Gearshift Controller Calibration With Model-Based Learning
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Solution Overview
Problem
Current automated calibration methods for gearshift controllers in automatic transmissions require a large number of gearshifts and are not effective for adaptation during normal driving due to their reliance on design-of-experiments approaches and rule-based adaptive policies, which are inefficient and unable to account for system changes over time.
Innovation Solution
A model-based learning method that reduces the number of gearshifts needed for calibration by using a sequence of gearshifts performed multiple times, averaging sensor data, and updating control parameters through learning controllers to adapt to changing conditions, allowing for automated calibration and adaptation during vehicle operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If design-of-experiments approach is used for calibration, then calibration can be performed in controlled lab environment, but the number of gearshifts required increases dramatically
Solution Approach 1:
The patent applies preliminary action by pre-defining multiple sequences of gearshifts that cover various operating conditions before actual calibration begins. These pre-planned sequences allow the calibration system to efficiently test multiple scenarios without requiring extensive real-time decision-making, thereby reducing the total calibration time while maintaining comprehensive coverage of transmission operating conditions.
Solution Approach 2:
The patent implements periodic action by repeating gearshift sequences multiple times under different operating conditions. Instead of performing each gearshift once, the system cycles through predefined sequences periodically, collecting data across multiple iterations to optimize calibration parameters. This periodic repetition enables efficient data collection and parameter optimization without requiring an excessive number of unique test scenarios.
2Measurement precision
If design-of-experiments approach is used for calibration, then objective evaluation of shift quality is achieved, but the method cannot adapt to system changes over time
Solution Approach 1:
The patent applies feedback by continuously monitoring actual shift quality metrics during gearshift operations and using this information to adjust calibration parameters in real-time. The system measures objective shift quality indicators such as shift duration, torque transfer characteristics, and vibration levels, then feeds this data back to the optimization algorithm. This closed-loop feedback mechanism enables the system to adapt to changing transmission conditions and wear over time while maintaining objective evaluation standards.
Solution Approach 2:
The patent implements dynamics by transitioning from static, pre-programmed test sequences to a dynamic calibration approach where test parameters and evaluation criteria can adapt based on observed system behavior. The calibration system dynamically adjusts operating conditions, gearshift timing, and evaluation thresholds based on real-time sensor data and system response, enabling both objective measurement and adaptation to system changes.
3Adaptability or versatility
If transmission has more speeds (8, 9, 10 speeds), then transmission capability is improved, but calibration effort increases significantly
Solution Approach 1:
The patent applies segmentation by dividing the calibration process into distinct modules, each handling specific gearshift sequences and operating condition ranges. Instead of attempting to calibrate all gearshifts simultaneously, the system segments the transmission operation into manageable sequences (e.g., low-speed sequences, high-speed sequences, transition sequences) that can be calibrated independently and then integrated. This segmentation reduces the overall calibration complexity for multi-speed transmissions by breaking down the large calibration space into smaller, more manageable subsets.
Data Source
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AI summary
Methods for automated calibration and adaption of a gearshift controller (39) are disclosed. In one aspect, the method automates calibration a gearshift controller (39) for controlling a sequence of gearshifts in either a stepped automatic transmission equipped with at least one speed sensor mounted on a dynamometer (42) or an automotive vehicle mounted on a dynamometer (42), where the dynamometer (42) is electronically controlled by a dynamometer controller (43). Each gearshift in the sequence includes a first phase, a second phase,... and an Nth phase. The gearshift controller (39) includes (initial values of) a first phase control parameters set, a second phase control parameters set,... and an Nth phase control parameters set for each gearshift in the sequence that are updated using a first phase learning controller, a second phase learning controller,... and an N*11 phase learning controller respectively.