Parameter Identification of Tire Model Based on Improved Particle Swarm Optimization Algorithm Tongji Univ

Format:

Conference/Event

Author/Creator:

Zhuo, Zhuo, author.

Contributor:

Wang, Jin

Zhang, Fengbo

Conference Name:

SAE 2015 World Congress & Exhibition (2015-04-21 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2015

Summary:

AbstractAccurate parameters of vehicle motion state are very important to the active safety of a vehicle. Currently the extended Kalman filter and unscented Kalman filter are widely used in estimation of the key state parameters, such as speed. In this situation, tire model must be used. The Magic Formula Tire Model is widely used in vehicle dynamics simulation because of its high versatility and accuracy. However, it requires a large number of parameters, which make the key state parameters of a real vehicle difficult to accurately obtain. Therefore, it is limited in real-time control of a vehicle. Firstly, the original Magic Formula Tire Model is simplified in this paper; then Jin Chi's Tire Model is introduced; thirdly, parameters of both the simplified Magic Formula and Jin Chi's Tire Model are identified using PSO (Particle Swarm Optimization) algorithm. Finally, Jin Chi's Tire Model is also used in parameters identification of experimental data

Notes:

Vendor supplied data

Publisher Number:

2015-01-1586

Access Restriction:

Restricted for use by site license