Transport Decarbonization: Energy Control and Optimization

Dear Colleagues,

Transport decarbonization is a critical global priority in the context of climate change mitigation and sustainable development. As transportation accounts for a significant portion of global greenhouse gas emissions, the transition toward electrified, intelligent, and low-carbon transport systems is central to achieving net-zero targets. With the rapid electrification of road, rail, and urban transit networks, energy optimization, control strategies, and the integration of renewable energy sources have become urgent research topics. Electrified transportation systems now intersect with complex energy infrastructures, requiring advanced planning, control, and predictive management to ensure reliable, efficient, and sustainable operations. This Special Issue focuses on addressing the technical and scientific challenges of decarbonizing the transport sector through energy system optimization, control innovation, and data-driven approaches.

This Special Issue aims to gather state-of-the-art research and innovative solutions in the field of transport decarbonization in terms of energy control and optimization.  It aligns with the journal’s scope by promoting interdisciplinary research that combines power systems engineering, transportation electrification, and intelligent optimization. The Special Issue will highlight cutting-edge developments in modeling, optimization, and control strategies that support the transition to sustainable transport infrastructures. By drawing on methodologies from artificial intelligence, machine learning, power electronics, and system resilience, this Special Issue aims to promote the dissemination of innovative ideas and best practices that can accelerate the transition to a sustainable transportation future.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

(1) Planning, operation, and control of electrified transportation;

(2) Modeling and control of microgrid and electric vehicle solutions;

(3) Modeling and control for energy storage in electrical railway networks;

(4) AI and machine learning in electrified transportation;

(5) Emergency operations of electrified transportation;

(6) Resilience assessment and optimization of electrified transportation.

We look forward to receiving your contributions.

Dr. Yinyu Chen
Dr. Wei Wang
Dr. Zhongbei Tian
Dr. Junyu Chen
Guest Editors

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