배출가스의 온도 및 유량이 최적 촉매 분포에 미치는 영향에 관한 연구

Abstract

In practical applications, monolithic catalytic converters are operated at non-isothermal conditions. In this case, the active metal distribution along the length of the converter may influence its performance. Indeed, better conversions can be achieved by controlling the distribution of the same quantity of active material. In this study, a 1D quasi-steady plug-flow reactor model has been adopted to predict the transient thermal and conversion characteristics of a monolithic catalytic converter. The optimal design of a longitudinal noble metal distribution of a fixed amount of catalyst is investigated to obtain the best performance of a dual monolithic catalytic converter by using a micro genetic algorithm with consideration of heat transfer, mass transfer, and chemical reaction in the monolith under various operating conditions. The optimal axial distribution of the catalyst is determined by solving the multi-objective optimization problems which are to minimize both the CO cumulative emissions during constant operating condition, and the difference between the integral value of a catalyst distribution function over the monolith volume and total catalytic surface area over total monolith volume.