Drive Controller Configuration Using RPM Loop Digital Twins
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Solution Overview
Problem
Existing controller optimization methods for complex drive systems are labor-intensive, require expert knowledge, and result in significant downtime due to the need for manual adjustments and continuous monitoring, especially when load configurations change.
Innovation Solution
A method using simulation models to determine controller configurations based on real measurements of the RPM speed control loop, creating a digital representation of the drive system to optimize controller settings without interrupting normal operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual optimization by specialists is performed, then controller settings can be optimized for specific mechanical behavior, but the process becomes very labor-intensive and time-consuming
Solution Approach 1:
The patent creates a digital twin (simulation model) that copies the physical drive system's mechanical behavior. This virtual model can be optimized repeatedly without affecting the actual system, eliminating the need for time-consuming manual iterations on the real machine while maintaining optimization precision.
Solution Approach 2:
The patent performs preliminary identification of the mechanical system's transfer function by measuring the drive system once, then uses this pre-acquired data to populate the simulation model. This preliminary action eliminates the need for repeated measurements and optimizations on the actual machine, significantly reducing downtime.
2Manufacturing precision
If iterative measurements and adjustments are performed on the actual machine, then controller settings can be optimized, but production downtime occurs
Solution Approach 1:
The patent transfers the optimization process to a digital twin that replicates the physical system's behavior. All iterative measurements and adjustments are performed in the virtual environment, completely eliminating production downtime while maintaining tuning accuracy through the faithful reproduction of mechanical characteristics.
Solution Approach 2:
The simulation model acts as an intermediary between the controller and the physical drive system. It mediates the optimization process by allowing virtual testing and adjustment without direct interference with the actual production system, thus maintaining both accuracy and productivity.
3Adaptability or versatility
If a common controller configuration is sought for different load configurations, then versatility is improved, but validation becomes very laborious as testing must be performed for all load configurations
Solution Approach 1:
The patent creates a universal simulation model that can represent multiple load configurations and operating conditions. This single virtual model serves multiple functions by allowing testing and validation across all possible scenarios without requiring separate physical tests for each configuration, thus achieving versatility without proportional increases in validation time.
Solution Approach 2:
The patent performs excessive virtual testing in the simulation environment by evaluating the common controller configuration against all possible load configurations and edge cases. This exhaustive virtual validation ensures universality while requiring minimal physical intervention, as the simulation can rapidly test scenarios that would be time-consuming to validate on actual equipment.
Data Source
AI summary
A controller configuration for a drive system with a drive is determined using at least one simulation model. One or more controlled system measurement results are received. One or the respective controlled system measurement result is obtained by measuring an RPM speed control loop of the drive system. A simulation model with a drive unit submodel and with one or more controlled system submodels is created for the or the respective RPM speed control loop. A system identification is carried out using the or the respective controlled system measurement result in order to obtain the or the respective controlled system submodel. A controller configuration is determined for the drive system using the simulation model.