publications | Clement Wong

2026

Fault Detection of Parallel-Connected Cell Groups Using Differential Voltage Analysis

A. Stefanopoulou, C. Wong, J. B. Siegel, and 3 more authors

U.S. Patent Application, Jan 2026

Filed Jan. 22, 2026

@article{wong2026fault,
  author = {Stefanopoulou, A. and Wong, C. and Siegel, J. B. and Yang, S. Y. and Choi, J. and Jin, H.},
  title = {Fault Detection of Parallel-Connected Cell Groups Using Differential Voltage Analysis},
  journal = {U.S. Patent Application},
  year = {2026},
  month = jan,
  number = {19/275,296},
  note = {Filed Jan. 22, 2026}
}

Health feature extraction from battery energy storage system field fault data

Clement Wong, Andrew Weng, Xin Hui Ooi, and 6 more authors

2026

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Health monitoring methods are critical for lithium-ion battery modules connected to the grid to prevent faults that can lead to catastrophic events. However, assessing the health of cells in modules from their operational data presents challenges including variable operating conditions, which directly confound health features, and sparse sensing in the modules, particularly within cells in parallel, which prevents observing critical states of individual cells. Here, we present a framework for extracting and calibrating health features for battery modules from their operational data to identify discriminative features for separating faulty parallel-connected cell groups within the modules. We applied this framework to operational data from 25 commercial grid-connected lithium-ion Battery Energy Storage System (BESS) modules. Each module consisted of 14 series-connected parallel groups, one of which was confirmed as faulty via post-mortem investigation; in total, the dataset included 25 faulty and 325 non-faulty cell groups. A statistical evaluation of these calibrated features demonstrated that group-level capacity, capacity degradation rate, and dV/dQ peak heights separate faulty parallel-connected cell groups within the modules with statistical significance (p<0.05). Conversely, group internal resistance did not (p>0.05), indicating that increased resistance was not a primary characteristic of the faults in this dataset. These findings challenge the exclusive reliance on resistance features for fault detection. The observed feature signatures suggest potential failure mechanisms, furthering the understanding of fault behavior in lithium-ion battery modules during field operation. More importantly, this work demonstrates a framework for robustly monitoring the health of cells in lithium-ion battery modules under real-world operations.
@article{wong2026healthfeatureextractionbattery, title = {Health feature extraction from battery energy storage system field fault data}, author = {Wong, Clement and Weng, Andrew and Ooi, Xin Hui and Wan, Zhiwen and Choi, Jeesoon and Yang, Seung Yoon and Jin, Heejun and Siegel, Jason and Stefanopoulou, Anna}, year = {2026}, archiveprefix = {arXiv}, primaryclass = {eess.SY}, url = {https://arxiv.org/abs/2606.26347} }
Quantifying imbalances in parallel-connected cell groups using group voltage and current

C. Wong, A. Weng, H. Movahedi, and 5 more authors

Journal of Energy Storage, 2026

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Insight into imbalances within a group of parallel-connected cells is critical for effective battery management but is challenging to obtain due to limited sensor data and measurement noise. This work presents a novel approach for quantifying imbalances in parallel-connected lithium-ion cells using only group-level current and voltage measurements. First, by modeling groups of two parallel-connected cells with varying capacity and resistance, we demonstrate that features of the group’s differential voltage with respect to differential state of charge (dV/dz) — specifically the height and skewness of the dV/dz peak corresponding to the graphite Stage 2 phase transition — can quantify imbalance in the capacity-resistance product (CR). Furthermore, we show that dV/dz peak features can quantify current rate and SOC imbalances, as these imbalances are proportional to CR imbalance. After establishing how imbalances can be quantified using the group dV/dz peak features, we introduce a novel algorithm, which we term OCP-informed Feature Identification, that accurately and precisely estimates these features from noisy voltage data, enabling a robust diagnosis of imbalances. Finally, we analyze how the sensitivity of the dV/dz peak features changes with the number of cells in parallel, providing insight into the scalability of the proposed diagnostic approach. This work lays the groundwork for diagnosing imbalances within parallel-connected cell groups in battery modules using the limited and noisy sensor measurements typically available in the field.
@article{Wong_2024, author = {Wong, C. and Weng, A. and Movahedi, H. and Choi, J. and Yang, S. Y. and Jin, H. and Siegel, J. B. and Stefanopoulou, A.}, doi = {https://doi.org/10.1016/j.est.2026.120507}, issn = {2352-152X}, journal = {Journal of Energy Storage}, keywords = { Capacity imbalance, Current rate imbalance, Differential voltage analysis, Lithium-ion batteries, Resistance imbalance, State-of-charge (SOC) imbalance,Parallel-connected cells}, pages = {120507}, title = {{Quantifying imbalances in parallel-connected cell groups using group voltage and current}}, url = {https://www.sciencedirect.com/science/article/pii/S2352152X26001714}, volume = {150}, year = {2026} }
The potential and viability of V2G for California BEV drivers

