Crankshaft Sensor Threshold Adaptation for Stop-Go Vehicles
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Solution Overview
Problem
Crankshaft sensors in vehicles equipped with the 'stop & go' function face challenges in accurately determining the position of the crankshaft during restarts, especially due to vibrations and thermal drift, leading to inaccurate detection thresholds and reduced precision.
Innovation Solution
A method to adapt the detection threshold of crankshaft sensors by detecting the stopping of the engine, measuring signal variations over intervals, and calculating new thresholds to account for thermal drift, allowing for precise detection from the first rising front after restart.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the detection threshold is fixed based on initial signal extrema, then the device complexity is reduced, but the measurement precision deteriorates due to thermal drift during engine stop periods
Solution Approach 1:
The detection threshold is transformed from a static fixed value to a dynamic adaptive value that automatically adjusts to signal drift. The system continuously monitors signal extrema during engine operation and updates the threshold accordingly, ensuring it remains aligned with the actual signal characteristics even after thermal drift occurs during stop periods.
Solution Approach 2:
The system uses its own signal output to automatically recalibrate the detection threshold without external intervention. By detecting signal extrema from the crankshaft sensor itself during engine restart, the system self-adjusts the threshold parameter, eliminating the need for external calibration equipment or manual adjustment.
2Measurement precision
If the detection threshold is adapted continuously, then the measurement precision is improved, but the device complexity and processing time increase
Solution Approach 1:
Instead of continuous adaptation, the system performs threshold adjustment periodically at specific events - namely at engine restart moments. The controller detects when the engine stops and restarts, then triggers the threshold recalculation process at these discrete intervals, balancing precision needs with processing efficiency.
Solution Approach 2:
The system prepares for threshold adaptation by continuously monitoring and storing signal extrema values during engine operation. When engine restart is detected, the previously stored signal characteristics are already available, allowing rapid threshold recalculation without requiring extensive real-time processing during the critical restart phase.
3Productivity
If the engine restarts quickly to reduce fuel consumption and emissions, then the loss of time and energy is reduced, but the measurement precision deteriorates due to insufficient time for threshold adaptation
Solution Approach 1:
The system performs preliminary monitoring of signal extrema during the engine stop period before restart occurs. This advance preparation ensures that when restart happens, the threshold adaptation can be immediately executed using pre-captured signal characteristics, eliminating the need for delayed restart waiting.
Solution Approach 2:
The system implements feedback by continuously monitoring the crankshaft sensor signal and using the detected extrema to automatically adjust the detection threshold. This closed-loop approach ensures that even during rapid restart, the threshold is optimally adapted based on actual signal conditions, maintaining precision without requiring extended adaptation time.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method enables optimized engine restarts with improved precision and reduced fuel consumption and pollutant emissions by adapting the detection threshold to new signal extrema, ensuring accurate detection of the crankshaft position from the first tooth after restart.
Implementation Method 1
a magnetic field generator (for example: a permanent magnet), a magnetic field detection means (Hall effect cell, magnetoresistive (MR) cell, giant magnetoresistive (GMR) cell, etc.
Implementation Method 2
magnetic field detection means (Hall effect cell, magnetoresistive (MR) cell, giant magnetoresistive (GMR) cell, etc.
Data Source
AI summary
Disclosed is a method for adapting a detection threshold (S1) of a magnetic field sensor for a crankshaft of a motor vehicle equipped with the “stop & go” function, the sensor delivering a signal (B) of variations of magnetic field having two states, such as: State 1: when the crankshaft is rotating: the signal includes rising fronts and falling fronts, State 2: when the crankshaft is stopped: the signal has an aperiodic progressive drift (ΔTAR). The method includes for state 2 steps making it possible to estimate the variation (Δ1, Δ2, Δ3, Δ4 . . . Δi) of the value (V1, V2 . . . Vi) of the signal (B) during the stopped phase of the crankshaft in order to adapt the detection threshold (S1) to a new value (S4) applicable for the detection of the first tooth upon restart of the engine (R).