Research Topic

Advanced Energy Storage System for Transportation Electrification

About this Research Topic

From fossil fuels to electricity, transportation is now moving to an electric-driven and sustainable paradigm, especially within the scope that more carbon-free electricity is generated from wind, solar and hydro, etc. To enable a reliable and efficient future transportation transition, the power quality from the energy storage system (ESS) has to be guaranteed in advance. Motivated by this, smarter, safer, and more reliable ESS has become a hot topic recently for transportation applications. Thanks to the booming of the energy storage techniques and artificial intelligence, advanced ESS can promise some desired performance to facilitate the development of next generation transportation. Narrowing to the specific focuses, the emerging technologies in batteries, super-capacitor and fuel cell have large potential for improving the energy and power density of ESS. The wide band-gap semiconductors can help designing the high efficiency of energy management and power conversion systems. Big data technique will benefit the estimation, diagnosis, and prognostic of the ESS.

The performance of the ESS greatly affects the progress of transportation electrification. The next generation ESS should be an optimal integration of energy storage, conversion system and the associated management system. In this thread, new research findings from theoretical and application point of view are demanded for the improvement of the ESS at present. Thus, this Research Topic aims to investigate the advanced ESS oriented for transportation electrification, which enables to mitigate the emerging challenges from storage components, power electronics and artificial intelligence. In this sense, this research topic serves to solicit and foster both high-quality original research and review articles from the recently emerging and cross-disciplinary field, to improve the design, modeling and control of the advanced ESS for transportation electrification.

Topics of interest include, but are not limited to the following:

· Advanced ESS design for electric mobility, i.e., electric vehicles, electric trains, electric ships and electric aircrafts.
· Management of ESS: state estimation, health prognostic, charge control, thermal/safety management, etc.
· Hybrid energy systems: architecture, sizing, energy management, etc.
· Fault prognosis and diagnosis in ESS of transportation electrification.
· Advanced artificial intelligence in energy management of ESS.
· Smarter manufacturing for advanced ESS.
· Real-time hardware in the loop (HIL) simulation of ESS.
· Cyber-physics, big data for promoting the utility of ESS in transportation electrification.


Keywords: Transportation Electrification, Artificial Intelligence, Intelligent Energy Management, Big Data, Energy Storage System


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.

From fossil fuels to electricity, transportation is now moving to an electric-driven and sustainable paradigm, especially within the scope that more carbon-free electricity is generated from wind, solar and hydro, etc. To enable a reliable and efficient future transportation transition, the power quality from the energy storage system (ESS) has to be guaranteed in advance. Motivated by this, smarter, safer, and more reliable ESS has become a hot topic recently for transportation applications. Thanks to the booming of the energy storage techniques and artificial intelligence, advanced ESS can promise some desired performance to facilitate the development of next generation transportation. Narrowing to the specific focuses, the emerging technologies in batteries, super-capacitor and fuel cell have large potential for improving the energy and power density of ESS. The wide band-gap semiconductors can help designing the high efficiency of energy management and power conversion systems. Big data technique will benefit the estimation, diagnosis, and prognostic of the ESS.

The performance of the ESS greatly affects the progress of transportation electrification. The next generation ESS should be an optimal integration of energy storage, conversion system and the associated management system. In this thread, new research findings from theoretical and application point of view are demanded for the improvement of the ESS at present. Thus, this Research Topic aims to investigate the advanced ESS oriented for transportation electrification, which enables to mitigate the emerging challenges from storage components, power electronics and artificial intelligence. In this sense, this research topic serves to solicit and foster both high-quality original research and review articles from the recently emerging and cross-disciplinary field, to improve the design, modeling and control of the advanced ESS for transportation electrification.

Topics of interest include, but are not limited to the following:

· Advanced ESS design for electric mobility, i.e., electric vehicles, electric trains, electric ships and electric aircrafts.
· Management of ESS: state estimation, health prognostic, charge control, thermal/safety management, etc.
· Hybrid energy systems: architecture, sizing, energy management, etc.
· Fault prognosis and diagnosis in ESS of transportation electrification.
· Advanced artificial intelligence in energy management of ESS.
· Smarter manufacturing for advanced ESS.
· Real-time hardware in the loop (HIL) simulation of ESS.
· Cyber-physics, big data for promoting the utility of ESS in transportation electrification.


Keywords: Transportation Electrification, Artificial Intelligence, Intelligent Energy Management, Big Data, Energy Storage System


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.

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Submission Deadlines

03 January 2021 Abstract
03 May 2021 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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Topic Editors

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Submission Deadlines

03 January 2021 Abstract
03 May 2021 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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