A method to improve the ability of design engineers to generate proper dynamic models of systems from sets of component models is developed. This two stage method, called Eigenvalue MODA, is a new model deduction procedure for developing proper models of hybrid systems. The first stage in Eigenvalue MODA consists of using a previously published Model Order Deduction Algorithm (MODA) to systematically increment the complexity of each component model in the system. The first stage continues until a set of Critical System Eigenvalues (CSE) has been defined. During the second stage, the complexity component models is incremented based on the convergence of the CSE. The second stage continues until each CSE has converged to within a user specified tolerance. Component models may be represented by first-order (state space) or second-order equations and may be modal expansion or finite segment models. An example shows that the deduction of the proper system model depends on the interactions between the component model representations and the model deduction method. Eigenvalue MODA is a model deduction method that facilitates the generation of models of sufficient accuracy with physically meaningful parameters and states. This makes the models useful for system design and, as such, Eigenvalue MODA would be a useful tool in an automated modeling environment for design engineers.

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