Traction Control Logic Based on Extended Kalman Filter for Omni-directional Electric Vehicle

Paper #:
  • 2012-01-0251

Published:
  • 2012-04-16
DOI:
  • 10.4271/2012-01-0251
Citation:
Chen, G., Zong, C., and Guo, X., "Traction Control Logic Based on Extended Kalman Filter for Omni-directional Electric Vehicle," SAE Technical Paper 2012-01-0251, 2012, doi:10.4271/2012-01-0251.
Pages:
10
Abstract:
Omni-directional electric vehicle built by our research group is an advanced electric vehicle whose four wheels can drive, steer and brake independently. The vehicle chassis system is composed of four in-wheel motors, four independent steer motors and electromagnetic brake system, and its control system is divided into logical control layer and underlying execution layer. The information exchange between these two layers is implemented by CAN bus. In this paper, the traction control logic for Omni-directional electric vehicle is developed. The study mainly involves two aspects: the vehicle states estimation and the traction control logic design. The vehicle states, including vehicle longitudinal velocity, lateral speed, side slip angle and yaw rate, etc, are estimated based on Extended Kalman Estimation and multiple degrees of freedom vehicle model. Longitudinal velocity is used to design the traction control logic; the other estimated states are the preconditions for the future study. To design the traction control logic, the slip ratio of each wheel is obtained according to the estimated velocity firstly. Through PID control, the single wheel slip ratio control is realized to make the slip ratio of each wheel below the optimum value. Then the vehicle traction control logic is introduced to eliminate the influence of the additional yaw moment to steer stability. Finally, the effectiveness of the estimation algorithm and the traction control logic are verified by the simulation in the environment of Matlab/simulink and Carsim.
Access
Now
SAE MOBILUS Subscriber? You may already have access.
Buy
Select
Price
List
Download
$27.00
Mail
$27.00
Members save up to 40% off list price.
Share
HTML for Linking to Page
Page URL

Related Items

Book
2013-12-16
Article
2016-09-06