This study aimed to develop a coach state estimation and prediction system to enhance driving safety. Different from existing vehicle stability estimation studies, the authors propose a hybrid method to estimate and predict the state of a coach in real time. First, the vehicle sideslip angle and yaw rate are estimated by a three-degrees-of-freedom vehicle model combined with an extended Kalman filter (EKF) estimation algorithm. Then, a steering system is established that replaces the front-wheel angle with the steering wheel input torque. Next, a seven-degrees-of-freedom vehicle model analyses the effects of various driving influencing factors on the vehicle sideslip angle and the boundary of the stable region of the phase plane of the vehicle sideslip angle rate, and a boundary value parameter database is obtained. A back propagation neural network (BPNN) model is then established to obtain the boundary function parameter values under multifactor coupling conditions. Furthermore, an online prediction of the steering wheel input torque in a time series is done, and the prediction value is input to the steering system and neural network model. The effectiveness of the proposed method was evaluated via simulations based on MATLAB/Simulink and TruckSim software.
Real-time estimation and prediction of lateral stability of coaches: a hybrid approach based on EKF, BPNN, and online autoregressive integrated moving average algorithm
IET Intelligent Transport Systems ; 14 , 13 ; 1892-1902
2021-01-15
11 pages
Article (Journal)
Electronic Resource
English
driving influencing factors , vehicle sideslip angle rate , prediction value , steering system , steering systems , Kalman filters , steering wheel input torque , seven-degrees-of-freedom vehicle model analyses , wheels , prediction system , autoregressive moving average processes , propagation neural network model , neural nets , time series , hybrid approach , three-degrees-of-freedom vehicle model , extended Kalman filter estimation algorithm , backpropagation , stability , vehicle dynamics , coach state estimation , driving safety , yaw rate , road vehicles , road safety , BPNN , boundary function parameter values , online prediction , EKF , state estimation , time estimation , online autoregressive integrated moving average algorithm , boundary value parameter database , vehicle stability estimation studies , front-wheel angle , nonlinear filters , hybrid method
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