Active Vehicle Height Control via Vision-Based Inverse-Phase Actuation
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Solution Overview
Problem
Existing vehicle height control systems fail to effectively improve riding comfort and maintain a stable vehicle posture when encountering speed bumps or uneven roads, as they lack efficient methods to anticipate and respond to road surface irregularities in real-time.
Innovation Solution
An active vehicle height control method that involves securing a road surface profile using a vision sensor, forming a target vehicle height profile through filtering, estimating vehicle behavior, determining an inverse-phase control force, and driving an actuator to minimize vehicle behavior by adjusting the vehicle height in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time road surface detection and active actuator control are implemented, then riding comfort and vehicle posture stability are improved, but device complexity and computational requirements increase
Solution Approach 1:
The system performs preliminary detection of road surface profiles using vision sensors before the vehicle encounters the unevenness. The controller pre-calculates the required actuator forces based on the detected road geometry, allowing the active suspension to anticipate and compensate for disturbances before they affect vehicle posture, thereby improving stability without requiring overly complex real-time reaction systems
Solution Approach 2:
The patent replaces traditional mechanical suspension components with an active actuator system controlled by electronic sensors and processors. The vision sensor system substitutes optical detection for mechanical road feelers, and the electronic control system replaces purely mechanical suspension linkages, reducing mechanical complexity while enabling more precise and adaptable control
2Measurement precision
If complex filtering algorithms are used to generate target vehicle height profile, then control precision is improved, but processing time and computational load increase
Solution Approach 1:
The filtering process is segmented into multiple discrete stages: initial road profile detection, preliminary filtering to remove noise, calculation of target vehicle height profile, and final control signal generation. Each stage processes only the necessary data for its specific purpose, reducing the computational burden at any single point while maintaining overall precision
Solution Approach 2:
The system applies filtering algorithms selectively based on the detected road conditions. For minor unevenness, simplified filtering is used to reduce processing time. For significant obstacles or complex road profiles, the full filtering algorithm is applied to ensure precision. This adaptive approach balances processing time and control precision based on actual operational needs
Data Source
AI summary
An active vehicle height control method may include securing a road surface profile for unevenness of a road ahead of a vehicle and forming a target vehicle height profile by filtering the road surface profile. In addition, a controller is configured to form a disturbance profile using the road surface profile and the target vehicle height profile. The controller estimates vehicle behavior for the disturbance profile. Furthermore, the controller determines an inverse-phase control force that minimizes the estimated vehicle behavior, and drives an actuator using the inverse-phase control force to adjust a height of the vehicle.