Adaptive Torque Converter Clutch Capacity Estimation
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Solution Overview
Problem
Existing hybrid vehicle systems with automatic transmissions and torque converter clutches face challenges in accurately determining torque converter clutch capacity, leading to suboptimal drivability under varying conditions.
Innovation Solution
A controller adjusts the torque converter clutch pressure based on estimated clutch capacity, using a model stored in memory, by applying a gain or offset to ensure impeller torque matches turbine speed during clutch disengagement, thereby improving clutch pressure control and estimation accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a static torque converter clutch model is used to determine clutch capacity, then the system is simple and acceptable for majority operating conditions, but vehicle drivability becomes suboptimal under varying conditions
Solution Approach 1:
The patent implements an adaptive clutch capacity model that dynamically adjusts the torque converter clutch capacity based on real-time operating conditions (impeller speed, turbine speed, clutch pressure). This transforms the static model into a dynamic one that continuously adapts to varying vehicle conditions, improving drivability while maintaining reasonable system complexity through structured adaptation algorithms.
Solution Approach 2:
The system employs feedback mechanisms by continuously monitoring impeller and turbine speeds, comparing actual clutch capacity with predicted capacity, and using the difference (error signal) to adapt the clutch capacity model. This closed-loop feedback enables the system to self-correct and optimize performance under varying operating conditions.
2Measurement precision
If clutch pressure is controlled based on static model predictions, then control implementation is straightforward, but accurate torque delivery becomes difficult under varying vehicle and ambient conditions
Solution Approach 1:
The clutch capacity model serves itself by using its own predictions and the observed system behavior to continuously improve its accuracy. The adaptive mechanism uses the difference between predicted and actual clutch capacity to automatically adjust model parameters, enabling the system to self-calibrate without external intervention.
Solution Approach 2:
The system changes the parameters of the clutch capacity model based on operating conditions. By adapting model parameters (such as clutch capacity coefficients) according to impeller speed, turbine speed, and temperature variations, the system maintains accurate torque delivery predictions across diverse vehicle and ambient conditions.
3Speed
If the torque converter clutch opens quickly, then response time is fast, but torque holes appear due to inaccurate capacity estimation
Solution Approach 1:
The system performs preliminary action by pre-adapting the clutch capacity model before clutch opening events. By continuously updating the model during normal operation and predicting the required clutch capacity for upcoming opening events, the system ensures accurate torque delivery control during rapid clutch transitions, preventing torque holes.
Data Source
AI summary
A hybrid vehicle includes an engine, an electric machine selectively coupled to the engine, a transmission having a torque converter impeller coupled to the electric machine and a torque converter clutch configured to selectively couple the impeller to a turbine, and a controller configured to control pressure of the torque converter clutch responsive to estimated clutch capacity, which is adjusted by the controller to equal impeller torque responsive to impeller speed exceeding turbine speed during clutch disengagement. A model of estimated torque converter clutch capacity may be stored in memory and adapted to actual clutch capacity by applying a gain or offset determined during opening of the clutch.