Crash Configuration Simulation for Pre-Crash Occupant Position Transfer
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Solution Overview
Problem
Current methods for assessing vehicle safety performance lack the detail needed to describe subtle changes in crash configurations, particularly in collision avoidance and injury prevention systems, and are computationally intensive, making it difficult to simulate pre-crash maneuvers effectively.
Innovation Solution
A computer-aided engineering (CAE) methodology that uses real-world data to simulate impact events, incorporating a simplified occupant kinetics model and structural simulations to predict the combined effect of collision avoidance and injury prevention features, filtering out cases with significant pre-crash position excursions for further analysis with detailed human body models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detailed human body models are used to simulate pre-crash maneuvers, then prediction accuracy of occupant position transfer is improved, but computational time and resources increase significantly
Solution Approach 1:
The simulation process is divided into two distinct stages: a pre-crash phase using simplified occupant models to filter and prepare cases, and a crash phase using detailed human body models for accurate injury prediction. This segmentation allows computational resources to be allocated efficiently, with simplified models handling the computationally intensive pre-crash analysis and detailed models focused only on critical crash scenarios.
Solution Approach 2:
Simplified occupant models are used in advance to perform preliminary simulations of pre-crash maneuvers, identifying and filtering cases that require detailed analysis. This preliminary action reduces the number of cases that need to be processed with computationally intensive detailed human body models, thereby reducing overall computational time while maintaining accuracy for critical cases.
2Measurement precision
If comprehensive crash configuration data is collected and simulated, then the detail and accuracy of crash outcome prediction is improved, but the complexity of the simulation system increases
Solution Approach 1:
The simulation system is segmented into modular components: simplified occupant models for pre-crash analysis, detailed human body models for crash analysis, and a case management system that coordinates between them. This modular segmentation allows each component to be optimized independently while maintaining overall system accuracy.
Solution Approach 2:
A case management system acts as an intermediary between simplified and detailed models, filtering and selecting cases that require detailed analysis based on pre-crash simulation results. This intermediary reduces the complexity burden by preventing unnecessary detailed simulations while ensuring all critical cases are analyzed with appropriate detail.
3Productivity
If simplified occupant models are used for pre-crash simulation, then computational efficiency is improved, but the ability to capture subtle changes in crash configuration is reduced
Solution Approach 1:
The method extracts and separates the pre-crash analysis function from the detailed crash analysis function. Simplified models handle the extraction of pre-crash maneuver characteristics and case filtering, while detailed models are reserved for extracting accurate crash outcome predictions from the filtered subset of critical cases.
Solution Approach 2:
Simplified occupant models perform preliminary analysis of pre-crash maneuvers to identify critical cases and prepare appropriate initial conditions for detailed crash simulations. This preliminary action maintains computational efficiency while ensuring that detailed models receive preprocessed data that captures essential crash configuration characteristics.
Data Source
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AI summary
A methodology, including: receiving first input related to expected states of a vehicle and another vehicle or object at impact event initiation with positions, orientations, and velocities as parameters used for impact event evaluation; receiving second input related to expected vehicle occupant position and position transfer during a pre-impact event maneuver; and simulating an impact event involving the vehicle and the another vehicle or object using both the first input and the second input to quantify the performance of a safety system of the vehicle with a combined effect from a collision avoidance feature and an injury prevention feature. The method further includes filtering out a case where a vehicle occupant pre-crash position excursion is expected to exceed a predetermined threshold.