The emergence of electric vehicles(EVs)is critical for reducing environmental impacts and advancing sustainable transportation.Despite the known benefits,the complexities of EV integration with urban systems,power inf...The emergence of electric vehicles(EVs)is critical for reducing environmental impacts and advancing sustainable transportation.Despite the known benefits,the complexities of EV integration with urban systems,power infrastructure,and environmental policies remain in-sufficiently explored.This literature review seeks to fill these gaps by synthesizing recent research across three key domains:environmental impact and sustainability,pattern analysis and system science,and methodology and operation of EV systems.The focus is on how EV adoption impacts climate change,net-zero emissions,air pollution,power grid dynamics,and mobility patterns,along with evaluating the effectiveness of AI-driven methodologies in enhancing EV operation.We conducted a systematic literature review of top-tier publications from journals such as Nature,Science,and PNAS,covering environmental science,urban systems engineering,and operational research related to EVs.Our findings highlighted that while EVs have the potential to reduce greenhouse gas emissions and improve urban air quality significantly,their actual environmental benefits depend heavily on factors such as electricity generation sources and the lifecycle impacts of battery production.Furthermore,we identified patterns in EV integration that can inform infrastructure planning and revealed the efficacy of advanced computational techniques,particularly reinforcement learning,in optimizing EV operations.Our major contributions include a comprehensive overview of the environmental impacts of EVs,insights into the challenges and opportunities of integrating EVs into urban systems,and showcasing the potential of AI-driven methodologies to enhance EV operations,with significant implications for policymakers,urban planners,and researchers.展开更多
基金supported by funding from the National Research Foundation Singapore and other public agencies under its Centre for Energy and Emissions Modelling Phase 2(CE2M2.0)Programme(No:U24N120001).
文摘The emergence of electric vehicles(EVs)is critical for reducing environmental impacts and advancing sustainable transportation.Despite the known benefits,the complexities of EV integration with urban systems,power infrastructure,and environmental policies remain in-sufficiently explored.This literature review seeks to fill these gaps by synthesizing recent research across three key domains:environmental impact and sustainability,pattern analysis and system science,and methodology and operation of EV systems.The focus is on how EV adoption impacts climate change,net-zero emissions,air pollution,power grid dynamics,and mobility patterns,along with evaluating the effectiveness of AI-driven methodologies in enhancing EV operation.We conducted a systematic literature review of top-tier publications from journals such as Nature,Science,and PNAS,covering environmental science,urban systems engineering,and operational research related to EVs.Our findings highlighted that while EVs have the potential to reduce greenhouse gas emissions and improve urban air quality significantly,their actual environmental benefits depend heavily on factors such as electricity generation sources and the lifecycle impacts of battery production.Furthermore,we identified patterns in EV integration that can inform infrastructure planning and revealed the efficacy of advanced computational techniques,particularly reinforcement learning,in optimizing EV operations.Our major contributions include a comprehensive overview of the environmental impacts of EVs,insights into the challenges and opportunities of integrating EVs into urban systems,and showcasing the potential of AI-driven methodologies to enhance EV operations,with significant implications for policymakers,urban planners,and researchers.
