Brake Squeal Prediction and Active Cancellation Under Wear
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Solution Overview
Problem
Existing vehicles face the challenge of unpredictable squeal noise generation in braking systems due to changes in friction coefficients and vibration characteristics over time, which are not adequately addressed during vehicle development, leading to user discomfort.
Innovation Solution
An apparatus and method that utilize a squeal noise prediction model to identify vehicle state data, predict squeal noise occurrence, and output targeted noise cancellation based on probability, frequency, amplitude, and user perception to reduce squeal noise effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a vehicle is designed to prevent squeal noise at the development stage, then initial noise performance is improved, but noise may be generated after wear occurs on disks and pads over time
Solution Approach 1:
The patent implements a dynamic noise cancellation system that continuously monitors vehicle state data (brake pad wear, disk condition, temperature, humidity) and adjusts noise cancellation parameters in real-time. This allows the system to adapt to changing friction characteristics and vibration modes as components wear, maintaining effective squeal noise suppression throughout the service life of braking components
Solution Approach 2:
The system employs feedback mechanisms by monitoring vehicle state data and comparing predicted squeal noise with actual noise levels. The noise cancellation parameters are continuously adjusted based on this feedback loop, enabling the system to respond to wear-induced changes in braking device dynamics and maintain optimal noise suppression performance
2Object-affected harmful factors
If noise cancellation is provided for all frequency ranges, then comprehensive noise reduction is achieved, but energy consumption increases
Solution Approach 1:
The patent applies local quality by targeting noise cancellation specifically at the identified squeal noise frequency range (1-16 kHz) rather than across all frequencies. The system generates anti-phase noise signals localized to the problematic frequency bands, reducing energy consumption while maintaining effective squeal noise suppression where it is most needed
Solution Approach 2:
The system dynamically changes noise cancellation parameters (amplitude, frequency, phase) based on real-time vehicle state data and predicted squeal characteristics. By adjusting these parameters to match the actual squeal noise profile, the system minimizes energy consumption while maximizing noise reduction effectiveness
3Measurement precision
If complex vehicle state data analysis is performed to predict squeal noise, then prediction accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent implements preliminary action by pre-processing and storing vehicle state data (brake pad wear, disk condition, temperature, humidity) and pre-calculating friction coefficient changes based on wear patterns. This preparation work is done before squeal noise occurs, allowing the system to quickly and accurately predict squeal noise without requiring complex real-time calculations, thus improving prediction accuracy while managing computational complexity
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 solution provides precise prediction and reduction of squeal noise, enhancing user satisfaction by adapting noise cancellation strategies based on vehicle state data and occupant locations, thereby improving driving experience.
Implementation Method 1
outputting noise having a phase inverted against the squeal noise through the noise actuator
Data Source
AI summary
In an apparatus for predicting squeal noise and a method of controlling the same. The apparatus includes a processor which may identify first input data extracted from a braking device of a vehicle, second input data corresponding to a vehicle wheel, third input data measured from an external sensor, or a combination thereof, obtain first output data on a probability that the squeal noise may be generated in the braking device, second output data on a frequency of the squeal noise, and third output data on an amplitude of the squeal noise by applying the data to a squeal noise prediction model, and output target noise and, by use of the target noise, cancels out the squeal noise that corresponds to the second output data and the third output data and is generated from the braking device based on the squeal noise expected to be generated from the braking device through the first output data.