A Research Of Occupant Comfort Model In Cabin Based On TS Fuzzy Inference System

In recent years, the comfort in the cabin is one of the problems passengers or creware most concerned about, and excellent comfort level in the cabin has become animportant indicator to consider the quality of the ship. Influence factors such as airtemperature, air velocity, clothing insulation etc have a big impact on comfort in cabin.The main task of this article is to study the influence factors in cabin and get a newcomfort index.Conventional methods of measuring human body’s comfort generally analyzefrom vibration comfort of the human body, thermal comfort and so on, rather than thecomprehensive evaluation of the comfortable in the cabin environment. In this paper,various factors that affect the human body comfort are considered. A new evaluationmodel of human comfort in the cabin is designed.This paper has used the improved thermal comfort PMV model to study the thermalcomfort in the cabin. The model considers air temperature, air velocity, clothinginsulation, mean radiant temperature, activity level, relative humidity, can fully reflectthe hot and cold feelings of most people in the same environment. Get the relationshipbetween air temperature, mean radiant temperature, air velocity, relative humidity andfinally come to a conclusion that these four impact factors increase gradually.In this paper, the vibration comfort evaluation methods have been studied, and getthe comprehensive evaluation of vibration comfort by the annoyance rate model.Through the results of the experiment and questionnaires, vibration accelerationshould be big enough when air temperature and relative humidity greatly influencedthe comfort in cabin and became the main impact factor. Vibration acceleration willeasily be ignored when it is small.Finally, the paper get a new evaluation model of human comfort in the cabin byusing TS fuzzy inference system, the membership function of input and output lingualvariables are set and the fuzzy rules are formed according to the environment inside the cabin. The result shows that the model can effectively reflect the influencesbetween every impact factor. The model is better than the PMV model because therange of values that impact the comfort index can be shown in the new model. Theannoyance rate is as important as air temperature and when it comes to50%thecomfort index will be maximum and will not change when the annoyance rate getbigger.With changing the meteorological environmental factors the comfort index can bebalanced when annoyance rate floated. Vibration and meteorological environmentalfactors are combined in this model and more outstanding performance in comfortevaluation in the cabin can be found in this model.