Browse Publications Technical Papers 971122
1997-02-24

Application of Neural Networks in the Estimation of Tire/Road Friction Using the Tire as Sensor 971122

The importance of friction between tire and road for the dynamic behavior of road vehicles has been emphasized in many publications. Continuously updated knowledge of the friction potential and the friction demand can help to improve maneuverability and thereby safety of vehicles under slippery road conditions. An on line estimation method, based on combination of side force and self aligning torque, generated by the tire, is theoretically founded on a simple brush type tire model.
The system is implemented in the front wheel suspension of a passenger car. To cope with the highly non-linear behavior of the wheel suspension and the actual tire, various static neural networks have been applied in the estimation procedure. Experiments have been carried out both in simulation using a full vehicle multi-body model and with an actual vehicle. Conclusions are drawn regarding the estimation principle, the application of neural networks and the implementation in a test vehicle.

SAE MOBILUS

Subscribers can view annotate, and download all of SAE's content. Learn More »

Access SAE MOBILUS »

Preview Document Add to Cart
Members save up to 16% off list price.
Login to see discount.
Special Offer: Download multiple Technical Papers each year? TechSelect is a cost-effective subscription option to select and download 12-100 full-text Technical Papers per year. Find more information here.
We also recommend:
TECHNICAL PAPER

FE-Based Tire Loading Estimation for Developing Strain-Based Intelligent Tire System

2015-01-0627

View Details

TECHNICAL PAPER

Estimation of Tire-Road Friction Using Tire Vibration Model

2002-01-1183

View Details

TECHNICAL PAPER

An Analysis of Tire Traction Properties and Their Influence on Vehicle Dynamic Performance

700377

View Details

X