{"title":"基于 GWO-LSTM 的柴油发动机氮氧化物排放预测","authors":"Biwei Lu, Jiehui Li","doi":"10.1007/s12239-024-00068-w","DOIUrl":null,"url":null,"abstract":"<p>Diesel engine NOx is the main harmful emission of motor vehicles. Accurate measurement of NOx emission is beneficial to the control of SCR (selective catalytic reduction) urea injection so as to reduce emissions. At present, NOx emission value is mainly obtained by NOx sensor or MAP calibration and these two methods have limitations in practical applications. In this study, PCA (principal component analysis) is used to reduce the dimension of diesel engine operating data of WHTC (the world harmonized transient cycle) bench test, which can make data visualized in three-dimensional space. Then transient diesel engine NOx prediction model is built based on LSTM, and GWO (grey wolf optimizer) is used to optimize the parameters of LSTM. The results showed that <i>R</i><sup>2</sup> (determination coefficients) of the GWO-LSTM is 0.987; In the untrained data set, MAE (mean absolute error), MAPE (mean absolute percentage error) and RMSE (root mean square error) are 18.75 × 10<sup>–6</sup>, 3.23% and 20.29 × 10<sup>–6</sup>, respectively. The same accuracy index are be compared with PSO-BP and static map. It is proved that the GWO-LSTM model can accurately predict the transient NOx emission of diesel engine, and also has good generalization ability with reliability, which provides a reference for software instead of hardware to control diesel engine emission.</p>","PeriodicalId":50338,"journal":{"name":"International Journal of Automotive Technology","volume":"8 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"NOX Emission Prediction of Diesel Engine Based on GWO-LSTM\",\"authors\":\"Biwei Lu, Jiehui Li\",\"doi\":\"10.1007/s12239-024-00068-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Diesel engine NOx is the main harmful emission of motor vehicles. Accurate measurement of NOx emission is beneficial to the control of SCR (selective catalytic reduction) urea injection so as to reduce emissions. At present, NOx emission value is mainly obtained by NOx sensor or MAP calibration and these two methods have limitations in practical applications. In this study, PCA (principal component analysis) is used to reduce the dimension of diesel engine operating data of WHTC (the world harmonized transient cycle) bench test, which can make data visualized in three-dimensional space. Then transient diesel engine NOx prediction model is built based on LSTM, and GWO (grey wolf optimizer) is used to optimize the parameters of LSTM. The results showed that <i>R</i><sup>2</sup> (determination coefficients) of the GWO-LSTM is 0.987; In the untrained data set, MAE (mean absolute error), MAPE (mean absolute percentage error) and RMSE (root mean square error) are 18.75 × 10<sup>–6</sup>, 3.23% and 20.29 × 10<sup>–6</sup>, respectively. The same accuracy index are be compared with PSO-BP and static map. It is proved that the GWO-LSTM model can accurately predict the transient NOx emission of diesel engine, and also has good generalization ability with reliability, which provides a reference for software instead of hardware to control diesel engine emission.</p>\",\"PeriodicalId\":50338,\"journal\":{\"name\":\"International Journal of Automotive Technology\",\"volume\":\"8 1\",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2024-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Automotive Technology\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1007/s12239-024-00068-w\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Automotive Technology","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s12239-024-00068-w","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
NOX Emission Prediction of Diesel Engine Based on GWO-LSTM
Diesel engine NOx is the main harmful emission of motor vehicles. Accurate measurement of NOx emission is beneficial to the control of SCR (selective catalytic reduction) urea injection so as to reduce emissions. At present, NOx emission value is mainly obtained by NOx sensor or MAP calibration and these two methods have limitations in practical applications. In this study, PCA (principal component analysis) is used to reduce the dimension of diesel engine operating data of WHTC (the world harmonized transient cycle) bench test, which can make data visualized in three-dimensional space. Then transient diesel engine NOx prediction model is built based on LSTM, and GWO (grey wolf optimizer) is used to optimize the parameters of LSTM. The results showed that R2 (determination coefficients) of the GWO-LSTM is 0.987; In the untrained data set, MAE (mean absolute error), MAPE (mean absolute percentage error) and RMSE (root mean square error) are 18.75 × 10–6, 3.23% and 20.29 × 10–6, respectively. The same accuracy index are be compared with PSO-BP and static map. It is proved that the GWO-LSTM model can accurately predict the transient NOx emission of diesel engine, and also has good generalization ability with reliability, which provides a reference for software instead of hardware to control diesel engine emission.
期刊介绍：
The International Journal of Automotive Technology has as its objective the publication and dissemination of original research in all fields of AUTOMOTIVE TECHNOLOGY, SCIENCE and ENGINEERING. It fosters thus the exchange of ideas among researchers in different parts of the world and also among researchers who emphasize different aspects of the foundations and applications of the field.
Standing as it does at the cross-roads of Physics, Chemistry, Mechanics, Engineering Design and Materials Sciences, AUTOMOTIVE TECHNOLOGY is experiencing considerable growth as a result of recent technological advances. The Journal, by providing an international medium of communication, is encouraging this growth and is encompassing all aspects of the field from thermal engineering, flow analysis, structural analysis, modal analysis, control, vehicular electronics, mechatronis, electro-mechanical engineering, optimum design methods, ITS, and recycling. Interest extends from the basic science to technology applications with analytical, experimental and numerical studies.
The emphasis is placed on contributions that appear to be of permanent interest to research workers and engineers in the field. If furthering knowledge in the area of principal concern of the Journal, papers of primary interest to the innovative disciplines of AUTOMOTIVE TECHNOLOGY, SCIENCE and ENGINEERING may be published. Papers that are merely illustrations of established principles and procedures, even though possibly containing new numerical or experimental data, will generally not be published.
When outstanding advances are made in existing areas or when new areas have been developed to a definitive stage, special review articles will be considered by the editors.
No length limitations for contributions are set, but only concisely written papers are published. Brief articles are considered on the basis of technical merit.
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