Hybrid physics-informed neural networks for lithium-ion battery modeling and prognosis

A Survey of Bayesian Calibration and Physics-informed Neural Networks in Scientific Modeling

(2021) Felipe A. C. Viana et al.   ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING

An ensemble prognostic method for lithium-ion battery capacity estimation based on time-varying weight allocation

(2020) Yujie Cheng et al.   APPLIED ENERGY

Physics-informed neural networks for missing physics estimation in cumulative damage models: a case study in corrosion fatigue

(2020) Arinan Dourado et al.   JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING

Cumulative Damage Modeling with Recurrent Neural Networks

(2020) Renato Giorgiani Nascimento et al.   AIAA JOURNAL

Data driven battery modeling and management method with aging phenomenon considered

(2020) Shuangqi Li et al.   APPLIED ENERGY

Prognostic health condition for lithium battery using the partial incremental capacity and Gaussian process regression

(2019) Xiaoyu Li et al.   JOURNAL OF POWER SOURCES

Remaining useful life prediction of lithium-ion batteries based on false nearest neighbors and a hybrid neural network

(2019) Guijun Ma et al.   APPLIED ENERGY

Aging trajectory prediction for lithium-ion batteries via model migration and Bayesian Monte Carlo method

(2019) Xiaopeng Tang et al.   APPLIED ENERGY

Clinical implementation of AI technologies will require interpretable AI models

(2019) Xun Jia et al.   MEDICAL PHYSICS

Deep convolutional neural networks with ensemble learning and transfer learning for capacity estimation of lithium-ion batteries

(2019) Sheng Shen et al.   APPLIED ENERGY

Overview of Lithium-Ion Battery Modeling Methods for State-of-Charge Estimation in Electrical Vehicles

(2018) Jinhao Meng et al.   Applied Sciences-Basel

A novel methodology to explain and evaluate data-driven building energy performance models based on interpretable machine learning

(2018) Cheng Fan et al.   APPLIED ENERGY

Artificial solid electrolyte interphase for aqueous lithium energy storage systems

(2017) Jian Zhi et al.   Science Advances

A hybrid framework combining data-driven and model-based methods for system remaining useful life prediction

(2016) Linxia Liao et al.   APPLIED SOFT COMPUTING

Hybrid-Electric Propulsion for Aircraft

(2015) C. Friedrich et al.   JOURNAL OF AIRCRAFT

Critical Link between Materials Chemistry and Cell-Level Design for High Energy Density and Low Cost Lithium-Sulfur Transportation Battery

(2015) D. Eroglu et al.   JOURNAL OF THE ELECTROCHEMICAL SOCIETY

Synthesize battery degradation modes via a diagnostic and prognostic model

(2012) Matthieu Dubarry et al.   JOURNAL OF POWER SOURCES

A multiscale framework with extended Kalman filter for lithium-ion battery SOC and capacity estimation

(2011) Chao Hu et al.   APPLIED ENERGY

Lithium−Air Battery: Promise and Challenges

(2010) G. Girishkumar et al.   Journal of Physical Chemistry Letters

Multiple surrogates: how cross-validation errors can help us to obtain the best predictor

(2009) Felipe A. C. Viana et al.   STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION

Thermodynamic model development for lithium intercalation electrodes

(2008) Deepak K. Karthikeyan et al.   JOURNAL OF POWER SOURCES