Batteries | Selected Papers from 2022–2023 on the Topic of Battery Modelling, Simulation and Management (III)

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. “Equivalent Circuit Model for High-Power Lithium-Ion Batteries under High Current Rates, Wide Temperature Range, and Various State of Charges”
by Danial Karimi, Hamidreza Behi, Joeri Van Mierlo and Maitane Berecibar
Batteries 2023, 9(2), 101; https://doi.org/10.3390/batteries9020101
Available online: https://www.mdpi.com/2313-0105/9/2/101

2. “An Optimized Random Forest Regression Model for Li-Ion Battery Prognostics and Health Management”
by Geng Wang, Zhiqiang Lyu and Xiaoyu Li
Batteries 2023, 9(6), 332; https://doi.org/10.3390/batteries9060332
Available online: https://www.mdpi.com/2313-0105/9/6/332

3. “A Review on the Degradation Implementation for the Operation of Battery Energy Storage Systems”
by Pedro Luis Camuñas García-Miguel, Jaime Alonso-Martínez, Santiago Arnaltes Gómez, Manuel García Plaza and Andrés Peña Asensio
Batteries 2022, 8(9), 110; https://doi.org/10.3390/batteries8090110
Available online: https://www.mdpi.com/2313-0105/8/9/110

4. “An Efficient EMS for BESS in Monopolar DC Networks with High Penetration of Renewable Generation: A Convex Approximation”
by Luis Fernando Grisales-Noreña, Oscar Danilo Montoya and Jesus C. Hernández
Batteries 2023, 9(2), 84; https://doi.org/10.3390/batteries9020084
Available online: https://www.mdpi.com/2313-0105/9/2/84

5. “Battery State of Health Estimate Strategies: From Data Analysis to End-Cloud Collaborative Framework”
by Kaiyi Yang, Lisheng Zhang, Zhengjie Zhang, Hanqing Yu, Wentao Wang, Mengzheng Ouyang, Cheng Zhang, Qi Sun, Xiaoyu Yan, Shichun Yang and et al.
Batteries 2023, 9(7), 351; https://doi.org/10.3390/batteries9070351
Available online: https://www.mdpi.com/2313-0105/9/7/351

6. “Surface Selenization of NiCo-Layered Double Hydroxide Nanosheets for High-Performance Supercapacitors”
by Mengdi Wang, Xingyu Liu and Xiang Wu
Batteries 2023, 9(1), 49; https://doi.org/10.3390/batteries9010049
Available online: https://www.mdpi.com/2313-0105/9/1/49

7. “High-Performance Supercapacitors: A Comprehensive Review on Paradigm Shift of Conventional Energy Storage Devices”
by K. C. Seetha Lakshmi and Balaraman Vedhanarayanan
Batteries 2023, 9(4), 202; https://doi.org/10.3390/batteries9040202
Available online: https://www.mdpi.com/2313-0105/9/4/202

8. “Effect of Lithium Salt Concentration on Materials Characteristics and Electrochemical Performance of Hybrid Inorganic/Polymer Solid Electrolyte for Solid-State Lithium-Ion Batteries”
by Debabrata Mohanty, Shu-Yu Chen and I-Ming Hung
Batteries 2022, 8(10), 173; https://doi.org/10.3390/batteries8100173
Available online: https://www.mdpi.com/2313-0105/8/10/173

9. “Modelling and Estimation of Vanadium Redox Flow Batteries: A Review”
by Thomas Puleston, Alejandro Clemente, Ramon Costa-Castelló and Maria Serra
Batteries 2022, 8(9), 121; https://doi.org/10.3390/batteries8090121
Available online: https://www.mdpi.com/2313-0105/8/9/121

10. “Transition Metal Dichalcogenides for High-Performance Aqueous Zinc Ion Batteries”
by Baishan Liu
Batteries 2022, 8(7), 62; https://doi.org/10.3390/batteries8070062
Available online: https://www.mdpi.com/2313-0105/8/7/62

11. “Efficient Battery Models for Performance Studies-Lithium Ion and Nickel Metal Hydride Battery”
by Umapathi Krishnamoorthy, Parimala Gandhi Ayyavu, Hitesh Panchal, Dayana Shanmugam, Sukanya Balasubramani, Ali Jawad Al-rubaie, Ameer Al-khaykan, Ankit D. Oza, Sagram Hembrom, Tvarit Patel and et al.
Batteries 2023, 9(1), 52; https://doi.org/10.3390/batteries9010052
Available online: https://www.mdpi.com/2313-0105/9/1/52

12. “Fast Identification of Micro-Health Parameters for Retired Batteries Based on a Simplified P2D Model by Using Padé Approximation”
by Jianing Xu, Chuanyu Sun, Yulong Ni, Chao Lyu, Chao Wu, He Zhang, Qingjun Yang and Fei Feng
Batteries 2023, 9(1), 64; https://doi.org/10.3390/batteries9010064
Available online: https://www.mdpi.com/2313-0105/9/1/64

13. “Data-Driven Battery Aging Mechanism Analysis and Degradation Pathway Prediction”
by Ruilong Xu, Yujie Wang and Zonghai Chen
Batteries 2023, 9(2), 129; https://doi.org/10.3390/batteries9020129
Available online: https://www.mdpi.com/2313-0105/9/2/129

14. “Lithium–Ion Battery Data: From Production to Prediction”
by Marwan Hassini, Eduardo Redondo-Iglesias and Pascal Venet
Batteries 2023, 9(7), 385; https://doi.org/10.3390/batteries9070385
Available online: https://www.mdpi.com/2313-0105/9/7/385