期刊文献+

柴油机SCR系统控制研究现状与技术挑战 被引量:6

Current Research and Future Technical Challenges of Diesel Engine SCR Control
下载PDF
导出
摘要 介绍了柴油机典型的后处理系统结构和催化剂对SCR系统性能的影响;通过SCR催化还原机理、催化器内部反应过程的分析阐述了SCR系统的建模及标定方法;对采用开环控制、闭环控制、自适应控制、模型预测控制等方法的SCR系统控制策略和应用现状进行详细总结和分析。结合SCR系统运行特点,从SCR的低温性能、氨覆盖率的计算、NOx传感器的交叉感应现象、催化剂的老化、SCR与其它后处理部件及发动机的协同优化控制五个方面提出了未来柴油机SCR系统的技术发展方向。 The typical structure of aftertreatment system of diesel engine and the catalyst of SCR on the performance of SCR system are introduced.By analyzing the catalytic reduction mechanism of SCR,the modeling and calibration methods of the internal dynamics and chemical reaction process of the catalyst is then described.The SCR system control strategy and application status using open-loop control,closed-loop control,adaptive control,model predictive control and other methods are summarized and analyzed in detail.Finally,according to the operating characteristics,the future of SCR control research is discussed from the low temperature performance of SCR,the calculation of ammonia coverage,the cross-sensitivity of NOx sensor,the aging of catalyst,multi-system collaborative optimization control of SCR with engine and other aftertreatment components.
作者 彭继银 黄粉莲 万明定 Peng Jiyin;Huang Fenlian;Wan Mingding(Yunnan Key Laboratory of Internal Combustion Engines,Kunming City,Yunnan Province 650500,China)
出处 《农业装备与车辆工程》 2019年第10期50-55,共6页 Agricultural Equipment & Vehicle Engineering
关键词 柴油机 选择性催化还原 催化剂 SCR模型 控制策略 技术挑战 diesel engine selective catalyst reduction catalyst SCR modeling control strategy technical challenge
  • 相关文献

参考文献4

二级参考文献29

  • 1胡于进,马威,王学林,易军.基于广义回归神经网络的发动机特性建模[J].机械与电子,2007(6):7-9. 被引量:6
  • 2Subramaniam M N, Dean Tomazic, Marek Tatur, et al. An artificial neural network-based approach for virtual NO, sensing [ C ]. SAE Paper 2008 - 01 - 0753,2008.
  • 3Brahma I, Rutland C J. Optimization of diesel engine operating parameters using neural networks [ C]. SAE Paper 2003-01 - 3228,2003.
  • 4Claes Ericson,Bjorn Westerberg. Modeling diesel engine combustion and NOx formation for model based control and simulation of engine and exhaust aftertreatment systems [ C ]. SAE Paper 2006- 01 -0687,2006.
  • 5Claes Ericson, Bjorn Westerberg. Transient emission predictions with quasi stationary models [ C ]. SAE Paper 2005 - 01 - 3852,2005.
  • 6HJ437--2008.车用压燃式、气体燃料点燃式发动机与汽车车载诊断(OBD)系统技术要求[S].2008.
  • 7Ehsan Majd Faghihi, Shamekhi A H. Development of a neural network model for selective catalytic reduction (SCR) catalytic converter and ammonia dosing optimization using multi objective genetic algorithm [ J ]. Chemical Engineering Journal, 2010,165 ( 2 ) : 508 - 516.
  • 8Staiano A, Tagliaferri R, Pedrycz W. Improving RBF networks performance in regression tasks by means of a supervised fuzzy clustering [ J]. Neurocomputing,2006,69 (13 -15 ) :1 570 -1 581.
  • 9MEIER-PETERH,BERNHARDTF.船舶工程技术手册[M].陈刚,宋新新,译.上海:上海交通大学出版社,2009:814.
  • 10PONTIKAKIS G N, KONSTANTAS G S, STAMATELOS A M. Three-way catalytic converter modeling as a mod- em engineering design tool [ J]. Journals of Engineering for Gas Turbine and Power, 2004(10) :906 -923.

共引文献24

同被引文献27

引证文献6

二级引证文献10

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部