Digital twin of electric vehicle battery systems: Comprehensive review of the use cases, requirements, and platforms
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DOI: 10.1016/j.rser.2023.113280
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- Yu, Jianxi & Liu, Pei & Li, Zheng, 2020. "Hybrid modelling and digital twin development of a steam turbine control stage for online performance monitoring," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
- Yoro, Kelvin O. & Daramola, Michael O. & Sekoai, Patrick T. & Wilson, Uwemedimo N. & Eterigho-Ikelegbe, Orevaoghene, 2021. "Update on current approaches, challenges, and prospects of modeling and simulation in renewable and sustainable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
- Yu, Wei & Patros, Panos & Young, Brent & Klinac, Elsa & Walmsley, Timothy Gordon, 2022. "Energy digital twin technology for industrial energy management: Classification, challenges and future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
- Wang, Yujie & Tian, Jiaqiang & Sun, Zhendong & Wang, Li & Xu, Ruilong & Li, Mince & Chen, Zonghai, 2020. "A comprehensive review of battery modeling and state estimation approaches for advanced battery management systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
- Hu, Xiaosong & Feng, Fei & Liu, Kailong & Zhang, Lei & Xie, Jiale & Liu, Bo, 2019. "State estimation for advanced battery management: Key challenges and future trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
- Teng, Sin Yong & Touš, Michal & Leong, Wei Dong & How, Bing Shen & Lam, Hon Loong & Máša, Vítězslav, 2021. "Recent advances on industrial data-driven energy savings: Digital twins and infrastructures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
- Di Silvestre, Maria Luisa & Favuzza, Salvatore & Riva Sanseverino, Eleonora & Zizzo, Gaetano, 2018. "How Decarbonization, Digitalization and Decentralization are changing key power infrastructures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 483-498.
- Kalogirou, Soteris A., 2001. "Artificial neural networks in renewable energy systems applications: a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 5(4), pages 373-401, December.
- Dai, Haifeng & Jiang, Bo & Hu, Xiaosong & Lin, Xianke & Wei, Xuezhe & Pecht, Michael, 2021. "Advanced battery management strategies for a sustainable energy future: Multilayer design concepts and research trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
- Held, Marcel & Tuchschmid, Martin & Zennegg, Markus & Figi, Renato & Schreiner, Claudia & Mellert, Lars Derek & Welte, Urs & Kompatscher, Michael & Hermann, Michael & Nachef, Léa, 2022. "Thermal runaway and fire of electric vehicle lithium-ion battery and contamination of infrastructure facility," Renewable and Sustainable Energy Reviews, Elsevier, vol. 165(C).
- Naseri, F. & Karimi, S. & Farjah, E. & Schaltz, E., 2022. "Supercapacitor management system: A comprehensive review of modeling, estimation, balancing, and protection techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
- Li, Weihan & Cui, Han & Nemeth, Thomas & Jansen, Jonathan & Ünlübayir, Cem & Wei, Zhongbao & Feng, Xuning & Han, Xuebing & Ouyang, Minggao & Dai, Haifeng & Wei, Xuezhe & Sauer, Dirk Uwe, 2021. "Cloud-based health-conscious energy management of hybrid battery systems in electric vehicles with deep reinforcement learning," Applied Energy, Elsevier, vol. 293(C).
- Leng, Jiewu & Ruan, Guolei & Jiang, Pingyu & Xu, Kailin & Liu, Qiang & Zhou, Xueliang & Liu, Chao, 2020. "Blockchain-empowered sustainable manufacturing and product lifecycle management in industry 4.0: A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
- Bhatti, Ghanishtha & Mohan, Harshit & Raja Singh, R., 2021. "Towards the future of smart electric vehicles: Digital twin technology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
- Jasiūnas, Justinas & Lund, Peter D. & Mikkola, Jani, 2021. "Energy system resilience – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
- Moreira, Naiara & Molina, Elías & Lázaro, Jesús & Jacob, Eduardo & Astarloa, Armando, 2016. "Cyber-security in substation automation systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1552-1562.
- Tao, Laifa & Ma, Jian & Cheng, Yujie & Noktehdan, Azadeh & Chong, Jin & Lu, Chen, 2017. "A review of stochastic battery models and health management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 716-732.
- Mousavi G., S.M. & Nikdel, M., 2014. "Various battery models for various simulation studies and applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 477-485.
- Ziming Xu & Jun Xu & Zhechen Guo & Haitao Wang & Zheng Sun & Xuesong Mei, 2022. "Design and Optimization of a Novel Microchannel Battery Thermal Management System Based on Digital Twin," Energies, MDPI, vol. 15(4), pages 1-20, February.
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- Hua Song & Huaizhi Chen & Yanbo Wang & Xiang-E Sun, 2024. "An Overview About Second-Life Battery Utilization for Energy Storage: Key Challenges and Solutions," Energies, MDPI, vol. 17(23), pages 1-26, December.
- Ama Ranawaka & Damminda Alahakoon & Yuan Sun & Kushan Hewapathirana, 2024. "Leveraging the Synergy of Digital Twins and Artificial Intelligence for Sustainable Power Grids: A Scoping Review," Energies, MDPI, vol. 17(21), pages 1-52, October.
- Ebbs-Picken, Takiah & Romero, David A. & Da Silva, Carlos M. & Amon, Cristina H., 2024. "Deep encoder–decoder hierarchical convolutional neural networks for conjugate heat transfer surrogate modeling," Applied Energy, Elsevier, vol. 372(C).
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Keywords
Artificial intelligence (AI); Battery management system (BMS); Battery passport; Battery recycling; Digital twin (DT); Electric vehicle (EV); Fault diagnosis; Internet-of-things (IoT); Machine learning (ML); Predictive maintenance; Remaining useful life (RUL); Second-life; Software architecture;All these keywords.
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