Solenoid Valve Transfer Characteristic Learning
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Solution Overview
Problem
Existing fluid pressure control systems in automotive applications, such as automatic transmissions, face challenges in accurately controlling solenoid-operated valves due to significant part-to-part variations and changes over time, leading to instability and poor performance, as conventional methods rely on static P-I maps and complex curve-fitting algorithms that are not suitable for real-time, embedded controllers.
Innovation Solution
A dynamic learning system that adjusts the default transfer characteristic of solenoid-operated valves based on observed operating points, using circular buffers to organize partial data and selectively realign control points, allowing for accurate feed-forward control signals and reduced output errors, even with limited computing resources and memory.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If extensive characterization strategies are employed to develop accurate P-I data tables, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The patent applies preliminary action by developing and storing a default P-I map during manufacturing that captures the general transfer characteristic. This pre-characterization provides a baseline that works for most solenoids, eliminating the need for complex real-time characterization systems while maintaining acceptable accuracy for the majority of cases.
Solution Approach 2:
The patent employs feedback by continuously monitoring the actual output pressure and comparing it with the desired pressure. The difference (error signal) is used to adjust the control current in real-time, compensating for deviations from the default P-I map without requiring complex pre-characterization of each individual solenoid.
2Device complexity
If static P-I maps are used for control, then device complexity is reduced, but reliability deteriorates due to part-to-part variations and changes over time
Solution Approach 1:
The patent applies dynamics by implementing a learning mechanism that continuously updates the P-I map during system operation. Instead of relying on a fixed static map, the system adapts to individual solenoid characteristics and changes over time (such as temperature effects or wear) by dynamically adjusting the transfer characteristic data based on observed performance.
Solution Approach 2:
The patent uses feedback to monitor actual pressure output and compare it with expected values from the P-I map. When deviations are detected, the system adjusts the control signals and updates the P-I map accordingly, ensuring reliable pressure control despite part-to-part variations or aging effects.
3Manufacturing precision
If complex curve fitting algorithms are used for real-time calibration, then manufacturing precision is improved, but productivity decreases due to computing resource requirements
Solution Approach 1:
The patent applies partial action by implementing a simplified learning mechanism that updates only the necessary portions of the P-I map based on observed operating conditions. Rather than performing complete curve fitting across the entire operating range, the system makes targeted adjustments to specific regions of the P-I map, reducing computational burden while maintaining accuracy where it matters most.
Solution Approach 2:
The patent uses a simplified, computationally inexpensive learning mechanism that can be executed quickly on embedded controllers. Instead of relying on heavy computational algorithms, the system employs straightforward update rules that require minimal processing power, making them suitable for real-time implementation in resource-constrained automotive environments.
Data Source
AI summary
In a pressure control system having a solenoid-operated fluid valve that has an output hydraulic pressure which varies in accordance with a solenoid input signal, a dynamic learning block is configured to adjust the initial, default values for control points stored in a pressure-current (P-I) data table based on observed (measured) operating points that reflect the solenoid's actual transfer characteristic. A feed forward control block is configured to generate the solenoid input signal having a level based on the adjusted control points in the data table, which improves the accuracy of the solenoid input signal. An adjustment method uses a plurality of circular buffers each configured to store observed operating points falling within a respective range, and provides a mechanism to allow adjustment of the control points based on only partial data.