| Autor: |
Nguyen Tuan-Anh, Nguyen Cong Tuan |
| Rok vydání: |
2018 |
| Předmět: |
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| Zdroj: |
Advances in Engineering Research and Application ISBN: 9783030047917 |
| DOI: |
10.1007/978-3-030-04792-4_67 |
| Popis: |
Vehicle inertial parameters play an important role in vehicle controls, especially for active safety systems. Therefore, accurate real-time estimation of vehicle inertial parameters such as sprung mass and moment of inertia can improve vehicle safety, efficiency, and performance. This article introduces a method for estimating vehicle sprung mass and pitch moment of inertia in real-time based on a Kalman-Bucy filter (KBF) and a simplified half-car vertical vibration model. The main advantages of this method are it requires only vertical acceleration sensors for measurement and the KBF estimator is designed for a continuous time system. Simulation results for both bump and roughness road implemented in Matlab Simulink have showed that the designed filter performed effectively by rejecting the process and measurement noises and tracking the real vehicle inertial parameters. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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