Endurance performance optimization method integrating climb, cruise and descending

Abstract

The present invention provides an endurance performance optimization method integrating climb, cruise and descending. The method comprises the following steps of selecting an optimal endurance cruisestrategy through cruise performance analysis under a single weight; integrally optimizing climb and level flight performance data of a climb interval in order to obtain an optimal endurance climb strategy; respectively accumulating oil consumption of the climb interval and a descending interval in order to obtain oil consumption of a climb section and a descending section, carrying out front-backsqueeze, computing the oil quantity of a cruise section, dividing different oil volume intervals, and carrying out endurance optimization of the whole cruise section in order to obtain endurance of the optimal cruise strategy; respectively accumulating the endurance of the climb interval and the descending interval in order to obtain the endurance of the whole climb section and the descending section; and piecewise accumulating the endurance of the climb section, the cruise section and the descending section in order to obtain the optimal endurance of the whole flight profile.

Description

technical field [0001] The present invention relates to the field of aviation technology, especially the technical field of flight time allocation planning Background technique [0002] At present, the biggest function of drones in the military field is reconnaissance, and the premise of reconnaissance is ultra-high flight time performance, that is, the ability to stand by in the air. A typical airtime flight profile includes three main mission segments: climb, cruise, and descent. Among them, cruising is divided into cruising segments with different weights. In order to achieve ultra-long voyage performance indicators, researchers have conducted comprehensive and in-depth research. For example, Zhang Yunfei proposed to adopt the flight strategy of changing attitude and speed when cruising at the same altitude to achieve the maximum flight time (Zhang Yunfei, Luo Xun, Xiang Jinwu, etc. Calculation of flight range and flight time of propeller aircraft at constant altitude[J...

AI Technical Summary

Problems solved by technology

However, the flight time of climbing, cruising and descending is not a small amount in the flight profile of the optimal flight time. If we only pursue the optimization of a single task segment, it will inevitably lead to local optimum, and cause shortcomings and deficiencies in other stages.

At the same time, the cruising segment occupies the vast majority of the entire voyage flight profile. If you choose the same speed for cruising, it is easy to fall into local optimization.

Therefore, considering only single or non-integral multiple mission segments is not enough to obtain optimal airtime performance

Images