The electrification of aircraft requires more than incremental changes to propulsion: it calls for a fundamentally new way of thinking about how aircraft, propulsion architectures, power management systems, and operations interact as a unified whole. At the Integrated Design of Efficient Aerospace Systems (IDEAS) Laboratory at the University of Michigan, we develop computational frameworks that couple physics-based modeling, multidisciplinary design optimization, and systems engineering, all accelerated by machine learning, to address the challenges and opportunities of this evolving field. This seminar will show how we leverage these frameworks to rapidly explore the complex trade-offs inherent in novel aircraft concepts. We will discuss recent technical results and insights from our research, emphasizing viable design strategies and architectures that demonstrate significant efficiency gains in electrified aircraft. Key topics will include trade-off analysis across vehicle configuration, propulsion–power integration, and operational profiles, illustrated with examples drawn from our open-source design tools and current projects.

This paper introduces a novel methodology, the Graph-based Propulsion System Analysis (GPSA) Framework, for the systematic analysis of aircraft propulsion systems. The methodology encodes propulsion architectures via an architecture matrix that delineates component connectivity, while complementary operational and efficiency matrices quantify power distribution strategies and transmission losses, respectively. An algorithm using a fixed-point iteration is developed to simulate both uni-directional and bi-directional power flows, enabling the evaluation of complex operational modes, including conventional propulsion and in-flight battery charging. Multiple numerical examples demonstrate the framework's robustness and flexibility in modeling configurations with multiple sources, sinks, and varying power path lengths. Furthermore, integration with the Future Aircraft Sizing Tool underscores its potential for use during early-phase design and trade space exploration. By overcoming previous limitations such as restrictions on serial power-transmitting components, this unified and adaptable framework advances the state of the art in propulsion system analysis and lays a solid foundation for future improvements in computational efficiency and component classification.

This study develops a harmonized Dash 8 Q300-class baseline in the Future Aircraft Sizing Tool (FAST) and evaluates a parallel hybrid-electric retrofit coupling high-temperature proton exchange membrane fuel cells (HT-PEMFCs), payload accounting, and layer-resolved liquid-hydrogen (LH2) tank pre-sizing for a 1518.64 km full-payload design mission. The HT-PEMFC model, calibrated against 413–473 K polarization data, uses a corrected PA-PBI conductivity relation. Increasing current density reduces installed cell count but lowers efficiency and raises hydrogen demand. At fixed hydrogen inventory, shorter tanks minimize volume, while longer tanks reduce liner mass but require more insulation. At 100% scheduled electric fraction with ideal fixed-current staging, minimum partial packaging volume is 13.66 m3 at 0.825 A/cm2, whereas minimum accounted propulsion-and-dispatch-fuel mass is 3.67 t at 1.20 A/cm2. Neither unconstrained optimum fits the 1.86 m cabin envelope; fixed-diameter cases retain 20–24 passengers at 100% scheduled electric fraction and 40–41 at 25%. The two optima remain separate across 512 engineering scenarios under fixed-current staging and coincide at 1.20 A/cm2 under full-area variable-current operation. At 0.035 W/(m K) foam conductivity, the 1.86 m tank-diameter constraint cannot be met within 20 m. Stack dispatch, tank insulation, cabin geometry, and hybridization level determine the preferred operating point.

Electrified aircraft are a promising solution to reduce aviation's carbon footprint across general and commercial aviation sectors. However, existing computational tools for aircraft design require information about the aircraft's configuration, forcing the designer to down-select before optimizing their design. As a result of the limited flexibility, suboptimal system architectures may be selected during the early phases of conceptual design. To address this, the Future Aircraft Sizing Tool (FAST), an open-source, MATLAB-based tool, was developed as a propulsion system-agnostic tool for early-phase conceptual design. Using limited design parameters, FAST facilitates rapid and comprehensive aircraft sizing and performance evaluation, utilizing an extensive database of over 450 historical aircraft. Both data-driven and physics-based models are combined to seamlessly integrate new electrification technologies into a design while rapidly predicting its performance. This capability enables early-stage design space exploration to rigorously assess a wide range of propulsion architectures, energy sources, and operational strategies for novel aircraft configurations. This paper presents the key features of FAST, including workflows for aircraft sizing and analysis. The paper also presents a case study involving a commercial freighter, demonstrating FAST's ability to perform design space exploration and early-phase trade studies.

Future transport aircraft concepts leveraging advanced propulsion systems enable more efficient flight, but face major certification barriers prior to entering service. One critical barrier is the poor applicability of “one engine inoperative” (OEI) performance requirements defined in FAA Part 25 and EASA CS-25 regulations that only apply to transport aircraft designed with 2–4 homogeneously sized gas turbine engines, making direct application to heterogeneous and distributed propulsion systems ambiguous. This work constructs generalized OEI performance requirements anchored to existing regulations and are parameterized by the specific excess power lost during a propulsion system failure, maintaining broad applicability to any aircraft and propulsion system architecture. Under the same parameterization, an “engine inoperative correction factor” is also constructed to scale the propulsion system size, enabling seamless integration into the aircraft sizing process. Both contributions are utilized to size a notional Elysian E9X, revealing system-level performance penalties for configurations sized under 4-, 5-, and 6-engine inoperative failure modes. The power loading decreases by up to 28%, thus increasing the aircraft’s maximum takeoff weight and battery energy stored onboard by up to 17% and 19%, respectively. Additional operational constraints prevent attaining system-level benefits for less severe propulsion system failure modes.

