Vehicle Noise Cancellation with Adaptive Secondary Path Models
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Solution Overview
Problem
Existing noise canceling systems in vehicles struggle to efficiently adapt to varying conditions such as temperature, humidity, and occupant presence, leading to potential noise boosting and instability in noise cancellation.
Innovation Solution
A vehicle noise canceling system that includes sensors for collecting data on environmental conditions and occupant presence, a controller for selecting an optimal secondary path model from pre-stored models based on this data, and a speaker for outputting anti-noise sound, with adaptive filters to correct for errors and maintain effective noise cancellation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed secondary path model is used in existing noise canceling systems, then the system structure remains simple, but the system cannot adapt to varying environmental conditions such as temperature, humidity, and occupant presence, leading to noise boosting and instability
Solution Approach 1:
The patent implements dynamic adaptation by switching between multiple pre-stored secondary path models based on real-time sensor data. The controller dynamically selects the most appropriate model according to current environmental conditions (temperature, humidity, occupant presence), transforming the static system into a dynamic one that adapts to changing conditions without requiring complex real-time model generation
Solution Approach 2:
The patent applies preliminary action by pre-storing multiple secondary path models corresponding to different environmental conditions before operation. Instead of generating models in real-time during operation, the system prepares multiple models in advance and simply selects from them based on sensor readings, reducing computational complexity while maintaining adaptability
2Reliability
If the secondary path model does not match current conditions, then the system maintains simple operation, but noise cancellation becomes unstable and may cause noise boosting
Solution Approach 1:
The patent implements feedback by continuously monitoring environmental conditions through sensors (temperature, humidity, occupant detection) and using this information to select the appropriate secondary path model. The system compares current sensor readings with pre-defined conditions for each model and automatically switches models to match current conditions, ensuring reliable noise cancellation without manual intervention
Solution Approach 2:
The system applies self-service by automatically selecting and switching between secondary path models based on sensor data without requiring external control or manual adjustment. The controller autonomously determines which model best matches current environmental conditions and applies it, making the system self-adjusting and reliable
3Adaptability or versatility
If multiple secondary path models are pre-stored for different conditions, then the system can adapt to various environments, but the memory requirement and model management complexity increase
Solution Approach 1:
The patent applies parameter changes by organizing multiple secondary path models according to key environmental parameters (temperature ranges, humidity levels, occupant configurations). Each model corresponds to specific parameter ranges, allowing the system to efficiently select appropriate models based on sensor readings without storing excessive redundant models
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
The system ensures stable and efficient noise cancellation by promptly adapting to changing conditions, preventing noise boosting and maintaining a comfortable environment for vehicle occupants.
Implementation Method 1
noise canceling (NC) is a technology that blocks unwanted sound by generating destructive interference that cancels out noise sounds
Data Source
AI summary
A noise cancelling system for a vehicle includes a microphone, at least one first sensor configured to collect first data related to an element that generates a noise sound, at least one second sensor configured to collect second data related to an element that changes a secondary path of the noise sound, a controller configured to select a secondary path model corresponding to the second data from among a plurality of pre-stored secondary path models, input the first data to a secondary path filter corresponding to the selected secondary path model, and generate an anti-noise signal based on output data of the secondary path filter and error data received from the microphone, and a speaker configured to output an anti-noise sound based on the anti-noise signal.