Detection of False-Data Injection Attacks in Supercapacitor Charging Systems

For charging energy storage systems of urban light trams, multiple modules are required in parallel to jointly bear the charging current. However, the traditional parallel multi-module charging system faces the risk of current fluctuation and imbalance caused by false-data injection attacks, reducing the reliability. This paper proposes a detection technology of false-data injection attacks in supercapacitors charging process based on adaptive cooperative control. The controller can dynamically analyze current volatility of each module in the process of charging current volatility. When the controller detects the output current fluctuation caused by injection attack, it executes the adaptive current equalization algorithm, automatically adjusts the current output value to approximate the reference current, so as to eliminate or reduce the impact of injection attack on the system. The experimental results verify the anti-interference capability, feasibility and practicability of the proposed distributed flow sharing control method.

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