Development and Validation of Prediction Model for Exhaust Emissions During Tractor Plow Tillage

In this study, to compensate for the constraints of high unit cost of portable emission measurement system (PEMS) and measurement environment, we developed a tractor operation-based emission prediction model. We also evaluated the developed prediction model using validation metrics. In addition to e...

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Main Authors: Ryu-Gap Lim, Tae-Bum Kim, Wan-Soo Kim, Seung-Yun Baek, Hyeon-Ho Jeon, Jee-Young Ham, Chul Yoo, Yong-Joo Kim
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Agriculture
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Online Access:https://www.mdpi.com/2077-0472/14/12/2334
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author Ryu-Gap Lim
Tae-Bum Kim
Wan-Soo Kim
Seung-Yun Baek
Hyeon-Ho Jeon
Jee-Young Ham
Chul Yoo
Yong-Joo Kim
author_facet Ryu-Gap Lim
Tae-Bum Kim
Wan-Soo Kim
Seung-Yun Baek
Hyeon-Ho Jeon
Jee-Young Ham
Chul Yoo
Yong-Joo Kim
author_sort Ryu-Gap Lim
collection DOAJ
description In this study, to compensate for the constraints of high unit cost of portable emission measurement system (PEMS) and measurement environment, we developed a tractor operation-based emission prediction model. We also evaluated the developed prediction model using validation metrics. In addition to engine load data, correlation analysis was conducted on engine temperature and fuel consumption variables. The results showed a high correlation of more than 0.5 between emissions and engine temperature, and a high correlation of more than 0.5 between emissions and fuel consumption for emissions except CO and THC. The R<sup>2</sup> values of the CO, THC, NOx, and PM emission prediction models were 0.81, 0.82, 0.85, and 0.97, respectively, showing good overall predictive performance. The prediction models for CO, THC, NOx, and PM emissions developed using the third-order regression analysis all showed excellent performance with an average absolute percentage error of around 2%. Therefore, the developed emission regression model can be used to predict tractor emissions using various variables. Through the exhaust emissions prediction model developed in this study, eco-friendly technology according to the optimal engine design is expected to increase. In addition, it is expected that agricultural machinery prices will be stabilized and export competitiveness will be secured.
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spelling doaj-art-362e7b09e22f40359f9c32249c38db712024-12-27T14:03:24ZengMDPI AGAgriculture2077-04722024-12-011412233410.3390/agriculture14122334Development and Validation of Prediction Model for Exhaust Emissions During Tractor Plow TillageRyu-Gap Lim0Tae-Bum Kim1Wan-Soo Kim2Seung-Yun Baek3Hyeon-Ho Jeon4Jee-Young Ham5Chul Yoo6Yong-Joo Kim7Department of Convergent Biosystems Engineering, Sunchon National University, Suncheon 57922, Republic of KoreaFuel Injection System Korea Central Distributor, Diesel Service Korea Co. Ltd., Daejeon 34357, Republic of KoreaDepartment of Bio-Industrial Machinery Engineering, Kyungpook National University, Daegu 41566, Republic of KoreaDepartment of Biosystems Machinery Engineering, Chungnam National University, Daejeon 34134, Republic of KoreaDepartment of Biosystems Machinery Engineering, Chungnam National University, Daejeon 34134, Republic of KoreaEmission Inventory Management Team, National Air Emission Inventory and Research Center, Cheongju 28160, Republic of KoreaEmission Inventory Management Team, National Air Emission Inventory and Research Center, Cheongju 28160, Republic of KoreaDepartment of Biosystems Machinery Engineering, Chungnam National University, Daejeon 34134, Republic of KoreaIn this study, to compensate for the constraints of high unit cost of portable emission measurement system (PEMS) and measurement environment, we developed a tractor operation-based emission prediction model. We also evaluated the developed prediction model using validation metrics. In addition to engine load data, correlation analysis was conducted on engine temperature and fuel consumption variables. The results showed a high correlation of more than 0.5 between emissions and engine temperature, and a high correlation of more than 0.5 between emissions and fuel consumption for emissions except CO and THC. The R<sup>2</sup> values of the CO, THC, NOx, and PM emission prediction models were 0.81, 0.82, 0.85, and 0.97, respectively, showing good overall predictive performance. The prediction models for CO, THC, NOx, and PM emissions developed using the third-order regression analysis all showed excellent performance with an average absolute percentage error of around 2%. Therefore, the developed emission regression model can be used to predict tractor emissions using various variables. Through the exhaust emissions prediction model developed in this study, eco-friendly technology according to the optimal engine design is expected to increase. In addition, it is expected that agricultural machinery prices will be stabilized and export competitiveness will be secured.https://www.mdpi.com/2077-0472/14/12/2334agricultural tractorplow tillageprediction modelportable emissions measurement system (PEMS)exhaust emissions
spellingShingle Ryu-Gap Lim
Tae-Bum Kim
Wan-Soo Kim
Seung-Yun Baek
Hyeon-Ho Jeon
Jee-Young Ham
Chul Yoo
Yong-Joo Kim
Development and Validation of Prediction Model for Exhaust Emissions During Tractor Plow Tillage
Agriculture
agricultural tractor
plow tillage
prediction model
portable emissions measurement system (PEMS)
exhaust emissions
title Development and Validation of Prediction Model for Exhaust Emissions During Tractor Plow Tillage
title_full Development and Validation of Prediction Model for Exhaust Emissions During Tractor Plow Tillage
title_fullStr Development and Validation of Prediction Model for Exhaust Emissions During Tractor Plow Tillage
title_full_unstemmed Development and Validation of Prediction Model for Exhaust Emissions During Tractor Plow Tillage
title_short Development and Validation of Prediction Model for Exhaust Emissions During Tractor Plow Tillage
title_sort development and validation of prediction model for exhaust emissions during tractor plow tillage
topic agricultural tractor
plow tillage
prediction model
portable emissions measurement system (PEMS)
exhaust emissions
url https://www.mdpi.com/2077-0472/14/12/2334
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