Online and Offline Identification of False Data Injection Attacks in Battery Sensors Using a Single Particle Model

O’Brien, Victoria A.; Rao, Vittal S.; Trevizan, Rodrigo D.

doi:10.1109/oajpe.2024.3493757

Title: Online and Offline Identification of False Data Injection Attacks in Battery Sensors Using a Single Particle Model

Journal Article · 06 November 2024 · IEEE Open Access Journal of Power and Energy

DOI: https://doi.org/10.1109/oajpe.2024.3493757 · OSTI ID:2479028

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Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Texas Tech Univ., Lubbock, TX (United States)

The cells in battery energy storage systems are monitored, protected, and controlled by battery management systems whose sensors are susceptible to cyberattacks. False data injection attacks (FDIAs) targeting batteries’ voltage sensors affect cell protection functions and the estimation of critical battery states like the state of charge (SoC). Inaccurate SoC estimation could result in battery overcharging and over discharging, which can have disastrous consequences on grid operations. This paper proposes a three-pronged online and offline method to detect, identify, and classify FDIAs corrupting the voltage sensors of a battery stack. To accurately model the dynamics of the series-connected cells a single particle model is used and to estimate the SoC, the unscented Kalman filter is employed. FDIA detection, identification, and classification was accomplished using a tuned cumulative sum (CUSUM) algorithm, which was compared with a baseline method, the chi-squared error detector. Online simulations and offline batch simulations were performed to determine the effectiveness of the proposed approach. Throughout the batch simulations, the CUSUM algorithm detected attacks, with no false positives, in 99.83% of cases, identified the corrupted sensor in 97% of cases, and determined if the attack was positively or negatively biased in 97% of cases.

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Research Organization:: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA); USDOE Office of Electricity (OE)

Grant/Contract Number:: NA0003525

OSTI ID:: 2479028

Report Number(s):: SAND--2024-15946J

Journal Information:: IEEE Open Access Journal of Power and Energy, Journal Name: IEEE Open Access Journal of Power and Energy Journal Issue: 0 Vol. 11; ISSN 2687-7910

Publisher:: IEEECopyright Statement

Country of Publication:: United States

Language:: English

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