Simulation and analysis of a direct current operated automotive air-conditioning system

Abstract

The automotive air-conditioning (AAC) system is the second largest consumer of energy after the power train in a typical passenger vehicle. An improvement on the performance of this system will save a significant amount of energy and significantly improve the vehicle performance. The study was divided into two main sections, namely, experimental work and parametric simulation. The experimental work was conducted to obtain the off-road air-side evaporator heat transfer correlation and refrigerant-side correlations of compressor work, refrigerant mass flow rate, cooling capacity, and heat rejected from the condenser. The experimental rig comprised the original components from the AAC system of a medium-sized passenger car equipped with an appropriately sized electric compressor and electronic expansion valve. Cabin compartment thermal load, air-side evaporator-cabin compartment, and thermal and energy AAC system performance mathematical models had been developed based on models proposed by previous studies. Comparison exercises indicated that the simulation from the cabin compartment thermal load mathematical model and experimental results were within 5% error and were highly consistent with published results. Parametric simulation studies revealed that vehicle surface with darker color, an increment in the number of occupants, vehicle speed and fractional ventilation of air intake, and lower cabin temperature tend to increase the cooling load and require additional cooling capacity up to 144.16 W (5.01%). As a result, compressor work increased, up to 89.12 W (10.82%). Consequently, maximum reduction of COP up to 5.53% was recorded due to dominant increase in compressor work, as opposed to an increase in cooling capacity. In short, the proposed simulation model is able to help designers and/or engineers to understand the best type of vehicles and AAC operating system that can enhance the overall performance of the vehicle, particularly an electric vehicle, in the most efficient way. Consequently, it can reduce the effort, time, and cost to develop AAC systems and vehicles in the future.