Onboard Vehicle Load Estimation for Center of Gravity Updates
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Solution Overview
Problem
Existing vehicle mass estimation methods do not accurately account for center of gravity location and moment of inertia, leading to severe issues in vehicle dynamics behavior, particularly due to the cost and complexity of additional sensors required for sensor-based methods and the limitations of model-based methods in estimating these parameters.
Innovation Solution
A system and method that utilize estimated vehicle mass and other CAN information, such as seat belt occupancy and fuel level, to update the moment of inertia and center of gravity location, employing recursive least square methods and prepopulated lookup tables to improve estimates and control vehicle systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor-based methods are used to estimate vehicle mass, then measurement precision is improved, but device complexity and cost increase due to additional sensors
Solution Approach 1:
The patent replaces physical sensors with a model-based estimation system that uses mathematical models and existing vehicle data (acceleration, torque, wheel velocity) to calculate vehicle mass and parameters, eliminating the need for additional sensors while maintaining estimation accuracy
Solution Approach 2:
The patent introduces a controller as an intermediary that processes existing vehicle data through mathematical models to derive mass and parameter estimates, acting as a mediator between available sensors and the required parameter information
2Device complexity
If model-based methods are used to estimate vehicle mass, then device complexity is reduced, but measurement precision deteriorates due to inability to accurately estimate center of gravity and moment of inertia
Solution Approach 1:
The patent makes the estimation system dynamic by continuously updating mass, center of gravity, and moment of inertia values as the vehicle operates, allowing the model to adapt to changing vehicle conditions and loads rather than using static initial values
Solution Approach 2:
The patent implements feedback mechanisms where the controller continuously monitors vehicle parameters and uses the estimated mass and load information to update the vehicle model, creating a closed-loop system that improves estimation accuracy over time
Solution Approach 3:
The patent changes the approach from estimating only mass to simultaneously estimating mass, center of gravity location, and moment of inertia by incorporating load value calculations that consider fuel level and seat occupancy, providing comprehensive parameter updates
3Measurement precision
If vehicle mass estimation is performed continuously, then measurement precision is improved, but use of energy increases due to computational requirements
Solution Approach 1:
The patent performs preliminary calculations by pre-populating lookup tables with moment of inertia and center of gravity data for different load conditions, allowing the controller to quickly retrieve pre-computed values rather than performing complex real-time calculations during vehicle operation
Data Source
AI summary
A method for vehicle mass estimation includes setting a vehicle mass value to an initial value and a driving resistance force value to an initial value, receiving at least a longitudinal acceleration value, driving/braking torque on each axle/wheel, and an angular wheel velocity value, and estimating a driving resistance force value based on the vehicle mass value and the angular wheel velocity value. The method also includes setting the driving resistance force value to the estimated driving resistance force value and determining a fuel level value and a seat occupancy value for at least one seat of an associated vehicle. The method also includes estimating, using the fuel level value and the seat occupancy value, a vehicle load value, and setting, based on the vehicle load value, at least one of a center of gravity value of the vehicle and a moment of inertia value of the vehicle.