Averaging-Based Energy Management Strategy for Hybrid Battery-Ultracapacitor Energy Storage System

Considering a battery as the energy source for steady average current and an ultracapacitor as the dynamic energy buffer, this paper proposes a novel control strategy based on average current demand. The methodology averages the demand current over a time window to determine battery current, combined with rules to maintain the ultracapacitor's state of charge above 50%. However, the battery current is significantly affected by the averaging time window. A small window causes fluctuations, while a large one imposes unwanted currents to control the ultracapacitor's state of charge. As so, by optimizing the averaging window, this strategy minimizes battery current stress and power loss. Simulations under an urban driving cycle compare the proposed strategy with a sole-battery configuration, dynamic programming (benchmark), and rule-based approaches (original strategy). The simulation results indicate that the proposed strategy smooths battery currents, achieves over 75% of dynamic programming's effectiveness in extending battery life, and reduces computational burden and memory usage by over 85%. The strategy's low computational burden, and causal nature enable real-time control, which is demonstrated practically on an experimental setup.