Active Suspension Model Updating for Smoother Vehicle Control
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Solution Overview
Problem
Conventional active suspension systems rely on simplified models that are not based on actual vehicle parameters, leading to inaccurate predictions and overreactive responses, which affect ride comfort and component wear.
Innovation Solution
The use of a modal expansion model that represents the vehicle as a linear combination of natural modes, allowing for the determination of actual vehicle parameters such as mass, damping, and stiffness matrices from sensor data, enabling more accurate predictions and smoother actuator responses over a longer period.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If simplified models are used for active suspension control, then device complexity is reduced, but prediction accuracy deteriorates
Solution Approach 1:
The patent transforms the suspension control problem from using simplified constant parameters to using time-varying parameters that adapt to changing road conditions. The modal parameters (mass, damping, stiffness) are continuously updated based on measured vibration data, allowing the system to maintain accuracy without increasing structural complexity.
Solution Approach 2:
The system uses the vehicle's own vibration responses to automatically identify and update its parameters. By measuring the natural frequencies and mode shapes from actual vehicle operation, the system self-calibrates without requiring external input or manual adjustment, maintaining accuracy while avoiding complex external sensing systems.
2Ease of operation
If simplified models are used for active suspension control, then ease of operation is improved, but reliability deteriorates
Solution Approach 1:
The patent implements a feedback mechanism where the actual vehicle response is continuously measured and used to update the modal parameters. This closed-loop approach ensures that the control system adapts to changing conditions, maintaining reliability while keeping the control algorithm structure simple and manageable.
3Device complexity
If conventional suspension systems are used, then device complexity is reduced, but energy consumption increases due to overreactive responses
Solution Approach 1:
The patent transitions from static, fixed-parameter suspension control to dynamic, adaptive control where the modal parameters continuously evolve with vehicle operation. This allows the system to respond appropriately to actual conditions rather than overreacting to transient disturbances, reducing unnecessary actuator activity and energy consumption.
Data Source
AI summary
An active suspension control system for a vehicle includes a mathematical model based on a modal expansion of the vehicle. Model parameters of the vehicle can be extracted from the modal expansion using sensor data generated on the vehicle, e.g., on demand and/or in real time. The model parameters and the modal expansion can be used to determine a vehicle state, predict future vehicle states, and control aspects of an active suspension system based on the predicted future vehicle states. The model parameters may also be used to update the mathematical model, e.g., to account for component wear over time, and/or to detect anomalies or defects in the active suspension system.