Stringent North American emission regulations present several challenges for lean-burn diesel vehicles that offer significant fuel economy advantages over gasoline vehicles. This article presents a useful systems approach to developing robust models and combining them to analyze diesel aftertreatment (AT) technologies: (1) the diesel oxidation catalyst (DOC) that oxidizes carbon monoxide (CO), unburned hydrocarbons (HCs), and nitric oxide (NO), and stores HCs and (2) the urea-based selective catalytic reduction (SCR) catalyst that hydrolyzes aqueous urea to ammonia (NH 3 ), which, in turn, reduces nitrogen oxides (NO x ). The DOC and SCR models integrate information from multiple sources detailed thermal balances, laboratory performance data, phenomenological descriptions of adsorption and desorption in the catalyst, and experience-based correlations using optimization and statistical tools. The DOC model predicts cumulative HC and CO tailpipe vehicle emissions as well as DOC NO x outlet composition (NO vs NO 2 ). The SCR model uses the exotherm and NO 2 information from the DOC model to predict NO x conversion and NH 3 slip. System-level analyses that have resulted in important insights are highlighted using case studies, including (1) extrapolation of the downstream injection exotherm vehicle data for a fresh DOC to an aged DOC; (2) analysis of the effects of NO 2 produced in the DOC, SCR aging conditions, and NH 3 storage capacity on the NO x reduction performance of the SCR on a 6000-lb light-duty truck, and (3) development of urea injection strategies based on a tradeoff between NO x reduction and NH 3 slip.
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Katare et al. (2007) studied this question.
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