An Optimization-Based Framework for Dynamic Model Development for a Three-Way Catalytic Converter Suitable for Urban Driving Condition

The three-way catalytic converter (TWC) is a vital component of the S.I. (Spark Ignition) engine to meet the current emission norms. TWC can perform the three conversion processes simultaneously. Hence, health diagnosis and performance monitoring of TWC is a major requirement of the power-train control system. In TWC modeling, the chemical species CO, THC, NOx, O₂, and CO₂ are the major components of the redox reaction over the wash-coat surface which impacts the overall conversion efficiency of the gases. This research work examines a generalized chemical model for a fresh catalytic converter validated for significant engine operating points in an urban drive cycle. The gas concentration measurements across the catalyst are harvested from an engine dynamo-meter test-bed. This work attempts to find the best method to optimize the chemical kinetic parameter of the Arrhenius equation parameters. An optimization framework is designed and has been tried on two different optimization methods to find the global optimal results for the prediction error. The pre-exponential factor and activation energy parameters for all possible reactions are optimized in the model using measured data.