2019211474 / DL-NASA-SOH-CNN-BILSTM-Attention
这是我关于使用深度学习方法去评估锂电池健康状态（SOH）的一点点工作，对象是NASA的锂电池容量衰退数据集，分析了加入锂电池运行的可监测数据对SOH的影响
☆35Updated last year
Alternatives and similar repositories for DL-NASA-SOH-CNN-BILSTM-Attention:
Users that are interested in DL-NASA-SOH-CNN-BILSTM-Attention are comparing it to the libraries listed below
- A prediction model to estimate the state of health (SOH) of a lithium-ion battery (LiB) in real-time based on temperature, voltage, and c…☆28Updated 2 years ago
- This research provides a prognostic framework for off-line SOH estimation of Li-ion battery. With a CNN-Transformer architecture, this pr…☆78Updated last year
- 使用改进的GAN去生成数据，并使用生成的数据去训练LSTM网络，从而提高预测电池SOH的准确率☆58Updated 2 years ago
- This paper summarizes a deep learning-based approach with an LSTM trained on the widely used Oxford battery degradation dataset and the h…☆60Updated 10 months ago
- ☆9Updated 2 years ago
- Developed a data-driven prognostic model using the Long short-term memory (LSTM) algorithm to predict the state of charge (SoC) and stat…☆38Updated 2 years ago
- A Deep Neural Network based model to predict the Remaining Useful Life cycles of battery and on the basis of State of Health of the batte…☆12Updated last year
- Rul prediction of lithium-ion batteries based on MMMe model，Details can be found in the paper “A MLP-Mixer and Mixture of Expert Model fo…☆19Updated last year
- Code for paper: Voltage relaxation-based state-of-health estimation of lithium-ion batteries using convolutional neural networks and tran…☆31Updated last year
- Comparison of various transfer learning models with the hybridization of an FCNN for battery RUL prediction☆43Updated 2 years ago
- The project focused on "Battery Remaining Useful Life (RUL) Prediction using a Data-Driven Approach with a Hybrid Deep Model combining Co…☆63Updated 9 months ago
- State of charge (SOC), State of Health (SOH) Estimation using Machine learning algorithms such as Linear regression, random forest, suppo…☆42Updated last year
- This study pioneers E-LSTM and CNN-LSTM deep learning models for precise Lithium-Ion Battery State of Health (SOH) prediction. Using MIT'…☆14Updated last year
- ☆57Updated 5 years ago
- Using particle filtering algorithm to estimate the residual life of lithium ion batteries, the university of Maryland public data set is …☆29Updated last year
- ☆16Updated 3 years ago
- The PyTorch implementation of Temperature Adaptive Transfer Network for Cross-Domain State of Charge Estimation of Li-ion Batteries at D…☆20Updated last year
- This project analyzes NASA's battery datasets to predict the State of Health (SOH) by extracting Health Indices (HI’s) and conducting cor…☆10Updated last year
- Deep learning of lithium-ion battery SOH using the DeTransformer model learns the aging characteristics of the battery and then makes pre…☆36Updated last year
- Lithium ion battery state of health estimation and remaining useful life prediction using ELM☆56Updated 3 years ago
- Code for paper "An end-to-end neural network framework for SOH estimation and RUL prediction of lithium battery"☆108Updated 3 years ago
- ☆24Updated 5 years ago
- ☆45Updated 4 months ago
- This is the code for battery RUL early prediction☆29Updated 3 years ago
- ☆10Updated 3 years ago
- The code is for the paper "Ma et al. A Two-Stage Integrated Method for Early Prediction of Remaining Useful Life of Lithium-ion Batteries…☆33Updated 2 years ago
- 2022-2 Capstone design, SOH Estimation Using Combined CNN-LSTM Model☆19Updated 7 months ago
- Battery data processing.☆26Updated last year
- ☆19Updated last year
- ☆13Updated 2 years ago