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http://dx.doi.org/10.7467/KSAE.2012.20.6.126

Tire Lateral Force Estimation System Using Nonlinear Kalman Filter  

Lee, Dong-Hun (Department of Automotive Engineering, Graduate School, Hanyang University)
Kim, In-Keun (Department of Automotive Engineering, Graduate School, Hanyang University)
Huh, Kun-Soo (Department of Automotive Engineering, Hanyang University)
Publication Information
Transactions of the Korean Society of Automotive Engineers / v.20, no.6, 2012 , pp. 126-131 More about this Journal
Abstract
Tire force is one of important parameters which determine vehicle dynamics. However, it is hard to measure tire force directly through sensors. Not only the sensor is expensive but also installation of sensors on harsh environments is difficult. Therefore, estimation algorithms based on vehicle dynamic models are introduced to estimate the tire forces indirectly. In this paper, an estimation system for estimating lateral force and states is suggested. The state-space equation is constructed based on the 3-DOF bicycle model. Extended Kalman Filter, Unscented Kalman Filter and Ensemble Kalman Filter are used for estimating states on the nonlinear system. Performance of each algorithm is evaluated in terms of RMSE (Root Mean Square Error) and maximum error.
Keywords
Tire lateral force; Sideslip angle; Lateral velocity; Extended kalman filter; Unscented kalman filter; Ensemble kalman filter;
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  • Reference
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