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Extended Kalman Filter Based Road Friction Coefficient Estimation and Experimental Verification
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 2, 2019 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
Accurate road friction coefficient is crucial for the proper functioning of active chassis control systems. However, road friction coefficient is difficult to be measured directly. Using the available onboard sensors, a model-based Extended Kalman filter (EKF) algorithm is proposed in this paper to estimate road friction coefficient. In the development of estimation algorithm, vehicle motion states such as sideslip angle, yaw rate and vehicle speed are first estimated. Then, road friction coefficient estimator is designed using nonlinear vehicle model together with the pre-estimated vehicle motion states. The proposed estimation algorithm is validated by both simulations and tests on a scaled model vehicle.
CitationLi, B., Sun, T., Fang, A., and Song, G., "Extended Kalman Filter Based Road Friction Coefficient Estimation and Experimental Verification," SAE Technical Paper 2019-01-0176, 2019, https://doi.org/10.4271/2019-01-0176.
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