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arXiv · 2310.10425

Continuously Adapting Random Sampling (CARS) for Power Electronics Parameter Design

Dominik Happel·Philipp Brendel·Andreas Rosskopf·Stefan Ditze
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Abstract

To date, power electronics parameter design tasks are usually tackled using detailed optimization approaches with detailed simulations or using brute force grid search grid search with very fast simulations. A new method, named "Continuously Adapting Random Sampling" (CARS) is proposed, which provides a continuous method in between. This allows for very fast, and / or large amounts of simulations, but increasingly focuses on the most promising parameter ranges. Inspirations are drawn from multi-armed bandit research and lead to prioritized sampling of sub-domains in one high-dimensional parameter tensor. Performance has been evaluated on three exemplary power electronic use-cases, where resulting designs appear competitive to genetic algorithms, but additionally allow for highly parallelizable simulation, as well as continuous progression between explorative and exploitative settings.

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Dominik Happel, Philipp Brendel, Andreas Rosskopf, Stefan Ditze. 2023-10-16. Continuously Adapting Random Sampling (CARS) for Power Electronics Parameter Design. https://arxiv.org/abs/2310.10425

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