About this Research Topic
Ground mobility is undergoing a paradigm shift towards efficient, green and intelligent transportation. Electrification and automation constitute two of the most important technological frontiers in this regard. Intelligent electrified vehicles (iEVs) represent a combination of these two promising technologies and have become a hot research area. Optimal control of the electrified vehicle with artificial intelligence is an emerging technology. It requires sufficient research and development at a system engineering level to allow global optimization of iEVs that balances mobility, economy, and learning capabilities. The development of iEVs is expected to bring significant evolution to transportation systems and change the role that the human driver will play in the future. Moreover, the potential contribution of these systems to traffic modes, infrastructure, policies, and roles make iEVs a challenging research topic in the next five years.
The development of iEVs is tightly conjoined, coordinated, and integrated with human and social characteristics, and this has been steadily growing to become an emerging research focus. Considering the development and limitations of current iEVs, innovative research concepts, significant theoretical findings, and application case studies with an emphasis on advanced controls for intelligent electrified vehicles are required. Advanced multi-disciplinary techniques such as automatic control, system engineering, data science, machine learning, and deep learning will enable the development of next-generation iEVs. The Research Topic aims to provide up-to-date research concepts, theoretical findings and practical solutions that could contribute to the electrification and automation of modern vehicles.
High-quality and original studies within a wide range of iEVs-related topics are welcomed. The studies are expected to bring novel contributions to the development and implementation of iEVs. Submissions to this Research Topic could include, but are not limited to, the following areas:
• Predictive control and optimization of advanced powertrain of EVs
• Electrified vehicle dynamics and control
• Advanced modeling and control of driver-vehicle interactions
• Cyber-physical system based EV control and optimization
• Integration of electrified vehicles with Intelligent Transportation Systems (ITS) and/or smart grids
• Fault detection and fault-tolerant control of EV systems
• Advanced energy management systems for iEVs
• Human factors in iEVs
• Machine learning methods for iEVs state estimation and prediction
• Testing, verification, and evaluation for iEVs application
Keywords: Intelligent Electrified Vehicles, Advanced Modeling and Control, Intelligent Transportation Systems, Intelligent Vehicles, Machine Learning
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.