首页> 外文会议>International Symposium on Computational and Business Intelligence >Automatic Tuning Methodology for Automotive Lean NOx Trap Catalyst Using Response Data
【24h】

Automatic Tuning Methodology for Automotive Lean NOx Trap Catalyst Using Response Data

机译:使用响应数据的汽车贫NOx捕集催化剂的自动调整方法

获取原文

摘要

This article provides an overview of the Lean NOx trap (LNT) catalysts' operating mechanism and proposes a method for auto-tuning the LNT model using response data. LNT catalysts are used in automotive applications to reduce NOx emissions from diesel engines, or lean-burn engines in general. The LNT catalyst is a complex nonlinear chemical system designed for cyclic operations, which can be very difficult to model in detail. Therefore, a simplified model was used which is based on the main chemical and physical processes typical to LNT. To tune the model, the method of choice of temperature for the lookup tables associated with multi-objective optimization and different input data sources was used: both steady state tests performed on a synthetic gas bench and more dynamic enginedynamometer tests.
机译:本文概述了贫NOx捕集器(LNT)催化剂的运行机理,并提出了一种使用响应数据自动调整LNT模型的方法。 LNT催化剂用于汽车应用中,以减少柴油发动机或一般稀薄燃烧发动机的NOx排放。 LNT催化剂是设计用于循环操作的复杂非线性化学系统,可能很难对其进行详细建模。因此,使用了简化的模型,该模型基于LNT典型的主要化学和物理过程。为了调整模型,使用了与多目标优化和不同输入数据源关联的查找表的温度选择方法:在合成气工作台上进行了稳态测试,以及更动态的发动机测功机测试。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

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