Prediction of NOx Transient Emission for Diesel Vehicle&nbsp;Based on CEEMDAN-SVR Model

YU Yang; WANG Yanyan; LI Jiaqiang; LIU Xueyuan; HE Chao; WEI Heng; JI Jianglin

Vehicle Engine ›› 2021, Vol. 0 ›› Issue (2) : 43-48.

Prediction of NO_x Transient Emission for Diesel Vehicle Based on CEEMDAN-SVR Model

YU Yang^1,2,WANG Yanyan^1,2,LI Jiaqiang^1,2,LIU Xueyuan^1,2,HE Chao^1,2,WEI Heng^1,2,JI Jianglin^1,2

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Abstract

Diesel engine has high fuel thermal efficiency, but too high nitrogen oxide(NO_x) emission limits its development. Accurate emission prediction of diesel vehicles in real road conditions is conducive to the development and design of diesel engine. The transient NO_x emission sequence has the characteristics of nonlinear, nonstationary and non-normal distribution, which makes it difficult to predict directly using the machine learning algorithm. In order to accurately predict the transient NO_x emission, the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) was applied to the diesel NO_x transient emission model. Combined with the efficient modeling capability of support vector regression (SVR) for complex time series, CEEMDAN-SVR was proposed as a diesel NO_x transient prediction model. CEEMDAN was used to decompose the NO_x emission sequence to obtain subsequences at different sampling frequencies. SVR was used to model and predict each sub-sequence, and then the final prediction result was obtained by integrating the predicted values of each subsequence. The results show that CEEMDAN algorithm can effectively reduce the non-stationarization of NO_x sequence and it becomes easier to extract local feature information of data through SVR machine learning model with lower prediction error.

Key words

diesel vehicle / nitrogen oxide / transient emission / support vector regression / adaptive noise / empirical mode decomposition

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YU Yang,WANG Yanyan,LI Jiaqiang,LIU Xueyuan,HE Chao,WEI Heng,JI Jianglin. Prediction of NO_x Transient Emission for Diesel Vehicle Based on CEEMDAN-SVR Model[J]. Vehicle Engine. 2021, 0(2): 43-48