Connected Suspension Platform for Adaptive Vehicle Setup
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Solution Overview
Problem
Current vehicle suspension systems lack the ability to provide personalized and adaptive settings based on the rider's skill level, vehicle specifications, and real-time environmental conditions, leading to suboptimal performance and maintenance challenges.
Innovation Solution
A connected component platform (CCP) system that utilizes sensors and mobile computing devices to collect data on vehicle performance, rider characteristics, and environmental conditions, providing real-time suspension setup recommendations and maintenance alerts, and automatically adjusts suspension settings using an active suspension controller.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If suspension settings are fixed at factory defaults, then device complexity is reduced, but adaptability to different riders and conditions deteriorates
Solution Approach 1:
The suspension system transitions from fixed factory defaults to dynamic, real-time adjustment based on sensor data about rider weight, terrain conditions, and riding style. The suspension controller continuously modifies damping characteristics and spring preload based on live feedback, making the system adaptive rather than static.
Solution Approach 2:
The system incorporates sensors that continuously monitor suspension performance, rider input, and environmental conditions. This feedback loop enables the suspension controller to automatically adjust settings based on actual riding conditions and performance data, resolving the contradiction between simplicity and adaptability.
2Productivity
If manual suspension adjustment is used, then ease of operation is improved, but productivity and performance optimization deteriorates
Solution Approach 1:
The suspension system performs self-adjustment through automated controllers that modify damping and spring characteristics based on sensor data. The system serves itself by automatically optimizing performance without requiring manual intervention, thereby improving productivity while maintaining ease of operation.
Solution Approach 2:
Manual mechanical adjustment is replaced with electronic control systems that use sensors, microprocessors, and actuators to automatically modify suspension characteristics. This substitution enables rapid, precise adjustments that optimize performance without requiring rider expertise or manual intervention.
3Measurement precision
If comprehensive sensor monitoring is implemented, then measurement precision is improved, but use of energy deteriorates
Solution Approach 1:
The sensor monitoring system operates periodically rather than continuously, collecting data at strategically timed intervals during the riding cycle. This approach maintains measurement precision for critical parameters while reducing overall energy consumption by keeping sensors in low-power states between measurements.
Solution Approach 2:
The system selectively monitors only the most critical suspension parameters and riding conditions rather than comprehensively tracking all possible variables. This partial monitoring approach achieves sufficient measurement precision for performance optimization while minimizing energy consumption from the battery-powered sensor suite.
Data Source
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AI summary
A system (200) comprising: a memory (710) ; at least one processor (705) configured to: initiate a connected component platform (CCP) application; receive information about at least one connected component on a vehicle; receive a sensor derived performance information for said vehicle; and develop, at said CCP application, a suspension setup recommendation for said vehicle based on said information about said at least one connected component and said sensor derived performance information; and a display (718) to present said suspension setup recommendation for said vehicle.