重庆大学学报2024，Vol.47Issue(1)：9-20,12.DOI:10.11835/j.issn.1000-582X.2022.112
LOLIMOT模型在CNG发动机NOx排放预测试验中的应用
Application of LOLIMOT to CNG engine NOx emission prediction test
摘要
Abstract
To solve the problem of insufficient prediction accuracy of the local linear model tree(LOLIMOT)emission model in the development of the selective catalytic reduction technology(SCR)control strategy,a method of optimizing the space boundary is proposed.This method aims to constrain the super-rectangular input space of the original model within the scope of physical definitions in the modified LOLIMOT model.Through the identification test of a compressed natural gas(CNG)engine,the effects of this method on prediction results are analyzed considering distribution characteristics and calculation principles.The results show that compared with the original algorithm,the linear correlation R2 of the improved algorithm is increased by 1.9%,verifying the effectiveness of the proposed strategy.The modified LOLIMOT algorithm demonstrates higher convergence speed and stability,offering valuable application advantages in the field of emission models.关键词
天然气发动机/NOx排放/预测模型/局部线性模型树Key words
compressed natural gas(CNG)engine/nitrogen oxides emissions/prediction model/local linear model tree分类
能源科技引用本文复制引用
刘佳奇,卢炽华,刘志恩..LOLIMOT模型在CNG发动机NOx排放预测试验中的应用[J].重庆大学学报,2024,47(1):9-20,12.基金项目
国家重点研发计划资助项目(2018YFB0106401).Supported by the National Key Research and Development Program(2018YFB0106401). （2018YFB0106401）
