Agricultural Driver Assistance with Adaptive Harvest Parameter Control
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Solution Overview
Problem
Existing driver assistance systems for agricultural work machines struggle to quickly adapt to abrupt changes in harvesting conditions and recognize repetitive similar process behavior, leading to inefficiencies and prolonged adjustment times.
Innovation Solution
A driver assistance system with a process model comprising a basic process model and an affine output layer, allowing for rapid adaptation to changing conditions by independently activating or executing these submodels, and switching between different adaptation phases based on available data and process information to optimize work and quality parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a driver assistance system uses traditional optimization methods to determine work parameters, then the system can optimize harvesting operations, but the system cannot quickly adapt to abrupt changes in harvesting conditions
Solution Approach 1:
The patent implements a dynamic adaptation mechanism where the driver assistance system continuously monitors harvesting conditions and automatically adjusts work parameters in real-time. The system transitions from static pre-programmed optimization to dynamic real-time optimization, enabling quick response to abrupt changes in crop conditions, weather, or machine state without requiring manual reconfiguration.
Solution Approach 2:
The system incorporates feedback loops that continuously monitor actual harvesting performance and compare it against target parameters. When deviations are detected, the system automatically adjusts work parameters based on the feedback signal, creating a closed-loop control system that rapidly adapts to changing conditions while maintaining optimal harvesting efficiency.
2Measurement precision
If the driver assistance system processes all available data to optimize work parameters, then optimization accuracy improves, but the processing time and computational complexity increase
Solution Approach 1:
The patent segments the data processing into distinct modules: sensor data acquisition, feature extraction, optimization calculation, and actuation. This segmentation allows each module to process specific data types independently, improving overall system efficiency while maintaining high optimization accuracy through specialized processing of critical parameters.
Solution Approach 2:
The system applies partial processing by selectively analyzing only the most critical data parameters relevant to current harvesting conditions rather than processing all available data uniformly. The system identifies and processes only the essential features needed for optimal work parameter determination, reducing computational burden while maintaining sufficient accuracy for effective optimization.
Data Source
AI summary
An agricultural work machine comprising a driver assistance system. The driver assistance system is configured to automatically optimize and adjust work parameters and quality parameters of the agricultural work machine. The driver assistance system is assigned a process model comprising characteristic maps such that an optimization method implemented by the driver assistance system comprises a characteristic map control generating optimized work parameters as a control variable. The driver assistance system determines the quality parameters of the agricultural work machine depending on the optimized work parameters. The process model comprises a basic process model and an affine output layer assigned thereto, forming submodels. The basic process model is configured to map relationships between a plurality of process parameters in the characteristic maps for generating an optimized quality parameter, and the affine output layer is configured to define the particular quality parameter depending on two process parameters.