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Publication . Conference object . Article . 2022

Application of Probabilistic principles to Set-Based Design for the optimisation of a hybrid-electric propulsion system

Andrea Spinelli; Luchien Anderson; Hossein Balaghi Enalou; Bahareh Zaghari; Timoleon Kipouros; Panagiotis Laskaridis;
Open Access
Published: 15 Feb 2022 Journal: IOP Conference Series: Materials Science and Engineering, volume 1,226, page 12,064 (issn: 1757-8981, eissn: 1757-899X, Copyright policy )
Publisher: IOP Publishing
Country: United Kingdom
Abstract Current research in hybrid-electric aircraft propulsion has outlined the increased complexity in design when compared with traditional propulsion. However, current design methodologies rely on aircraft-level analysis and do not include the consideration of the impact of new technologies and their uncertainty. This can be a key factor for the development of future hybrid-electric propulsion systems. In this paper, we present a methodology for exploring the design space using the principles of Set-Based Design, which incorporates probabilistic assessment of requirements and multidisciplinary optimisation with uncertainty. The framework can explore every design parameter combination using a provided performance model of the system under design and evaluate the probability of satisfying a minimum required figure of merit. This process allows to quickly discard configurations incapable of meeting the goals of the optimiser. A multidisciplinary optimiser then is used to obtain the best points in each surviving configuration, together with their uncertainty. This information is used to discard undesirable configurations and build a set of Pareto optimal solutions. We demonstrate an early implementation of the framework for the design of a parallel hybrid-electric propulsion system for a regional aircraft of 50 seats. We achieve a considerable reduction to the required function evaluations and optimisation run time by avoiding the ineffective areas of the design space but at the same time maintaining the optimality potential of the selected sets of design solutions.
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ACM Computing Classification System: ComputerApplications_COMPUTERSINOTHERSYSTEMS

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