On Board Diagnosis of Internal Combustion Engines: A New Model Definition and Experimental Validation

In recent years there has been an increasing worldwide effort to limit polluting emissions from road vehicles. The On Board II Diagnostic (OBD II) regulations adopted by California Air Resources Board (CARB) are among the most restrictive rules. They require on-board devices which monitor emission control systems in order to identify deterioration or malfunction of components.

For automotive purpose, the high cost of achieving hardware redundancy can be reduced by substituting software redundancy. This approach requires an engine model definition. In this work the application of the Artificial Neural Networks (ANNs) technology, is analyzed and validated by experiments. First model has been tested under varying load conditions with very encouraging results.