Vehicle Load Estimation via Inertial Sensor Spectral Analysis
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Solution Overview
Problem
Existing systems for estimating vehicle load and its distribution are often costly, complex, and prone to errors due to variable load conditions, which can lead to vehicle overload and stability issues, particularly in vehicles like vans and trash compactors.
Innovation Solution
A system using a combination of accelerometers and gyroscopes to detect vehicle vertical acceleration and pitch angular speed, processing these signals through Fast Fourier Transform and band-pass filters to estimate load parameters, with a calibration phase determining specific frequency bands and relations for accurate load estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If non-inertial sensors such as scales and strain gauges are used to measure vehicle load, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces mechanical measurement systems (scales, strain gauges) with an inertial measurement system using accelerometers and gyroscopes combined with signal processing. This substitution eliminates the need for complex mechanical load cells and strain gauge installations while achieving accurate load estimation through dynamic measurement and spectral analysis of acceleration signals.
2Device complexity
If inertial sensors and signal processing are used to estimate vehicle load, then device complexity is reduced, but measurement precision may deteriorate under variable load conditions
Solution Approach 1:
The patent employs dynamic measurement and signal processing techniques that adapt to variable load conditions. By using spectral analysis (FFT) to separate different frequency components of acceleration signals and applying band-pass filtering to isolate load-related frequencies, the system maintains measurement precision despite varying load distributions and vehicle dynamics.
Solution Approach 2:
The system uses a calibration phase where the relationship between inertial measurements and actual load is established, creating a feedback mechanism that improves estimation accuracy. The signal processing pipeline including FFT, filtering, and integration continuously refines load estimates based on the calibrated model, compensating for variable operating conditions.
3Loss of information
If existing load estimation systems are implemented, then load parameters can be determined, but the risk of overload and stability issues persists due to measurement errors
Solution Approach 1:
The patent implements a preliminary calibration phase that establishes the relationship between inertial measurements and actual load characteristics before normal operation. This advance calibration creates a reliable reference model that enables accurate load estimation during subsequent vehicle operation, allowing proactive detection of overload conditions and improper load distribution before they become safety issues.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides accurate and cost-effective estimation of vehicle load and its distribution, reducing the risk of overload and improving stability with minimal installation complexity and low-cost instrumentation.
Implementation Method 1
a sensor for detecting a vehicle vertical acceleration
Implementation Method 2
a sensor for detecting a pitch angular speed of the vehicle
Data Source
Figure 1
Figure 2
Figure 3a~3c
AI summary
The object of the present invention is a system (1) for the estimation of one or more parameters (L, D) related to the load of a vehicle. The system comprises: - one or more sensors for detecting one or more kinematic quantities of the vehicle (I) suitable to generate signals representing said vehicle kinematic quantities; - one or more modules (2) for determining one or more frequency spectra pairs (FFT1,FFT2), each pair associated to one of said one or more vehicle kinematic quantities (I), from the signal representing the respective vehicle kinematic quantity filtered in a first and in a second predetermined frequency bands; - One or more modules (7) for determining said one or more parameters (L, D) related to the load of the vehicle, from said one or more frequency spectra pairs (FFT1,FFT2).