Vehicle Sensor Calibration for Active Road Noise Control
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Solution Overview
Problem
The placement of reference sensors for active road noise control in vehicles is challenging due to varying structural designs, leading to costly and time-consuming optimization processes, and existing methods like Principal Component Analysis are not computationally efficient for real-time implementation.
Innovation Solution
An automatic calibration system that mounts vibrational sensors on key structure elements and a microphone in the cabin to determine the optimal arrangement of reference sensors by calculating multiple-coherence functions, reducing the number of sensors needed and enhancing computational efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a high number of reference sensors are mounted on structure elements to improve road noise control performance, then the noise cancellation effectiveness is improved, but the device complexity and cost increase
Solution Approach 1:
The patent extracts and eliminates redundant reference sensors from the system by using calibration data to identify which sensors provide unique information. The calibration process determines a reduced set of reference sensors that maintain effective road noise control while removing unnecessary sensors, directly resolving the contradiction between performance and complexity.
Solution Approach 2:
The patent initially uses a high number of reference sensors (excessive action) during the calibration phase to comprehensively capture all vibration sources and transfer paths. This excessive sampling enables the system to identify and eliminate redundancies, resulting in an optimized reduced set for production that maintains performance with lower complexity.
2Measurement precision
If extensive simulations and mathematical optimization algorithms are performed to determine optimal sensor locations, then the sensor placement accuracy is improved, but the time and computational cost increase
Solution Approach 1:
The patent performs comprehensive calibration and optimization actions in advance during the vehicle development phase. By conducting the extensive measurements, simulations, and mathematical optimization beforehand, the system determines the optimal reduced set of reference sensor locations before production. This preliminary action eliminates the need for time-consuming optimization during real-time operation or later stages.
Solution Approach 2:
The calibration system uses the vehicle's own structure and available measurement infrastructure to perform self-calibration. By utilizing the vehicle's existing vibration sources (engine, road input) and measurement capabilities, the system determines optimal sensor locations without requiring external test equipment or extensive additional simulations, reducing both time and computational resources.
3Reliability
If Principal Component Analysis is applied to decorrelate reference signals, then the signal independence is improved, but the computational cost becomes too high for real-time implementation
Solution Approach 1:
The patent extracts and removes redundant information from the reference signals during the offline calibration phase. By analyzing the coherence between candidate reference sensors and the error microphone signal, the system identifies and eliminates sensors that provide correlated information. This extraction of redundancy before production results in a reduced sensor set with inherently decorrelated signals, eliminating the need for computationally intensive PCA during real-time operation.
4Object-affected harmful factors
If specifically optimized shapes and materials are used for structure elements to attenuate vibrations, then the road noise attenuation is improved, but the vehicle mass and design constraints increase
Solution Approach 1:
The patent replaces passive mechanical noise control (optimized shapes and materials) with active noise control using sensors and actuators. Instead of adding mass through structural modifications, the system uses a reduced set of reference sensors to capture vibrations and employs active control algorithms to generate anti-noise signals, achieving road noise attenuation without increasing vehicle mass or imposing design constraints on structural elements.
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 method allows for a computationally inexpensive and efficient determination of the optimal sensor arrangement, reducing the number of reference sensors required and enabling real-time active road noise control, thereby improving passenger comfort without significant design or mass constraints.
Implementation Method 1
mounting a plurality of vibrational sensors of the calibration system on a plurality of structure elements of the vehicle... and the vibrational sensors being configured to generate a plurality of vibrational input signals based on vibrations of the respective structure elements
Implementation Method 2
mounting at least one microphone of the calibration system inside the cabin of the vehicle, the at least one microphone being configured to capture at least one acoustic input signal
Data Source
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AI summary
The present disclosure provides a method for determining an arrangement of reference sensors for active road noise control (ARNC) in a vehicle by means of an automatic calibration system, wherein the method comprises: mounting a plurality of vibrational sensors on a plurality of structure elements of the vehicle to generate a plurality of vibrational input signals; mounting at least one microphone inside a cabin of the vehicle to capture at least one acoustic input signal; and determining the arrangement of reference sensors from the plurality of vibrational sensors by determining a subset of vibrational sensors which sense the main mechanical inputs of road noise contributing to the at least one acoustic input signal.