A Comprehensive Energy Management Strategy for Energy Storage Systems in MEA under Pulsed Loads based on Fuzzy Logic and Random Forest Prediction

Hybrid energy storage system (HESS), integrating lithium batteries (BAT) and supercapacitors (SC), plays a vital role in ensuring power stability for more electric aircraft (MEA). This paper proposes a comprehensive energy management strategy (EMS) to address the challenges posed by pulsed power loads. Building on a traditional low-pass filter framework, the EMS incorporates a fuzzy logic controller that adaptively adjusts the filter's cutoff frequency based on SC state-of-charge and power imbalance, thereby preventing overcharge and over discharge. To overcome the limitations of PI control under rapid load transients, a predictive compensation strategy is introduced using the random forest (RF) algorithm. The RF model forecasts DC bus voltage based on system power states, enabling proactive SC power injection through droop control. Hardware-in-the-loop simulations across four representative flight scenarios are conducted to validate the effectiveness of the proposed strategy.