Energy Based Method for Generation of Optimum Flight Paths

One key to increasing aviation safety and airport efficiency is the proper management of aircraft energy states. Aircraft accident statistics are replete with examples of aircraft that crossed the runway threshold with excessive energy or maintained insufficient energy to reach the runway. This trend has resulted in aircrews that are trained in conservative energy management that trades efficiency for simplicity. Additionally, traditional aircraft flight displays provide limited aircraft energy state cues that do not enable efficient management of aircraft energy states. In this thesis, a method for generating global optimum flight profiles is demonstrated that yields results that can be utilized by aircraft in flight and provides the associated flight information necessary to fly these profiles. Traditional flight path optimization techniques typically seek to optimize both spatially and temporally, resulting in unacceptable computation times. This method optimizes descent time (based on aircraft energy state and rates of change of energy) while allowing longitudinal spatial variables to be dependent upon the resultant flight profile. The results are optimum descent profiles that aircrew only initiate once the profile's prescribed longitudinal spatial distance is reached. These optimum descent profile solutions significantly reduce time to descend over more traditional approaches while also ensuring that the aircraft retain the highest ground speed by remaining at altitude as long as possible. Additionally, providing aircraft-specific flight path cues that inherently manage the rates at which aircraft energy can be gained or lost significantly enhances safety. Additionally, the optimizer results clearly indicate a general energy flight profile "rule of thumb'* that would allow realistic initial estimated flight profiles to be generated. These profiles could be analytically computed and are sufficiently close to the optimum that they would negate the need for optimization. Utilizing nearly optimal computed profiles as the initial vector provided to the optimizer results in optimum solutions within the first few iterations of optimization. This method is readily adaptable to the Next Generation Air Transportation System (NGATS) environment and compatible with its* goals of expanding capacity and ensuring safety [1]. As representative aircraft would be continually computing their respective optimum flight times, the problem of sequencing aircraft is greatly simplified. The requirement for a common use "official airport winds aloft profile" and for aircraft to communicate their optimum profiles to the host airport would necessitate the use of the "internet in the sky".