Refine
Year of publication
Institute
- Fachbereich Elektrotechnik und Informationstechnik (720) (remove)
Language
- English (720) (remove)
Document Type
- Article (407)
- Conference Proceeding (241)
- Part of a Book (39)
- Book (23)
- Conference: Meeting Abstract (6)
- Patent (2)
- Conference Poster (1)
- Doctoral Thesis (1)
Keywords
- Enterprise Architecture (5)
- MINLP (5)
- Engineering optimization (4)
- Optimization (3)
- Powertrain (3)
- Technical Operations Research (3)
- Telecommunication (3)
- Competence Developing Games (2)
- Energy efficiency (2)
- Engineering education (2)
In product development, numerous design decisions have to be made. Multi-domain virtual prototyping provides a variety of tools to assess technical feasibility of design options, however often requires substantial computational effort for just a single evaluation. A special challenge is therefore the optimal design of product families, which consist of a group of products derived from a common platform. Finding an optimal platform configuration (stating what is shared and what is individually designed for each product) and an optimal design of all products simultaneously leads to a mixed-integer nonlinear black-box optimization model. We present an optimization approach based on metamodels and a metaheuristic. To increase computational efficiency and solution quality, we compare different types of Gaussian process regression metamodels adapted from the domain of machine learning, and combine them with a genetic algorithm. We illustrate our approach on the example of a product family of electrical drives, and investigate the trade-off between solution quality and computational overhead.
In this paper, an approach to propulsion system modelling for hybrid-electric general aviation aircraft is presented. Because the focus is on general aviation aircraft, only combinations of electric motors and reciprocating combustion engines are explored. Gas turbine hybrids will not be considered. The level of the component's models is appropriate for the conceptual design stage. They are simple and adaptable, so that a wide range of designs with morphologically different propulsive system architectures can be quickly compared. Modelling strategies for both mass and efficiency of each part of the propulsion system (engine, motor, battery and propeller) will be presented.