Short-Term Driving Tendency Index for Shift Control
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Solution Overview
Problem
Conventional systems fail to accurately reflect a driver's short-term driving tendency, leading to dissatisfaction due to assumptions of constant driving behavior, which changes with feelings, road conditions, and other factors, resulting in inappropriate shift control.
Innovation Solution
A method and system that determine a short-term driving tendency using input variables like accelerator pedal position, vehicle speed, and road gradient, applying fuzzy rules to calculate a short-term driving tendency index, allowing precise control of the shift based on current driving conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If long-term learning methods are used to determine driving tendency, then the system can capture overall driving patterns, but it cannot reflect short-term changes in driver will due to temporary feelings or road conditions
Solution Approach 1:
The patent divides driving tendency determination into two independent modules: long-term learning module that captures overall driving patterns, and short-term determination module that responds to immediate driving conditions. This segmentation allows each module to specialize in its time scale without interference, resolving the contradiction between capturing overall patterns and responding to short-term changes.
Solution Approach 2:
The system dynamically switches between long-term learned tendencies and short-term determined tendencies based on current driving conditions. When short-term conditions (accelerator pedal position, vehicle speed, gradient) indicate a change in driver will, the system prioritizes short-term determination over long-term learning results, enabling adaptive response to temporary feelings or road conditions.
2Stability of the object's composition
If conventional systems control shift based on learned driving tendency, then they maintain consistent vehicle behavior, but they fail to differentiate between driver pushing accelerator for uphill driving versus speed increase
Solution Approach 1:
The patent introduces short-term driving tendency determination as an intermediary layer between raw sensor inputs (accelerator pedal position, vehicle speed, gradient) and shift control decisions. This intermediary analyzes current driving context to distinguish between uphill driving and speed increase scenarios, preventing wrong shift control while maintaining overall vehicle behavior consistency through the long-term learning foundation.
3Device complexity
If the system assumes constant driving tendency, then control logic is simplified, but it cannot adapt to temporary changes in driver feeling or road condition
Solution Approach 1:
The system implements dynamic adaptability by allowing driving tendency to change between long-term learned values and short-term determined values based on current conditions. This dynamic approach enables the system to adapt to temporary changes in driver feeling or road condition without requiring complete relearning, maintaining reasonable control logic complexity while improving adaptability.
Data Source
AI summary
A method of determining a short term driving tendency and a system of controlling shift using the same that reflects precisely a will of a driver on the shift by determining a short term driving tendency is disclosed. The method may include detecting input variables, determining whether determination condition of the short term driving tendency is satisfied, calculating tendencies and output membership function values according to a plurality of fuzzy rules based on the input variables if the determination condition of the short term driving tendency is satisfied, and determining a short term driving tendency index based on the tendencies and the output membership function values according to the plurality of fuzzy rules.