To prepare for the upcoming entry into service of electric and hybrid-electric aircraft, regulators may have to update or develop new regulations and standards to ensure safe operations of these new vehicles. To ensure public acceptance, these vehicles need to demonstrate an equivalent level of safety consistent with existing regulations. However, the ability to fly in different modes (forward flight, vertical flight) and the different powertrain elements may require significant changes to regulations to ensure that an insightful representation of the usable energy is provided to flight crews. This requires an understanding of the major operational differences between conventional and electric aircraft, and how these differences impact the trajectories a vehicle can fly. For instance, there is no simple analog to fuel gauges for measuring the extractable energy available on board electric aircraft, as energy related metrics can vary with a range of variables, such as component temperatures, battery health, and environmental conditions. It is thus more complex for flight crews to gauge in real-time how much usable energy is available and to figure out which trajectories are feasible with respect to both energy and power. To assess the feasibility of trajectories and quantify the adequacy of novel energy tracking metrics and methodologies, a trajectory energy management simulation environment is implemented allowing the simulation of various energy metrics across a range of vehicles and missions. This allows decision makers and regulators to assess the importance of these metrics for safe operation across a wide variety of missions. The impact of ambient air temperature, battery state of health, and initial battery, motor, and inverter temperatures are assessed for a typical flight mission. It is concluded that state of health, ambient temperature, and initial battery temperature all had significant impacts on the final state of charge and amount of extractable energy. Additionally, at high ambient temperatures and in aggressive climbs, motor temperature limits and inverter temperature limits can sometimes be reached, further complicating the assessment of what can be done with the amount of energy stored on board. Proper management of these constraints is therefore crucial for optimizing trajectories with respect to energy metrics. Future work is proposed regarding further expansion of the framework simulating aircraft with vertical takeoff and landing capability, and flight-dynamics algorithms that will enable simulation of optimal energy mission profiles.
Vehicles designed for urban air mobility (UAM) or on-demand mobility (ODM) applications typically adopt an architecture enabling vertical takeoff and landing (VTOL) capabilities. UAM or ODM systems featuring these capabilities typically have a smaller ground footprint but are subject to a number of performance compromises that make sizing and optimizing the vehicles more challenging. These design challenges can be further compounded when additional environmental considerations are taken into account and in particular if electric propulsion is considered. Alternative architectures such as short takeoff and landing (STOL) and super-short takeoff and landing (SSTOL) vehicles are thus investigated because they present possible advantages in terms of energy efficiency, overall vehicle performance, and noise footprint. However, the larger ground footprint of the infrastructure necessary to operate these systems means that these systems may be more difficult to integrate into a urban and suburban environment. One objective of this research is to estimate the geo-density of airparks suitable for STOL and SSTOL operations based on vehicle performance and ground footprint parameters. In turn, this helps establish requirements for the field performances of STOL and SSTOL vehicles to be considered for ODM and UAM applications. This research proposes and interactive and parametric design and trade-off analysis environment to help decision makers assess the suitability of candidate cities for STOL and SSTOL operations. Preliminary results for the Miami metropolitan area show that an average airpark geo-density of 1.66 airparks per square mile can be achieved with a 300 foot long runway.
Air Mobility (AM) operating models have steadily made their way into public conscience over the past decade due to increased research activity pioneered by large technology corporations such as Uber and Amazon. Estimates concur that there are around 250 startup businesses with 22 major players working on such technologies with over $25 billion dollars in venture capital funding in 2017[1]. Given the meteoric rise of Air Mobility as one of the leading 21 st century disruptive technologies, research effort across the spectrum of functions that can make AM concepts a reality are burgeoning -ranging from vehicle design to operations planning. More specifically, research efforts within the operations planning space deal with service route identification, ground infrastructure (such as charging stations and ports) placement and others. To this effect, the present study seeks to evaluate the feasibility and tractability of a formalized optimization method towards the siting of "vertiports" -ground infrastructure that aids the embarkation and disembarkation of AM commuters -as applied to a Sub-Urban Air Mobility (sUAM) operating model. Mixed-Integer Programming (MIP) formulations offer qualified benefits over other heuristic methods and the authors are confident of their relative performance given the proven track record of such methods in solving generalized facility loca-
The thin-haul commuter concept refers to an envisioned class of four to nine passenger aircraft operating very short flights and providing scheduled and on-demand air services from smaller airports. Its objective is to enhance regional mobility reach by combining the flexibility of automobile travel with the shorter commute times associated with air travel. To achieve economic viability, the thin-haul commuter concept must provide appreciable economic advantages when compared to current commuter aircraft. This may be achieved by increasing the revenue potential through innovative pricing and scheduling, while drastically reducing operating costs, in particular, energy, maintenance, and labor costs. These ambitious objectives require the infusion of new cutting edge technologies. The use of distributed electric propulsion is investigated to reduce both energy and maintenance expenditures. New avionics systems are considered to enable simplified operations and thus to reduce both labor and training costs. The purpose of this on-going research is to assess the viability of the thin-haul aviation concept by investigating both the operational and economic impact of introducing a fleet of distributed electric propulsion aircraft into the operations of a commuter airline. This paper presents the development of an integrated economics and operations model that incorporates preliminary estimates of a distributed electric propulsion vehicle performance as well as some aspects of typical commuter operator schedules. The model helps compare advanced electric vehicles with more conventional commuters, and therefore enables a preliminary assessment of the expected cost savings. Nomenclature
The fleet acquisition process represents a major gamble for airlines and aircraft leasing companies due to the fixed assumptions made when business plans are laid out and the abundance of uncertainties both at the technical and market levels. Indeed, the evaluation of aircraft and engine acquisitions is riddled with uncertainties regarding the product development (development schedule), the economic performance of the assets once in operations (operating cost), and the demand for air transportation. The trend in recent years has been for original equipment manufacturers to offer contracts and guarantees during sales campaigns that limit the exposure of airlines to technical uncertainty and that shift some of the operating risks from the airlines to the manufacturers. Airlines have embraced these “power-by-the-hour” maintenance contracts because they offer a way to mitigate operating risks and to anticipate cash outflows. Estimating the fair value of these contracts is paramount due to the significant risks faced by companies underwriting them. At the same time, valuing them is a daunting task due to the uncertainty regarding maintenance costs and their sensitivity to both the operations and the operating environment. Traditional evaluation methods are not always well adapted to perform these evaluations as they do not capture the problem in its entirety and they tend to oversimplify by using generic routes and surrogate models. This paper simultaneously proposes a customer-centric methodology to properly evaluate long-term aircraft and engine investments and a real-options inspired methodology to value long-term maintenance contracts and manufacturer guarantees.
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