Flight trajectory optimization is being looked as a way of reducing flight costs, fuel burned and emissions generated by the fuel consumption. The objective of this work is to find the optimal trajectory between two points.ududTo find the optimal trajectory, the parameters of weight, cost index, initial coordinates, and meteorological conditions along the route are provided to the algorithm. This algorithm finds the trajectory where the global cost is the most economical. The global cost is a compromise between fuel burned and flight time, this is determined using a cost index that assigns a cost in terms of fuel to the flight time. The optimization is achieved by calculating a candidate optimal cruise trajectory profile from all the combinations available in the aircraft performance database. With this cruise candidate profile, more cruises profiles are calculated taken into account the climb and descend costs. During cruise, step climbs are evaluated to optimize the trajectory. The different trajectories are compared and the most economical one is defined as the optimal vertical navigation profile.ududFrom the optimal vertical navigation profile, different lateral routes are tested. Taking advantage of the meteorological influence, the algorithm looks for the lateral navigation trajectory where the global cost is the most economical. That route is then selected as the optimal lateral navigation profile.ududThe meteorological data was obtained from environment Canada. The new way of obtaining data from the grid from environment Canada proposed in this work resulted in an important computation time reduction compared against other methods such as bilinear interpolation.ududThe algorithm developed here was evaluated in two different aircraft: the Lockheed L-1011 and the Sukhoi Russian regional jet. The algorithm was developed in MATLAB, and the validation was performed using Flight-Sim by Presagis and the FMS CMA-9000 by CMC Electronics – Esterline.ududAt the end of this work a new method of calculating the missed approach fuel burned and its emissions is developed and explained. This calculation was performed using an emissions database and a Visual Basic for applications code in Excel.
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机译:飞行轨迹优化正在被视为降低飞行成本,燃烧的燃油以及燃油消耗产生的排放的一种方式。这项工作的目的是找到两点之间的最佳轨迹。 ud ud为找到最佳轨迹,将沿路线的权重,成本指数,初始坐标和气象条件的参数提供给算法。该算法找到了全局成本最经济的轨迹。全球成本是燃料消耗和飞行时间之间的折衷,这是通过使用成本指数确定的,该成本指数将燃料成本分配给飞行时间。通过从飞机性能数据库中可用的所有组合计算候选最佳巡航轨迹轮廓来实现优化。使用该巡航候选配置文件,可以考虑爬升和下降成本来计算更多的巡航配置文件。在巡航期间,对爬坡进行评估以优化轨迹。比较了不同的轨迹,最经济的轨迹被定义为最佳垂直导航轮廓。 ud ud从最佳垂直导航轮廓中测试了不同的横向路线。该算法利用气象学的影响,寻找横向导航轨迹,其中全球成本最经济。然后选择该路线作为最佳横向导航配置文件。 ud ud气象数据来自加拿大环境。与其他方法(例如双线性插值)相比,这项工作中提出的从加拿大环境中从网格获取数据的新方法大大减少了计算时间。 ud ud在两种不同的飞机上对此处开发的算法进行了评估:洛克希德L- 1011年和苏霍伊俄罗斯支线飞机。该算法是在MATLAB中开发的,验证是使用Presagis的Flight-Sim和CMC Electronics的EMSline的FMS CMA-9000进行的。开发并解释了其排放。使用排放数据库和Visual Basic for Excel中的应用程序代码执行此计算。
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