Benchmarking of adjoint sensitivity-based optimization techniques using a vehicle ride case study

• Yitao Zhu ^[2] ; Corina Sandu ^[1] ; Daniel Dopico ^[3] ; Adrian Sandu ^[1]
  1. [1] Virginia Tech - Wake Forest University

     Virginia Tech - Wake Forest University

     Estados Unidos

     
  2. [2] Inc
  3. [3] University of la coruna

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• Localización: Mechanics based design of structures and machines, ISSN 1539-7734, Vol. 46, Nº. 2, 2018, págs. 254-266
• Idioma: inglés
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• Resumen

  • Several studies on multibody dynamics optimization have been conducted. One important limitation of these studies is their computational e?ciency, especially when optimizing a complex system’s performance. The co-authors developed a very e?cient optimization technique based on an adjoint sensitivity analysis methodology. The scope of this article is to validate this technique by conducting a benchmark analysis against some of the most popular optimization methods, including gradient-based optimization using finite differences, design of experiment using optimal Latin hypercube, and design of experiment using full factorial design matrix. A vehicle system is used as a case study for optimizing its ride comfort.