Studies On Thermal Comfort, Cooling Load Calculation and

2.1. Studies on Thermal Comfort, Cooling Load Calculation and Underhood Thermal Management

Lots of studies can be found in literature about thermal comfort in buildings and different enclosures. An example to this is the study conducted by Atmaca (2006), which investigated the effects of thermal comfort parameters such as temperature, humidity and air velocity on cervical range of motion experimentally.

For this purpose, each of the three thermal comfort parameters was used as a variable while the others are kept constant in a controlled laboratory room, and the effects of variable parameter were investigated. Human responses to thermal environment such as skin temperature; skin wettedness, sensible and latent heat losses were determined from the developed simulation program. Finally, experimental data and simulation results were assessed simultaneously, and the most appropriate thermal environmental conditions, which did not cause cervical mobility limitations, were determined and they were suggested for both academic and industrial users.

Since thermal comfort in vehicles is a very important subject, researchers and academicians pays attention to this subject and lots of studies can be found in literature about vehicular thermal comfort. Here are some examples.

Körbahtı (1999), analyzed the parameters that affect the heating condition in buses and heat distribution in a bus and on the outer shell of the intercity bus was calculated under definite conditions.

Kaynakli and Kilic (2005), presented a theoretical and experimental analysis of the in-cabin thermal comfort during the heating period by dividing the human body into 16 segments, with the change of temperature measured and calculated in both experimental and theoretical basis. The air temperature, velocity and relative humidity inside the automobile were acquired experimentally through multiple sensors distributed across the passenger compartment.

In the study performed by Sevilgen (2010), Three-dimensional numerical analysis of temperature and airflow distribution in the automobile cabin was conducted by using Computational Fluid Dynamics method. For this purpose, a three dimensional automobile cabin including window and outer surfaces was modeled by using the real dimensions of a car. In order to evaluate the results of numerical analysis according to thermal comfort, a virtual manikin divided into 17 parts with real dimensions and physiological shape was added to the model of the automobile cabin.

Alahmer et. al. (2011), provided a comprehensive review of the different models developed to predict vehicular cabins thermal comfort, in addition to the different experimental techniques used. The study investigated the different challenges that exist in predicting and evaluating the thermal comfort for vehicular cabins when compared with thermal comfort in buildings. These challenges are mainly related to the fast transient behaviors involved especially the cases of cooling the cabin after a hot soak condition, in addition to the non-uniformities in the thermal environment associated with the high localized air velocity, air temperature distribution, solar flux, and radiation heat flux from surrounding interior surfaces; in addition to other variations related to trip durations and passenger clothing levels.

An overview of preferable microclimate conditions in warm indoor ambient is given in the study conducted by Ruzic, (2011). The data presented in the study were based on numerous experiments with human subjects under different ambient conditions. Focus was on combination of air temperature and local velocity of

airflow in the region of head and upper body, as thermally most sensitive parts of human body. The results showed that values proposed by standards for thermal comfort, generally used for assessment of indoor thermal environment, could be too restrictive. Preferable conditions are shifted towards higher air velocities.

Furthermore, microclimate parameters that will provide thermal balance of the passenger's body with the surrounding (cab interior) and thermal comfort could not be presented by single value, but by the range of values. The chosen combination of the values would be dependent of individual preferences and local and overall microclimate conditions around different parts of the body. This means that the system must allow precise regulation of local air temperature and velocity in several zones around each passenger's body.

Wu and Ahmed (2012), studied a novel mode of air supply, which has the potential to improve ventilation performance, without increasing the fresh air supply rate. Because, Aircraft cabin ventilation is essential during commercial passenger flights and efficient fresh air delivery has become an important research issue in the field of HVAC.

Different cooling load calculation techniques were studied and compared by several researchers.

Spitler et. al. (1997), described the radiant time series method and the generation of the response factors and the radiant time series coefficients and gives a brief comparison to the heat balance method in their study. At the end of the study, RTS method was compared to the other cooling load calculation methods and RTS method found simpler, more accurate than the other techniques.

Mui and Wong (2007), investigated energy performance and consumption, an example weather year and some occupant load profiles of offices. In the study, the usefulness of the existing example weather year and occupant load variations was investigated. The methods established would be useful for an effective design and an accurate cooling load calculation of air-conditioned buildings, in meeting the demand of occupant loads and updated outdoor information. In particular, a new example weather year and a mathematical model of generating the time variant occupant load profiles using Monte Carlo sampling techniques were used as a basis to calculate the

cooling load variations. With the integration of the time varied occupant load profile, the difference of the cooling load capacity would vary from 1% to 5%, but the change of the weather year was not significant. The proposed model would not be limited to the cooling load capacity determination for certain office buildings in Hong Kong but would also be applicable elsewhere to various building system designs with properly selected model parameters.

Hourly dynamic cooling load capacities (heat gain) of a sample building according to radiant time series (RTS) method by using Meteorological Data such as solar radiation, outside air temperature and wind speed along the years 1997-2008 was determined by Özgören et. al., (2011).

Since a calculation procedure that is widely accepted for the cooling load analysis of the volumes that are non-stationary and have many variable parameters, such as buses, does not exist, Büyükalaca et. al. (2011), used “Radiant Time Series”

method for the calculation of cooling load of a bus. “Radiant Time Series” method was introduced briefly and the important points for the application of the method to a bus were given.

Thermal protection is increasingly important in the development process of passenger cars. Tightly packaged engine compartments and strongly increased engine power demand extensive testing and analysis. (Binner et. al., 2006). And so lots of studies were conducted by several researchers on that subject.

Winnard et. al. (1995), conducted a study of the underhood thermal management of a light truck in a dynamometer, using cell blowers to simulate road speeds. The goal was to determine how the temperatures in the underhood could be reduced.

Fournier and Digges (2004), investigated 4 different models of automobiles under hood temperatures in their study with a test procedure similar to present study.

In their study, 11 thermo-couples were installed to 4 different vehicles’ under hood and measurements were done with 3 different test conditions, which are stationary, constant speed driving and uphill driving.

Binner et. al., (2006), in their study investigated the under hood temperature distribution of a sport car under maximum speed and low speed uphill climbing test conditions.

Fournier and Bayne, (2007), also indicated the test conditions and specifications of underhood temperature measurement techniques in detail in their study.

The ultimate aim of the study, conducted by Khaled et. al. (2009), was to reengineer the underhood architecture so as to reduce the cooling air flow rate in the underhood component and hence the aero thermal cooling drag.

Ekeroth and Martinsson (2011), in their study focused on the numerical simulation of a heavy truck traveling uphill at a 30km/h speed, which is similar to our uphill climbing test condition.