25.Method for predicting passenger thermal comfort in railway vehicles

  • A method has been developed to predict passenger thermal comfort which correlates closely with the physiological and psychological state of passengers.
  • Subjective experiments in thermal environments were conducted in main line and commuter vehicles. Results demonstrated that the proposed prediction method reflected passenger thermal comfort accurately, with a correlation of over 0.8.

In order to improve the on-board thermal environment for rail passengers, it is important to be able to accurately evaluate and predict thermal comfort levels. A method for determining thermal comfort already exists for indoor spaces in the ISO 7730. However, there is no standard specifying a similar method for the railway environment which has specific characteristics, for example, contrary to indoor spaces, temperature and humidity variation in railway vehicles can be very drastic, and there are also significant differences in thermal comfort from season to season. Consequently, taking these specificities into account, a new method has been proposed for determining thermal comfort levels specially adapted to railway rolling stock (Fig. 1).

The proposed method is made up of physiological and psychological predictions. A human thermal model with a built-in body temperature regulation function is used to estimate the various thermal physiological states of the passenger, such as skin temperature and perspiration in various thermal environments in railway vehicles. It is also possible to take into account the clothing and posture of the passenger in these estimations. To estimate psychological states, a statistical model is built on data collected from subjective experiments conducted in railway vehicles stationed at rolling stock centers in different seasons (a total of 350 people for a temperature range of 20℃〜32℃), and this is applied to predict passenger thermal comfort (level of discomfort and percentage of dissatisfied customers).

Comparing predicted thermal comfort results with the actual comfort of subjects participating in a simulated thermal experiment revealed a correlation of over 0.8 between them (Fig. 2, Fig. 3). This method will make it possible to quantitatively evaluate air-conditioning adjustment from the passenger thermal comfort perspective in railway vehicles.

Fig. 1 Overview diagram of the proposed thermal comfort prediction method for thermal environments in railway vehicles.
Fig. 2 Example of dissatisfaction level prediction in relation to thermal environment, using the proposed method
Fig. 3 Comparison between actual comfort level values and predicted comfort levels using the new method
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