US 12,709,421 B1Granted

CBR-based energy management framework for hybrid UAVs based on state extraction

AssigneeKing Fahd University of Petroleum and Minerals

InventorsMohammad Nayel Alzyod, Ali Taleb Al-Awami, Haitham Hassan Saleh

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Abstract

An apparatus for managing energy in an unmanned aerial vehicle (UAV) including a hybrid powertrain that is configured to provide electric power to onboard power-consuming units coupled to a DC bus and includes a fuel cell coupled through a boost converter, a battery coupled through a bidirectional converter, and a supercapacitor directly coupled to the DC bus. The apparatus includes processing circuitry configured to optimize weighting factors of an equivalent consumption minimization (ECM) model for multiple load profile scenarios, extract a state variable dataset including state variables and fuel cell power reference values, and generate a representative dataset through data reduction. Based on real-time state measurements, the processing circuitry identifies historical cases from the representative dataset and allocates power among the fuel cell, battery, and supercapacitor.

Claims20

Dependent claims

A method for managing energy in an unmanned aerial vehicle (UAV), the UAV including a hybrid powertrain configured to provide electric power to onboard power-consuming units coupled to a DC bus, the hybrid powertrain comprising a fuel cell coupled to the DC bus through a boost converter, a battery coupled to the DC bus through a bidirectional converter, and a supercapacitor directly coupled to the DC bus, the method comprising:

for each of a plurality of load profile scenarios, optimizing a weighting factor of an equivalent consumption minimization (ECM) model;
extracting a state variable dataset based on the plurality of load profile scenarios and the optimized weighting factors, each entry of the state variable dataset corresponding to a time instance and including a plurality of state variables and an associated fuel cell power reference value;
generating a representative dataset of cases by applying data reduction to the state variable dataset;
and
performing real-time energy management of the hybrid powertrain by identifying, based on real-time state measurements of the UAV, a plurality of historical cases from the representative dataset and allocating power among the fuel cell, the battery, and the supercapacitor based on the identified plurality of historical cases.

2 more elements

An apparatus for managing energy in an unmanned aerial vehicle (UAV), the UAV including a hybrid powertrain configured to provide electric power to onboard power-consuming units coupled to a DC bus, the hybrid powertrain comprising a fuel cell coupled to the DC bus through a boost converter, a battery coupled to the DC bus through a bidirectional converter, and a supercapacitor directly coupled to the DC bus, the apparatus comprising:

processing circuitry configured to
for each of a plurality of load profile scenarios, optimize a weighting factor of an equivalent consumption minimization (ECM) model,
extract a state variable dataset based on the plurality of load profile scenarios and the optimized weighting factors, each entry of the state variable dataset corresponding to a time instance and including a plurality of state variables and an associated fuel cell power reference value,
generate a representative dataset of cases by applying data reduction to the state variable dataset, and
perform real-time energy management of the hybrid powertrain by identifying, based on real-time state measurements of the UAV, a plurality of historical cases from the representative dataset and allocating power among the fuel cell, the battery, and the supercapacitor based on the identified plurality of historical cases.

2 more elements

Dependencies are inferred from the claim text.