在车顶下方和车门内部的空余空间浸渍有机相变材料 (PCM)-椰子油来调节车内温度和相对湿度来维持人体热舒适度。 . 讨论了使用和不使用 PCM 时车厢内的温度和相对湿度。在本研究的下一阶段，对回归进行多前馈反向传播 (MBP) 人工神经网络建模。后来，使用响应面方法 (RSM) 执行变量效应和优化。结果表明，车内温度平均降低13℃，相对湿度平均增加8.6%。这种方法是一种简单可行的解决方案，可以防止在阳光下停放时汽车驾驶室出现不良加热和湿度急剧下降，从而保证节能、安全和提高汽车内饰质量。开发的 MBP 模型可以很容易地用于预测热舒适因素。根据响应面分析，环境温度和温度与 PCM 以及没有 PCM 的机舱内湿度和有 PCM 的湿度之间建立了很强的关联。