MSc.Thesis Defense:Mert Özçelik

ESTIMATION OF LIFE CYCLE GREENHOUSE GAS EMISSIONS OF ELECTRIC DELIVERY TRUCKS

Mert Özçelik
Industrial Engineering, MSc. Thesis, 2024

Thesis Jury

Asst. Prof. Tuğçe Yüksel (Thesis Advisor)

Asst. Prof. Sinan Yıldırım (Thesis Co-advisor)

Prof. Bülent Çatay

Assoc. Prof. Öznur Taştan

Assoc. Prof. Mustafa Gökçe Baydoğan

Date & Time: July 24th, 2024 –  10 AM

Place: FENS L029

Zoom Link: https://sabanciuniv.zoom.us/j/99309043472

Keywords : vehicle electrification, battery electric delivery trucks, greenhouse gas emissions, machine learning, simulation

Abstract

In this study, we investigate the regional differences in emission benefits of battery electric delivery truck electrification. In this regard, we build a simulation framework to quantify the regional differences in the use phase emissions across the United States. A vital part of our framework is the machine learning model we develop to predict the unit energy consumption of a battery electric delivery truck based on real world driving data. Using our framework, we perform two case studies to quantify the effect of ambient temperature and driving profile on the use phase emissions, respectively. In the first case study, we observe that our machine learning model can capture the increase in energy consumption at low temperatures quite well, however more data is needed to predict high temperature effects. As expected, the emissions are lower in regions where electricity production is cleaner. In the second case study, we observe that our framework can differentiate between the energy consumption under aggressive and gentle driving profiles.