Prediction Method of Compatibility between Ride Comfort and Load of Off-Road Vehicles using Bayesian Active Learning

DOI

Bibliographic Information

Other Title
  • Bayesian Active Learning を用いたオフロード車両の乗り心地と路面入力荷重の両立性予測手法

Abstract

Driving on rough roads in off-road vehicles, the suspension characteristics that contribute to ride comfort may conflict with the magnitude of the load from the road surface due to overcoming rocks. In order to balance multiple different performance indicators, the optimal combination of design variables has been searched by trial and error. In the early stage of vehicle development, it is necessary to consider not only the characteristics of each part in the vehicle but also the external environment of the vehicle in the design variables. In this paper, Bayesian Active Learning is adopted to obtain the feasible region about the design variables for off-road vehicles. A practical numerical example of a multi-disciplinary vehicle design problem is demonstrated, and it is represented by the effectiveness of the proposed method.

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Keywords

Details 詳細情報について

  • CRID
    1390581070827063552
  • DOI
    10.11351/jsaeronbun.55.342
  • ISSN
    18830811
    02878321
  • Text Lang
    ja
  • Data Source
    • JaLC
  • Abstract License Flag
    Disallowed

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