Distributed Thrust Allocation for eVTOL Motor-Out Descent Control
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Solution Overview
Problem
Electric vertical take-off and landing (eVTOL) multicopters lack the ability to glide in emergency situations due to the absence of wings, posing safety concerns, particularly in the event of a motor failure, as they rely entirely on rotors for flight and cannot perform controlled landings without additional, heavier components.
Innovation Solution
A distributed flight control system that uses optimization problems with a single solution to generate thrust values for each motor, allowing for safer and more controlled emergency landings by allocating thrust in a manner that compensates for motor outages, utilizing a strictly convex optimization problem to ensure all flight controllers produce identical thrust values, thereby maintaining vehicle stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If eVTOL multicopters use rotor-based flight without wings, then they can achieve vertical take-off and landing capability, but they cannot glide or perform controlled landings in emergency situations
Solution Approach 1:
The control system is divided into multiple independent flight controllers, each capable of independently calculating thrust values for all motors using optimization algorithms. This segmentation allows the system to maintain functionality even when individual controllers or motors fail, enabling controlled landings without requiring additional heavy components like wings
Solution Approach 2:
The system dynamically changes operational parameters by using optimization algorithms to adjust thrust values for each motor based on real-time conditions. This allows the multicopter to adapt to motor failures and perform controlled landings by redistributing thrust among remaining functional motors, compensating for the lack of gliding capability
2Adaptability or versatility
If a distributed flight control system uses optimization problems with multiple solutions, then flexibility in thrust allocation is improved, but vehicle stability deteriorates due to inconsistent thrust values from different flight controllers
Solution Approach 1:
The system pre-defines optimization criteria and constraints that ensure a single optimal solution. By establishing the optimization problem structure in advance with proper objective functions and constraints, the system guarantees that all flight controllers will converge to the same thrust allocation, maintaining vehicle stability while preserving flexibility
Solution Approach 2:
The system uses feedback mechanisms where each flight controller independently calculates thrust values based on the same optimization problem and compares results with other controllers. This feedback loop ensures consistency across the distributed system, allowing flexible thrust allocation while maintaining vehicle stability through verification and coordination
Data Source
AI summary
Thrust values for motors in an aircraft are generated where each flight controller in a plurality of flight controllers generates a thrust value for each motor in a plurality of motors using an optimization problem with a single solution. Each flight controller in the plurality of flight controllers passes one of the generated thrust values to a corresponding motor in the plurality of motors, where other generated thrust values for that flight controller terminate at that flight controller. The plurality of motors perform the passed thrust values.