Modeling and Optimization of Exhaust After-Treatment System for a Heavy-Duty Diesel Engine using 1D Simulation 2019-26-0249
The Indian automotive industry has taken a big leap towards stringent Bharat Stage VI (BS VI) emission standards by year 2020. A digital driven design and development focusing on developing innovative and commercially viable technologies for combustion and exhaust after-treatment system is the need of the time. One-dimensional (1D) simulation serves as a best alternative to its counterparts in terms of obtaining faster and accurate results, which makes it an ideal tool for carrying out optimization studies at system level. In this work, 1D analytical methodology for design and optimization of exhaust after-treatment system (EAT) for a heavy-duty diesel application has been performed using GT-Power by understanding its thermodynamic behavior. A two-site, 1D model for a selective catalytic reduction (SCR) catalyst was developed and validated with the experimental reactor data. Chemical kinetics for ammonia adsorption and desorption, nitrogen oxide (NO) and ammonia oxidation and ammonia SCR reactions have been included in the catalyst model. Genetic algorithm was used to calibrate the rate constants of the Arrhenius equations for the reactions with the experimental data. The calibrated 1D SCR model along with 1D models of other sub-components of the EAT system has been used to carry out system performance and optimization studies. The studies reveal that the performance of the SCR in reducing the oxides of nitrogen (NOx) is the best at an NO2/NOx ratio of 0.5. Since this ratio is highly dependent on the performance of upstream catalytic systems, design of experiments tool will be used to study the effects of sizing and precious metal loadings in these sub-components of EAT system on the overall emission conversion performance. The possibility of using a zone coated DOC catalyst for improving the performance of the EAT system will be explored too.
K Vamshi Krishna, Nitin Chauhan, Brijesh P Patel, Manish Shrivastava
VIT University, Tata Motors, Ltd., ARAI
Symposium on International Automotive Technology 2019