Hybrid Capacitive Weight Sensor for Occupant Classification
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Solution Overview
Problem
Existing occupant classification systems in vehicles often inaccurately detect objects such as water bottles, groceries, or children in child restraint seats, leading to false alerts and incorrect airbag deployment, due to reliance on single sensing methods like capacitance or weight alone.
Innovation Solution
A hybrid occupant classification system using both capacitive sensors to measure capacitance and pressure or weight sensors, which differentiates between occupants and objects by comparing measured values against predetermined thresholds, enabling accurate classification and adjusting vehicle systems accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single sensing method (capacitance or weight) is used for occupant detection, then the device complexity is reduced, but the measurement precision and reliability deteriorate due to false detection of objects as occupants
Solution Approach 1:
The patent combines multiple sensing methods (capacitive sensing and weight/pressure sensing) into a unified occupant classification system. The controller integrates signals from both sensor types to distinguish between actual occupants and objects, thereby improving detection accuracy without requiring a single overly complex sensor
2Reliability
If capacitance sensing alone is used, then the device complexity is low, but the reliability deteriorates when objects like water bottles or groceries are detected as occupants
Solution Approach 1:
The patent introduces an intermediary comparison mechanism where the controller evaluates both capacitance values and weight/pressure measurements against predetermined thresholds. This intermediary step allows the system to cross-validate sensor readings and reliably distinguish between occupants and objects before triggering safety system responses
3Measurement precision
If weight or pressure sensing alone is used, then the device complexity is reduced, but the measurement precision deteriorates in distinguishing between small occupants and large objects
Solution Approach 1:
The patent utilizes parameter changes by comparing multiple physical parameters (capacitance and weight/pressure) simultaneously. The controller adjusts its classification logic based on the combination of these parameters, enabling precise differentiation between small occupants and large objects through multi-parameter analysis rather than relying on a single threshold
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 reduces false alerts and improves accuracy in distinguishing between occupants and objects, ensuring correct airbag deployment and seatbelt reminders, thereby enhancing safety and reliability.
Implementation Method 1
a capacitive sensor configured to measure capacitance
Implementation Method 2
A sensor is configured to measure at least one of weight and pressure on the seat
Data Source
AI summary
An occupant classification system comprises a capacitive sensor configured to measure capacitance. The capacitive sensor is at least partially arranged between a seat frame and at least one of a seat cover and a seat cushion of a seat. A sensor is configured to measure at least one of weight and pressure on the seat. The sensor is at least partially arranged between a vehicle structure and a component of the seat. A controller is configured to generate an occupant classification based on the measured capacitance and the at least one of the measured weight and the measured pressure on the seat.