Hybrid-electric aircraft (HEA) are frequently proposed as a near-term pathway to reduce aviation fuel consumption and operating costs, but their practical viability depends on whether aircraft-level efficiency gains translate into competitive performance within airline operations. Most prior studies evaluate HEA using isolated mission analyses or simplified fleet models, which do not capture key constraints for real-world deployment. This work develops a trajectory-adaptive HEA power management framework for optimizing mission-level and charging-constrained sequential operations, and then links optimized HEA operating costs to a Fleet Assignment Model representing a full-service airline network. At the aircraft level, gas turbine and electric motor power are optimized along the mission trajectory subject to battery state-of-charge, charging, and performance constraints. The framework is used to evaluate both independent missions and multi-flight sequences, showing that limited turnaround charging can make route-specific optimization operationally optimistic for HEA using current battery technology levels. Adaptive power management reduces sequence fuel burn by up to 3\% with current technology and more than 7\% with improved battery assumptions relative to a conventional ERJ175 baseline. To examine broader fleet-level implications, mission-optimized HEA operating costs are embedded in a Fleet Assignment Model to evaluate where HEA may be economically competitive within an existing network. The results indicate route-level operating-cost competitiveness under modeled conditions as optimized HEA are preferentially assigned to selected regional markets. The proposed approach provides a structured framework for evaluating HEA viability across aircraft-, sequence-, and network-level operations.

This paper presents a novel methodology for predicting key aircraft design parameters using Gaussian process regressions (GPRs) applied to a comprehensive, open-source database of over 400 aircraft and 200 engines. The database, made freely available through the Future Aircraft Sizing Tool (FAST), enables aircraft designers to apply detailed historical data in early-stage conceptual design and provides full visibility into the data underlying the regressions-unlike traditional regression models, where the training data and model fit are often not disclosed. The nonparametric GPR models developed in this work allow for flexible input configurations, improving the accuracy of predicting critical parameters, such as operating empty weight and uninstalled engine weight, compared to established regressions from the literature. By incorporating a broader range of inputs, these models reduce prediction errors and provide tighter error distributions, leading to more reliable estimates during early design phases. This paper outlines a methodology for adapting conventional aircraft data to explore hybrid-electric and fully electric aircraft designs, ensuring that historical data can be leveraged effectively for novel propulsion systems. Additionally, the flexibility of the GPR framework allows users to create their own regressions and update predictions as new data becomes available, making it a useful tool for researchers working with their own datasets.

Air transportation-and the transportation system overall-is an energy-intensive industry. Sustainable aviation technology such as hybrid-electric aircraft (HEA) seeks to reduce the energy expenditure, thereby reducing operating costs and potentially increasing access to air transport options. The successful adoption of new aircraft technology such as HEA requires ensuring that airline operations can accommodate new aircraft types in a cost- and revenue-optimal manner. In this paper, we seek to address the optimal assignment of aircraft type-including new HEA types-within a full-service airline network, consisting of both mainline and regional flights. We utilize an integer programming model to rigorously characterize this optimal assignment problem. This model allows us to explore several different HEA adoption scenarios, and eventually will enable the joint optimization of both the aircraft (e.g., through aircraft sizing and design studies) and airline operations.

This study evaluates the feasibility and benefits of introducing battery-powered hybrid electric aircraft (HEA) into regional airline operations. Using 2019 U.S. domestic flight data, the ERJ175LR is selected as a representative aircraft, and several HEA variants are designed to match its mission profile under different battery technologies and power management strategies. These configurations are then tested across over 800 actual daily flight sequences flown by a regional airline. The results show that well-designed HEA can achieve 3–7% fuel savings compared to conventional aircraft, with several variants able to complete all scheduled missions without disrupting turnaround times. These findings suggest that HEA can be integrated into today’s airline operations, particularly for short-haul routes, without the need for major infrastructure or scheduling changes, and highlight opportunities for future co-optimization of aircraft design and operations.

