Title :
Soft sensor application in vehicle yaw rate measurement based on Kalman filter and vehicle dynamics
Author_Institution :
State Key Lab of Automobile Dynamic Simulation, Jilin Univ., Changchun, China
Abstract :
The accurate measurement of vehicle yaw rate is vital for vehicle dynamics control, such as yaw control and traction control. Generally, vehicle yaw rate is measured by gyro that costs too much to be used commercially as an on-vehicle sensor. Based on soft sensor technique in inferential control theory, a novel method for the estimation of vehicle yaw rate is proposed. The estimation is based on Kalman filter and 2 degree-of-freedom vehicle dynamic models to realize the estimation of way rate of linear minimize mean square error. Results of simulation and experiment show an accurate and low-cost estimation of yaw rate is achieved and soft sensor estimation method is feasible in measurement of vehicle state.
Keywords :
Kalman filters; mean square error methods; parameter estimation; position control; road vehicles; sensors; traction; vehicle dynamics; Kalman filter; inferential control theory; linear minimize mean square error; on-vehicle sensor; soft sensor application; traction control; vehicle dynamics control; vehicle yaw rate measurement; yaw control; Accelerometers; Control systems; Control theory; Costs; Delay estimation; Filters; State estimation; Tires; Vehicle dynamics; Vehicle safety;
Conference_Titel :
Intelligent Transportation Systems, 2003. Proceedings. 2003 IEEE
Print_ISBN :
0-7803-8125-4
DOI :
10.1109/ITSC.2003.1252704
