Advanced Intelligent Management Technologies of New Energy Batteries

Dear Colleagues,

New energy batteries are pivotal for sustainable energy storage solutions, from electric vehicles to grid storage. Their reliable and safe operation hinges on accurate state monitoring and prediction. However, challenges such as nonlinear degradation mechanisms, varied/extreme operating conditions, and limited on-board computing resources hinder the accuracy and robustness of existing methods. This Special Issue aims to gather cutting-edge research advances in the state monitoring and prediction of new energy batteries, with a focus on fundamental challenges and innovative solutions in sensor technology, data-driven algorithms, electrochemical modelling and hybrid methodologies, hoping to bridge the lab-scale innovations and on-board/grid-scale applications. We encourage submissions exploring both theoretical breakthroughs and empirical studies to foster a comprehensive understanding of battery behavior and predictive capabilities. The scope includes state estimation (state-of-charge, state-of-health, state-of-power, state-of-energy, state-of-safety, remaining useful life, etc.), fault diagnosis and their prediction/prognosis across diverse new energy battery chemistries (lithium-ion, sodium-ion, fuel cell, flow batteries, etc.).

Potential topics include, but are not limited to, the following:

• Advanced SOC, SOH, SOP, SOE and SOS estimation algorithms.
• Fault diagnosis and prognosis for new energy batteries.
• Multi-physics coupling modeling for battery state estimation/prediction.
• Novel sensing technologies and multi-sensor data fusion for new energy battery monitoring.
• Physics-informed artificial intelligentmodels for battery state estimation/prediction.
• Low-computational-cost algorithms for on-board battery management systems.

Dr. Sijia Yang
Prof. Dr. Zeyu Chen
Dr. Jichao Hong
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Batteries is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• lithium-ion battery
• fuel cells
• lithium–sulfur battery
• solid-state battery
• flow battery
• energy storage systems
• electrical vehicles
• battery management systems
• SOX (SOC, SOH, SOP, SOE, SOS, SOT) estimation and prediction
• lifetime prediction
• battery safety diagnostics and prognostics
• fault diagnosis
• anomaly detection
• artificial intelligence
• physics-guided modeling