Energy and Power Management Optimization for Sequential Daily Operations in Regional Hybrid-Electric Aircraft
Abstract
Hybrid-Electric Aircraft (HEA) present a potential pathway to enhance propulsive efficiency and reduce operating costs in regional airline operations. This study introduces an adaptive power management strategy that optimizes allocation of electric and gas turbine engine power across sequential daily flights while addressing operational constraints such as limited gate charging durations and available ground time. HEA models are developed using physics-based and data-driven methods within the open-source Future Aircraft Sizing Tool (FAST). In contrast to prior studies that rely on fixed power splits or single-mission strategies, the proposed approach dynamically adjusts power distribution across mission phases to maximize efficiency and performance over a range of missions. Key findings indicate that sequence-optimized power management can achieve approximately a 2–3% reduction in fuel burn compared to a conventional baseline, utilizing conservative battery technology assumptions of 250 Wh/kg pack-level specific energy and a 150 kW charging power limit. The study also finds that optimizing power allocation across a full day of operations yields greater benefits than optimizing each flight independently. These results demonstrate the feasibility of HEA integration into regional airline markets, offering improved operational efficiency and cost savings while maintaining compatibility with existing fleet schedules.
Emma Cassidy
PhD student and Graduate Research Assistant
Emma is a PhD candidate in Aerospace Engineering at the University of Michigan and works as a Graduate Student Research Assistant in the IDEAS Lab. Her research interests are sustainable aviation, experimental aircraft design, and commercial aircraft operations.
Yipeng Liu
Master’s student and Research Assistant
Yipeng Liu is a research assistant at the IDEAS lab at U-M, working on the hybrid electric aircraft operations project.
