Abstract
Fault detection for automotive semi-active shock absorbers is a challenge due to the non-linear dynamics and the strong influence of the disturbances such as the road profile. First obstacle for this task, is the modeling of the fault, which has been shown to be of multiplicative nature. Many of the most widespread fault detection schemes consider additive faults. Two model-based fault algorithms for semiactive shock absorber are compared: an observer-based approach and a parameter identification approach. The performance of these schemes is validated and compared using a commercial vehicle model that was experimentally validated. Early results shows that a parameter identification approach is more accurate, whereas an observer-based approach is less sensible to parametric uncertainty.
Highlights
Observer-based Fault EstimationA Fault Detection and Isolation (FDI) system based on an Unknown Input Observer (UIO) and the QoV model (1) is proposed. The idea is to synthesize a residual, which is sensitive to the damper fault and insensitive to disturbances (i.e. road profile)
One method is based on classical least square parametric identification to estimate a multiplicative fault
The second method is based on an Unknown Input Observer, which is used to calculate a residual and to estimate the loss of force due to an additive fault
Summary
A FDI system based on an UIO and the QoV model (1) is proposed. The idea is to synthesize a residual, which is sensitive to the damper fault and insensitive to disturbances (i.e. road profile). An important result of applying the UIO theory to this domain is, without road information, the system is non-observable and non-detectable [11] For the decoupled system (7), the observer poles in s = 0 are related to the input contribution to the state estimation. The input related with these integrators is the unsprung-mass acceleration, which is a measured output, but it was considered as an input to achieve the decoupling of the system from the road profile. The cut-frequency ω f of the filter is set at 0.14 Hz. By using the estimated states with the UIO observer and the measurement of the sprung mass acceleration, the residual can be computed to detect a fault (loss of damping force): r(t) y3.
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