TY - GEN
T1 - Estimation of vehicle mass and road slope based on steady-state Kalman filter
AU - Hao, Shengqiang
AU - Luo, Peipei
AU - Xi, Junqiang
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - To solve the problem that control system of the intelligent vehicle is hard to measure the vehicle mass and road gradient, this paper built a longitudinal dynamics model of vehicle. Based on theoretical model, discrete steady-state Kalman filter was used to estimate gradient of slope and vehicle mass, and simulation platform was established by Carsim and Maltab/Simulink to verify the accuracy and instantaneity of the algorithm. A proper acceleration sensor was selected, according to the stable Kalman filter theory. A real test was conducted, and the instantaneity and accuracy of this method for vehicle mass and road slope was verified by comparing with the data from inertial navigator.
AB - To solve the problem that control system of the intelligent vehicle is hard to measure the vehicle mass and road gradient, this paper built a longitudinal dynamics model of vehicle. Based on theoretical model, discrete steady-state Kalman filter was used to estimate gradient of slope and vehicle mass, and simulation platform was established by Carsim and Maltab/Simulink to verify the accuracy and instantaneity of the algorithm. A proper acceleration sensor was selected, according to the stable Kalman filter theory. A real test was conducted, and the instantaneity and accuracy of this method for vehicle mass and road slope was verified by comparing with the data from inertial navigator.
KW - Acceleration sensor
KW - Carsim/Matlab Co-simulation
KW - Discrete Steady-state Kalman filter
KW - Recognition of the Road slope and Vehicle Mass
UR - http://www.scopus.com/inward/record.url?scp=85050860009&partnerID=8YFLogxK
U2 - 10.1109/ICUS.2017.8278412
DO - 10.1109/ICUS.2017.8278412
M3 - Conference contribution
AN - SCOPUS:85050860009
T3 - Proceedings of 2017 IEEE International Conference on Unmanned Systems, ICUS 2017
SP - 582
EP - 587
BT - Proceedings of 2017 IEEE International Conference on Unmanned Systems, ICUS 2017
A2 - Xu, Xin
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE International Conference on Unmanned Systems, ICUS 2017
Y2 - 27 October 2017 through 29 October 2017
ER -