Clement Wong, Amalie Trewartha, Steven B. Torrisi, and 1 more author

2026

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Vehicle-to-Grid (V2G) adoption is hindered by uncertainties regarding its effects on battery lifetime and vehicle usability. These uncertainties are compounded by limited insight into real-world vehicle usage. Here, we leverage real-world Californian BEV usage data to design and evaluate a user-centric V2G strategy. We identified four clustered driver profiles for V2G assessment, ranging from "Daily Chargers" to "Public Chargers". We show that V2G participation is most feasible for "Daily Chargers," and that the effects on battery lifetime depend on calendar aging sensitivity. For batteries with low sensitivity, V2G participation increases capacity loss for all drivers. However, for batteries with high sensitivity, V2G participation can lead to negligible changes in capacity or even improved capacity retention, particularly for drivers who tend to keep their batteries at high states of charge. Our findings enable stakeholders to better assess the potential and viability of V2G adoption.
@article{Wong2025_PotentialV2G, title = {The potential and viability of V2G for California BEV drivers}, author = {Wong, Clement and Trewartha, Amalie and Torrisi, Steven B. and Filipowicz, Alexandre L. S.}, year = {2026}, archiveprefix = {arXiv}, primaryclass = {eess.SY}, url = {https://arxiv.org/abs/2603.10880} }

2025

SimV2G: Personalized Interface to Simulate and Promote Vehicle-to-Grid Participation

C. Wong, J. Q. Li, A. Trewartha, and 2 more authors

In Adjunct Proceedings of the International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutoUI), 2025

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We demonstrate a web app user interface that simulates the benefits and trade-offs of Vehicle-to-Grid (V2G) given an individual’s electric vehicle driving habits. Users input their own driving and charging data (or explore example usage patterns), specify their battery type, and indicate their availability for V2G. The interface then generates a personalized V2G schedule and presents both the potential financial benefits (e.g., earnings from supplying energy to the grid) and impact on battery health. This interactive and personalized interface aims to mitigate known barriers to V2G participation and increase consumer interest in the technology.
@inproceedings{Wong2025SimV2G, author = {Wong, C. and Li, J. Q. and Trewartha, A. and Torrisi, S. B. and Filipowicz, A. L. S.}, title = {{SimV2G: Personalized Interface to Simulate and Promote Vehicle-to-Grid Participation}}, booktitle = {{Adjunct Proceedings of the International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutoUI)}}, year = {2025}, doi = {10.1145/3744335.3758968}, url = {https://dl.acm.org/doi/10.1145/3744335.3758968} }
V2G Validation: A Concept Validation Study of UI Features to Promote Vehicle-to-Grid Adoption

M. P. Van, C. Wong, D. A. Shamma, and 3 more authors

In Adjunct Proceedings of the International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutoUI), 2025

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This paper presents a data review conducted as part of a larger study commissioned by the Queensland Government. The overall study focuses on improving transportation and mobility access for people with disabilities (PwDs) by developing design principles for accessible autonomous vehicles (AAVs). Existing literature highlights the cumulative disadvantage faced by PwDs, including lack of mobility, social inclusion, and violation of human rights due to barriers in transportation. An autonomous future has the potential to provide accessible transport options, leading to improved access to medical care, employment, social inclusion, and safety. The data review, based on available numerical and metric data research identifies key information for accessible AVs, such as wheeled mobility user anthropometric percentiles, clear floor space requirements, recommended ramp angles, interior layout configurations, and door dimensions. However, there is a need for further research in co-design prototyping, analysis of standards, and current design best practices. The data review, alongside the larger ongoing research, aims to provide a comprehensive set of design principles for an AVs that caters to the diverse needs of PwDs including blind and low-vision, deaf/hard of hearing, mobility impaired, intellectual, and developmental disability, and elderly populations. The review concludes by discussing clusters of information identified, gaps in data, and opportunities for further research.
@inproceedings{Van2025, author = {Van, M. P. and Wong, C. and Shamma, D. A. and Hogan, C. and Lee, M. L. and Filipowicz, A. L. S.}, title = {{V2G Validation: A Concept Validation Study of UI Features to Promote Vehicle-to-Grid Adoption}}, booktitle = {{Adjunct Proceedings of the International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutoUI)}}, year = {2025}, doi = {10.1145/3744335.3758514}, url = {https://dl.acm.org/doi/10.1145/3744335.3758514} }

