Skip to main content
U.S. Department of Energy
Office of Scientific and Technical Information

Detecting False Data Injection Attacks to Battery State Estimation Using Cumulative Sum Algorithm.

Conference ·

Abstract not provided.

Research Organization:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Organization:
USDOE Office of Electricity (OE)
DOE Contract Number:
NA0003525
OSTI ID:
1891065
Report Number(s):
SAND2021-12449C; 700652
Resource Relation:
Conference: Proposed for presentation at the The 53rd North American Power Symposium (NAPS 2021) held November 14-16, 2021 in College Station, Texas.
Country of Publication:
United States
Language:
English

References (9)

An Event Detection Approach Based on Improved CUSUM Algorithm and Kalman Filter conference October 2020
Battery Energy Storage State-of-Charge Forecasting: Models, Optimization, and Accuracy journal May 2019
Sigma-point Kalman filtering for battery management systems of LiPB-based HEV battery packs journal October 2006
Characterization of Kalman filter residuals in the presence of mismodeling journal January 2000
Sensor fault detection and isolation for a lithium-ion battery pack in electric vehicles using adaptive extended Kalman filter journal January 2017
Summation Detector for False Data-Injection Attack in Cyber-Physical Systems journal June 2020
Battery Energy Storage System (BESS) and Battery Management System (BMS) for Grid-Scale Applications journal June 2014
On the Performance Degradation of Cyber-Physical Systems Under Stealthy Integrity Attacks journal September 2016
Energy Management and Optimization Methods for Grid Energy Storage Systems journal January 2018