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TECHNICAL BRIEFS

Adaptive Threshold Based Diagnostics for Steer-By-Wire Systems

[+] Author and Article Information
Pierluigi Pisu1

Center for Automotive Research, The Ohio State University, Columbus, OH 43212pisu.1@osu.edu

Andrea Serrani

Department of Electrical Engineering, The Ohio State University, Columbus, OH 43210serrani.1@osu.edu

Song You

 Delphi Research Labs, 51786 Shelby Parkway, Shelby, MI 48315song.you@delphi.com

Laci Jalics

 Delphi Research Labs, 51786 Shelby Parkway, Shelby, MI 48315laci.jalics@delphi.com

1

Corresponding author.

J. Dyn. Sys., Meas., Control 128(2), 428-435 (Apr 04, 2005) (8 pages) doi:10.1115/1.2199859 History: Received November 05, 2003; Revised April 04, 2005

In the process of implementing modular fault diagnostics for X-by-Wire systems (Pisu, 2000), it was discovered that distinguishing between the model uncertainties and occurrence of faults is a real challenge. It is imperative to solve the problems that exist in using fixed observer and threshold, including the observer model mismatch, generated threshold misfit, diagnostic parameter uncertainties, and incorrect diagnostic output during high stress but normal vehicle operation. Compared to the fixed observer and threshold strategy, the improved adaptive threshold-based diagnostics described in this report are more robust and applicable because of the addition of adaptation into the diagnostic observer and threshold generator. The report also describes an approach to fault detection and isolation in the presence of model and parameter uncertainties. This approach has been successfully implemented in the NAVDyn (Non-Linear Analysis of Vehicle Dynamics) simulation model using Matlab/Simulink, and simulation results are provided to verify that the strategy and implementation are viable.

Copyright © 2006 by American Society of Mechanical Engineers
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Figures

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Figure 1

Free body diagram for a steer-by-wire system

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Figure 2

General process of observer-based fault detection and isolation

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Figure 3

FDI scheme for the roadwheel system

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Figure 4

General process of adaptive threshold-based fault detection and isolation

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Figure 5

Motor currents, fault in irw2 sensor

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Figure 6

Residual evaluation 1 for a fault in irw2 sensor with parameter variation Δa1

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Figure 7

Residual evaluation 2 for a fault in irw2 sensor with parameter variation Δa1

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Figure 8

Residual evaluation 3 for a fault in irw2 sensor with parameter variation Δa1

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Figure 9

Residual evaluation 4 for a fault in irw2 sensor with parameter variation Δa1

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Figure 10

Residual evaluation 5 for a fault in irw2 sensor with parameter variation Δa1

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Figure 11

Residual evaluation 6 for a fault in irw2 sensor with parameter variation Δa1

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Figure 12

Motor currents with fault in irw2 sensor

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Figure 13

Residual evaluation 1 for a fault in irw2 sensor in presence of an uncertainty in the parameter a2

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Figure 14

Residual evaluation 2 for a fault in irw2 sensor in presence of an uncertainty in the parameter a2

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Figure 15

Residual evaluation 3 for a fault in irw2 sensor in presence of an uncertainty in the parameter a2

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Figure 16

Residual evaluation 4 for a fault in irw2 sensor in presence of an uncertainty in the parameter a2

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