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Several types of noise exist in automobiles. The flow-induced noise in the expansion device can be very disturbing since the expansion device is located near the occupants. In many studies, the flow-induced noise is found to be mitigated when the orientation of the tube is changed. However, no study explores the reason why flow-induced noise changes when the orientation of the tube is changed. The flow-induced noise varies along with the flow regimes near the expansion devices. In this paper, an experimental based research is used to study how the tube orientation changes the flow regimes under the same operating conditions. A pumped R134a system with transparent tubes (1/4-inch ID) is used to visualize the flow regimes near the manual expansion valve. The transparent tube is a continuous connection of horizontal tubes, 45° inclined tubes, and vertical tubes.

Air source heat pumps as the heating system for full electric vehicles are drawing more and more attention in recent years. Despite the high energy efficiency, frost accumulation on the heat pump evaporator is one of the major challenges associated with air source heat pumps. The evaporator needs to be actively defrosted periodically and heat pump heating will be interrupted during defrosting process. Proper defrost control is needed to obtain high average heat pump energy efficiency. In this paper, a new method for generating air source heat pump defrost control policy using reinforcement learning is introduced. This model-free method has several advantages. It can automatically generate optimal defrost control policy instead of requiring manually determination of the control policy parameters and logics.