Batteries | Selected Papers from 2022–2023 on the Topic of Battery Modelling, Simulation and Management (I)
We are pleased to invite you to read selected papers on the topic of battery modelling, simulation and management” in Batteries (ISSN: 2313-0105), from the previous two years. The list of these papers is below.
1. “Online State-of-Health Estimation of Lithium-Ion Battery Based on Incremental Capacity Curve and BP Neural Network”
by Hongye Lin, Longyun Kang, Di Xie, Jinqing Linghu and Jie Li
Batteries 2022, 8(4), 29; https://doi.org/10.3390/batteries8040029
Available online: https://www.mdpi.com/2313-0105/8/4/29
2. “Physics-Based SoH Estimation for Li-Ion Cells”
by Pietro Iurilli, Claudio Brivio, Rafael E. Carrillo and Vanessa Wood
Batteries 2022, 8(11), 204; https://doi.org/10.3390/batteries8110204
Available online: https://www.mdpi.com/2313-0105/8/11/204
3. “A Review of Lithium-Ion Battery Capacity Estimation Methods for Onboard Battery Management Systems: Recent Progress and Perspectives”
by Jichang Peng, Jinhao Meng, Dan Chen, Haitao Liu, Sipeng Hao, Xin Sui and Xinghao Du
Batteries 2022, 8(11), 229; https://doi.org/10.3390/batteries8110229
Available online: https://www.mdpi.com/2313-0105/8/11/229
4. “Online State of Health Estimation of Lithium-Ion Batteries Based on Charging Process and Long Short-Term Memory Recurrent Neural Network”
by Kang Liu, Longyun Kang and Di Xie
Batteries 2023, 9(2), 94; https://doi.org/10.3390/batteries9020094
Available online: https://www.mdpi.com/2313-0105/9/2/94
5. “Lithium-Ion Battery State of Health Estimation with Multi-Feature Collaborative Analysis and Deep Learning Method”
by Xianbin Yang, Bin Ma, Haicheng Xie, Wentao Wang, Bosong Zou, Fengwei Liang, Xiao Hua, Xinhua Liu and Siyan Chen
Batteries 2023, 9(2), 120; https://doi.org/10.3390/batteries9020120
Available online: https://www.mdpi.com/2313-0105/9/2/120
6. “State Estimation Models of Lithium-Ion Batteries for Battery Management System: Status, Challenges, and Future Trends”
by Long Zhou, Xin Lai, Bin Li, Yi Yao, Ming Yuan, Jiahui Weng and Yuejiu Zheng
Batteries 2023, 9(2), 131; https://doi.org/10.3390/batteries9020131
Available online: https://www.mdpi.com/2313-0105/9/2/131
7. “High-Entropy Metal Oxide (NiMnCrCoFe)3O4 Anode Materials with Controlled Morphology for High-Performance Lithium-Ion Batteries”
by Xuan Liang Wang, En Mei Jin, Gopinath Sahoo and Sang Mun Jeong
Batteries 2023, 9(3), 147; https://doi.org/10.3390/batteries9030147
Available online: https://www.mdpi.com/2313-0105/9/3/147
8. “Accurate Prediction Approach of SOH for Lithium-Ion Batteries Based on LSTM Method”
by Lijun Zhang, Tuo Ji, Shihao Yu and Guanchen Liu
Batteries 2023, 9(3), 177; https://doi.org/10.3390/batteries9030177
Available online: https://www.mdpi.com/2313-0105/9/3/177
9. “Lithium-Ion Battery State-of-Charge Estimation Using Electrochemical Model with Sensitive Parameters Adjustment”
by Jingrong Wang, Jinhao Meng, Qiao Peng, Tianqi Liu, Xueyang Zeng, Gang Chen and Yan Li
Batteries 2023, 9(3), 180; https://doi.org/10.3390/batteries9030180
Available online: https://www.mdpi.com/2313-0105/9/3/180
10. “Transfer Learning Based on Transferability Measures for State of Health Prediction of Lithium-Ion Batteries”
by Zemenu Endalamaw Amogne, Fu-Kwun Wang and Jia-Hong Chou
Batteries 2023, 9(5), 280; https://doi.org/10.3390/batteries9050280
Available online: https://www.mdpi.com/2313-0105/9/5/280
11. “Hybrid Modeling of Lithium-Ion Battery: Physics-Informed Neural Network for Battery State Estimation”
by Soumya Singh, Yvonne Eboumbou Ebongue, Shahed Rezaei and Kai Peter Birke
Batteries 2023, 9(6), 301; https://doi.org/10.3390/batteries9060301
Available online: https://www.mdpi.com/2313-0105/9/6/301
12. “State of Charge and Temperature Joint Estimation Based on Ultrasonic Reflection Waves for Lithium-Ion Battery Applications”
by Runnan Zhang, Xiaoyu Li, Chuanyu Sun, Songyuan Yang, Yong Tian and Jindong Tian
Batteries 2023, 9(6), 335; https://doi.org/10.3390/batteries9060335
Available online: https://www.mdpi.com/2313-0105/9/6/335
13. “State of Charge Estimation for Lithium-Ion Battery Based on Unscented Kalman Filter and Long Short-Term Memory Neural Network”
by Yi Zeng, Yan Li and Tong Yang
Batteries 2023, 9(7), 358; https://doi.org/10.3390/batteries9070358
Available online: https://www.mdpi.com/2313-0105/9/7/358
14. “State-of-Charge Estimation of Lithium-Ion Batteries Based on Dual-Coefficient Tracking Improved Square-Root Unscented Kalman Filter”
by Simin Peng, Ao Zhang, Dandan Liu, Mengzeng Cheng, Jiarong Kan and Michael Pecht
Batteries 2023, 9(8), 392; https://doi.org/10.3390/batteries9080392
Available online: https://www.mdpi.com/2313-0105/9/8/392
15. “Integration of Computational Fluid Dynamics and Artificial Neural Network for Optimization Design of Battery Thermal Management System”
by Ao Li, Anthony Chun Yin Yuen, Wei Wang, Timothy Bo Yuan Chen, Chun Sing Lai, Wei Yang, Wei Wu, Qing Nian Chan, Sanghoon Kook and Guan Heng Yeoh
Batteries 2022, 8(7), 69; https://doi.org/10.3390/batteries8070069
Available online: https://www.mdpi.com/2313-0105/8/7/69