Vehicle Seat Load Limiter Configuration via Multidimensional Model
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Solution Overview
Problem
Vehicles' restraint systems face challenges in accommodating passengers of varying sizes and ages, as the load on the restraint system differs significantly, affecting both the occupant's safety and the system's performance, particularly in second-row seats where requirements for occupant protection can lead to unwanted results like head contact with the front seat or higher chest loads.
Innovation Solution
A multidimensional load limiter system that self-adjusts based on real-time data from sensors, optimizing the load limiting value for seat belt payout to balance body impact and restraint interaction, using a control algorithm that considers occupant classification, seat positions, and available space, thereby reducing chest loads and preventing head contact.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the restraint system is designed to accommodate larger occupants, then the load on the restraint system increases, but the impact force on smaller occupants becomes excessive
Solution Approach 1:
The restraint control module dynamically adjusts the load limiter setting value in real-time based on sensed parameters (seat position, occupant weight, vehicle speed) to optimize restraint performance for each specific situation, preventing excessive impact forces on smaller occupants while maintaining adequate restraint for larger occupants
Solution Approach 2:
The system changes the load limiter parameter (setting value) based on multiple input parameters including seat position, occupant weight classification, and vehicle speed, allowing the restraint system to adapt its characteristics to match different occupant sizes and crash scenarios
2Device complexity
If a fixed load limiter setting is used, then system complexity is reduced, but performance varies suboptimally across different crash scenarios
Solution Approach 1:
The restraint system automatically senses relevant parameters (seat position, occupant weight, vehicle speed) and self-adjusts the load limiter setting value without requiring manual intervention, optimizing performance for each crash scenario while maintaining simple operation for the user
Solution Approach 2:
The system transitions from a fixed, static configuration to a dynamic, adaptive configuration that automatically adjusts the load limiter setting value based on real-time sensing of crash conditions, occupant characteristics, and seat position
Data Source
AI summary
A vehicle seat restraint system includes a control system and a second-row restraint system. The control system receives a first-row seat value and a second-row seat value from seat sensors. The control system generates relative position data for a first-row seat and a second-row seat based upon the first-row seat value and the second-row seat value. The control system selects a load limiter setting value using a multidimensional load limiter model based upon body impact values as a function of load limiter setting values and the relative position data, a selected load limiter setting value outside a value avoidance zone for the body impact values. The second-row restraint system is configured by the control system with the selected load limiter setting value. The control system may also determine an occupant weight value and select the load limiter setting value using the occupant weight value.