Aerial vehicle and control method thereof, using hybrid distributed propulsion system

An aerial vehicle, comprising:

• an electric generator;
• a battery configured to be charged with power;
• a plurality of propulsion assemblies, each of the plurality of propulsion assemblies comprising an electric motor and at least one of a fan, a rotor, or a propeller;
• and
• a processor configured to use a neural network, wherein the processor is configured to:
• identify whether a current location of the aerial vehicle corresponds to an urban area or a suburban area, using the neural network;
• based on the current location of the aerial vehicle, determine at least one of the propulsion assemblies for generating flight power of the aerial vehicle,
• in accordance with the determination that the current location of the aerial vehicle corresponds to the urban area, generate flight power using at least one propulsion assembly selected form among the plurality of propulsion assemblies, and
• in accordance with the determination that the current location of the aerial vehicle corresponds to the suburban area, generate flight power using all of the plurality of propulsion assemblies for generating the flight power of the aerial vehicle.

A method of controlling an aerial vehicle, the method comprising:

• identifying whether a current location of the aerial vehicle corresponds to an urban area or a suburban area;
• identifying a flight stage of the aerial vehicle, wherein the flight stage corresponds to one of a take-off stage, an ascending stage, a cruise stage, a descending stage, or a landing stage;
• obtaining, using a neural network, an output based on input data including the current location of the aerial vehicle, the flight stage of the aerial vehicle,
• determining, based on the current location of the aerial vehicle, and the flight stage,
• in accordance with a determination that the current location of the aerial vehicle corresponds to the urban area, selecting, based on the output of the neural network, one or more propulsion assemblies from among the plurality of propulsion assemblies for generating flight power of the aerial vehicle;
• in accordance with a determination that the current location of the aerial vehicle corresponds to the suburban area and the flight stage corresponds to the cruise stage, selecting, based on the output of the neural network, all of the plurality of propulsion assemblies for generating the flight power of the aerial vehicle;
• obtaining, based on the output of the neural network, information for controlling rotational speeds of at least one of fans, rotors, or propellers included in the selected one or more propulsion assemblies or all of the plurality of propulsion assemblies;
• and
• generating the flight power by controlling the rotational speeds based on the information.