Adversarial Defensive Framework for State-of-Health Prediction of Lithium Batteries-Reference-Cited by-同舟云学术

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Adversarial Defensive Framework for State-of-Health Prediction of Lithium Batteries

Published:2023-10 Issue:10 Volume:38 Page:13147-13155
ISSN:0885-8993
Container-title:IEEE Transactions on Power Electronics
language:
Short-container-title:IEEE Trans. Power Electron.

Author:

Tiane Anas¹^ORCID,Okar Chafik²^ORCID,Chaoui Hicham³^ORCID

Affiliation:

1. Department of Electronics, Carleton University, Ottawa, ON, Canada

2. National School of Applied Science of Tetouan, Abdelmalek Essaâdi University, Tétouan, Morocco

3. Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX, USA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/63/10242187/10160193.pdf?arnumber=10160193

Reference45 articles.

1. Understanding adversarial training: Increasing local stability of neural nets through robust optimization;shaham,2015

2. Battery Thermal Runaway Fault Prognosis in Electric Vehicles Based on Abnormal Heat Generation and Deep Learning Algorithms

3. Adversarial Sample Detection for Deep Neural Network through Model Mutation Testing

4. A Multiagent Deep Reinforcement Learning Based Approach for the Optimization of Transformer Life Using Coordinated Electric Vehicles

5. Automated testing of deep-neural-network-driven autonomous cars;tian;Proc 40th Int Conf Softw Eng,0

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Combined Meta-Learning With CNN-LSTM Algorithms for State-of-Health Estimation of Lithium-Ion Battery;IEEE Transactions on Power Electronics;2024-08

2. Asynchronous deep reinforcement learning with gradient sharing for State of Charge balancing of multiple batteries in cyber–physical electric vehicles;Journal of the Franklin Institute;2024-04

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