Developing extreme fast charge battery protocols–A review spanning materials to systems
Extreme fast charging (XFC) has become a focal research point in the lithium-battery
community over the last several years. As adoption of electric vehicles increases, fast …
community over the last several years. As adoption of electric vehicles increases, fast …
Feature–target pairing in machine learning for battery health diagnosis and prognosis: A critical review
Z Huang, L Sugiarto, YC Lu - EcoMat, 2023 - Wiley Online Library
Lithium‐ion batteries (LIBs) have been dominating the markets of electric vehicles and grid
energy storage. Accurate monitoring of battery health status has been one of the most critical …
energy storage. Accurate monitoring of battery health status has been one of the most critical …
Battery state-of-health diagnostics during fast cycling using physics-informed deep-learning
Rapid, in-situ Li-ion battery state-of-health (SOH) quantification is challenging. Li-ion battery
aging can vary significantly with chemistry, operating conditions, cycling demands, electrode …
aging can vary significantly with chemistry, operating conditions, cycling demands, electrode …
[HTML][HTML] Battery calendar aging and machine learning
Eric J. Dufek, PhD, is the department manager for the Energy Storage and Electric
Transportation Department at Idaho National Laboratory. His research interests span from …
Transportation Department at Idaho National Laboratory. His research interests span from …
[HTML][HTML] Accelerated battery life predictions through synergistic combination of physics-based models and machine learning
There are tremendous economic and technical benefits to shortening battery test periods
through robust predictive methods. Accurate long-term forecasting of battery life enables …
through robust predictive methods. Accurate long-term forecasting of battery life enables …
[HTML][HTML] Predicting battery lifetime under varying usage conditions from early aging data
Accurate battery lifetime prediction is important for maintenance, warranties, and cell design.
However, manufacturing variability and usage-dependent degradation make life prediction …
However, manufacturing variability and usage-dependent degradation make life prediction …
Data‐Driven Online Prognosis of Rechargeable Batteries: Prospect and Perspective
KY Liu, TT Wang, X Liu, HJ Peng - Batteries & Supercaps, 2024 - Wiley Online Library
Along with the growing popularity of electric vehicles (EVs) and smart grids, rechargeable
batteries are playing an increasingly important role in the field of energy storage. To ensure …
batteries are playing an increasingly important role in the field of energy storage. To ensure …
[HTML][HTML] Battery data integrity and usability: Navigating datasets and equipment limitations for efficient and accurate research into battery aging
KL Gering, MG Shirk, S Kim, CM Walker… - Frontiers in Energy …, 2023 - frontiersin.org
A tremendous commitment of resources is needed to acquire, understand and apply battery
data in terms of performance and aging behavior. There are many state of performance …
data in terms of performance and aging behavior. There are many state of performance …
[HTML][HTML] Performance Analysis of Electric Vehicles with a Fuel Cell–Supercapacitor Hybrid System
C Armenta-Déu, A Arenas - Eng, 2023 - mdpi.com
This paper presents a new methodology to evaluate the performance of an electric vehicle
hybrid power system consisting of a fuel cell and a supercapacitor. The study compares the …
hybrid power system consisting of a fuel cell and a supercapacitor. The study compares the …
AI for Manufacturing and Healthcare: a chemistry and engineering perspective
Artificial Intelligence (AI) approaches are increasingly being applied to more and more
domains of Science, Engineering, Chemistry, and Industries to not only improve efficiencies …
domains of Science, Engineering, Chemistry, and Industries to not only improve efficiencies …