Vehicle Mass Estimation via Dynamic Force Balance
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Solution Overview
Problem
Existing methods for estimating vehicle mass are inaccurate due to noise in speed signals and variations in vehicle loading, leading to suboptimal vehicle performance under different conditions.
Innovation Solution
A method that uses existing vehicle hardware to estimate mass by detecting changes in acceleration and recording data points during specific events, applying equations to calculate more accurate mass estimates, and updating the mass estimate based on drive and brake forces, aerodynamic forces, and acceleration measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If vehicle mass is fixed at a particular value in the control system, then the control system is simple to implement, but the vehicle performance is suboptimal under varying load conditions
Solution Approach 1:
The patent implements dynamic mass estimation by continuously calculating vehicle mass using real-time acceleration data from the accelerometer and force data from the powertrain controller. The mass estimate is updated based on the equation M = (Fd - Fb - Fa - Fr) / ax, where Fd is drive force, Fb is brake force, Fa is aerodynamic force, Fr is rolling resistance force, and ax is longitudinal acceleration. This dynamic approach allows the control system to adapt to varying load conditions while maintaining reasonable complexity.
2Measurement precision
If acceleration is measured using speed data at close time intervals, then acceleration can be determined, but the acceleration signal is buried in noise
Solution Approach 1:
The patent uses the powertrain controller as an intermediary to obtain force data (drive force, brake force, aerodynamic force, rolling resistance force) that mediates the acceleration calculation. Instead of directly differentiating noisy speed signals, the system calculates acceleration indirectly through the force balance equation, where the accelerometer provides a separate measurement that validates and refines the mass estimation without requiring direct differentiation of noisy speed data.
Solution Approach 2:
The system implements feedback by continuously comparing the acceleration measured by the accelerometer with the acceleration calculated from force data and mass estimates. This feedback loop allows the system to refine the mass estimate over time and filter out noise by relying on the more reliable accelerometer measurement rather than noisy speed signal differentiation.
3Measurement precision
If vehicle mass estimation varies with loading and configuration, then the estimation reflects actual conditions, but the determination becomes difficult to predict with minimal error
Solution Approach 1:
The patent makes the existing powertrain controller and accelerometer serve multiple functions: the powertrain controller not only controls engine/power output but also provides force data for mass estimation, and the accelerometer not only measures acceleration for control but also provides validation for mass estimation. This multi-functionality reduces device complexity while improving mass estimation accuracy across varying load conditions.
Data Source
AI summary
A method for estimating the mass of a vehicle system includes a number of steps including a first step of providing a vehicle system having at least a powertrain and a vehicle control module. Three different mass estimates are assigned with the last mass estimate being the most accurate. The mass estimates are used in the vehicle control module calculations for vehicle control parameters in the event that the weight of the vehicle changes.