Identification and fault detection of an active vehicle suspension

You are here: Homepage > Search

Identification and fault detection of an active vehicle suspension

Fischer, Daniel / Zimmer, Markus / Isermann, Rolf

After a short introduction into the topic of active vehicle suspension systems, a mathematical model of the considered active vehicle suspension, which is presented in a test rig, is derived. It is shown how the unknown parameters can be obtained experimentally by parameter estimation. Algorithms are developed to identify a quarter car test rig, which is equipped with a hydraulic fully loaded active suspension. The results of parameter estimation are used for model based fault detection and identification, in order to obtain reliable knowledge of the system's state. All results are shown for measurements from an active suspension on a test rig. The presented fault detection and isolation approach provides reliable fault detection for an active suspension system distinguishing 15 sensor and process faults such as sensor offset and gain faults as well as friction, leakage and clogging. For this, a model-based approach based on parameter estimation is presented. Using the DSFI (Discrete Square root Filter in Information form) algorithm, 13 physical parameters of the system are estimated with measured data with minor deviations to reference values between 6 % and 13 %. The resulting fault symptom classification shows an almost isolated nature. As a result, at least all process faults - except friction and body acceleration sensor offset - can unambiguously be distinguished.