Axial Piston Pump Control Modeling for Safe Operating Region Expansion
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Solution Overview
Problem
Existing axial piston pumps exhibit unpredictable operating behaviors due to variations in production tolerances, leading to uncertain safe and unsafe operating points, which can result in faults and damage without clear division of the operating space.
Innovation Solution
A method involving a control model and a safety model is employed to determine control model parameters, where the safety model assesses the probability of safe operation at each point, and additional operating points are selected to maximize variance and ensure fault-free operation, gradually expanding the known safe operating space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If production tolerances vary within limits, then manufacturing flexibility is improved, but operating behavior becomes unpredictable and safe operating points cannot be clearly identified
Solution Approach 1:
The patent applies preliminary action by conducting virtual testing of the axial piston pump across a comprehensive grid of operating points before actual deployment. This pre-characterization of safe operating regions, performed in advance using simulation models, allows the system to anticipate and avoid unsafe operating conditions without requiring real-time complex analysis during actual operation.
Solution Approach 2:
The patent uses copying by creating a virtual twin model of the axial piston pump that replicates its physical behavior. This digital copy is used to perform extensive testing and determine safe operating regions without physically testing every possible operating point, thereby resolving the contradiction between manufacturing flexibility and operational predictability.
2Reliability
If the operating space is fully explored to identify safe regions, then operational safety is improved, but the complexity of determining control parameters increases
Solution Approach 1:
The patent applies segmentation by dividing the continuous operating space into discrete operating points arranged in a grid structure. This segmentation allows systematic exploration of safe regions through a manageable set of discrete test cases, transforming the complex continuous optimization problem into a more tractable discrete evaluation problem while maintaining comprehensive safety coverage.
Solution Approach 2:
The patent performs the complex determination of safe operating regions in advance through virtual testing, before the actual control system is deployed. This preliminary characterization eliminates the need for complex real-time analysis during operation, reducing operational complexity while ensuring safety.
3Reliability
If additional operating points are added to expand safe operating region, then operational safety is improved, but the time required for model adjustment increases
Solution Approach 1:
The patent determines safe operating regions and updates control models in advance through virtual testing before actual deployment. This preliminary action eliminates the need for time-consuming real-time model adjustment during operation, as the safe operating regions are pre-characterized and stored for direct use during actual pump operation.
Data Source
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AI summary
The invention relates to a method for determining control model parameters of a control model of an axial piston pump (2). The method models at least one control variable (lA, IB) of an adjustment unit (13) of the axial piston pump as a function of operating variables, with operating points of the axial piston pump each being characterised by operating values of the operating variables, the method comprising: providing (110) initial control model parameters of the control model and an operating state set comprising a plurality of initial first operating points; providing (120) initial safety model parameters of a safety model on the basis of a safety set comprising a plurality of initial second operating points and associated safety values; executing the following steps at least once: determining (130) a further operating point which is not yet included in the operating state set, the further operating point being determined such that a variance of the control model is maximised, on the condition that a likelihood obtained by the safety model that error-free operation at the further operating point is not possible is less than or equal to a predefined safety threshold; updating (140) the operating state set and the control model parameters and updating (145) the safety set and the safety model parameters under consideration of the further operating point.