Route-Aware Suspension Switching for Response Delay and Energy Waste
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Solution Overview
Problem
Automated adjustable suspension systems in vehicles face delays in responding to changing road conditions, leading to discomfort for drivers and inefficient energy use, as they require time and energy to adjust settings based on real-time sensor inputs.
Innovation Solution
A control system that uses route data and road type information to predict optimal suspension configurations ahead of time, allowing for pre-emptive adjustments and minimizing unnecessary changes by estimating stable stretches and energy gains, thereby reducing delays and energy expenditure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If automated suspension adjustment systems react to changing road conditions in real-time, then the suspension can adapt to current road conditions, but the system experiences delays in responding to changing circumstances due to the time required to process sensor signals and make adjustments
Solution Approach 1:
The control system uses route data and map data to predict upcoming road sections and their characteristics in advance. By processing this information before the vehicle reaches the relevant road section, the system prepares suspension adjustments beforehand, eliminating the response delay that would occur with real-time sensor-based reactions alone.
2Adaptability or versatility
If the automated suspension system continuously adjusts settings based on real-time sensor signals, then the suspension can respond to changing conditions, but the system consumes excessive energy due to frequent adjustments
Solution Approach 1:
The system predicts upcoming road sections using route and map data, allowing it to plan suspension adjustments in advance. This predictive approach enables the system to make adjustments only when and where they are truly needed, rather than continuously reacting to every sensor signal, thereby reducing unnecessary energy consumption.
Solution Approach 2:
The control system independently evaluates predicted road conditions against current suspension settings and determines whether adjustments are beneficial. By using its own predictive capabilities rather than continuously reacting to external sensor inputs, the system avoids energy-wasting adjustments and makes autonomous decisions about when modification is worthwhile.
3Ease of operation
If the suspension system makes frequent adjustments to optimize for varying road conditions, then ride comfort can be improved, but the switching between configurations takes time and energy
Solution Approach 1:
The control system uses predicted route information to anticipate upcoming road sections requiring suspension adjustments. By preparing adjustments in advance based on predictable road conditions rather than reacting to every immediate change, the system reduces the total number of adjustments needed, thereby conserving energy while maintaining ride comfort.
Solution Approach 2:
The system continuously monitors current suspension settings and compares them with predicted optimal settings for upcoming road sections. This feedback mechanism allows the system to make intelligent decisions about whether adjustments are truly necessary, avoiding energy-wasting switching when conditions don't warrant it, while ensuring adjustments are made when they will improve ride comfort.
Data Source
AI summary
A control system (400) is provided for an adjustable suspension of a vehicle (100). The adjustable suspension is operable in at least two different configurations. The control system is configured to receive route data (110) indicative of an expected route of the vehicle, receive map data (120) comprising road type information for a road section of the expected route, and output a switch signal to instruct the adjustable suspension (104) to switch between the two different configurations in dependence on the expected route and the road type information, before the vehicle (100) reaches the road section.