Predictive Suspension Control Using Stereo Camera Lean Angle Adaptation
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Solution Overview
Problem
Predictive suspension control systems for single-track vehicles like motorcycles and scooters face challenges due to restricted processing capabilities and dynamic driving characteristics, limiting their efficiency and adaptability compared to two-track vehicles.
Innovation Solution
A predictive suspension control system utilizing a stereo camera sensor to generate image data, extract relevant image portions based on future vehicle path data, calculate road unevenness, and adapt suspension parameters in real-time, specifically designed to handle the dynamic movements of single-track vehicles by adjusting the search direction and correlation area of the stereo algorithm based on the vehicle's lean angle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If predictive suspension control is implemented for single-track vehicles, then driving comfort and handling are improved, but processing capabilities and computational resources are severely restricted
Solution Approach 1:
The patent segments the image processing task by extracting only the relevant image portion corresponding to the future vehicle path using predicted path data, rather than processing the entire image. This segmentation reduces computational load while maintaining predictive suspension control functionality for single-track vehicles
Solution Approach 2:
The system applies local quality by adapting the search direction and correlation area of the stereo algorithm specifically to the lean angle of the vehicle. This localized adaptation optimizes processing for the dynamic characteristics of single-track vehicles without requiring full-system complexity
2Measurement precision
If the entire image data is processed to detect road irregularities, then measurement precision is improved, but computation time increases
Solution Approach 1:
The patent extracts only the relevant image portion that corresponds to the future vehicle path based on predicted path data, removing unnecessary image data from processing. This extraction maintains detection precision for road irregularities while significantly reducing computation time
Solution Approach 2:
The system performs partial action by processing only the necessary portion of the image data rather than the entire image. This partial processing approach achieves sufficient measurement precision for predictive suspension control without the excessive computation time required for full-image processing
3Measurement precision
If the stereo algorithm processes all image areas, then road surface scanning accuracy is improved, but processing efficiency decreases
Solution Approach 1:
The patent segments the stereo algorithm processing to focus only on the relevant image portion corresponding to the future vehicle path, improving processing efficiency while maintaining scanning accuracy through targeted analysis of critical areas
Solution Approach 2:
The system changes parameters by adapting the search direction and correlation area of the stereo algorithm based on the vehicle's lean angle. This parameter adaptation optimizes both scanning accuracy and processing efficiency for the dynamic conditions of single-track vehicles
4Adaptability or versatility
If predictive suspension control is adapted for dynamic vehicle movements, then adaptability is improved, but device complexity increases
Solution Approach 1:
The patent implements dynamics by adapting the search direction and correlation area of the stereo algorithm based on the lean angle of the vehicle. This dynamic adaptation improves versatility for handling single-track vehicle movements without requiring complex system architecture
Solution Approach 2:
The system achieves adaptability through parameter changes in the stereo algorithm based on lean angle data, allowing the predictive suspension control to adapt to dynamic vehicle movements without increasing overall device complexity
Data Source
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AI summary
The invention addresses the area of predictive suspension control system for a vehicle, particularly a two-wheel vehicle such as a motor cycle or a scooter. The system for adapting a suspension includes a stereo sensor unit which for generating image data, a computing unit which extracts a relevant image portion from the image data based on future vehicle path data, and calculates road unevenness on a future vehicle path of the vehicle based on the generated image data. A suspension control unit generates an adaptation signal for adapting the suspension based on the calculated road unevenness. The computing unit adapts a search direction of a stereo algorithm or a correlation area of the stereo algorithm based on a lean angle of the vehicle to generate the three-dimensional partial image data from the relevant image portion, and fits a road model to the three-dimensional partial image data to calculate the road unevenness.