共轨高功率密度柴油机瞬态运行周期下的氮氧化物、烟尘和燃料消耗预测

IF 1.5 Q3 ENGINEERING, CHEMICAL
N. Walke, M. R. Nandgaonkar, N. V. Marathe
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引用次数: 3

摘要

目前,柴油发动机面临着控制瞬态循环NOx和烟尘排放的挑战,以满足更严格的排放标准,并控制现场作业中的排放。开发用于瞬态运行周期的氮氧化物和烟尘排放预测的模拟工具已成为最重要的目标,这可以显着减少调整这些排放所需的实验时间和成本。因此,在本工作中,通过选择合适的燃烧和排放模型并将其耦合到发动机循环模型中,建立了一个0D综合预测模型。进一步修改选定的燃烧和排放模型,以提高其在整个操作区域的预测精度。燃烧和排放模型的响应已经验证了负载和“开始喷射”的变化。模型预测的瞬态油耗、空气处理系统参数、氮氧化物和烟尘排放与涡轮增压高功率密度共轨发动机“非道路瞬态循环”(NRTC)的实测数据吻合良好。结果表明,0D模型可用于现代发动机瞬态排放的预测。本文还讨论了如何将所制定的方法推广到其他应用和燃料的瞬态排放预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
NOx, Soot, and Fuel Consumption Predictions under Transient Operating Cycle for Common Rail High Power Density Diesel Engines
Diesel engine is presently facing the challenge of controlling NOx and soot emissions on transient cycles, to meet stricter emission norms and to control emissions during field operations. Development of a simulation tool for NOx and soot emissions prediction on transient operating cycles has become the most important objective, which can significantly reduce the experimentation time and cost required for tuning these emissions. Hence, in this work, a 0D comprehensive predictive model has been formulated with selection and coupling of appropriate combustion and emissions models to engine cycle models. Selected combustion and emissions models are further modified to improve their prediction accuracy in the full operating zone. Responses of the combustion and emissions models have been validated for load and “start of injection” changes. Model predicted transient fuel consumption, air handling system parameters, and NOx and soot emissions are in good agreement with measured data on a turbocharged high power density common rail engine for the “nonroad transient cycle” (NRTC). It can be concluded that 0D models can be used for prediction of transient emissions on modern engines. How the formulated approach can also be extended to transient emissions prediction for other applications and fuels is also discussed.
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来源期刊
Journal of Combustion
Journal of Combustion ENGINEERING, CHEMICAL-
CiteScore
2.00
自引率
28.60%
发文量
8
审稿时长
20 weeks
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