Estimation and Decomposition of Rack Force for Driving on Uneven Roads

06/29/2020
by   Akshay Bhardwaj, et al.
0

The force transmitted from the front tires to the steering rack of a vehicle, called the rack force, plays an important role in the function of electric power steering (EPS) systems. Estimates of rack force can be used by EPS to attenuate road feedback and reduce driver effort. Further, estimates of the components of rack force (arising, for example, due to steering angle and road profile) can be used to separately compensate for each component and thereby enhance steering feel. In this paper, we present three vehicle and tire model-based rack force estimators that utilize sensed steering angle and road profile to estimate total rack force and individual components of rack force. We test and compare the real-time performance of the estimators by performing driving experiments with non-aggressive and aggressive steering maneuvers on roads with low and high frequency profile variations. The results indicate that for aggressive maneuvers the estimators using non-linear tire models produce more accurate rack force estimates. Moreover, only the estimator that incorporates a semi-empirical Rigid Ring tire model is able to capture rack force variation for driving on a road with high frequency profile variation. Finally, we present results from a simulation study to validate the component-wise estimates of rack force.

READ FULL TEXT

page 12

page 14

research
08/01/2019

Estimation of Tire-Road Friction for Autonomous Vehicles: a Neural Network Approach

The performance of vehicle active safety systems is dependent on the fri...
research
09/25/2020

Lateral Force Prediction using Gaussian Process Regression for Intelligent Tire Systems

Understanding the dynamic behavior of tires and their interactions with ...
research
03/10/2023

Estimating friction coefficient using generative modelling

It is common to utilise dynamic models to measure the tyre-road friction...
research
09/05/2023

In Situ Soil Property Estimation for Autonomous Earthmoving Using Physics-Infused Neural Networks

A novel, learning-based method for in situ estimation of soil properties...
research
06/07/2023

A Robust Hybrid Observer for Side-slip Angle Estimation

For autonomous driving or advanced driving assistance, it is key to moni...
research
09/04/2023

Motion Cueing Algorithm for Effective Motion Perception: A frequency-splitting MPC Approach

Model predictive control (MPC) is a promising technique for motion cuein...
research
11/23/2009

How slow is slow? SFA detects signals that are slower than the driving force

Slow feature analysis (SFA) is a method for extracting slowly varying dr...

Please sign up or login with your details

Forgot password? Click here to reset