2024

Differential Voltage Analysis and Patterns in Parallel-Connected Pairs of Imbalanced Cells

Clement Wong, Andrew Weng, Sravan Pannala, and 3 more authors

In 2024 American Control Conference (ACC), 2024

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Diagnosing imbalances in capacity and resistance within parallel-connected cells in battery packs is critical for battery management and fault detection, but it is challenging given that individual currents flowing into each cell are often unmeasured. This work presents a differential voltage analysis method for identifying imbalances in parallel-connected battery cells using only voltage and current pair measurements. Specific characteristics of the differential voltage curve, particularly the peak height and skewness during constant current discharge, respond predictably to capacity and resistance imbalances. While these peak shape features can identify the combined effect of both imbalance types, they cannot separately distinguish between capacity versus resistance imbalances individually.
@inproceedings{ACC_Wong_2024, author = {Wong, Clement and Weng, Andrew and Pannala, Sravan and Choi, Jeesoon and Siegel, Jason B. and Stefanopoulou, Anna}, booktitle = {2024 American Control Conference (ACC)}, title = {Differential Voltage Analysis and Patterns in Parallel-Connected Pairs of Imbalanced Cells}, year = {2024}, pages = {3492-3497}, keywords = {Resistance;Voltage measurement;Shape;Fault detection;Current measurement;Battery management systems;Discharges (electric)}, doi = {10.23919/ACC60939.2024.10644672}, url = {https://ieeexplore.ieee.org/document/10644672} }

Impact of Pretension and Cycling Window on Degradation of Graphite/Silicon Composite Anodes

Z. Wan, S. Pannala, H. Movahedi, and 4 more authors

In ECS Meeting Abstracts, 2024

Bib

@inproceedings{Wan_2024,
  author = {Wan, Z. and Pannala, S. and Movahedi, H. and Wong, C. and Solbrig, C. and Siegel, J. B. and Stefanopoulou, A.},
  title = {Impact of Pretension and Cycling Window on Degradation of Graphite/Silicon Composite Anodes},
  booktitle = {ECS Meeting Abstracts},
  year = {2024}
}

Current Imbalance in Dissimilar Parallel-Connected Batteries and the Fate of Degradation Convergence1

A. Weng, H. Movahedi, C. Wong, and 2 more authors

Journal of Dynamic Systems, Measurement, and Control, 2024

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This paper proposes an analytical framework describing how initial capacity and resistance variability in parallel-connected battery cells may inflict additional variability or reduce variability while the cells age. We derive closed-form equations for current and SOC imbalance dynamics within a charge or discharge cycle. These dynamics are represented by a first-order equivalent circuit model and validated against experimental data. To demonstrate how current and state of charge (SOC) imbalance leads to cell degradation, we developed a successive update scheme in which the intercycle imbalance dynamics update the intracycle degradation dynamics, and vice versa. Using this framework, we demonstrate that current imbalance can cause convergent degradation trajectories, consistent with previous reports. However, we also demonstrate that different degradation assumptions, such as those associated with SOC imbalance, may cause divergent degradation. We finally highlight the role of different cell chemistries, including different OCV function nonlinearities, on system behavior, and derive analytical bounds on the SOC imbalance using Lyapunov analysis.
@article{Weng_current_imbalance, author = {Weng, A. and Movahedi, H. and Wong, C. and Siegel, J. B. and Stefanopoulou, A.}, doi = {10.1115/1.4064028}, issn = {0022-0434}, journal = {Journal of Dynamic Systems, Measurement, and Control}, number = {1}, pages = {11106}, title = {{Current Imbalance in Dissimilar Parallel-Connected Batteries and the Fate of Degradation Convergence1}}, url = {https://doi.org/10.1115/1.4064028}, volume = {146}, year = {2024} }

2023

Voltage Differential Analysis during Power Discharge Operation in Energy Storage Systems

C. Wong, J. B. Siegel, and A. Stefanopoulou

In ECS Meeting Abstracts, May 2023

Bib

@inproceedings{Wong_2023,
  author = {Wong, C. and Siegel, J. B. and Stefanopoulou, A.},
  title = {{Voltage Differential Analysis during Power Discharge Operation in Energy Storage Systems}},
  booktitle = {ECS Meeting Abstracts},
  year = {2023},
  month = may,
  publisher = {The Electrochemical Society, Inc.}
}