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
2020-12-01
11 pages
Article (Journal)
Electronic Resource
English
seven‐degrees‐of‐freedom vehicle model analyses , nonlinear filters , backpropagation , neural nets , road safety , coach state estimation , yaw rate , three‐degrees‐of‐freedom vehicle model , BPNN , hybrid method , front‐wheel angle , wheels , stability , online autoregressive integrated moving average algorithm , driving safety , driving influencing factors , vehicle dynamics , EKF , steering system , road vehicles , boundary function parameter values , prediction value , extended Kalman filter estimation algorithm , steering systems , Kalman filters , time estimation , vehicle sideslip angle rate , steering wheel input torque , time series , autoregressive moving average processes , boundary value parameter database , vehicle stability estimation studies , online prediction , hybrid approach , state estimation , propagation neural network model , prediction system
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