Ageing-aware battery discharge prediction with deep learning

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Advanced neural interfaces are transforming applications ranging from neuroscience research to diagnostic tools (for mental state recognition, tremor and seizure detection) as well as prosthetic devices (for motor and communication recovery). By integratin ...

Dielectric Elastomer Actuators (DEAs) are a type of smart material described as compliant capacitors. They show impressive performances as soft actuators, such as a high strain and fast response. Nonetheless, replicating natural muscle function with DEAs h ...

Battery health prediction is significant while challenging for intelligent battery management. This article proposes a general framework for both short-term and long-term predictions of battery health under unseen dynamic loading and temperature conditions ...

The current restrictions on the registration of combustion engines in different countries and the harmful impacts of fossil fuels on the environment and human health have motivated decision-makers to use batteries and/or fuel cells as alternatives for comb ...

A user’s benefit from the energy stored in a battery over its lifetime depends on the time-varying characteristics of the battery, which are in turn affected by the chosen usage behavior. Both the capacity shrinkage and the number of lifetime cycles are st ...

Advanced battery electrodes require a cautious design of microscale particles with built-in nanoscale features to exploit the advantages of both micro- and nano-particles relative to their performance attributes. Herein, the dynamic behavior of nanosized S ...

The Fast Discharge Units (FDUs) of the Superconducting (SC) Toroidal Field (TF) coils in the European demonstration fusion power plant DEMO warrant the machine integrity over its full lifetime against severe failure events, such as SC coil quenches or any ...

Implanted medical devices (IMDs) have been widely developed to support the monitoring and recording of biological data inside the body or brain. Wirelessly powered IMDs, a subset of implantable electronics, have been proposed to eliminate the limitations r ...

Detailed population maps play an important role in diverse fields ranging from humanitarian action to urban planning. Generating such maps in a timely and scalable manner presents a challenge, especially in datascarce regions. To address it we have develop ...

In this study, a flexible, free-standing Fe -doped CoP nanoarrays electrode for superior lithium -ion storage has been successfully fabricated. The electrode combines the advantages of a Fe -doping and a flexible carbon cloth (CC) support, resulting in a h ...

A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...

Species distribution modeling is a highly versatile tool for understanding the intricate relationship between environmental conditions and species occurrences. However, the available data often lacks information on confirmed species absence and is limited ...

Layered cathodes are among the most promising cathodes for high-energy-density Li-ion batteries, yet hindered by the structural degradation from both bulk strain and surface oxygen loss at high voltage (above 4.5 V). Herein, we report a pre-fatigue trainin ...

This paper presents a comparison of machine learning (ML) methods used for three-dimensional localization of partial discharges (PD) in a power transformer tank. The study examines ML and deep learning (DL) methods, ranging from support vector machines (SV ...

Epilepsy, a major neurological disease, requires careful diagnosis and treatment. However, the detection of epileptic seizures remains a significant challenge. Current clinical practice relies on expert analysis of EEG signals, a process that is time-consu ...

Low-temperature plasmas (LTPs) at atmospheric pressure hold great promise for disinfection and sterilization applications. When compared to traditional sterilization technologies like autoclaving, LTPs may offer several benefits, including reduced energy c ...

Modern computing has enhanced our understanding of how social interactions shape collective behaviour in animal societies. Although analytical models dominate in studying collective behaviour, this study introduces a deep learning model to assess social in ...

Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

Monitoring forests, in particular their response to climate and land use change, requires studying long time scales. While efficient deep learning methods have been developed to process short time series of satellite imagery, leveraging long time series of ...

In an era where portable electronic devices are indispensable for a wide range of activities, the need for displays that provide both long-lasting battery life and excellent visibility in different lighting conditions is increasingly important. Emissive di ...

Ageing-aware battery discharge prediction with deep learning

Chattez avec Graph Search

Integrating Neural Interfaces with Machine Learning: Enabling Self-Sufficient and Ubiquitous Prosthetic and Diagnostic Devices

Inversing the actuation cycle of dielectric elastomer actuators for a facial prosthesis

Health Prediction for Lithium-Ion Batteries Under Unseen Working Conditions

Electrochemical devices and computer science: water/thermal management of proton exchange membrane fuel cells and electrolyzers in different scales

Optimal Depth of Discharge for Electric Batteries with Robust Capacity-Shrinkage Estimator

Dynamic Behavior of Spatially Confined Sn Clusters and Its Application in Highly Efficient Sodium Storage with High Initial Coulombic Efficiency

DEMO toroidal field coil fast discharge unit integration studies

Integrated Wireless Power, Data Communication, and Thermal Sensing System for Autonomous Multisite Brain Implants

High-resolution population maps derived from Sentinel-1 and Sentinel-2

Flexible free-standing Fe-CoP-NAs/CC nanoarrays for high-performance full lithium-ion batteries

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

On the selection and effectiveness of pseudo-absences for species distribution modeling with deep learning

A pre-fatigue training strategy to stabilize LiCoO2 at high voltage

Partial discharge localization in power transformer tanks using machine learning methods

Resource-Efficient Continual Learning for Personalized Online Seizure Detection

Characterization of low-temperature plasmas generated by dielectric barrier discharges for bacterial inactivation

Predicting the long-term collective behaviour of fish pairs with deep learning

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

MEMS-based Tunable Metasurface for Reflective Display Applications