Hydraulic Drive Load Collective Scaling for Variable-Speed Networks
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Solution Overview
Problem
Designing an optimized load collective for a variable speed drive network in hydraulic machines is challenging due to complex and varying actuator loads, especially in machines used for multiple tasks.
Innovation Solution
A method involving multiple measurement sets for speed and force from hydraulic machine operations, extraction of a generalized motion pattern, and selection of scaling parameters to adhere to required maximum values, ensuring optimized load collective for variable speed drive networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If variable-speed pump/motor technology is used in networked drive systems, then energy efficiency is improved and component downsizing is enabled, but the complexity of drive design increases due to mapping from actuator loads to drive loads
Solution Approach 1:
The patent applies parameter changes by systematically varying scaling factors for time, piston stroke, and load parameters to transform measured actuator load data into optimized drive load collectives. This allows the complex mapping from actuator loads to drive loads to be resolved through controlled parameter transformation, maintaining energy efficiency while managing design complexity through structured parameter adjustment.
2Ease of manufacture
If drive systems are sized based on maximum actuator loads, then simple sizing is achieved, but the drive size is oversized for networked systems where loads are combined
Solution Approach 1:
The patent applies preliminary action by measuring and analyzing actual actuator load patterns before finalizing drive system sizing. Instead of directly using maximum actuator loads, the method first collects operational data, extracts motion patterns, and then determines appropriate scaling factors to create an optimized load collective that accurately represents combined drive loads, enabling precise sizing before manufacturing.
Solution Approach 2:
The patent applies dynamics by transforming static maximum load values into dynamic load collectives that capture the temporal and operational characteristics of actual machine usage. Through scaling factors applied to time, stroke, and load parameters, the system adapts the load representation to reflect real-world operational variability, enabling drives to be sized for actual rather than theoretical maximum conditions.
3Manufacturing precision
If multiple measurement sets and generalized motion patterns are used to optimize load collective, then drive system sizing is improved, but the time and complexity of the design process increases
Solution Approach 1:
The patent applies copying by creating a generalized motion pattern that replicates the essential characteristics of multiple measured load cycles. Instead of analyzing each individual measurement set separately, the method synthesizes a representative composite pattern that captures the dominant operational features, significantly reducing analysis time while maintaining the precision needed for optimal drive system sizing.
Data Source
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AI summary
The invention relates to a computer implemented method for finding an optimized load collective for a variable speed drive network of a hydraulic machine comprising multiple cylinder pistons, the optimized load collective being selected from a set of load collectives, the method of selecting the optimized load collective comprising the steps of: - Obtaining multiple measurement sets (S10) for both speed and force for each piston from a hydraulic machine executing one or several specific task(s) under defined work conditions; - Obtaining required maximum values for piston's speed, force, and power, either predetermined or on the basis of the measurement sets; - Extracting a generalized motion pattern (S12) from the measurement sets; - Creating scaled cycles based on generalized motion pattern using a physical simulation model of the hydraulic machine; and - Selecting scaling parameters to adhere to and to represent required maximum values.