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Inside the Virtual Test Aircraft (VIRTTAC) Benchmark Model: Simulation Architecture

One of the major goals of research and innovation in aviation is to enhance the overall air traffic safety and to make traveling even more comfortable for both pilots and passengers. Novel aircraft safety and control features are normally developed for distinct a aircraft type due to e.g. a certain demand from the aircraft manufacturer or its availability for research facilities in terms of the existence of high-quality simulation models or flight testing capabilities. In the last years, numerous interesting and noticeable innovations to enhance aviation safety have been published for different aircraft types. For example, a very small study of developments in the field of aircraft flight envelope protection revealed that 12 different aircraft types or models were used in numerous publications [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]. Hence, comparison of all the different developments is very difficult. Furthermore, the assessment of the applicability of a published new methodology for a different type of aircraft is very difficult as normally the reader’s knowledge about the underlying system is quite small. To overcome this problem and provide a common simulation model to the research community, NASA introduced in 2011 a generic aircraft simulation model called the “Transport Class Model” (TCM) derived from a sub-scale “Generic Transport Model” (GTM) simulation[18]. It is a fully functioning aircraft simulation including realistic engine and actuator behavior, sensor models and a flight control system. Although a significant number of failure scenarios were considered, computed and tested in CFD and wind tunnels [19], only a few of them were implemented in the distributed Simulink simulation model. Moreover, the problem of comparability between various new developments is also present within the field of aircraft system identification. Various algorithms for parameter estimation and simulation model identification as well as related software tools have been developed during the last decades, but most of them were tested and verified for different aircraft. For example, Refs. [20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38] show results of various system identification techniques for more than 20 different aircraft types. Consequently, there is the problem to assess the quality of each methodology as there is no common base for an objective evaluation. The proposed high-quality model will be made available to all developers and will constitute a good complement to the already existing/available models.