[HTML][HTML] A review of non-probabilistic machine learning-based state of health estimation techniques for Lithium-ion battery
Lithium-ion batteries are used in a wide range of applications including energy storage
systems, electric transportations, and portable electronic devices. Accurately obtaining the …
systems, electric transportations, and portable electronic devices. Accurately obtaining the …
Tinyml meets iot: A comprehensive survey
L Dutta, S Bharali - Internet of Things, 2021 - Elsevier
The rapid growth in miniaturization of low-power embedded devices and advancement in
the optimization of machine learning (ML) algorithms have opened up a new prospect of the …
the optimization of machine learning (ML) algorithms have opened up a new prospect of the …
Artificial Neural Networks, Gradient Boosting and Support Vector Machines for electric vehicle battery state estimation: A review
Abstract In recent years, Artificial Intelligence has been widely used for determining the
current state of Li-ion batteries used for Electric Vehicle applications. It is crucial to have an …
current state of Li-ion batteries used for Electric Vehicle applications. It is crucial to have an …
[HTML][HTML] A review of machine learning state-of-charge and state-of-health estimation algorithms for lithium-ion batteries
Z Ren, C Du - Energy Reports, 2023 - Elsevier
Vehicle electrification has been proven to be an efficient way to reduce carbon dioxide
emissions and solve the energy crisis. Lithium-ion batteries (LiBs) are considered the …
emissions and solve the energy crisis. Lithium-ion batteries (LiBs) are considered the …
Deep learning enabled state of charge, state of health and remaining useful life estimation for smart battery management system: Methods, implementations, issues …
State of Charge (SOC), state of health (SOH), and remaining useful life (RUL) are the crucial
indexes used in the assessment of electric vehicle (EV) battery management systems (BMS) …
indexes used in the assessment of electric vehicle (EV) battery management systems (BMS) …
Efficient hardware architectures for accelerating deep neural networks: Survey
In the modern-day era of technology, a paradigm shift has been witnessed in the areas
involving applications of Artificial Intelligence (AI), Machine Learning (ML), and Deep …
involving applications of Artificial Intelligence (AI), Machine Learning (ML), and Deep …
Applications of artificial neural network based battery management systems: A literature review
Lithium-ion batteries have gained significant prominence in various industries due to their
high energy density compared to other battery technologies. This has led to their …
high energy density compared to other battery technologies. This has led to their …
State of health estimation and remaining useful life assessment of lithium-ion batteries: A comparative study
Y Toughzaoui, SB Toosi, H Chaoui, H Louahlia… - Journal of Energy …, 2022 - Elsevier
Lithium-ion batteries are widely used due to their attractive features. They have emerged as
the primary storage system for electric cars, solar power, and marine vehicles …
the primary storage system for electric cars, solar power, and marine vehicles …
[HTML][HTML] Remaining useful life prediction for lithium-ion battery storage system: A comprehensive review of methods, key factors, issues and future outlook
Develo** battery storage systems for clean energy applications is fundamental for
addressing carbon emissions problems. Consequently, battery remaining useful life …
addressing carbon emissions problems. Consequently, battery remaining useful life …
Offline and online blended machine learning for lithium-ion battery health state estimation
This article proposes an adaptive state-of-health (SOH) estimation method for lithium-ion (Li-
ion) batteries using machine learning. Practical problems with feature extraction, cell …
ion) batteries using machine learning. Practical problems with feature extraction, cell …