Software tools offer powerful support in the areas of engineering specification, design, implementation, and test. The tools are at their most potent when they actively promote agility and responsiveness throughout a product life cycle <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">and</i> leave a legacy of knowledge to inform future product development. Model-based design facilitates these benefits by considering a simulation of the system under development as an executable specification. This executable specification may be regarded as ldquoone truthrdquo across engineering teams with the simulation being abstracted or enhanced as appropriate. First-principle, data-driven, and physical modeling further strengthens model-based design, by allowing the agility and responsiveness afforded by model-based design to be relevant for both algorithmic <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">and</i> nonalgorithmic design considerations. Indeed, models are a powerful means to offer support for in-service operation, diagnostics of unintended operations and assessment and upgrades of control systems and/or system architectures during the entire life-cycle of a product. This paper will consider the benefits of physical modeling and model-based design through an example of a high acceleration linear motor. The motor type, power electronic-drive switching strategy, and power-electronic drive architecture will be considered. Finally, the use of parallel computing within the context of this application will be discussed, in particular as an effective means to generate results for a large number of operational scenarios in a time-effective manner.
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