Agricultural Driver Assistance with Adaptive Process Model Control
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Solution Overview
Problem
Existing driver assistance systems for agricultural machinery, such as combine harvesters, struggle to quickly adapt to abrupt changes in harvesting conditions and fail to recognize recurring similar process behaviors, leading to inefficiencies and suboptimal performance.
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 these sub-models, and utilizing adaptation phases based on available data to optimize working and quality parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a map-based optimization approach is used to determine optimized working parameters, then optimized parameters can be quickly determined under homogeneous harvesting conditions, but the system exhibits inertia and cannot quickly adapt to rapidly changing harvesting conditions
Solution Approach 1:
The patent applies dynamics by making the process model adaptive and updatable in real-time. The system transitions from a static map-based approach to a dynamic model that continuously learns from new data, allowing it to adapt its structure and parameters as harvesting conditions change, thereby resolving the contradiction between quick determination and adaptability
Solution Approach 2:
The patent changes the parameters of the process model itself, not just the operating parameters. By updating the mathematical relationships and structure of the process model based on new harvesting data, the system can quickly determine optimized parameters while adapting to changing conditions, eliminating the inertia of fixed map-based systems
2Adaptability or versatility
If the entire stored characteristic map is constantly updated to enable rapid adaptation to changing process conditions, then the system can react dynamically to new conditions, but the adaptation process takes too long and dwell times are extended
Solution Approach 1:
The patent segments the process model into modular components that can be updated independently. Rather than constantly updating the entire characteristic map, the system updates specific segments or parameters of the model as needed, enabling rapid adaptation without the time penalty of complete model reconfiguration
Solution Approach 2:
The patent applies partial action by updating only the necessary portions of the process model rather than the entire model. This selective updating approach allows the system to adapt to changing conditions quickly by modifying only the relevant parameters and relationships, avoiding the excessive time required for complete model updates
3Manufacturing precision
If a complex process model is used to accurately describe process relationships, then optimization results improve with sufficient data, but the system requires too much data and time to robustly adapt
Solution Approach 1:
The patent makes the model complexity dynamic, allowing the system to adjust the level of model detail based on data availability. When data is limited, the system uses a simpler model structure that can adapt quickly; when sufficient data is available, it transitions to a more complex model that provides higher precision optimization results, thus resolving the contradiction between accuracy and data requirements
Data Source
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AI summary
The invention relates to an agricultural machine (1) comprising a driver assistance system (45) which is designed and configured to automatically optimize and adjust working parameters (44, 50a..i) and quality parameters (49, 49a) of the agricultural machine (1), wherein a process model (47) comprising characteristic curve fields (48) is assigned to the driver assistance system (45), such that an optimization method (56) to be implemented by the driver assistance system (45) is designed as a characteristic curve control (57) and the optimization method (56) generates optimized working parameters (44, 50a..i) as a control variable (51) and the driver assistance system (45) adjusts the working parameters (44, 50a..i) depending on the optimized working parameters (44, 50a..i).i) determines the quality parameters (49, 49a) of the agricultural machinery (1), wherein the process model (47) comprises a basic process model (58) and an associated affine output layer (59), wherein the basic process model (58) and the affine output layer (59) form sub-models (60) of the process model (47), and the basic process model (58) is set up and configured to map the relationships of a multitude of process parameters (61) in characteristic fields to generate an optimized quality parameter (49, 49a), and the affine output layer (59) is configured and configured to define the respective quality parameter (49, 49a) as a function of two process parameters (61).