Autonomous Power Control Processor for Load Imbalance
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Solution Overview
Problem
Conventional power demand management systems fail to effectively address load imbalances and optimize power distribution across multiple power sources in systems like multi-engine vehicles, leading to undesirable asymmetry and stability issues.
Innovation Solution
A method and apparatus that utilize a power control processor to generate power demand action plans based on operating characteristics and fault conditions, autonomously adjusting power demand constraints and optimizing power distribution between multiple power sources to meet system-level objectives, such as energy efficiency or operational life.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional power demand management systems are used, then system simplicity is maintained, but power distribution efficiency deteriorates leading to load imbalances and thrust asymmetry
Solution Approach 1:
The power demand management system is segmented into multiple independent control processors, each responsible for specific power sources. This allows decentralized autonomous control of each power source while maintaining overall system coordination, improving power distribution efficiency without requiring a monolithic complex control system.
Solution Approach 2:
The control system dynamically adjusts power demand constraints and operating characteristics based on real-time fault conditions and operational objectives. The autonomous control processors continuously optimize power distribution by comparing current operating parameters with pre-stored data, enabling adaptive response to changing conditions while maintaining system simplicity through automated decision-making.
2Duration of action of stationary object
If autonomous control processors are implemented, then operational life is extended through optimized power management, but system complexity increases
Solution Approach 1:
Power demand constraints and operating characteristics are pre-calculated and stored in memory before operation. The autonomous control processors retrieve and apply these pre-determined parameters during operation, eliminating the need for complex real-time calculations while extending operational life through optimized power management.
Solution Approach 2:
The control processors autonomously monitor fault conditions and adjust power distribution without external intervention. Each processor independently compares operating parameters with pre-stored data and self-adjusts power demand constraints, reducing the need for complex centralized control while maximizing operational life through continuous optimization.
3Productivity
If power demand constraints are set as functions of time based on operational objectives, then system performance is optimized, but control complexity increases
Solution Approach 1:
Power demand constraints are defined as time-varying parameters based on operational objectives such as takeoff, cruise, and landing phases. The control processors automatically adjust these parameters according to the current flight phase, optimizing system performance without requiring complex control logic by leveraging pre-defined parameter schedules.
Data Source
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AI summary
A method of determining the power demand on a power subsystem (2) of a system (1) by optimising a respective demand-dependent operating characteristic based on one or more operating conditions affecting the power subsystem, the method comprising: using a system-authority (3, 14) to determine system-level power demand limits on the basis of a system-level objective associated with an operating period; inputting the power demand limits to a separate power control processor (4, 16) configured for regulating the power demand on the power subsystem (2); determining each of said operating conditions; and using the power control processor (4, 16) autonomously to determine the overall power demand on the power subsystem (2) within said system-level limits, based on each of said operating conditions, thereby to optimise said operating characteristic. A method of regulating the power demand during the operating period is also disclosed. The method finds particular application in vehicles, turbomachinery and plant equipment, notably multi-engine aircraft and marine vehicles.