On Board Diagnosis for Three-Way Catalytic Converters

On-board fault diagnosis is critical for the automotive industry. Recently, new on-board diagnostic system requirements (OBD II) have been enforced on California vehicles and new legislation will become stricter and stricter; moreover such requirements have also been extended in Europe (EOBD). Government regulations will require monitoring vehicle emissions and alerting the driver if the exhaust after-treatment system is not working properly. To meet these requirement, sophisticated diagnostic algorithms have to be developed. This paper presents a model-based stochastic approach for fault detection with application to automotive exhaust-gas after-treatment systems. The algorithm, based on relatively simple control-oriented models of the three-way catalytic converter and the oxygen sensor, is suitable for real-time, on-board applications. The overall strategy has been tuned and validated on the basis of experimental data.