Related papers: Data augmentation for battery materials using latt…
Due to the increasing volume of Electric Vehicles in automotive markets and the limited lifetime of onboard lithium-ion batteries (LIBs), the large-scale retirement of LIBs is imminent. The battery packs retired from Electric Vehicles still…
The reliability and safety of Lithium-ion batteries (LiBs) are of great concern in the energy storage industry. Nevertheless, the real-time monitoring of their degradation remains challenging due to limited quantitative metrics available…
Online Class-Incremental (OCI) learning has sparked new approaches to expand the previously trained model knowledge from sequentially arriving data streams with new classes. Unfortunately, OCI learning can suffer from catastrophic…
Data Augmentation (DA) is known to improve the generalizability of deep neural networks. Most existing DA techniques naively add a certain number of augmented samples without considering the quality and the added computational cost of these…
Fast and reliable validation of novel designs in complex physical systems such as batteries is critical to accelerating technological innovation. However, battery research and development remain bottlenecked by the prohibitively high time…
The degradation process of lithium-ion batteries is intricately linked to their entire lifecycle as power sources and energy storage devices, encompassing aspects such as performance delivery and cycling utilization. Consequently, the…
Meta-devices have gained significant attention and have been widely utilized in optical systems for focusing and imaging, owing to their lightweight, high-integration, and exceptional-flexibility capabilities. However, based on the…
Capacity degradation of lithium-ion batteries under long-term cyclic aging is modelled via a flexible sigmoidal-type regression set-up, where the regression parameters can be interpreted. Different approaches known from the literature are…
Early degradation prediction of lithium-ion batteries is crucial for ensuring safety and preventing unexpected failure in manufacturing and diagnostic processes. Long-term capacity trajectory predictions can fail due to cumulative errors…
Lithium-ion batteries (LiBs) have transformed electrochemical energy storage technologies and made a substantial contribution to grid-scale energy storage and the e-mobility revolution. Notwithstanding their many benefits, safety issues…
To further improve Lithium-ion batteries (LiBs), a profound understanding of complex battery processes is crucial. Physical models offer understanding but are difficult to validate and parameterize. Therefore, automated machine-learning…
This paper discusses and evaluates ideas of data balancing and data augmentation in the context of mathematical objects: an important topic for both the symbolic computation and satisfiability checking communities, when they are making use…
In this paper, we introduce an approach for the prediction of capacity for over 100,000 spinel compounds relevant for battery materials, from which we propose the 20 most promising candidate materials. In the design of batteries, selecting…
Data augmentation plays a key role in modern machine learning pipelines. While numerous augmentation strategies have been studied in the context of computer vision and natural language processing, less is known for other data modalities.…
Cell inconsistency within a lithium-ion battery system poses a significant challenge in maximizing the system operational time. This study presents an optimization-driven active balancing method to minimize the effects of cell inconsistency…
Deep neural networks have emerged as very successful tools for image restoration and reconstruction tasks. These networks are often trained end-to-end to directly reconstruct an image from a noisy or corrupted measurement of that image. To…
Lithium ion batteries have been a central part of consumer electronics for decades. More recently, they have also become critical components in the quickly arising technological fields of electric mobility and intermittent renewable energy…
Rechargeable lithium-ion (Li-ion) batteries are a ubiquitous element of modern technology. In the last decades, the production and design of such batteries and their adjacent embedded charging and safety protocols, denoted by Battery…
Liquid metal batteries (LMBs) are a promising grid-scale storage device however, the scalability of this technology and its electrochemical performance is limited by mass transport overpotentials. In this work, a numerical model of a…
Lithium-ion batteries (LIBs) are the leading technology used in consumer electronics, electric vehicles, and grid-level electrochemical energy storage applications. The ever-increasing use of LIBs has highlighted a gap in understanding of…