Driveline Controller Adaptability via Dynamic Control Map
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Solution Overview
Problem
Existing vehicle driveline controllers struggle to provide high maneuverability across various duty cycles and accommodate different operator driving styles, particularly in off-highway vehicles with hydrostatic transmissions, as they fail to adapt control strategies effectively to changing conditions and operator preferences.
Innovation Solution
A controller with an adaptable control map that receives input signals from multiple sources, extracts features indicative of duty cycles and operator styles, and adjusts control commands accordingly, enhancing sensitivity and responsiveness based on real-time data from input devices and driveline conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed control map is used in the driveline controller, then the control strategy is simple and reliable, but the system cannot adapt to different duty cycles and operator driving styles, reducing maneuverability and versatility
Solution Approach 1:
The control map is transformed from a static fixed structure to a dynamic adaptable structure that can change its parameters based on detected features. The controller continuously monitors input signals, extracts duty cycle and driving style features, and adjusts control map parameters in real-time to match current operating conditions and operator preferences.
Solution Approach 2:
The invention changes the parameters of the control map based on extracted features. By modifying control map parameters according to detected duty cycles and operator driving styles, the system achieves adaptability without requiring a completely new controller architecture, thus balancing versatility with manageable complexity.
2Ease of operation
If the control map is made adaptable to different conditions, then maneuverability and performance are improved, but the control system complexity and difficulty of calibration increase
Solution Approach 1:
The controller performs self-calibration by automatically extracting features from input signals and adjusting control map parameters without requiring external intervention. The system monitors its own operation, identifies duty cycles and driving styles, and autonomously adapts the control map, eliminating the need for manual recalibration and reducing operational complexity.
Solution Approach 2:
The system implements continuous feedback by monitoring input signals, extracting features related to duty cycle and operator style, and using this information to adjust control map parameters. This closed-loop feedback mechanism enables the controller to maintain optimal performance across varying conditions while keeping the adaptation process automated and manageable.
3Adaptability or versatility
If multiple input signals are processed to extract features for adaptation, then the adaptability and responsiveness are enhanced, but the processing time and computational load increase
Solution Approach 1:
The system extracts only the essential features from multiple input signals that are most relevant to duty cycle identification and driving style detection. By focusing on key features rather than processing all signal data equally, the controller achieves high adaptability while minimizing computational overhead and processing time.
Solution Approach 2:
The controller processes input signals at different levels of detail based on current needs. For routine operations, only essential features are extracted to minimize processing time. When adaptation is more critical, additional feature extraction is performed. This selective processing approach balances responsiveness with acceptable processing delays.
Data Source
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AI summary
The invention relates to a controller (3) for controlling a vehicle driveline (100), in particular a driveline (100) comprising a hydrostatic transmission (17), wherein the controller (3) is configured to: output a control command (19) for controlling at least one driveline component (4) according to a control map (5), the control map (5) defining a dependence of the control command (19) on at least one of: a control position of an input device (2), and at least one first condition of the driveline (100); receive at least one input signal (8, 18), the input signal (8, 18) comprising a plurality of signal values recorded at different times, wherein the signal values of the at least one input signal (8, 18) are indicative of at least one of: the control position of the input device (2), the at least one first condition of the driveline (100), and at least one second condition of the driveline (100); derive a feature (27a, 27b, 28a, 28b; 35a, 35b, 36a, 36b) from the plurality of signal values; and adapt the control map (5) based on the derived feature (27a, 27b, 28a, 28b; 35a, 35b, 36a, 36b). The invention further relates to a vehicle driveline (100) including said controller (3) and to a method of calibrating a controller (3) for controlling a vehicle driveline (100).