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In this paper, an automobile wind resistance prediction method is proposed to address the problems of high cost and long time-consuming of traditional automobile aerodynamic shape design methods as well as the low accuracy of the current wind resistance prediction model. First, an MPV simulation model is constructed for computational fluid dynamics (CFD) simulation, from which the relevant input feature parameters are selected. Then, the AOA-CatBoost prediction algorithm is modeled. Finally, the model is evaluated by relevant indicators. The experimental results show that the AOA-CatBoost wind resistance prediction model has high consistency with the results of real-vehicle tests, and the model can effectively predict the wind resistance of the vehicle.

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A Study on Automobile Wind Resistance Prediction of E-vehicle Based on AOA-CatBoost Hybrid Modeling

  • 会议论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年

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  • Chuanbo Liu,
  • Yuhan Liu,
  • Guangyuan Yang,
  • Zhu Bin

摘要

In this paper, an automobile wind resistance prediction method is proposed to address the problems of high cost and long time-consuming of traditional automobile aerodynamic shape design methods as well as the low accuracy of the current wind resistance prediction model. First, an MPV simulation model is constructed for computational fluid dynamics (CFD) simulation, from which the relevant input feature parameters are selected. Then, the AOA-CatBoost prediction algorithm is modeled. Finally, the model is evaluated by relevant indicators. The experimental results show that the AOA-CatBoost wind resistance prediction model has high consistency with the results of real-vehicle tests, and the model can effectively predict the wind resistance of the vehicle.