1. Estimation of vehicle mass and road slope based on steady-state Kalman filter
- Author
-
Shengqiang Hao, Junqiang Xi, and Peipei Luo
- Subjects
Computer Science::Robotics ,Steady state (electronics) ,Inertial frame of reference ,Computer science ,Control theory ,Control system ,CarSim ,Kalman filter ,Proper acceleration ,Measure (mathematics) - Abstract
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.
- Published
- 2017
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