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.