Fangfang YANG

Fangfang YANG

City University of Hong Kong

H-index: 27

Asia-Hong Kong

About Fangfang YANG

Fangfang YANG, With an exceptional h-index of 27 and a recent h-index of 26 (since 2020), a distinguished researcher at City University of Hong Kong, specializes in the field of Prognostics and Health Management, Deep Learning and Its Applications.

His recent articles reflect a diverse array of research interests and contributions to the field:

A feature fusion-based convolutional neural network for battery state-of-health estimation with mining of partial voltage curve

A Bayesian deep learning pipeline for lithium‐ion battery SOH estimation with uncertainty quantification

State of Health Estimation for Second-Life Lithium-Ion Batteries in Energy Storage System With Partial Charging-Discharging Workloads

An LSTM-SA model for SOC estimation of lithium-ion batteries under various temperatures and aging levels

Early prediction of battery lifetime based on graphical features and convolutional neural networks

Battery prognostics using statistical features from partial voltage information

An Informer-LSTM Network for State-of-Charge Estimation of Lithium-Ion Batteries

Capacity estimation of lithium-ion batteries based on data aggregation and feature fusion via graph neural network

Fangfang YANG Information

University

Position

___

Citations(all)

3216

Citations(since 2020)

3028

Cited By

864

hIndex(all)

27

hIndex(since 2020)

26

i10Index(all)

37

i10Index(since 2020)

36

Email

University Profile Page

City University of Hong Kong

Google Scholar

View Google Scholar Profile

Fangfang YANG Skills & Research Interests

Prognostics and Health Management

Deep Learning and Its Applications

Top articles of Fangfang YANG

Title

Journal

Author(s)

Publication Date

A feature fusion-based convolutional neural network for battery state-of-health estimation with mining of partial voltage curve

Energy

Zhenfeng Lu

Zicheng Fei

Benfei Wang

Fangfang Yang

2024/2/1

A Bayesian deep learning pipeline for lithium‐ion battery SOH estimation with uncertainty quantification

Quality and Reliability Engineering International

Yuqi Ke

Mingzhu Long

Fangfang Yang

Weiwen Peng

2024/2

State of Health Estimation for Second-Life Lithium-Ion Batteries in Energy Storage System With Partial Charging-Discharging Workloads

IEEE Transactions on Industrial Electronics

Yiyue Jiang

Yuqi Ke

Fangfang Yang

Jinchen Ji

Weiwen Peng

2024/1/11

An LSTM-SA model for SOC estimation of lithium-ion batteries under various temperatures and aging levels

Journal of Energy Storage

Guanxu Chen

Weiwen Peng

Fangfang Yang

2024/4/20

Early prediction of battery lifetime based on graphical features and convolutional neural networks

Applied Energy

Ning He

Qiqi Wang

Zhenfeng Lu

Yike Chai

Fangfang Yang

2024/1/1

Battery prognostics using statistical features from partial voltage information

Mechanical Systems and Signal Processing

Fangfang Yang

Zhenfeng Lu

Xiaojun Tan

Kwok-Leung Tsui

Dong Wang

2024/3/15

An Informer-LSTM Network for State-of-Charge Estimation of Lithium-Ion Batteries

Kai Guo

Yaohui Zhu

Yuyang Zhong

Kunchao Wu

Fangfang Yang

2023/10/12

Capacity estimation of lithium-ion batteries based on data aggregation and feature fusion via graph neural network

Applied Energy

Zhe Wang

Fangfang Yang

Qiang Xu

Yongjian Wang

Hong Yan

...

2023/4/15

Deep learning powered rapid lifetime classification of lithium-ion batteries

eTransportation

Zicheng Fei

Zijun Zhang

Fangfang Yang

Kwok Leung Tsui

2023

State of health estimation of lithium-ion battery with automatic feature extraction and self-attention learning mechanism

Zhongbao Wei

Haokai Ruan

Xiaolei Bian

Hongwen He

2020

A power model considering initial battery state for remaining useful life prediction of lithium-ion batteries

Reliability Engineering & System Safety

Fanbing Meng

Fangfang Yang

Jun Yang

Min Xie

2023/9/1

State of health prediction of lithium-ion batteries based on autoregression with exogenous variables model

Simone Barcellona

Loredana Cristaldi

Marco Faifer

Emil Petkovski

Luigi Piegari

...

2021/6/7

A deep attention-assisted and memory-augmented temporal convolutional network based model for rapid lithium-ion battery remaining useful life predictions with limited data

Journal of Energy Storage

Zicheng Fei

Zijun Zhang

Fangfang Yang

Kwok Leung Tsui

2023

A Resnet-SVR Model for Lithium-ion Battery State of Health Estimation

Yueying Xiao

Zhenfeng Lu

Fangfang Yang

2023/10/20

Data mining methods and applications

Kwok-Leung Tsui

Victoria Chen

Wei Jiang

Fangfang Yang

Chen Kan

2023/4/21

Battery Capacity Estimation based on Convolutional Neural Network

Zhenfeng Lu

Benfei Wang

Xiaojun Tan

Fangfang Yang

2022/10/13

Early-stage lifetime prediction for lithium-ion batteries: A deep learning framework jointly considering machine-learned and handcrafted data features

Journal of Energy Storage

Zicheng Fei

Zijun Zhang

Fangfang Yang

Kwok Leung Tsui

Lishuai Li

2022

A geometric approach for real-time forward kinematics of the general Stewart platform

Sensors

Fangfang Yang

Xiaojun Tan

Zhe Wang

Zhenfeng Lu

Tao He

2022/6/26

Evaluation of mean-time-to-failure based on nonlinear degradation data with applications

IISE Transactions

Lochana K Palayangoda

Ronald W Butler

Hon Keung Tony Ng

Fangfang Yang

Kwok Leung Tsui

2022/3/4

A hybrid DNN-KF model for real-time SOC estimation of lithium-ion batteries under different ambient temperatures

Guanxu Chen

Shancheng Jiang

Min Xie

Fangfang Yang

2022/10/13

See List of Professors in Fangfang YANG University(City University of Hong Kong)