Cover Image

To Charge or to Sell? EV Pack Useful Life Estimation via LSTMs, CNNs, and Autoencoders

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bosello, Michael, Falcomer, Carlo, Rossi, Claudio, Pau, Giovanni
Format:	Preprint
Published:	2021
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Predicting Clinical Outcomes with Waveform LSTMs
by: Albada, Michael
Published: (2025)

CNN-LSTM Hybrid Deep Learning Model for Remaining Useful Life Estimation
by: G, Muthukumar, et al.
Published: (2024)

Are Sparse Autoencoders Useful? A Case Study in Sparse Probing
by: Kantamneni, Subhash, et al.
Published: (2025)

A Quantile Regression Approach for Remaining Useful Life Estimation with State Space Models
by: Frizzo, Davide, et al.
Published: (2025)

Federated Learning for Early Prediction of EV Charging Demand
by: Perifanis, Vasilis, et al.
Published: (2026)

A Novel Multimodal RUL Framework for Remaining Useful Life Estimation with Layer-wise Explanations
by: Razzaq, Waleed, et al.
Published: (2025)

Automated Machine Learning for Remaining Useful Life Predictions
by: Zöller, Marc-André, et al.
Published: (2023)

Are Sparse Autoencoders Useful for Java Function Bug Detection?
by: Melo, Rui, et al.
Published: (2025)

Mixup Domain Adaptations for Dynamic Remaining Useful Life Predictions
by: Furqon, Muhammad Tanzil, et al.
Published: (2024)

Data-Driven Optimization of EV Charging Station Placement Using Causal Discovery
by: Junker, Julius Stephan, et al.
Published: (2025)

Evidential Domain Adaptation for Remaining Useful Life Prediction with Incomplete Degradation
by: Hou, Yubo, et al.
Published: (2026)

Chargax: A JAX Accelerated EV Charging Simulator
by: Ponse, Koen, et al.
Published: (2025)

A Multi-View Multi-Timescale Hypergraph-Empowered Spatiotemporal Framework for EV Charging Forecasting
by: Li, Jinhao, et al.
Published: (2025)

Supervised Contrastive Learning based Dual-Mixer Model for Remaining Useful Life Prediction
by: Fu, En, et al.
Published: (2024)

A Change Point Detection Integrated Remaining Useful Life Estimation Model under Variable Operating Conditions
by: Arunan, Anushiya, et al.
Published: (2024)

ACTIVA: Amortized Causal Effect Estimation via Transformer-based Variational Autoencoder
by: Sauter, Andreas, et al.
Published: (2025)

HyBattNet: Hybrid Framework for Predicting the Remaining Useful Life of Lithium-Ion Batteries
by: Tran, Khoa, et al.
Published: (2025)

IIP-Mixer:Intra-Inter Patch Mixing Architecture for Battery Remaining Useful Life Prediction
by: Ye, Guangzai, et al.
Published: (2024)

FINN-GL: Generalized Mixed-Precision Extensions for FPGA-Accelerated LSTMs
by: Khandelwal, Shashwat, et al.
Published: (2025)

Enabling Delayed-Full Charging Through Transformer-Based Real-Time-to-Departure Modeling for EV Battery Longevity
by: Lee, Yonggeon, et al.
Published: (2025)

Disentangled Graph Autoencoder for Treatment Effect Estimation
by: Fan, Di, et al.
Published: (2024)

Deep Domain Adaptation for Turbofan Engine Remaining Useful Life Prediction: Methodologies, Evaluation and Future Trends
by: Wang, Yucheng, et al.
Published: (2025)

A Survey on Graph Neural Networks for Remaining Useful Life Prediction: Methodologies, Evaluation and Future Trends
by: Wang, Yucheng, et al.
Published: (2024)

Multiscale Dual-path Feature Aggregation Network for Remaining Useful Life Prediction of Lithium-Ion Batteries
by: Lv, Zihao, et al.
Published: (2025)

Meta-Learning and Knowledge Discovery based Physics-Informed Neural Network for Remaining Useful Life Prediction
by: Wang, Yu, et al.
Published: (2025)

On The Potential of The Fractal Geometry and The CNNs Ability to Encode it
by: Zini, Julia El, et al.
Published: (2024)

Uncertainty-Aware Deep Learning Framework for Remaining Useful Life Prediction in Turbofan Engines with Learned Aleatoric Uncertainty
by: Sharma, Krishang
Published: (2025)

BACE-RUL: A Bi-directional Adversarial Network with Covariate Encoding for Machine Remaining Useful Life Prediction
by: Zhang, Zekai, et al.
Published: (2025)

A Multi-Task Targeted Learning Framework for Lithium-Ion Battery State-of-Health and Remaining Useful Life
by: Wang, Chenhan, et al.
Published: (2026)

A Novel Preprocessing-Driven Approach to Remaining Useful Life (RUL) Prediction Using Temporal Convolutional Networks (TCN)
by: Imbert, Florent, et al.
Published: (2026)

MPRE: Multi-perspective Patient Representation Extractor for Disease Prediction
by: Yu, Ziyue, et al.
Published: (2024)

Discrete Variational Autoencoding via Policy Search
by: Drolet, Michael, et al.
Published: (2025)

Hybrid Gaussian Process Regression with Temporal Feature Extraction for Partially Interpretable Remaining Useful Life Interval Prediction in Aeroengine Prognostics
by: Niu, Tian, et al.
Published: (2024)

Fed-Joint: Joint Modeling of Nonlinear Degradation Signals and Failure Events for Remaining Useful Life Prediction using Federated Learning
by: Jeong, Cheoljoon, et al.
Published: (2025)

Group and Exclusive Sparse Regularization-based Continual Learning of CNNs
by: Tousside, Basile, et al.
Published: (2026)

A Stable Neural Statistical Dependence Estimator for Autoencoder Feature Analysis
by: Hu, Bo, et al.
Published: (2026)

Survival Analysis with Machine Learning for Predicting Li-ion Battery Remaining Useful Life
by: Xue, Jingyuan, et al.
Published: (2025)

Are Foundation Models Useful for Bankruptcy Prediction?
by: Kostrzewa, Marcin, et al.
Published: (2025)

Conditional Clifford-Steerable CNNs with Complete Kernel Basis for PDE Modeling
by: Szarvas, Bálint László, et al.
Published: (2025)

A Multi-Granularity Supervised Contrastive Framework for Remaining Useful Life Prediction of Aero-engines
by: He, Zixuan, et al.
Published: (2024)