| Prediction of instantaneous real-world emissions from diesel light-duty vehicles based on an integrated artificial neural network and vehicle dynamics model J Seo, B Yun, J Park, J Park, M Shin, S Park Science of The Total Environment 786, 147359, 2021 | 49 | 2021 |
| Estimation of Total Transport CO2 Emissions Generated by Medium- and Heavy-Duty Vehicles (MHDVs) in a Sector of Korea J Seo, J Park, Y Oh, S Park Energies 9 (8), 638, 2016 | 49 | 2016 |
| Emission factor development for light-duty vehicles based on real-world emissions using emission map-based simulation J Seo, J Park, J Park, S Park Environmental Pollution 270, 116081, 2021 | 42 | 2021 |
| Optimizing model parameters of artificial neural networks to predict vehicle emissions J Seo, S Park Atmospheric Environment 294, 119508, 2023 | 34 | 2023 |
| Estimation of CO2 emissions from heavy-duty vehicles in Korea and potential for reduction based on scenario analysis J Seo, H Kim, S Park Science of the Total Environment 636, 1192-1201, 2018 | 24 | 2018 |
| Development of a cold-start emission model for diesel vehicles using an artificial neural network trained with real-world driving data J Seo, B Yun, J Kim, M Shin, S Park Science of the Total Environment 806, 151347, 2022 | 18 | 2022 |
| Estimation of CO2 reduction by parallel hard-type power hybridization for gasoline and diesel vehicles Y Oh, J Park, JT Lee, J Seo, S Park Science of the Total Environment 595, 2-12, 2017 | 18 | 2017 |
| Development of vehicle emission rates based on vehicle-specific power and velocity J Park, J Seo, S Park Science of The Total Environment 857, 159622, 2023 | 15 | 2023 |
| Developing an official program to calculate heavy-duty vehicles CO2 emissions in Korea J Seo, S Park Transportation Research Part D: Transport and Environment 120, 103774, 2023 | 13 | 2023 |
| Development strategies to satisfy corporate average CO2 emission regulations of light duty vehicles (LDVs) in Korea Y Oh, J Park, JT Lee, J Seo, S Park Energy Policy 98, 121-132, 2016 | 13 | 2016 |
| Greenhouse Gas Emissions from Heavy-duty Natural Gas Vehicles in Korea J Seo, S Kwon, S Park Aerosol and Air Quality Research 20 (6), 1418-1428, 2020 | 5 | 2020 |
| Machine learning-based estimation of gaseous and particulate emissions using internally observable vehicle operating parameters J Seo, Y Lim, J Han, S Park Urban Climate 52, 101734, 2023 | 2 | 2023 |
| Comprehensive Thermal Modeling and Analysis of a 2019 Nissan Leaf Plus for Enhanced Battery Electric Vehicle Performance R Al Haddad, C Mansour, N Kim, J Seo, M Nemer SAE Technical Paper, 2024 | 1 | 2024 |
| Impact of Cold Ambient Temperature and Extreme Conditions on Electric Vehicles P Walsh, R Isaac, R Vijayagopal, A Rousseau, J Seo, N Kim Program Record (Vehicle Technologies Office), 2024 | | 2024 |
| HES 를 활용한 대형자동차의 CO2 배출량에 영향을 미치는 차량 변수의 민감도 분석 서지구， 김자륭， 김남용， 김종완， 박성욱 한국자동차공학회 논문집 30 (9), 2022 | | 2022 |
| Development of the Heavy-duty vehicle Emission Simulator (HES) for estimating fuel consumption and CO2 emission from heavy-duty vehicles J Seo 한양대학교, 2022 | | 2022 |
Sungwook ParkHanyang University在 hanyang.ac.kr 的电子邮件经过验证
