Model Based Design – Calibration and Hardware tolerance evaluation by using System simulation predicting tailpipe emission. =

Thanks to the most recent technology, fully electric vehicles are becoming reality. Everything is going to move towards electric transportation, but combustion engines are still one of the most widely used technologies, not only in automotive industry. Probably, in the future, a perfect combination of them will be the right step before a complete transition to electric vehicle but in the meantime, it is essential to continue working to make engines more efficient, in terms of fuel consumption, performance and emissions. Emissions are probably one of the biggest challenges for car manufacturers, who equip vehicles with complex but efficient exhaust systems to reduce pollutants, making exhaust system design a critical point in the vehicle engineering process. Design errors, such as incorrect sensor positions or fluid dynamic problems, could lead to system malfunctions or even worse, delays in the production process, as some tests are performed just before the start of production. Consequently, building a model with a simple plant and a basic physical structure for real-time emission control is an essential step to reduce experimental work, speed up the production process, reduce costs and obtain a priori information on the efficiency of the exhaust system. The goal is to build a model that can complement the tests currently performed to assess exhaust system efficiency, to significantly reduce costs and design steps. This report will present all the steps taken to build the complete Toolchain that is currently efficient for predicting the influence of sensor location, the impact of engine failures and the verification of exhaust system efficiency. In order to be able to simulate the above system, models were created using different software such as Stateflow (Controller), Simulink (A/F sensors, Controller, Engine OUT), Exothermia-suite (TWC, PIPE, GPF) and Etas (Engine OUT). The initial task was to support the team in the Three-way catalyst, Gasoline particle filters, Sensors, Control logic and the Engine out model, which simulates emissions cylinder by cylinder. For my part, the controller was suitably simplified for steady-state operation to reduce the simulation time but keep the results consistent. All models were coupled for co-simulation and the toolchain was improved to confirm the exhaust emission prediction. Finally, a model sensitivity analysis was performed, i.e., the ability of the model to produce reliable results in terms of predicting emission behavior. The first tests analyzed the impact of Control Logic parameters under optimal operating conditions, approving an excellent emission prediction. Then tests reproduced some non-optimal operating conditions and hardware tolerance to verify the model's ability to estimate emissions. The results obtained are astounding, the model can achieve excellent emission prediction, which offers the potential to improve the Model-Based Design approach for exhaust gas after treatment. In any case, the model seems to predict emissions correctly with good accuracy. Obviously, the model can be improved, but the pollutant trends are as predicted, so this leads to a fairly good and optimistic conclusion. These results confirm the usage of the model for calibration and design purpose, with a significant reduction in time and costs.