10.18453/rosdok_id00004752 Yuan, Chengdong Chengdong Yuan http://d-nb.info/gnd/1237698871 https://orcid.org/0000-0002-2204-6814 Universität Rostock 2024 000 Generalities, Science 620 Engineering & allied operations 2024 en https://purl.uni-rostock.de/rosdok/id00004752 urn:nbn:de:gbv:28-rosdok_id00004752-5 This thesis presents the application of mathematical model order reduction (MOR) and parametric model order reduction (pMOR) methods for generating accurate surrogates of energy harvesters. Differing from conventional non-parametric MOR approaches, multivariate moment matching-, matrix interpolation-, and algebraic parameterization-based pMOR methods are used to construct a parametric reduced-order model (pROM), which enables the preservation of the predefined parameters, e.g., boundary conditions, material properties, or geometrical parameters, in symbolic form within a pROM.