Vehicle Transmission Torque Estimation Using Adaptive Nonlinear Functions
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Solution Overview
Problem
Existing vehicle transmission control systems face challenges in accurately and adaptively estimating torque values, particularly during shift events, due to reliance on quasi-static nonlinear models with multiple functions that are difficult to adjust when estimates deviate from measured values.
Innovation Solution
A method and system for controlling vehicle transmissions using a first torque estimate defined by a single nonlinear function of a transmission parameter, which is modified based on measured torque values outside of shift events, allowing for adaptive learning and improved accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple nonlinear functions are used in the torque estimation model, then the model can capture complex transmission behavior, but the model becomes difficult to adjust and adapt when estimates deviate from measured values
Solution Approach 1:
The patent segments the torque estimation problem by separating the static nonlinear model from the adaptive correction mechanism. The static model uses multiple nonlinear functions to capture complex transmission behavior, while the adaptive mechanism independently adjusts parameters based on measured data, making the overall system adjustable despite the complexity of the underlying model.
Solution Approach 2:
The patent implements parameter changes by periodically updating the nonlinear model parameters using measured torque data. Instead of changing the functional form of the model, the system adjusts the parameters of the existing nonlinear functions through adaptive techniques, allowing the model to adapt to varying operating conditions while maintaining its structural complexity.
2Reliability
If adaptive modeling techniques are implemented to improve torque estimates, then estimation accuracy can be periodically improved, but the adjustment process becomes complex when multiple nonlinear functions are involved
Solution Approach 1:
The patent implements feedback by continuously comparing measured torque values with estimated torque values and using the difference to adjust model parameters. This feedback loop enables the system to periodically improve estimation accuracy by learning from actual transmission behavior, while the feedback mechanism itself remains relatively simple despite the complexity of the underlying nonlinear model.
Solution Approach 2:
The system performs self-service by automatically adjusting its own parameters based on measured data without requiring manual intervention. The adaptive modeling technique enables the torque estimation model to self-correct and improve its accuracy over time by utilizing the difference between measured and estimated values to update its parameters autonomously.
3Ease of operation
If a single nonlinear function is used for torque estimation, then the model becomes easier to adjust adaptively, but the model may lack the capability to accurately represent complex transmission behavior
Solution Approach 1:
The patent applies dynamics by making the model parameters time-varying and adaptive. While the functional form remains relatively simple, the parameters of the nonlinear function are continuously updated based on measured data, allowing the model to adapt to changing transmission conditions. This dynamic parameter adjustment compensates for the simplicity of the functional form and maintains estimation accuracy.
Solution Approach 2:
The patent utilizes parameter changes by periodically updating the nonlinear function parameters based on the difference between measured and estimated torque values. This approach allows a relatively simple functional form to achieve accurate torque estimation by adapting its parameters to match actual transmission behavior under varying operating conditions.
Data Source
AI summary
A control system for a vehicle transmission includes a controller configured to output a first torque estimate defined in terms of one nonlinear function of a transmission parameter for a particular value of the transmission parameter. The controller also receives a measured torque of the transmission at the particular value of the transmission parameter, and outputs a modified torque estimate for the particular value of the transmission parameter based on the measured torque.