Design of a Fault Detection and Isolation System for Intelligent Vehicle Navigation System

Wei Huang,Xiaoxin Su

doi:10.1155/2015/279086

Abstract

This paper deals with the design of a fault detection and isolation (FDI) system for an intelligent vehicle, a vehicle equipped with advanced driver assistance system (ADAS). The ADASs are outfitted with sensors for acquiring various information about the vehicle and its surroundings. Since these sensors are sensitive to faults, an efficient FDI system should be developed. The designed FDI system is comprised of three parts: a detection part, a decision part, and a fault management part. The detection part applies a generalized observer scheme (GOS). In the GOS, there is bank of extended Kalman filters (EKFs), each excited by all except one sensor measurement. The residual generated from the measurement update of each EKF is therefore sensitive to all sensor faults but one. This way, the fault sensitivity pattern of the residual makes it possible to detect a fault and locate the faulty sensor. The designed FDI system has been implemented and tested off-line with actual experiment data. Good results have been obtained with diagnosing individual sensor faults and outputting fault-free vehicle states.

Highlights

Nowadays, the development of advanced driver assistance system (ADAS), which aids the driver by controlling the vehicle, is emphasized in the road transportation research
(5) Bank of observers, each excited by all outputs except one: this method improves the robustness of the fault detection and isolation (FDI) system but can only diagnose a single sensor fault
This work deals with the design of sensors fault detection and isolation (FDI) system for a Smart car

Summary

Introduction

The development of ADASs, which aids the driver by controlling the vehicle, is emphasized in the road transportation research. (1) Observer, excited by one output: from this output the other outputs can be reconstructed and compared with the corresponding measurements (single sensor fault detection). (5) Bank of observers, each excited by all outputs except one (generalized observer scheme, GOS): this method improves the robustness of the FDI system but can only diagnose a single sensor fault. The main contributions of this work are that, unlike previous studies this work will emphasize on the following: in order to ensure the proper functioning of ADASs on an intelligent vehicle, a model-based FDI system is designed to diagnose a single sensor fault with the consideration of the system’s disturbance and noise.

Sensors Measurements Specification

Vehicle State Estimation

Fault Detection and Isolation System Design

Fault occurred

Conclusions and Future Work