Vehicle Seat Occupant Detection Using Multi-Frequency Interference Rejection
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Solution Overview
Problem
Occupant detection systems in vehicles face interference from environmental conditions like humidity and moisture, leading to inaccurate readings, particularly in distinguishing between adults and children or inanimate objects, which can result in inappropriate airbag deployment.
Innovation Solution
A control system with a sensing device and electronic device that acquires data across multiple frequencies, compares system response data sets over time to create delta sets, and uses heuristic filtering to reject anomalous data, thereby distinguishing between transient and sustained electrical interference and adapting to minimize errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If environmental conditions like humidity and moisture are present, then the occupant detection system may produce inaccurate readings, but adding filtering circuitry to protect the electronic system can still allow non-damaging electrical interference to pass through and introduce errors
Solution Approach 1:
The patent segments the frequency spectrum into multiple discrete frequency bands for analysis. By dividing the signal processing into multiple frequency components, the system can identify and reject interference affecting specific bands while maintaining accuracy in unaffected bands, thereby resolving the contradiction between reliability and environmental sensitivity.
Solution Approach 2:
The system implements feedback by continuously monitoring signal characteristics across multiple frequencies and using this information to dynamically adjust the detection process. The comparison of system response data sets over time creates a feedback mechanism that identifies and corrects for environmental interference, improving reliability without requiring additional protective circuitry.
2Measurement precision
If additional filtering circuitry is added to reduce electrical interference errors, then the electronic system is better protected, but the additional circuitry can introduce other errors which may be equally undesirable
Solution Approach 1:
The patent replaces physical filtering circuitry with a digital signal processing approach. Instead of using additional analog filtering components that would increase device complexity and potentially introduce new errors, the system uses software-based frequency analysis and comparison algorithms to achieve the same interference rejection, thereby maintaining measurement precision while reducing device complexity.
3Reliability
If digital filtering is used on the electrical signal from the sensing device, then transient electrical interference is reduced, but long duration electrical interference cannot be detected
Solution Approach 1:
The system performs preliminary action by acquiring and storing multiple system response data sets over time before making a detection decision. This pre-acquisition of temporal data enables the system to detect long-duration interference patterns that single-point digital filtering would miss, while still maintaining the ability to reject transient interference through the multi-frequency analysis.
Solution Approach 2:
The patent implements continuous monitoring by repeatedly acquiring system response data sets across multiple frequencies over extended periods. This continuous action allows the system to detect both transient and long-duration interference, resolving the contradiction between handling different interference durations that limited digital filtering approaches cannot address.
Data Source
AI summary
An occupant system includes a sensing device disposed in a seat and an electronic device configured to acquire data from the sensing device. The electronic device includes a system controller which uses that data to determine an appropriate system response. Data is acquired in at least two different system configurations and in at least two different time periods. A data set is created which represents a comparison of data acquired in the different configurations and times. The elements of this data set are compared to each other to identify anomalous data and respond accordingly.