Analysis and Interpretation of Steering Geometry of Automobile Using Artificial Neural Network Simulation

HTML  XML Download Download as PDF (Size: 978KB)  PP. 231-239  
DOI: 10.4236/eng.2019.114016    717 Downloads   2,385 Views  Citations
Author(s)

ABSTRACT

Vehicle dynamics is the one of the most important factors in the analysis and predicting the steering behavior of automobile. The paper details the evaluation of the Artificial Neural Network (ANN) structures to estimate the steering geometry parameters of four wheel vehicle. One of the aspects of vehicle performance is performance of steering geometry. Steering geometry parameters kingpin inclination angle, caster angle, camber angle, toe angle, scrub radius, toe in and toe out are measured using alignment techniques and caster/camber gauges. Suspension system components pivot upon a rubber bushing which is compressed between an inner and outer metal sleeve. Excess clearance developed in the joints of suspension system in turn causes changes in steering geometry. This is obviously essential for any automobile for a major challenge in terms of operation, performance, servicing and maintenance. ANN models applicable to each of these steering parameters were developed. Steering geometry is evaluated through the independent and dependent variables of front suspension. Dependent variables such as steering geometry parameters kingpin inclination angle, caster angle, camber angle, toe angle, scrub radius, toe in and toe out are determined with the help of independent variables. These dependent variables are validated through ANN simulation. The result obtained through ANN is in close agreement to the experimental observation.

Share and Cite:

Belkhode, P. (2019) Analysis and Interpretation of Steering Geometry of Automobile Using Artificial Neural Network Simulation. Engineering, 11, 231-239. doi: 10.4236/eng.2019.114016.

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.