Passenger cars and light trucks consume 80% of the total oil imported by U.S.A. Mobile air conditioners (MACs) increase vehicle fuel consumption and exhaust gas emissions. They operate most of the time in a transient state.
It is currently impossible to test the performance of an air conditioner during transient operation without it being associated with its intended conditioned space, the car cabin. In this research work a new smart test facility is designed, built, and verified. This facility makes it possible to test the MAC independent of the vehicle, but yet under realistic dynamic conditions.
The facility depends on simulation software that measures the conditions of the air supplied by the MAC and subsequently adjusts the conditions of the air returning to the MAC depending on the results of a thermal numerical model of the car cabin that takes into consideration sensible and latent loads, as well as passengers’ control settings. It was successful in controlling the temperature and relative humidity within ±0.9°C and ±5% of their respective intended values. The test facility is used to investigate the dynamic performance of a typical R134a MAC system. The tests include pull-down, drive cycle, and cyclic on/off tests.
The analysis focuses on the latent capacity and moisture removal due to the difficulty in measuring these variables during field tests. The results show that the most energy efficient method to pull-down the air temperature inside a hot-soaked cabin is to start with fresh air as long as the temperature in the cabin exceeds that of the ambient and then switch to recirculated air. The effect of re-evaporation is illustrated by showing the off-cycle latent capacity. Cyclic tests show that the net moisture removal rate has a minimum at around a 2 minute duty cycles.
This implies a means of controlling the coil latent heat factor by varying duty cycle. The automotive air conditioning system is numerically modeled and used in cooperation with the cabin model to conduct numerical tests. The numerical simulation results are compared to the experimental results and the error is less than 1.5 K of cabin air temperature.
Source: University of Maryland
Author: Gado, Amr El-Sayed Alaa El-Din
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