Transactions of the Korean Society of Automotive Engineers (한국자동차공학회논문집)

The Korean Society of Automotive Engineers (한국자동차공학회)
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Real-Time Dynamic Simulation of Vehicle and Occupant Using a Neural Network

시뮬레이터에서 동역학 실시간 처리를 위한 신경망 적용

  • 손권 (부산대학교 기계공학부) ;
  • 최경현 (제주대학교 기계생산에너지공학부) ;
  • 송남용 (부산대학교 대학원) ;
  • 이동재 (부산대학교 대학원)
  • Published : 2002.03.01
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Abstract

A momentum backpropagation neural network is prepared to carry out real-time dynamics simulations of a passenger car. A full-car model of fifteen degrees of freedom was constructed for vehicle dynamics analysis. Human body dynamics analysis was performed for a male driver(50 percentile Korean adult) restrained by a three point seatbelt system. The trained data using the neural network were obtained using a dynamic solver, ADAMS . The neural network were formed based on the dynamics of the simulator. The optimized hidden layer was obtained by selecting the optimal number of hidden layers. The driving scenario including bump passing and lane changing has been used for the estimation of the proposed neural network. A comparison between the trained data and neural network outputs is found to be satisfactory to show the applicability of the suggested approach.

Keywords

References

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