This paper considers a method by which the dynamic variables (states) of a suspension system can be estimated in real time using only a limited set of vehicle transducers. The method uses Kalman filter observers, which are designed using known examples of state and transducer time histories. Two sources of data are considered for this: vehicle tests on a four poster shake rig, and quarter vehicle simulations. A kinematic study of filters from both sources reveals that a 'minimal' sensor set, comprising hub and body mounted accelerometers alone, is capable of a high level of accuracy in state estimation. A Kalman filter of this type is tested in the simulated closed-loop control of a semi-active system, and the performance is seen to compare favourably with that of a corresponding full-state feedback system.
Real time estimation of vehicle suspension characteristics using Kalman filtering
Echtzeitüberwachung des Verhaltens von Radaufhängungen mit Hilfe von Kalman-Filterung
1994
9 Seiten, 7 Bilder, 5 Tabellen, 7 Quellen
Aufsatz (Konferenz)
Englisch
Real Time Estimation of Vehicle Suspension Characteristics Using Kalman Filtering
British Library Conference Proceedings | 1994
|Real Time Estimation of Vehicle Suspension Characteristics Using Kalman Filtering
British Library Conference Proceedings | 1994
|Real time estimation of vehicle suspension characteristics using Kalman filtering
Kraftfahrwesen | 1994
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