Aircraft Economic Usage Optimization System
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Solution Overview
Problem
Rotorcraft operators face challenges in optimizing aircraft operations to reduce fuel consumption, maintenance costs, and component wear due to limited analytical capabilities and lack of experience, especially for small operators.
Innovation Solution
A system and method that utilizes sensors and an optimization algorithm to analyze vehicle performance characteristics, provide real-time feedback to pilots, and suggest changes in flight operations to improve economic efficiency, including reducing wear and downtime by optimizing flight parameters such as airspeed, altitude, and rotor speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If operators perform rudimentary analysis of flight operations to reduce fuel consumption, then fuel efficiency may be improved, but the process is time-consuming and requires significant human capital and experience
Solution Approach 1:
The system enables self-service by automatically collecting flight data from sensors, processing it through algorithms, and generating optimization recommendations without requiring external human analysis. The aircraft system serves itself by autonomously monitoring its own performance parameters and providing actionable insights to pilots.
Solution Approach 2:
The patent replaces manual mechanical analysis methods with automated electronic data processing. Instead of operators manually reviewing flight records and making adjustments, the system uses computers to automatically collect, analyze, and process flight data, substituting human analytical effort with automated computational systems.
2Reliability
If operators analyze historical operational data to estimate maintenance costs and component wear, then approximate maintenance planning is possible, but the process is very time-consuming and small operators lack the required experience and human capital
Solution Approach 1:
The system implements continuous feedback by monitoring current flight parameters in real-time and comparing them against optimal ranges. This feedback loop provides ongoing information about component wear and maintenance needs, allowing operators to make timely decisions without lengthy historical analysis. The system continuously feeds back performance data to guide operational adjustments.
Solution Approach 2:
The system performs preliminary analysis by continuously monitoring and evaluating flight data in advance of maintenance needs. It identifies potential issues and recommends preventive actions before components actually fail or require maintenance, allowing operators to plan ahead without time-consuming reactive analysis.
3Productivity
If pilots fly without real-time optimization guidance, then operational simplicity is maintained, but fuel efficiency and component life extension are not optimized
Solution Approach 1:
The system acts as an intermediary between the pilot and the aircraft systems. It processes complex data from multiple sensors and translates it into simple, actionable recommendations that the pilot can easily understand and implement. The intermediary system handles the complexity of data analysis while presenting simplified guidance to the operator.
Solution Approach 2:
The system optimizes economic efficiency by recommending changes in flight parameters such as airspeed, altitude, and rotor speed. These parameter adjustments are designed to improve fuel efficiency and extend component life while remaining within normal operational ranges that pilots are already familiar with, maintaining ease of operation.
Data Source
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AI summary
A method of optimizing the economic operation of an aircraft is described. The method comprises the steps of: inputting an input data to a usage optimization algorithm; processing the input data in the usage optimization algorithm; and cueing the pilot to make a change in the operation of the aircraft for purposes of improving the economic operation of the aircraft.