Vehicle Suspension Control Using Road Preview and Sensor Feedback
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Solution Overview
Problem
Current vehicle suspension control methods face challenges in accurately identifying pavement smoothness variations and making quick adjustments to alleviate large shocks, with existing methods either passively adjusting damping force or risking false identification due to complexity and diversity of actual pavements and driving scenarios.
Innovation Solution
A suspension control method and system that uses image acquisition and processing to identify pavement smoothness variations, generating control signals to adjust suspension parameters, and incorporates sensors to detect pavement characteristic information for real-time correction of these signals, ensuring accurate and adaptive damping adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a front wheel position sensor is used to monitor vertical bounces and shock absorber travel direction for passive damping force adjustment, then the suspension system can identify pavement variations, but it cannot make quick adjustments in large shock conditions to relieve large shocks
Solution Approach 1:
The system uses a visual sensing system to perform preliminary identification of pavement variations before the vehicle encounters them. This allows the suspension control system to prepare and adjust damping parameters in advance, enabling quick response to large shocks rather than waiting for passive sensor detection after the shock occurs.
Solution Approach 2:
The system implements a feedback mechanism where the visual sensing system continuously monitors pavement conditions and provides real-time information to the control unit. This closed-loop feedback enables dynamic adjustment of suspension parameters based on actual pavement variations, improving both response speed and shock relief capability.
2Measurement precision
If a visual sensing system is used to identify pavement variations in front, then the suspension control can be proactive, but there is a risk of false identification or failure in identification due to complex and diverse actual pavements and driving scenarios
Solution Approach 1:
The system merges multiple sensing approaches by combining the visual sensing system with existing suspension sensors (acceleration sensors, displacement sensors). This multi-sensor fusion approach cross-validates pavement variation identification, reducing false positives while maintaining system complexity at an acceptable level through integrated processing.
Solution Approach 2:
The control unit acts as an intermediary that processes and validates information from both the visual sensing system and traditional suspension sensors. This intermediary layer filters and cross-checks data before generating control signals, improving identification accuracy while managing system complexity through intelligent data fusion rather than simply adding more sensors.
Data Source
AI summary
This application relates to a suspension control method and system, a vehicle, and a storage medium. The suspension control method includes: acquiring a pavement image in a traveling direction; identifying a variation type corresponding to a pavement smoothness variation according to the pavement image; generating a control signal according to the identified variation type, to adjust a suspension parameter; detecting, by using a sensor coupled to a suspension, pavement characteristic information corresponding to the variation type; and generating a correction signal based on the pavement characteristic information, to correct the control signal. The suspension control method can identify the pavement smoothness variation more accurately and set the suspension damping parameter according to an identification result.