Sensor-Controlled Bicycle Suspension Damping for Pedaling Efficiency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Bicycle suspension components require manual adjustment by riders to optimize performance based on terrain and riding conditions, leading to inefficiencies and loss of power during pedaling.
Innovation Solution
An adjustable suspension component with a damper that can operate in multiple damping states, controlled by a processor and motion controller, which adjusts based on sensor data from accelerometers and other sensors to automatically change damping levels for optimal performance without user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual adjustment of suspension components is used, then riders can optimize performance based on terrain, but it leads to inefficiencies and power loss during pedaling
Solution Approach 1:
The suspension system automatically adjusts damping levels using sensors and a processor to detect riding conditions, eliminating the need for manual rider intervention. The system serves itself by continuously monitoring and adapting to terrain changes, thereby preventing power loss during pedaling while maintaining optimal suspension performance.
Solution Approach 2:
The damper is designed with multiple adjustable damping states that can dynamically change based on detected riding conditions. The motion controller transitions the damper between different damping levels in real-time, allowing the suspension to adapt its characteristics according to terrain and pedaling phase, thus optimizing performance without manual intervention.
2Productivity
If automatic adjustment based on sensor data is implemented, then real-time optimization is achieved, but device complexity increases
Solution Approach 1:
The processor is designed to handle multiple functions: detecting riding conditions through sensor data, determining pedaling phase, controlling both front and rear suspension dampers, and managing different damping states. This multi-functional approach consolidates control logic into a single unit, reducing overall system complexity while enabling comprehensive real-time optimization.
Solution Approach 2:
The system continuously receives sensor data about riding conditions and pedaling phase, processes this information, and adjusts damper settings accordingly. This closed-loop feedback mechanism enables automatic real-time optimization of suspension performance based on actual riding conditions, achieving productivity improvement through intelligent control.
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.