WIM Sensor Calibration Using Road Profile Simulation
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Solution Overview
Problem
Current Weigh in Motion (WIM) sensors face challenges in accurately measuring wheel forces due to dynamic effects caused by uneven road surfaces and vehicle suspension, leading to reduced measurement accuracy and increased wear on roadways.
Innovation Solution
A method involving the simulation of wheel forces using a quarter car model to account for road profile variations, determining dynamic wheel forces, and generating a calibration function to minimize the influence of road profile on measured forces, thereby improving measurement accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a WIM sensor is used to measure wheel forces on a roadway, then vehicle weight information can be obtained for enforcement and toll purposes, but measurement accuracy is reduced due to dynamic effects from uneven road surfaces and vehicle suspension
Solution Approach 1:
The patent applies preliminary action by recording the road profile in advance using a separate measurement vehicle before WIM sensor calibration. The recorded road profile data is then used during simulation to predict and compensate for dynamic effects on wheel forces, allowing the calibration to account for real-world road conditions rather than assuming a perfectly smooth surface.
Solution Approach 2:
The patent uses copying by creating a simulated model of the vehicle-w road interaction that replicates real-world conditions. The simulation copies the actual road profile data and vehicle dynamics to generate predicted wheel forces under various conditions, allowing calibration without requiring physical testing under all possible scenarios.
2Measurement precision
If calibration is performed using a static weighing station, then the vehicle weight is known accurately, but dynamic effects that influence wheel force on the roadway are not taken into account
Solution Approach 1:
The patent introduces an intermediary element - a simulation model - that bridges the gap between static weighing station data and dynamic roadway conditions. The simulation acts as a mediator that takes static weight information and road profile data as inputs, then generates corrected wheel force values that account for dynamic effects, thereby connecting the static calibration data to real-world dynamic conditions.
Solution Approach 2:
The patent applies parameter changes by transforming the calibration approach from purely static parameters (vehicle weight only) to include dynamic parameters (road profile, vehicle speed, suspension characteristics). The simulation model adjusts the wheel force calculations based on varying parameters such as road unevenness amplitude and frequency, vehicle velocity, and suspension stiffness, allowing accurate calibration across different driving conditions.
3Measurement precision
If the road profile is recorded and used in simulation to determine wheel force dependency, then the influence of road profile on measured forces can be minimized, but the calibration process becomes more complex
Solution Approach 1:
The patent replaces the traditional mechanical calibration approach (physical vehicle weighing and direct sensor calibration) with a computational simulation system. Instead of physically testing the WIM sensor under various road conditions, the system uses computer-based simulation to model the vehicle-road interaction and calculate correction factors, thereby reducing the need for complex physical calibration setups while improving accuracy.
Data Source
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AI summary
The invention relates to a method for generating a calibration function (C) of a WIM sensor (7); which WIM sensor (7) is arranged in a roadway (1); which WIM sensor (7) measures a wheel force exerted on the surface of the roadway (1); wherein the road profile (2) of a roadway (1) is recorded; wherein a wheel force (F9) is determined by a simulation (102); wherein the dependency of the wheel force (F9) on the road profile (2) is determined by simulation (102) for at least one position (P) of the road profile (2) recorded in step a); and wherein the dependency is used to minimize the influence of the road profile (2) on the measured wheel force (W) of the WIM sensor (7).