A hybrid propulsion unmanned aerial vehicle demand power prediction method

Abstract

The invention discloses a method for forecasting demanded power of a hybrid propulsion unmanned aerial vehicle, comprising: collecting flight state information and flight environment information of the unmanned aerial vehicle, generating a first offline data set; establishing an LVQ neural network model capable of identifying working conditions , train the LVQ neural network model offline; calculate the state transition probability matrix of the three state parameters under the take-off climb, cruise and descent phases; determine the current flight phase of the UAV, and call the corresponding state transition of the flight phase Probability matrix, and according to the UAV's current altitude, flight angle of attack and flight speed three state parameters, predict the state parameters at the next moment; the predicted state parameters at the next moment calculate the flight demand power of the UAV at the next moment . The method of the present invention has strong practicability, and is conducive to promoting the development of energy management strategy technology based on demand power prediction of unmanned aerial vehicles.

Description

technical field [0001] The invention belongs to the technical field of unmanned aerial vehicles, and in particular relates to a method for predicting demanded power of a hybrid propulsion unmanned aerial vehicle. Background technique [0002] In recent years, with the gradual maturity of hybrid technology in the automotive field and the national proposal of the concept of "green aviation", multi-power source hybrid propulsion drones have received more and more attention. However, the hybrid propulsion technology of multiple power sources is still subject to various constraints. Among them, the development of energy management strategies for multiple power sources needs to consider many factors. At present, when formulating energy management strategies for most UAVs, they mostly start from a global perspective based on the flight mission profile. The strategies formulated ignore the influence of uncertain factors such as changing actual flight conditions, and the single ener...

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Problems solved by technology

[0004] Aiming at the deficiencies of the above-mentioned prior art, the purpose of the present invention is to provide a hybrid propulsion unmanned aerial vehicle demand power prediction method to solve the problem that the energy management strategy of the existing unmanned aerial vehicle is difficult to adapt to various flying tools with uncertainty. situation, and the lack of prediction of demand power leads to poor stability, economy and safety of drones

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