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This paper presents a novel physical parameter estimation framework for on-site model characterization, using a two-phase modelling strategy with Physics-Informed Neural Networks (PINNs) and transfer learning (TL). In the first phase, a…

Machine Learning · Computer Science 2026-01-23 Josu Yeregui , Iker Lopetegi , Sergio Fernandez , Erik Garayalde , Unai Iraola

This paper proposes a fully unsupervised methodology for the reliable extraction of latent variables representing the characteristics of lithium-ion batteries (LIBs) from electrochemical impedance spectroscopy (EIS) data using information…

Signal Processing · Electrical Eng. & Systems 2021-07-14 Seongyoon Kim , Yun Young Choi , Jung-Il Choi

The physics-based Doyle-Fuller-Newman (DFN) model, widely adopted for its precise electrochemical modeling, stands out among various simulation models of lithium-ion batteries (LIBs). Although the DFN model is powerful in forward predictive…

Computational Engineering, Finance, and Science · Computer Science 2025-04-30 Weipeng Xu , Kaiqi Yang , Yuzhi Zhang , Shichao Sun , Sheng Mao , Tianju Xue

With the popularity of electric vehicles, the demand for lithium-ion batteries is increasing. Temperature significantly influences the performance and safety of batteries. Battery thermal management systems can effectively control the…

Machine Learning · Computer Science 2026-01-07 Zheng Liu , Yuan Jiang , Yumeng Li , Pingfeng Wang

Monitoring physical activity energy expenditure (PAEE) in daily life is essential for characterizing individual health and metabolic status. Although indirect calorimetry provides gold-standard PAEE measurements, it is impractical for…

Systems and Control · Electrical Eng. & Systems 2026-05-07 Shuhao Que , Remco Poelarends , Valentina Breschi , Ying Wang

The optimization of the electrodes manufacturing process constitutes one of the most critical steps to ensure high-quality Lithium-Ion Battery (LIB) cells, in particular for automotive applications. Because LIB electrode manufacturing is a…

For Prognostics and Health Management (PHM) of Lithium-ion (Li-ion) batteries, many models have been established to characterize their degradation process. The existing empirical or physical models can reveal important information regarding…

Signal Processing · Electrical Eng. & Systems 2023-09-12 Pengfei Wen , Zhi-Sheng Ye , Yong Li , Shaowei Chen , Pu Xie , Shuai Zhao

In this paper, we study a suitable experimental design of electrochemical impedance spectroscopy (EIS) to reduce the number of frequency points while not significantly affecting the uncertainties of the estimated cell's equivalent circuit…

Systems and Control · Electrical Eng. & Systems 2025-01-13 Vladimir Sovljanski , Mario Paolone , Sylvain Tant , Damien Pierre Sainflou

This paper proposes physical-based, reduced-order electrochemical models that are much faster than the electrochemical pseudo 2D (P2D) model, while providing high accuracy even under the challenging conditions of high C-rate and strong…

Chemical Physics · Physics 2023-05-30 Tianhan Gao , Wei Lu

The correct assessment of battery states is essential to maximize battery pack performances while ensuring reliable and safe operation. This work introduces EIS2MOD, a novel modelling framework for Li-ion cells based on Distribution of…

Systems and Control · Electrical Eng. & Systems 2022-03-17 Pietro Iurilli , Claudio Brivio , Rafael E. Carrillo , Vanessa Wood

Electrochemical impedance spectroscopy (EIS) is the most informative diagnostic for lithium-ion batteries: its frequency-resolved spectra decompose cell behavior into distinct electrochemical processes, revealing mechanism-specific…

Systems and Control · Electrical Eng. & Systems 2026-05-18 Shafayeth Jamil , Rehan Kapadia

In order to achieve a better understanding of degradation processes in lithium-ion batteries, the modelling of cell dynamics at the mircometer scale is an important focus of current mathematical research. These models lead to…

Numerical Analysis · Mathematics 2018-03-09 Mario Ohlberger , Stephan Rave , Sebastian Schmidt , Shiquan Zhang

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

Electrochemical Impedance Spectroscopy (EIS) is a crucial technique for assessing corrosion of a metallic materials. The analysis of EIS hinges on the selection of an appropriate equivalent circuit model (ECM) that accurately characterizes…

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…

A derivation of the single particle model (SPM) is made from a porous electrode theory model (or Newman model) of half-cell (dis)charge for an electrode composed of uniformly sized spherical electrode particles of a single chemistry. The…

Chemical Physics · Physics 2019-07-23 G. Richardson , I. Korotkin , R. Ranom. M. Castle , J. M. Foster

This article examines the problem of Lithium-Sulfur (Li-S) battery state estimation. Such estimation is important for the online management of this energy-dense chemistry. The literature uses equivalent circuit models (ECMs) for Li-S state…

Systems and Control · Electrical Eng. & Systems 2021-02-17 Chu Xu , Timothy Cleary , Daiwei Wang , Guoxing Li , Christopher Rahn , Donghai Wang , Rajesh Rajamani , Hosam K. Fathy

Lithium-Ion (Li-I) batteries have recently become pervasive and are used in many physical assets. To enable a good prediction of the end of discharge of batteries, detailed electrochemical Li-I battery models have been developed. Their…

Machine Learning · Computer Science 2020-12-09 Ajaykumar Unagar , Yuan Tian , Manuel Arias-Chao , Olga Fink

We introduce a computational efficient data-driven framework suitable for quantifying the uncertainty in physical parameters and model formulation of computer models, represented by differential equations. We construct physics-informed…

Machine Learning · Statistics 2023-02-01 Michail Spitieris , Ingelin Steinsland

Passivity-based control ensures system stability by leveraging dissipative properties and is widely applied in electrical and mechanical systems. Port-Hamiltonian systems (PHS), in particular, are well-suited for interconnection and damping…

Systems and Control · Electrical Eng. & Systems 2025-05-06 Thomas Beckers , Leonardo Colombo