Self-Calibrating Load Sensor for Active Aero Downforce
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current motor vehicles equipped with active aerodynamic devices face challenges in accurately measuring and controlling downforce due to sensor drift, which can be exacerbated by environmental factors like crosswinds and traffic, leading to reduced aerodynamic performance and increased drag.
Innovation Solution
A self-calibrating load sensor system with a closed-loop control scheme that uses mapped vehicle data to detect sensor drift and apply offsets to correct errors, eliminating the need for regular recalibration and improving the accuracy of downforce measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If load sensors are used to measure downforce on active aerodynamic devices, then aerodynamic performance can be controlled, but sensor drift occurs over time leading to measurement errors
Solution Approach 1:
The system performs preliminary calibration actions during vehicle production to establish baseline sensor readings under known downforce conditions. This preliminary calibration data is stored and used as a reference for ongoing drift detection and correction, allowing the system to proactively compensate for sensor degradation before it significantly impacts performance.
Solution Approach 2:
The system implements continuous feedback loops where sensor readings are constantly compared against expected values derived from calibration data and real-time vehicle operating conditions. When drift is detected through this feedback mechanism, the system automatically adjusts control commands to active aerodynamic devices to compensate for the measurement errors, maintaining accurate downforce control despite sensor degradation.
2Measurement precision
If extensive sensor calibration strategies are implemented during vehicle production, then measurement accuracy improves, but manufacturing complexity and costs increase
Solution Approach 1:
The system enables sensors to self-calibrate and self-correct during normal vehicle operation without requiring external calibration equipment or complex manufacturing processes. By using readily available vehicle operating data and embedded processing, the system performs its own calibration maintenance, eliminating the need for extensive factory calibration procedures and reducing manufacturing complexity.
Solution Approach 2:
The system dynamically adjusts calibration parameters and offset values based on changing vehicle conditions, sensor drift patterns, and environmental factors. Rather than relying on fixed calibration values established during manufacturing, the system continuously adapts calibration parameters to maintain accuracy, simplifying the initial manufacturing process while preserving measurement precision throughout the vehicle's lifecycle.
3Force
If active aerodynamic devices are deployed to improve aerodynamics, then vehicle stability and downforce increase, but drag and wind-borne noise also increase
Solution Approach 1:
The system dynamically adjusts the position and configuration of active aerodynamic devices based on real-time downforce measurements, vehicle speed, and operating conditions. Rather than maintaining fixed positions, the devices are continuously optimized to provide the minimum necessary downforce for current conditions, reducing unnecessary drag and wind-borne noise while maintaining vehicle stability when needed.
Data Source
AI summary
Disclosed are self-calibrating load sensor systems for active aerodynamics devices, methods for making or using such load sensor systems, and motor vehicles equipped with a self-calibrating load sensor system to govern operation of the vehicle's active aero device(s). An active aero sensing system includes a load sensor that mounts to the vehicle body, and detects downforces on the vehicle. A memory device stores mapped vehicle downforce data calibrated to the motor vehicle. A vehicle controller receives downforce signals generated by the load sensor, and calculates an average downforce value from these signals. The controller determines if the average downforce differs from a calibrated downforce value retrieved from the memory device. If so, the controller responsively applies an offset value to subsequent downforce signals received from the load sensor, and dynamically controls operation of the active aero device based, at least in part, on these signals modified by the offset value.