Analysis of factors affecting energy consumption of electrified vehicles using adaptive cruise control technology

Abstract

Greenhouse gas (GHG) emission is a significant cause of climate change and a barrier to achieving sustainable development, especially the transport sector accounts for a quarter of global GHG emissions. In Thailand, road transport accounts for over half of all transport-related GHG emissions. To deal with GHG emissions and pollution crises, electrified vehicles (EVs) are becoming a more viable option for achieving zero-emission transportation and have been widely recognized in several countries, such as China, the European Union (EU), and the United States (US). However, the anxiety of drivers regarding the capability of travel distance and sufficient charging stations is a crucial factor in the transition from fossil fuel to electricity. While next-generation automotive vehicles are incessantly developed, autonomous vehicles, which help humans to drive safely and comfortably, are popular in markets because AVs have Advanced Driver Assistance Systems (ADAS) features such as Adaptive Cruise Control (ACC) or Lane Keeping Assistance (LKA). Due to the growth of AVs and EVs, this study aims to investigate the factors that influence the energy consumption of AVs, focusing on battery electric vehicle (BEV), hybrid electric vehicle (HEV), and Internal combustion engine vehicles (ICEV), having ACC technology to provide insights. which is the energy consumption and environment of AVs, for stakeholders who are government policies maker and consumers. Moreover, this study used machine learning (ML) to predict energy consumption and analyze factors influencing the energy consumption of testing vehicles. This study found that utilizing the ACC of the test vehicles is inefficient in reducing the energy consumption because these vehicles maintain a constant speed, necessitating the continuous operation of the engine and motors. In addition, activating the ACC of BEV and ICEV results in frequent acceleration and deceleration, leading to increased energy consumption than usual driving. In terms of testing efficiency energy consumption of next-generation automotive vehicles, ICEVs are the most energy consumption than BEVs and HEVs in all route modes. The influence factors, such as speed and slope, are also significant factors that impact the performance and energy of test vehicles.