...
首页> 外文期刊>Applied Energy >A fast and accurate physics-based model for the NO_X emissions of Diesel engines
【24h】

A fast and accurate physics-based model for the NO_X emissions of Diesel engines

机译:一种快速,精确的基于物理的柴油机NO_X排放模型

获取原文
获取原文并翻译 | 示例
           

摘要

To date, models for the nitrogen-oxide emissions of Diesel engines are either of empirical or phenome-nological nature. The former are fast and quantitatively accurate in the identified region, but lack the generality and extrapolation capability of the latter. The model presented in this work combines the advantages of both model types and thus complies with typical requirements of computationally intensive fields such as dynamic optimisation and model-based control. This unique aggregation of features is achieved by extracting the most relevant physical phenomena and extending them by physically motivated empirical elements. Exploiting the assumptions made and using a setpoint-relative formulation leads to a simple model structure, comprising one map and 10 scalar parameters only. Execution speed is roughly 500 times faster than real-time and throughout the entire engine operating-range, also during transient operation, relative errors are below 10% even for the largest allowable, simultaneous variation of all inputs. Apart from engine speed and injected fuel-mass, the model requires the cylinder-charge, its composition, and the start of combustion with the corresponding pressure and temperature as inputs. The latter can either be obtained from measured in-cylinder pressure signals, or may be calculated from quantities provided by a model for the air path of the engine.
机译:迄今为止,柴油机氮氧化物排放的模型具有经验性质或现象学性质。前者在确定的区域内快速且定量准确,但缺乏后者的一般性和外推能力。这项工作中提出的模型结合了两种模型类型的优点,因此符合计算密集型领域(例如动态优化和基于模型的控制)的典型要求。通过提取最相关的物理现象并通过物理动机的经验元素来扩展它们,可以实现这些功能的独特集合。利用所做的假设并使用相对于设定点的公式可得出简单的模型结构,该模型结构仅包含一个图和10个标量参数。在整个发动机工作范围内,以及在瞬态运行期间,执行速度都比实时速度快大约500倍,即使对于所有输入的最大允许同时变化,相对误差也低于10%。除了发动机转速和喷射的燃料质量外,该模型还需要汽缸充气,其成分和以相应的压力和温度作为输入的燃烧开始。后者既可以从测得的缸内压力信号中获得,也可以从发动机的空气路径模型提供的数量中计算得出。

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