Bicycle Suspension Damping Control for Changing Riding Conditions
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Solution Overview
Problem
Existing bicycle suspension systems lack the ability to automatically adjust damping levels in real-time based on varying riding conditions and bicycle states, leading to suboptimal performance and rider experience.
Innovation Solution
A suspension component for bicycles that includes a damper operable in multiple damping states, a motion controller to adjust the damper between these states, and a processor that uses sensor data to activate the motion controller, allowing for automatic adjustments of the damping level based on detected parameters such as pedaling, vibration, and pitch angle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual adjustment of damping levels is used, then device complexity is reduced, but adaptability to varying riding conditions deteriorates
Solution Approach 1:
The suspension system transitions from static manual adjustment to dynamic automatic adjustment. The processor continuously monitors sensor data (accelerometers, gyroscopes, pedaling detection) and dynamically changes damping levels in real-time based on detected riding conditions, terrain, and bicycle state, making the system adaptive without requiring manual intervention.
Solution Approach 2:
The system implements closed-loop feedback control by continuously sensing riding conditions through multiple sensors, processing this information to determine optimal damping settings, and adjusting the damper accordingly. This feedback mechanism enables the system to automatically adapt to changing conditions while maintaining controlled complexity through automated decision-making algorithms.
2Adaptability or versatility
If automatic adjustment system is implemented, then adaptability improves, but device complexity increases
Solution Approach 1:
The processor serves multiple functions: it processes sensor data from accelerometers and gyroscopes, detects pedaling states, determines bicycle pitch angles, selects appropriate damping levels, and controls the motion controller. This multi-functionality consolidates what could be multiple separate systems into a single integrated unit, improving adaptability while managing overall system complexity.
Solution Approach 2:
The suspension system is self-regulating, using its own sensor data to automatically determine and adjust damping levels without external input. The system monitors its own state (through integrated sensors) and makes independent adjustment decisions, reducing the need for complex external control systems or manual intervention.
3Measurement precision
If multiple sensors are used for detection, then measurement precision improves, but device complexity increases
Solution Approach 1:
Multiple sensors (accelerometers, gyroscopes, pedaling detection sensors) are merged into a single integrated sensing system processed by one processor. This consolidation allows the system to achieve high measurement precision through multiple data sources while managing complexity by processing all sensor inputs through a unified control algorithm rather than requiring separate control systems for each sensor.
Data Source
AI summary
Example adjustable suspension components for bicycles are described herein. An example bicycle suspension component includes a damper operable in a low damping state, a high damping state, and an intermediate damping state between the low damping state and the high damping state, a motion controller operable to change the damper between the low damping state, the intermediate damping state, and the high damping state, and a processor to, based on sensor data, activate the motion controller to change the damper between the intermediate damping state and one of the low damping state or the high damping state.