IoB: Internet-of-batteries for electric Vehicles–Architectures, opportunities, and challenges DOI Creative Commons
Heng Li, Muaaz Bin Kaleem, Zhijun Liu

и другие.

Green Energy and Intelligent Transportation, Год журнала: 2023, Номер 2(6), С. 100128 - 100128

Опубликована: Сен. 7, 2023

The concept of the Internet-of-Batteries (IoB) has recently emerged and offers great potential for control optimization battery utilization in electric vehicles (EV). This concept, which combines aspects Internet-of-Things (IoT) with latest advancements technology cloud computing, can provide a wealth new information about health performance. be used to improve management number ways, including continuous prognosis improved vehicle management. In this paper, we reviewed detail basic structure IoB, based on many existing studies. We also explored benefits approach, such as Implementing IoB EVs is not without challenges, faces security data, cross-platform functionality, technical complexities applying large scale. However, are significant continued research development, it ability revolutionize EV industry. purpose review paper comprehensive overview discussing its challenges. provides roadmap future development highlighting key areas that need addressed fully realize technology.

Язык: Английский

Big data-driven prognostics and health management of lithium-ion batteries:A review DOI
Kui Chen, Yang Luo, Zhou Long

и другие.

Renewable and Sustainable Energy Reviews, Год журнала: 2025, Номер 214, С. 115522 - 115522

Опубликована: Фев. 27, 2025

Язык: Английский

Процитировано

3

Fault prognosis of Li-ion batteries in electric vehicles: Recent progress, challenges and prospects DOI
Heng Li, Muaaz Bin Kaleem, Kailong Liu

и другие.

Journal of Energy Storage, Год журнала: 2025, Номер 116, С. 116002 - 116002

Опубликована: Март 8, 2025

Язык: Английский

Процитировано

3

Boosting battery state of health estimation based on self-supervised learning DOI Creative Commons
Yunhong Che, Yusheng Zheng, Xin Sui

и другие.

Journal of Energy Chemistry, Год журнала: 2023, Номер 84, С. 335 - 346

Опубликована: Июнь 8, 2023

State of health (SoH) estimation plays a key role in smart battery prognostic and management. However, poor generalization, lack labeled data, unused measurements during aging are still the major challenges to accurate SoH estimation. Toward this end, paper proposes self-supervised learning framework boost performance Different from traditional data-driven methods which rely on considerable training dataset obtained numerous cells, proposed method achieves robust estimations using limited data. A filter-based data preprocessing technique, enables extraction partial capacity-voltage curves under dynamic charging profiles, is applied at first. Unsupervised then used learn characteristics unlabeled through an auto-encoder-decoder. The learned network parameters transferred downstream task fine-tuned with very few sparsely boosts framework. has been validated different chemistries, formats, operating conditions, ambient. accuracy can be guaranteed by only three initial 20% life cycles, overall errors less than 1.14% error distribution all testing scenarios maintaining 4%, robustness increases aging. Comparisons other supervised machine demonstrate superiority method. This simple data-efficient promising real-world applications variety scenarios.

Язык: Английский

Процитировано

36

Accurate Model Parameter Identification to Boost Precise Aging Prediction of Lithium‐Ion Batteries: A Review DOI Open Access
Shicong Ding, Yiding Li, Haifeng Dai

и другие.

Advanced Energy Materials, Год журнала: 2023, Номер 13(39)

Опубликована: Авг. 18, 2023

Abstract Precise prediction of lithium‐ion cell level aging under various operating conditions is an imperative but challenging part ensuring the quality performance emerging applications such as electric vehicles and stationary energy storage systems. Accurate real‐time battery‐aging models, which require exact understanding degradation mechanisms battery components materials, could in turn provide new insights for materials basic research. Furthermore, primary barrier to meaningful artificial intelligence/machine learning accelerating period exploitation accurate mechanistic descriptors. This review comprehensively summarizes evolution deterioration at material different environments usage scenarios, including intricate relationships between mechanisms, modes, external influences, are cornerstones modeling simulation machine techniques. Recent advances electrochemical models coupled with internal well identification tracking parameters shown, particular emphasis on electrode balance anticipated trend learning‐assisted reliable remaining useful life prediction. will continue play essential role advanced smart research management, enhancing its while shortening experimental sequences.

Язык: Английский

Процитировано

36

IoB: Internet-of-batteries for electric Vehicles–Architectures, opportunities, and challenges DOI Creative Commons
Heng Li, Muaaz Bin Kaleem, Zhijun Liu

и другие.

Green Energy and Intelligent Transportation, Год журнала: 2023, Номер 2(6), С. 100128 - 100128

Опубликована: Сен. 7, 2023

The concept of the Internet-of-Batteries (IoB) has recently emerged and offers great potential for control optimization battery utilization in electric vehicles (EV). This concept, which combines aspects Internet-of-Things (IoT) with latest advancements technology cloud computing, can provide a wealth new information about health performance. be used to improve management number ways, including continuous prognosis improved vehicle management. In this paper, we reviewed detail basic structure IoB, based on many existing studies. We also explored benefits approach, such as Implementing IoB EVs is not without challenges, faces security data, cross-platform functionality, technical complexities applying large scale. However, are significant continued research development, it ability revolutionize EV industry. purpose review paper comprehensive overview discussing its challenges. provides roadmap future development highlighting key areas that need addressed fully realize technology.

Язык: Английский

Процитировано

35