Apr 13, 2020 · The experimental results demonstrate that this approach can detect thermal faults accurately. It is adaptive to different battery chemistries ...
Abstract—Detecting thermal faults is critical to the safety of lithium-ion batteries. This paper, therefore, proposes a neural network-based approach.
Oct 22, 2024 · The experimental results demonstrate that this approach can detect thermal faults accurately. It is adaptive to different battery chemistries ...
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Feb 29, 2024 · This research built a lithium-ion battery thermal fault diagnosis model that optimized the original mask region-based convolutional neural network.
Neural networks (NN) coupled with an equivalent circuit model (ECM) have been used to predict the surface temperature of LIB [3] , [4]. In this approach, the NN ...
This work proposes a graph-based autoencoder, which uses graph data of voltage sensors to strengthen the reconstruction ability of the traditional autoencoder.
6 days ago · Current regression methods for battery fault detection often analyze charging and discharging as a single continuous process, missing important ...
Aug 2, 2021 · This paper presents a fault diagnosis method for the electric vehicle power battery using the improved radial basis function (RBF) neural network.
This paper proposes a hybrid algorithm combining the symmetrized dot pattern (SDP) method and a convolutional neural network (CNN) for fault detection in ...
Sep 23, 2023 · We develop a realistic deep-learning framework for electric vehicle (EV) LiB anomaly detection. It features a dynamical autoencoder tailored for dynamical ...