Neural Network Based Approach for the Generation of Road Feel in a Steer-By-Wire System

Abstract

Steer-by-wire is an advanced steering system which connects the steering wheel with the front wheel by using motors and sensors. Generating the road feel in steer by wire system is an important criterion since there is no mechanical connection between the steering wheel and the front wheel. In present work, Neural Network method is proposed for generating artificial road feel to the driver using the vehicle dynamic parameters such as vertical displacement, self-aligning moment and front wheel angle as inputs. Proposed neural network model was trained using the vehicle dynamic models for estimating the current to be supplied to the feedback motor according to the changing road conditions. Three different road profiles are selected such as dry, wet and icy for the simulation purpose and the estimated motor current values for the road surfaces using neural network are presented. From the simulation results for the sinusoidal road surface and sinusoidal steering angle driver input, it is clear that the neural network based method is able to produce the varying road feel to the driver for the different road conditions.