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Reliability Case Analysis of an Autonomous Air Cooling System (AACS) for Aerospace Applications
Technical Paper
2018-01-1916
ISSN: 0148-7191,
e-ISSN: 2688-3627
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English
Abstract
Current More Electric Aircraft (MEA) utilize Liquid Cooling Systems (LCS) for cooling on-board power electronics. In such LCS, coolant pipes around the structure of the aircraft are used to supply water glycol based coolant to sink heat from power electronics and other heat loads in the electronic bay. The extracted heat is then transferred to ram air through downstream heat exchangers.
This paper presents a reliability examination of a proposed alternative Autonomous Air Cooling System (AACS) for a twin engine civil MEA case study. The proposed AACS utilizes cabin air as the coolant which is in turn supplied using the electric Environmental Control System (ECS) within the MEA. The AACS consists of electrical blowers allocated to each heat load which subsequently drive the outflow cabin air through the heat sinks of the power electronics for heat extraction. No additional heat exchanger is required after this stage in which the heated air is directly expelled overboard. One key advantage is the avoidance of liquid coolant leakage with the removal of liquid coolant from the MEA.
It is necessary that the expected reliability of the AACS is in line with the equivalent LCS and is compliant with Federal Aviation Administration/previous Joint Aviation Authorities (FAA/JAA) reliability limits. Accordingly, this paper evaluates the reliability of the proposed AACS as well as the subsequent operation of safety critical components of the ECS and Electrical Power System (EPS) that the AACS is cooling. The analysis results show that the proposed AACS can provide comparable reliability to an LCS and is expected to be compliant with FAA/JAA reliability limits.
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Fong, C., Norman, P., and Seki, N., "Reliability Case Analysis of an Autonomous Air Cooling System (AACS) for Aerospace Applications," SAE Technical Paper 2018-01-1916, 2018, https://doi.org/10.4271/2018-01-1916.Data Sets - Support Documents
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