Dynamic Active Noise Cancellation for Urban Air Mobility
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Solution Overview
Problem
Current noise reduction methods for urban air mobility and similar noise-generating platforms, such as flying taxis and high-speed trains, are ineffective in free space environments and fail to adapt to the dynamic movement of these vehicles, limiting their noise cancellation capabilities.
Innovation Solution
A method and system that utilize telemetry data from noise generation platforms to generate counterwave sound data, processed through a communication infrastructure and active noise cancellation devices, to reduce noise in urban environments by considering motion-related data, noise data, and environmental factors, allowing for dynamic noise cancellation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If current noise reduction methods are used for flying taxis, then noise disturbance is reduced at lower frequencies, but the methods fail to work effectively in free space environments and cannot adapt to dynamic movement of vehicles
Solution Approach 1:
The system dynamically adapts to the moving noise source by continuously receiving telemetry data (position, speed, rotor speed) and updating the counterwave generation in real-time. The noise cancellation system transitions from a static to a dynamic approach, where the counterwave parameters are continuously adjusted based on the current state of the flying taxi, enabling effective noise cancellation during dynamic flight phases.
Solution Approach 2:
The system implements feedback by utilizing telemetry data from the flying taxi (position, speed, rotor speed) to continuously inform and adjust the counterwave generation process. This closed-loop approach allows the noise cancellation system to respond to changes in the noise source characteristics and maintain effectiveness as the vehicle moves through different flight phases.
2Object-affected harmful factors
If additional telemetry data processing is implemented, then noise cancellation effectiveness is improved, but system complexity increases
Solution Approach 1:
The system segments the noise cancellation functionality into distinct modular components: telemetry data acquisition module, data processing module, counterwave generation module, and actuation module. This segmentation allows each component to be optimized independently and facilitates easier maintenance and scaling of the system while managing overall complexity.
Solution Approach 2:
The patent introduces a communication infrastructure as an intermediary that bridges the flying taxi and the ground-based noise cancellation system. This intermediary handles data transmission and coordination, allowing the complex telemetry processing to be performed remotely on the ground while keeping the vehicle itself relatively simple.
3Object-affected harmful factors
If counterwave generation is performed in real-time, then noise cancellation is effective, but processing time constraints limit performance at higher frequencies
Solution Approach 1:
The system performs preliminary actions by pre-processing and analyzing telemetry data to predict the noise source characteristics before the actual noise generation occurs. By anticipating the noise patterns based on rotor speed and position data, the system can prepare counterwave parameters in advance, reducing the critical processing time during the actual noise cancellation phase.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach effectively reduces noise disturbance in urban environments, enabling wider acceptance of flying taxis, potential operation during restricted times, and reducing energy consumption by allowing vehicles to fly at lower altitudes, while also applying to other movable noise sources like high-speed trains.
Implementation Method 1
outputting the counterwave sound data as sound waves, so as to reduce the noise emanating from the noise generation platform
Data Source
AI summary
An active noise cancellation method and system in which the noise generation platform records noise data with an array of microphones and sends that noise data to a noise cancellation processing system. The noise data is converted to counterwave sound data that are again converted by stationary loudspeaker arrays into sound counterwaves with the potential to eliminate or at least reduce the noise from the noise generation platform. The noise generation platform may be an aerial vehicle or a ground vehicle, such as a high-speed train.