Modeling and Verification of Tire Nonlinearity Effect on Accuracy of Vehicle Yaw Rate Calculation

Author:

Min Delei1,Wei Yintao1

Affiliation:

1. Tsinghua University

Abstract

<div class="section abstract"><div class="htmlview paragraph">The desired yaw rate is a vital target parameter for vehicle stability control, which is currently determined as a steady-state yaw rate by the linear single-track vehicle model. Tire nonlinearity deteriorates the effect of vehicle stability control at larger lateral acceleration. This paper proposes a new calculation method of the steady-state yaw rate considering the tire nonlinearity based on the brush tire model. To validate and verify the proposed method, step steering tests of the target vehicle under different lateral accelerations are carried out on a real proving ground. The results show that when the lateral acceleration is relatively small, the difference between the calculation results of the proposed method and the traditional one is not apparent, and both methods can provide a good estimation for the steady-state yaw rate; however, when the lateral acceleration is relatively large, the difference becomes apparent. It can be shown that the linear tire model cannot be able to calculate the steady-state yaw rate accurately, while the brush tire model agrees well with the observation. This difference shows the importance of considering tire nonlinearity in vehicle stability control, especially in extreme driving conditions. By analyzing the existence of the solution of the yaw rate equation, this paper finds that the vehicle speed upper limit under which the vehicle can be able to achieve steady-state steering is also affected by the tire nonlinearity. A Simulink vehicle model is built to verify the steady-state vehicle speed upper limit for vehicles with different steering characteristics. The results of the modeling and tests provide certain guidelines for developing a vehicle stability control system.</div></div>

Publisher

SAE International

Subject

Artificial Intelligence,Mechanical Engineering,Fuel Technology,Automotive Engineering

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