Vehicle Interior Acoustic Calculation Using Dynamic Seat Occupancy
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Solution Overview
Problem
Current methods for calculating the acoustic behavior of a vehicle interior are based on static geometric models, failing to accurately account for dynamic changes caused by occupants, leading to suboptimal active noise reduction and speech recognition performance.
Innovation Solution
A method that calculates acoustic behavior using situational acoustic parameters selected based on actual seat occupancy, incorporating data from seat occupancy sensors, weight, pressure distribution, and driving conditions, to create a more realistic volume model for the acoustic algorithm, enhancing the accuracy of noise reduction and speech recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a static geometric interior model is used for acoustic calculations, then the calculation is simple and fast, but the accuracy of acoustic behavior prediction is poor due to inability to account for dynamic occupancy changes
Solution Approach 1:
The patent transitions from a static geometric interior model to a dynamic model that incorporates real-time seat occupancy data. The acoustic calculation model now adapts to changing occupancy conditions by selecting appropriate acoustic parameters based on detected occupancy status, enabling accurate prediction of acoustic behavior under varying conditions while maintaining computational efficiency.
Solution Approach 2:
The patent employs different acoustic parameters for different occupancy scenarios. An acoustic parameter database stores multiple parameter sets corresponding to different occupancy configurations. The system selects the appropriate parameter set based on real-time occupancy detection, allowing accurate acoustic prediction without requiring a completely complex model for every possible scenario.
2Measurement precision
If seat occupancy sensors and dynamic occupancy data are incorporated into acoustic calculations, then the accuracy of acoustic behavior model is improved, but the system complexity and data processing requirements increase
Solution Approach 1:
The patent leverages existing seat occupancy sensors originally designed for safety warning functions to also serve acoustic calculation purposes. This multi-functional approach avoids adding dedicated acoustic sensors while still achieving accurate occupancy-based acoustic modeling, thereby reducing overall system complexity.
Solution Approach 2:
The system performs preliminary occupancy detection using seat sensors before conducting acoustic calculations. By pre-determining occupancy status and selecting appropriate acoustic parameters in advance, the system simplifies the main acoustic calculation process and reduces real-time computational burden.
3Measurement precision
If an average passenger model is used for unoccupied seats, then the calculation remains simple, but the accuracy of acoustic prediction deteriorates due to inability to represent actual occupancy variations
Solution Approach 1:
The patent applies different acoustic models to different seat positions based on actual occupancy detection. Instead of using a uniform average passenger model for all seats, the system selectively applies occupancy-specific acoustic parameters only to seats that are actually occupied, while maintaining simpler models for unoccupied seats. This localized approach improves accuracy where needed without unnecessarily increasing overall system complexity.
Data Source
AI summary
The invention relates to a method for the situative calculation of the acoustic method of a vehicle interior, said method involving a calculation of the acoustic method of the vehicle interior (F) by means of an acoustic algorithm (A) into which situative acoustic parameters (AP) flow, said parameters being selected on the basis of an actual seat occupation (B(Sn)) in the vehicle interior (F).