| Autor: |
Kerim Kahraman, Mümin Tolga Emirler, Levent Guvenc, Baris Efendioglu, Bilin Aksun Güvenç |
| Rok vydání: |
2009 |
| Předmět: |
|
| Zdroj: |
ECC |
| DOI: |
10.23919/ecc.2009.7075122 |
| Popis: |
Vehicle yaw stability control systems like ESP are important active safety systems used for maintaining lateral stability of the vehicle during unexpected, adverse driving situations like μ-split braking, driving on icy road and sudden side wind. Vehicle yaw rate is the key data in an ESP system. This paper explores the possibility of estimating vehicle yaw rate based on other available measurements like tire speeds. The motivating reasons for using such an estimator are to reduce sensor costs by using a virtual sensor rather than an actual sensor and/or to check the correct operation of the yaw rate sensor and to have an alternative method of closing the loop in the case of a yaw rate sensor malfunction. Conventional observers and Kalman filters are used in this paper to estimate vehicle yaw rate. These estimators are tested using offline simulations with a single track and a higher fidelity Carmaker model. A hardware-in-the-loop, real-time simulator with driver input capability is used to check the successful operation of the designed estimators in a more realistic manner. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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