Adaptive Online Power Management for More Electric Aircraft With Hybrid Energy Storage Systems
Yu Wang, Fang Xu, Shiwen Mao, Shanshui Yang, Yinxing Shen
Abstract
More electric aircraft (MEA) has become the trend of future advanced aircraft for its potential to be more efficient and reliable. The optimal power management, thus, plays an important role in MEA, especially when using hybrid energy storage systems (HESSs). In this article, we propose a novel adaptive online power management (AOPM) algorithm for MEA, which aims to minimize the power fluctuation of the generators based on the battery-supercapacitor HESS. The problem is first formulated as a constrained stochastic programming problem. We then present an online algorithm to approximately solve the problem using the Lyapunov optimization method, which does not require any statistics and future knowledge of the electricity demand. We further propose the AOPM algorithm for MEA by incorporating an adaptive strategy with the online algorithm. Trace-driven simulation results demonstrate the effectiveness, efficiency, and adaptability of the proposed power management algorithm for MEA.