Vehicle Suspension Weight Estimation with Sag Compensation
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Solution Overview
Problem
Existing vehicle systems for estimating weight-related parameters, such as total vehicle weight, tongue load, and axle loads, become inaccurate over time due to suspension degradation from wear and damage, leading to unsafe towing conditions.
Innovation Solution
A method and system that utilizes static and dynamic sensor data to estimate weight-related parameters, compensates for suspension degradation by updating a suspension model, and fuses static and dynamic estimates to provide accurate weight values, including a suspension sag estimation model to determine and accommodate for system wear.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If suspension displacement measurements are used to estimate weight-related parameter values, then the system can provide weight estimates, but the accuracy degrades over time due to suspension component wear and damage
Solution Approach 1:
The system performs preliminary characterization of the suspension system by collecting dynamic sensor data during driving conditions when the trailer is not coupled. This data is used to establish a baseline suspension model before actual towing operations, allowing the system to proactively account for suspension characteristics and degradation rather than relying solely on static measurements that deteriorate over time
Solution Approach 2:
The system continuously monitors suspension displacement measurements and compares them against the established suspension model. When discrepancies are detected indicating degradation, the system updates the suspension model accordingly. This closed-loop feedback mechanism ensures the estimation system adapts to suspension wear and maintains accuracy throughout the suspension system's operational life
2Device complexity
If a suspension model is used to estimate weight parameters, then the system can operate with limited sensors, but the model becomes inaccurate as suspension components wear or become damaged
Solution Approach 1:
The suspension model serves itself by automatically updating using data from the existing sensor system. The same sensors used for weight estimation also provide data for model refinement, eliminating the need for additional characterization sensors or complex calibration procedures. The system uses its own operational data to maintain and improve its accuracy
Solution Approach 2:
The system dynamically adjusts suspension model parameters based on observed behavior during driving. By monitoring changes in suspension displacement responses to known inputs (road irregularities, vehicle maneuvers), the system infers and updates parameters such as spring rates, damping coefficients, and friction characteristics, allowing the model to adapt to wear and damage without physical inspection or recalibration
3Device complexity
If static sensor data alone is used for weight estimation, then the system is simple to implement, but accuracy is reduced due to suspension degradation and static measurement limitations
Solution Approach 1:
The system merges static sensor data collected when the vehicle is stationary with dynamic sensor data collected during driving operations. By combining these two data sources and processing them through an integrated estimation algorithm, the system achieves higher accuracy than either method alone could provide, while maintaining implementation simplicity through unified processing logic
Data Source
AI summary
Methods and systems are provided for estimating weight-related parameter values of a vehicle. The system includes a sensor system, a display device, and a controller configured to, by a processor, receive, from the sensor system, static sensor data sensed while the vehicle is stationary and coupled to a trailer and dynamic sensor data while the vehicle is being driven and not coupled to the trailer, wherein the static sensor data includes a deflection value associated with a suspension system of the vehicle, estimate, while the vehicle is stationary, one or more weight-related parameter values using a suspension model and the static sensor data, determine degradation of the suspension system over time using a suspension sag estimation model and the dynamic sensor data, update the suspension model to accommodate for the degradation of the suspension system, and display the one or more weight-related parameter values on the visual display.