首页> 外文OA文献 >Physics based modeling of urea selective catalytic reduction systems
【2h】

Physics based modeling of urea selective catalytic reduction systems

机译:基于物理的尿素选择性催化还原系统建模

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

This thesis addresses control-oriented modeling of urea-selective catalytic reduction (SCR) after-treatment systems used for reducing NO, emission in diesel vehicles. Starting from first-principles, appropriate simplifications are made in the underlying energy and species equations to yield simple governing equations of the Urea-SCR. The resulting nonlinear partial differential equations are discretized and linearized to yield a family of linear finite-dimensional state-space models of the SCR at different operating points. It is shown that this family of models can be reduced to three operating regions that are classified based on the relative NO, and NH3 concentrations. Within each region, parametric dependencies of the system on physical mechanisms are derived. A further model reduction is shown to be possible in each of the three regions resulting in a second-order linear model with sufficient accuracy. These models together with structured parametric dependencies on operating conditions set the stage for a systematic advanced control design that can lead to a high NO, conversion efficiency with minimal peak-slip in NH3. All model properties are validated using simulation studies of a high fidelity nonlinear model of the Urea-SCR, and compared with experimental data from a flow-reactor.
机译:本文针对用于减少柴油车辆NO排放的尿素选择性催化还原(SCR)后处理系统进行面向控制的建模。从第一原理开始,对基本的能量和物种方程式进行了适当的简化,以得出Urea-SCR的简单控制方程式。对所得的非线性偏微分方程进行离散化和线性化,以得出SCR在不同工作点处的线性有限维状态空间模型族。结果表明,该系列模型可以简化为基于相对NO和NH3浓度分类的三个操作区域。在每个区域内,得出系统对物理机制的参数依赖性。在三个区域中的每个区域中,进一步进行模型简化都是可能的,从而可以以足够的精度生成二阶线性模型。这些模型以及对操作条件的结构化参数依赖性为系统高级控制设计奠定了基础,该控制设计可实现高NO转化效率和NH3最小峰滑。所有模型属性均通过对Urea-SCR的高保真度非线性模型的仿真研究进行了验证,并与流量反应器的实验数据进行了比较。

著录项

  • 作者

    Na Hanbee;

  • 作者单位
  • 年度 2010
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号