Vehicle Weight Estimation Using Torque Profile Error Matching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for determining the weight of a vehicle are either impractical, such as using external weighing devices that are not always available, or inaccurate, like installing load sensors which can be difficult and expensive to implement.
Innovation Solution
A system that uses a processor to analyze vehicle data, including torque profiles, to identify vehicle maneuvers and generate simulated torque profiles based on a vehicle dynamics model. This system then calculates error profiles by comparing simulated and measured torque profiles, allowing it to estimate the vehicle's weight by minimizing these error profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If external weighing devices are used to measure vehicle weight, then measurement accuracy is improved, but device complexity and cost increase
Solution Approach 1:
The patent creates a virtual copy of the weighing function by using a vehicle dynamics model to simulate torque profiles and compare them with measured torque data. Instead of using physical weighing devices, the system copies the measurement function through computational modeling, thereby achieving accurate weight measurement without complex external hardware.
Solution Approach 2:
The patent replaces the mechanical weighing system with a computational approach. By substituting physical load sensors and scale mechanisms with a vehicle dynamics model that processes torque profile data, the system eliminates complex mechanical components while maintaining measurement capability through mathematical modeling and data analysis.
2Measurement precision
If load sensors are installed in the vehicle to measure weight, then measurement capability is improved, but ease of operation and cost worsen due to installation difficulty
Solution Approach 1:
The patent copies the weight measurement capability from physical load sensors to a virtual model. By using the vehicle dynamics model to simulate and compare torque profiles, the system achieves measurement capability without requiring physical sensor installation, thereby eliminating installation complexity while maintaining measurement functionality.
Solution Approach 2:
The patent extracts the essential measurement function from the physical sensor system and relocates it to a computational model. By taking out the weight measurement capability from the mechanical sensor domain and implementing it through vehicle dynamics modeling and torque profile analysis, the system eliminates the need for sensor installation while preserving measurement capability.
3Measurement precision
If traditional weighing methods are used, then measurement accuracy is improved, but productivity decreases due to inability to measure during operation
Solution Approach 1:
The patent transforms the static weighing process into a dynamic measurement system. By using the vehicle dynamics model to continuously analyze torque profiles during vehicle operation, the system enables real-time weight measurement that adapts to changing vehicle conditions, thereby improving productivity while maintaining measurement accuracy through continuous data processing.
Solution Approach 2:
The patent ensures continuous weight measurement capability by processing torque profile data throughout vehicle operation. Instead of requiring intermittent stops for weighing, the system continuously analyzes torque data during normal vehicle use, maintaining measurement accuracy while eliminating interruptions to productivity through uninterrupted data collection and analysis.
Data Source
AI summary
Systems and methods for determining an estimated weight of a vehicle are provided. The system includes at least one data storage and at least one processor. The at least one data storage is configured to store vehicle data associated with the vehicle. The at least one processor is configured to: identify a plurality of vehicle maneuvers based on the vehicle data, each vehicle maneuver being associated with a portion of the vehicle data, each portion of the vehicle data comprising a measured torque profile; generate a plurality of simulated torque profiles for each vehicle maneuver; generate a plurality of error profiles, an error profile being generated for each vehicle maneuver based on differences between the plurality of simulated torque profiles and the measured torque profile corresponding to that vehicle maneuver; and determine the estimated weight of the vehicle based on the plurality of error profiles.