Application of Extended Kalman Filter in Simultaneous State and Parameter Estimation of a Nonlinear Full Vehicle Ride Model

A. Alasty and A. Ramezani (Iran)


Identification, Extended Kalman Filter, Passenger Car, Ride Comfort.


A methodology is developed for the simultaneous state and physical parameter estimation of a full vehicle nonlinear multibody ride model. A random road profile is designed as a persistent excitation. Input-output data required for the identification is obtained from ADAMS/CAR simulations of a more accurate and complex model. Robustness of the identification method is studied by adding different noise levels to the ADAMS output signals. Validation of the results is carried out by comparison of the identified model outputs with results of experiments done on the same vehicle, which its ADAMS model was available. Test was performed on the Shenck Hydropuls road simulator. Accuracy of estimated parameters is also evaluated by information available from other sources such as technical drawings and performance tests of the vehicle parts.

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