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This paper proposes a novel two-layer Volt/VAR control (VVC) framework to regulate the voltage profiles across an unbalanced active distribution system, which achieves both the efficient open-loop optimization and accurate closed-loop…

Systems and Control · Electrical Eng. & Systems 2019-12-25 Yifei Guo , Qianzhi Zhang , Zhaoyu Wang , Fankun Bu , Yuxuan Yuan

Battery degradation modes influence the aging behavior of Li-ion batteries, leading to accelerated capacity loss and potential safety issues. Quantifying these aging mechanisms poses challenges for both online and offline diagnostics in…

Signal Processing · Electrical Eng. & Systems 2024-12-16 Yuanhao Cheng , Hanyu Bai , Yichen Liang , Xiaofan Cui , Weiren Jiang , Ziyou Song

Large scale integration of distributed energy resources and electric vehicles in a transactive energy environment present new challenges in terms of voltage stability and fluctuations in a power distribution system. The impact of different…

Systems and Control · Electrical Eng. & Systems 2021-04-30 Sai Munikoti , Kumarsinh Jhala , Kexing Lai , Balasubramaniam Natarajan

Lithium plating during fast charging is a critical degradation mechanism that accelerates capacity fade and can trigger catastrophic safety failures. Recent work has shown that plating onset can manifest in incremental-capacity analysis as…

Machine Learning · Computer Science 2026-03-17 Ayush Patnaik , Jackson Fogelquist , Adam B Zufall , Yiwei Ji , Stephen K Robinson , Peng Bai , Xinfan Lin

The reliability and safety of Lithium-ion batteries (LiBs) are of great concern in the energy storage industry. Nevertheless, the real-time monitoring of their degradation remains challenging due to limited quantitative metrics available…

Battery prognostics and health management predictive models are essential components of safety and reliability protocols in battery management system frameworks. Overall, developing a robust and efficient battery model that aligns with the…

Data Analysis, Statistics and Probability · Physics 2022-12-05 Hamed Sadegh Kouhestani , Lin Liu , Ruimin Wang , Abhijit Chandra

Battery technology is increasingly important for global electrification efforts. However, batteries are highly sensitive to small manufacturing variations that can induce reliability or safety issues. An important technology for battery…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Amariah Condon , Bailey Buscarino , Eric Moch , William J. Sehnert , Owen Miles , Patrick K. Herring , Peter M. Attia

The prediction of battery rate performance traditionally relies on computation-intensive numerical simulations. While simplified analytical models have been developed to accelerate the calculation, they usually assume battery performance to…

Materials Science · Physics 2024-04-09 Hongxuan Wang , Fan Wang , Ming Tang

A voltage regulation method for slow voltage variations at distribution level is proposed, based on a view of the loads, generators and storage along a distribution line as point weights. The "centers of mass" of the absorbed and injected…

Systems and Control · Electrical Eng. & Systems 2021-05-14 Panayiotis Moutis , Pavlos S. Georgilakis , Nikos D. Hatziargyriou

This work explores controllability and the control effort required for lithium-ion batteries. Battery packs have become a critical technology in both personal and professional applications as a means to store large amounts of energy.…

Systems and Control · Electrical Eng. & Systems 2026-04-14 Preston T. Abadie , Donald J. Docimo

Ensuring accurate violation detection in power systems is paramount for operational reliability. This paper introduces an enhanced voltage recovery violation index (EVRVI), a comprehensive index designed to quantify fault-induced delayed…

Systems and Control · Electrical Eng. & Systems 2026-04-09 Mohammad Almomani , Muhammad Sarwar , Venkataramana Ajjarapu

Machine learning (ML) techniques have rapidly found applications in many domains of materials chemistry and physics where large data sets are available. Aiming to accelerate the discovery of materials for battery applications, in this work,…

Materials Science · Physics 2019-05-24 Rajendra P. Joshi , Jesse Eickholt , Liling Li , Marco Fornari , Veronica Barone , Juan E. Peralta

This paper investigates a decentralized optimization methodology to coordinate Electric Vehicles (EV) charging in order to contribute to the voltage control on a residential electrical distribution feeder. This aims to maintain the voltage…

Systems and Control · Computer Science 2015-09-30 Olivier Beaude , Yujun He , Martin Hennebel

Linear sweep and cyclic voltammetry techniques are important tools for electrochemists and have a variety of applications in engineering. Voltammetry has classically been treated with the Randles-Sevcik equation, which assumes an…

Chemical Physics · Physics 2017-03-15 David Yan , Martin Z. Bazant , P. M. Biesheuvel , Mary C. Pugh , Francis P. Dawson

Recent data-driven approaches have shown great potential in early prediction of battery cycle life by utilizing features from the discharge voltage curve. However, these studies caution that data-driven approaches must be combined with…

Applications · Statistics 2020-10-16 Valentin Sulzer , Peyman Mohtat , Suhak Lee , Jason B. Siegel , Anna G. Stefanopoulou

Incremental capacity analysis (ICA) and differential voltage analysis (DVA) are two effective approaches for battery degradation monitoring. One limiting factor for their real-world application is that they require constant-current (CC)…

Systems and Control · Electrical Eng. & Systems 2026-01-12 Qinan Zhou , Gabrielle Vuylsteke , R. Dyche Anderson , Jing Sun

Parameter estimation is of foundational importance for various model-based battery management tasks, including charging control, state-of-charge estimation and aging assessment. However, it remains a challenging issue as the existing…

Systems and Control · Electrical Eng. & Systems 2022-07-13 Ning Tian , Yebin Wang , Jian Chen , Huazhen Fang

In optimizing performance and extending the lifespan of lithium batteries, accurate state prediction is pivotal. Traditional regression and classification methods have achieved some success in battery state prediction. However, the efficacy…

Machine Learning · Computer Science 2024-10-07 Lidang Jiang , Changyan Hu , Sibei Ji , Hang Zhao , Junxiong Chen , Ge He

Physics-based electrochemical battery models derived from porous electrode theory are a very powerful tool for understanding lithium-ion batteries, as well as for improving their design and management. Different model fidelity, and thus…