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Modern air vehicles face increasing internal heat loads that must be appropriately understood in design and managed in operation. This paper examines one solution to creating more efficient and effective thermal management systems (TMSs): vapor cycle systems (VCSs). VCSs are increasingly being investigated by aerospace government and industry as a means to provide much greater efficiency in moving thermal energy from one physical location to another. In this work, we develop the AFRL (Air Force Research Laboratory) Transient Thermal Modeling and Optimization (ATTMO) toolbox: a modeling and simulation tool based in Matlab/Simulink that is suitable for understanding, predicting, and designing a VCS. The ATTMO toolbox also provides capability for understanding the VCS as part of a larger air vehicle system. The toolbox is presented in a modular fashion whereby the individual components are presented along with the framework for interconnecting them.

As the cost and complexity of modern aircraft systems advance, emphasis has been placed on model-based design as a means for cost effective subsystem optimization. The success of the model-based design process is contingent on accurate prediction of the system response prior to hardware fabrication, but the level of fidelity necessary to achieve this objective is often called into question. Identifying the key benefits and limitations of model fidelity along with the key parameters that drive model accuracy will help improve the model-based design process enabling low cost, optimized solutions for current and future programs. In this effort, the accuracy and capability of a vapor cycle system (VCS) model were considered from a model fidelity and parameter accuracy standpoint. A range of model fidelity was evaluated in terms of accuracy, capability, simulation speed, and development time.

Dynamic and steady-state averaged models of an aircraft's power systems are developed to better understand various aspects of operation such as coupling between energy domains, energy requirements, transient and fault conditions/recovery, power quality/reliability, system and subsystem-level losses, operational efficiency, and to explore numerous system architectures. These models focus on the electrical, thermal, hydraulic, mechanical, and pneumatic power systems traditionally found in commercial aircraft. Subsystems of components are capable of interfacing with each other and with an engine model that produces auxiliary power. One of the major challenges involved in modeling extensive systems of this nature is to arrive at an optimum trade-off between simulation execution time and the desired level of fidelity in the result.