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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 …
Review on state of charge estimation techniques of lithium-ion batteries: A control-oriented approach
Energy storage has become one of the most critical issues of modern technology. In this
regard, lithium-ion batteries have proven effective as an energy storage option. To optimize …
regard, lithium-ion batteries have proven effective as an energy storage option. To optimize …
Lithium-ion battery state of health estimation using a hybrid model based on a convolutional neural network and bidirectional gated recurrent unit
This paper proposes a real-time state of health (SOH) estimation model based on a deep
learning (DL) framework. The proposed model is a combination of two different …
learning (DL) framework. The proposed model is a combination of two different …
[HTML][HTML] Artificial intelligence approaches for advanced battery management system in electric vehicle applications: A statistical analysis towards future research …
In order to reduce carbon emissions and address global environmental concerns, the
automobile industry has focused a great deal of attention on electric vehicles, or EVs …
automobile industry has focused a great deal of attention on electric vehicles, or EVs …
State of charge estimation of Li-ion batteries based on deep learning methods and particle-swarm-optimized Kalman filter
M Li, C Li, Q Zhang, W Liao, Z Rao - Journal of Energy Storage, 2023 - Elsevier
The estimation of SOC is a key issue for the high-efficient and reliable operation of Li-ion
batteries, thus has been increasingly concerned in current years with the development of …
batteries, thus has been increasingly concerned in current years with the development of …
A case study of a tiny machine learning application for battery state-of-charge estimation
Growing battery use in energy storage and automotive industries demands advanced
Battery Management Systems (BMSs) to estimate key parameters like the State of Charge …
Battery Management Systems (BMSs) to estimate key parameters like the State of Charge …
EdgeCog: A real-time bearing fault diagnosis system based on lightweight edge computing
L Fu, K Yan, Y Zhang, R Chen, Z Ma… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Deep learning has made important contributions to classification tasks applied to fault
diagnosis. However, it is crucial to integrate the technologies into real industrial applications …
diagnosis. However, it is crucial to integrate the technologies into real industrial applications …
A soft actor-critic reinforcement learning framework for optimal energy management in electric vehicles with hybrid storage
The efficient energy management of electric vehicles (EVs) equipped with hybrid energy
storage systems (HESS) poses a significant challenge due to its vast search space …
storage systems (HESS) poses a significant challenge due to its vast search space …
Metaheuristics‐optimized deep learning to predict generation of sustainable energy from rooftop plant microbial fuel cells
Plant microbial fuel cells (PMFCs) are an emergent green‐energy technology that
continuously converts solar energy into electricity. Placing PMFCs on the roofs of urban …
continuously converts solar energy into electricity. Placing PMFCs on the roofs of urban …
A new lithium polymer battery dataset with different discharge levels: SOC estimation of lithium polymer batteries with different convolutional neural network models
In this study, a new dataset was created for use to estimate the state of charge (SOC) of
lithium polymer batteries. A new experimental system was created to obtain the dataset by …
lithium polymer batteries. A new experimental system was created to obtain the dataset by …