关键词: AMT；中间轴制动器；BP 神经网络

Abstract: The middle shaft brake is a key component of the automated manual transmission (AMT), which is mainly used for gear shifting during the driving process to achieve a smoother driving experience. Back propagation (BP) neural network is a proxy mathematical model that can adaptively adjust parameters and optimize weights. During gear shifting of an AMT, power interruption may occur, and the duration of the power interruption affects the driving comfort of the vehicle. This article analyzes the gear shifting control strategy and the related parameters affected by the middle shaft brake working time. It is found that there are nonlinear relationships and multiple influencing factors in this control process. Therefore, it is proposed to use BP neural network to establish a prediction model to predict the middle shaft brake time, and achieve more precise and sensitive control of the middle shaft brake, thereby achieving better shifting effect.

Key words: AMT; Intermediate shaft brake; BP neural network