Deep neural network battery life and voltage prediction by using data of one cycle only

Co-Estimation of State of Charge and Capacity for Lithium-ion Batteries with Multi-Stage Model Fusion Method

(2021) Rui Xiong et al.   Engineering

State-of-charge estimation of LiFePO4 batteries in electric vehicles: A deep-learning enabled approach

(2021) Jinpeng Tian et al.   APPLIED ENERGY

Deep neural network battery charging curve prediction using 30 points collected in 10 min

(2021) Jinpeng Tian et al.   Joule

Detecting undesired lithium plating on anodes for lithium-ion batteries – A review on the in-situ methods

(2021) Yu Tian et al.   APPLIED ENERGY

Closed-loop optimization of fast-charging protocols for batteries with machine learning

(2020) Peter M. Attia et al.   NATURE

Extreme Learning Machine-Based Thermal Model for Lithium-Ion Batteries of Electric Vehicles under External Short Circuit

(2020) Ruixin Yang et al.   Engineering

Data-driven prediction of battery cycle life before capacity degradation

(2019) Kristen A. Severson et al.   Nature Energy

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

(2019) Xiaopeng Tang et al.   APPLIED ENERGY

Methods for interpreting and understanding deep neural networks

(2018) Grégoire Montavon et al.   DIGITAL SIGNAL PROCESSING

Cycling degradation testing and analysis of a LiFePO4 battery at actual conditions

(2017) S. Panchal et al.   INTERNATIONAL JOURNAL OF ENERGY RESEARCH

Explaining nonlinear classification decisions with deep Taylor decomposition

(2017) Grégoire Montavon et al.   PATTERN RECOGNITION

Influence of different open circuit voltage tests on state of charge online estimation for lithium-ion batteries

(2016) Fangdan Zheng et al.   APPLIED ENERGY

Can we open the black box of AI?

(2016) Davide Castelvecchi   NATURE

Critical review of on-board capacity estimation techniques for lithium-ion batteries in electric and hybrid electric vehicles

(2015) Alexander Farmann et al.   JOURNAL OF POWER SOURCES