NASA proposed the SUbsonic Single Aft eNgine electrofan concept (SUSAN) to meet the increasing demand for electrified aircraft designs, which has the potential to reduce CO2 emissions by 50% and limit aviation's environmental impact. SUSAN's propulsion system consists of one turbofan engine and sixteen distributed electric propulsors. It is designed as a commercial transport that carries a 180-passenger payload for 2,500 nautical miles, while cruising at Mach 0.785 and 37,000 ft. SUSAN's design includes multiple advanced technologies, such as a single aft engine with boundary layer ingestion, distributed electric propulsion system, and several state-of-art electric subsystems. This paper integrates various technologies and methods developed for SUSAN within a single modeling and simulation environment. SUSAN is modeled using the Future Aircraft Sizing Tool (FAST) developed by the University of Michigan. Using aircraft specifications and a design mission profile gathered from literature, FAST evaluates the system-level feasibility and performance of SUSAN and its integrated technologies. Additional propulsion system and BLI models are introduced to incorporate SUSAN's advanced technologies into its design. The resulting SUSAN model has an MTOW of 189,394 lbm, an OEW of 117,460 lbm, and a predicted block fuel burn for the design mission of 30,701 lbm. The SUSAN model has a high lift to drag ratio of 20.49, encouraging further investigation into how these advanced technologies can reduce dependency on control surface sizing and improve aircraft efficiency overall. FAST predicts the cruise TSFC for the aft engine 0.4372 lbm/(lbf center dot hr), which includes the effects of BLI technology.

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.

This study presents a comprehensive analysis of historical trends and future projections for key performance parameters (KPPs) in commercial turbofan aircraft, focusing on operational empty weight to maximum takeoff weight ratio (OEW/MTOW), thrust-to-weight ratio (T/W), thrust-specific fuel consumption (TSFC), and lift-to-drag ratio (L/D). Leveraging the open-source FAST Aerobase, comprising over 400 commercial airframes and 200 engines, drawn from authoritative sources such as FAA and EASA certifications, along with enhanced regression modeling, this study systematically examines the evolution of each KPP in response to technological advancements, market demands, and regulatory constraints. The analysis reveals that TSFC improvements align closely with technological advances and primarily increases in bypass ratio enabled by core downsizing. Trends in OEW/MTOW and T/W are dominated by market-driven range, size, and regulatory factors rather than pure material or propulsion breakthroughs, which indicates limited room for further improvement without disruptive configurations. Cruise L/D improvements have been primarily enabled by wingtip devices, although they are approaching structural and regulatory limits. This work lays a robust foundation for the open-source Future Aircraft Sizing Tool (FAST), equipping designers with data-driven insights to support early-stage design decisions and providing a transparent resource for understanding the historical and technical drivers of commercial aircraft performance.

Without radical technological advancements, the global aviation industry will continue to be a major carbon emitter. To reduce aviation's carbon emissions, innovative aircraft technology, including electrified aircraft propulsion, is under development. However, current aircraft sizing tools require detailed design information that may not be available early in the development process, particularly for novel technologies. This can yield suboptimal designs and inhibits innovation. A computational tool is needed to easily and rapidly size an aircraft configuration while allowing the designer to explore the design space, examine tradeoffs, and evaluate alternative designs. The Future Aircraft Sizing Tool (FAST), developed in Matlab, addresses this challenge by rapidly sizing aircraft with any propulsion architecture, including conventional, electric, and hybrid electric systems, even with limited initial data. FAST enables engineers to explore various aircraft configurations, evaluate design alternatives, assess performance across a flight envelope, and visualize concepts during the sizing process. By supporting early stage design, FAST addresses a gap in currently available computational tools for developing sustainable aviation technologies to help reduce the industry's carbon footprint.

Hydrogen propulsion using low-temperature proton exchange membrane fuel cells (LT-PEMFC) offers a promising alternative to conventional combustion engines by reducing component complexity, lowering operating temperatures, and potentially decreasing operating costs. This paper presents a comprehensive system-level analysis of hydrogen-powered LT-PEMFC propulsion systems for aircraft. Custom-developed models integrate fuel cells with auxiliary subsystems, including thermal management, compression, and power electronics, to size the propulsion system and fuel capacity according to a defined mission profile. Key performance metrics, including range, endurance, and liquid hydrogen volume requirements, are evaluated for a generic general aviation class baseline aircraft sized with an automotive-derived net 150 kW LT-PEMFCs. The analysis considers six key design variables (gross takeoff weight (GTOW), lift-to-drag ratio, propulsion efficiency, propulsion specific power, liquid hydrogen gravimetric index, and GTOW mass fraction) along with three operational parameters (climb rate, service ceiling, and cruise speed). Validation against an established flight mission demonstrates close agreement in liquid hydrogen consumption predictions. Under baseline operational conditions, the aircraft with a 1,814 kg GTOW is predicted to achieve a range of 3,203 km and 17.5 hours of flight. Sensitivity analyses indicate that when subjected to alternative design and operational constraints, incremental improvements in the GTOW mass fraction enable an additional 100 km of range with a minimal adjustment, while enhancements in the lift-to-drag ratio and propulsion efficiency reduce the liquid hydrogen required by 64% and 50% per 100 km relative to other design variables, respectively. Advanced technology improvements suggest a maximum performance potential of 15,474 km in range and 84.7 hours of flight time. These findings provide critical insights for optimizing fuel cell propulsion systems and establishing a clean-sheet design framework for next-generation hydrogen-powered aircraft.