Connected Suspension Platform for Personalized Tuning Guidance
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Solution Overview
Problem
Current vehicle suspension systems fail to provide optimal performance for riders due to inadequate settings and maintenance, requiring expert knowledge and manual adjustments, which can lead to suboptimal riding experiences and inefficient component usage.
Innovation Solution
The FOX™ connected component platform collects and evaluates real-time data from various sources, including rider characteristics, vehicle specifications, and environmental conditions, to provide personalized suspension adjustments and maintenance recommendations, utilizing a connected component platform that includes sensors and a mobile application for optimal setup and performance enhancement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual suspension adjustments are made by users, then some level of performance can be achieved, but the performance is suboptimal due to lack of expert knowledge
Solution Approach 1:
The system automatically collects sensor data, evaluates component conditions, and generates maintenance recommendations without requiring user expertise. The connected component platform performs self-diagnosis and provides actionable insights, enabling users to maintain optimal suspension performance through automated guidance rather than manual adjustment
Solution Approach 2:
The system continuously monitors suspension component data through sensors and provides real-time feedback to users via mobile applications. This feedback loop enables users to understand component status and make informed adjustments based on objective data rather than subjective assessment, bridging the gap between amateur operation and expert performance
2Reliability
If expert-level suspension setup is provided, then optimal performance is achieved, but the system complexity and processing requirements increase
Solution Approach 1:
The connected component platform divides the suspension system into individually monitorable components, each with its own sensors and data stream. This segmentation allows the system to process and evaluate specific component conditions independently, reducing overall system complexity while maintaining comprehensive performance optimization
Solution Approach 2:
The mobile application serves as an intermediary between the complex sensor network and the user. It consolidates raw sensor data into actionable maintenance recommendations, shielding users from system complexity while delivering expert-level performance guidance through a simple interface
3Reliability
If continuous monitoring of suspension components is implemented, then performance optimization is improved, but battery life is reduced
Solution Approach 1:
The system implements periodic monitoring intervals rather than continuous monitoring, collecting sensor data at strategically determined moments. This approach maintains performance optimization capabilities while significantly reducing power consumption and extending battery life between charges
Solution Approach 2:
The system dynamically adjusts monitoring parameters such as sampling frequency and data collection intensity based on riding conditions and component status. During normal operation, monitoring occurs at lower intensity to conserve battery, while increasing to higher intensity when performance issues are detected or during critical riding phases
4Measurement precision
If comprehensive sensor data collection is performed, then maintenance accuracy is improved, but processing requirements increase
Solution Approach 1:
The system extracts only the most critical data points and features from comprehensive sensor readings for processing. By identifying and focusing on key performance indicators and anomaly detection parameters, it achieves high maintenance accuracy without requiring intensive processing of all available sensor data
Solution Approach 2:
The mobile application creates simplified representations of complex sensor data, translating raw component measurements into intuitive maintenance recommendations. This data transformation reduces processing requirements by pre-processing and filtering information before presenting it to users in actionable formats
Data Source
AI summary
A connected component platform (CCP) is disclosed. The CCP receives user information and sensor derived data. The system also includes an overall data evaluator to access a performance database and use the user information in conjunction with information from the performance database to evaluate the received user information as a method to develop user guidance data in the area of suspension tuning and suspension maintenance recommendations. The system further includes a data evaluation results formator to receive the user guidance data from the overall data evaluator, format the user guidance data into a user accessible digital format, and output the user guidance data in the user accessible digital format.