Servo Motor Parameter Identification With Cloud-Edge Coordination
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Solution Overview
Problem
Existing motor parameter identification algorithms for permanent magnet synchronous motors are low in accuracy and real-time performance, which affects the control performance of the motor due to changes in motor parameters such as resistance, inductance, and flux linkage caused by temperature and external interference.
Innovation Solution
A cloud and edge integrated method for identifying servo motor parameters, where the cloud identification engine processes and identifies internal resistance using a neural network algorithm, and the edge identification engine combines this result with real-time data to determine d-q axes inductances and flux linkage, employing data processing and filtering to enhance accuracy and remove noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing motor parameter identification algorithms are used, then the identification process can be completed, but the accuracy and real-time performance are low
Solution Approach 1:
The patent segments the parameter identification process into two distinct parts: cloud-based identification (for high-accuracy offline parameter identification) and edge-based identification (for real-time parameter tracking). This segmentation allows each part to specialize in its strength, resolving the contradiction between accuracy and real-time performance.
Solution Approach 2:
The patent introduces an intermediary mechanism where the cloud identification results serve as initial values or references for the edge identification process. This intermediary relationship allows the edge device to leverage cloud computing power while maintaining real-time responsiveness, thus improving both accuracy and real-time performance simultaneously.
2Reliability
If motor parameters are not identified in real-time, then the identification process is simpler, but the control performance deteriorates due to parameter changes from temperature and external interference
Solution Approach 1:
The patent implements a dynamic identification system where the edge device continuously updates motor parameters in real-time based on operating conditions. This dynamic approach ensures control performance is maintained despite temperature changes and external interference, while the cloud-edge architecture manages the complexity through distributed processing.
Solution Approach 2:
The patent establishes a feedback mechanism where real-time parameter identification results are fed back to the control system to adjust control strategies. This feedback loop maintains reliable control performance under varying conditions, and the cloud-edge collaborative architecture manages the complexity by distributing computational tasks.
3Measurement precision
If cloud computing power is used for complex parameter identification, then accuracy improves, but system complexity and data transmission requirements increase
Solution Approach 1:
The patent segments the computational workload by placing complex, accuracy-critical identification tasks in the cloud while keeping simpler real-time tracking tasks at the edge. This segmentation improves accuracy for complex parameters while managing system complexity through distributed architecture.
Solution Approach 2:
The patent creates a universal cloud-edge collaborative platform that can handle different types of parameter identification tasks. The system is designed to be multi-functional, accommodating both offline cloud-based identification and online edge-based identification, thereby managing complexity through a unified architectural framework.
Data Source
AI summary
The present invention discloses a cloud and edge integrated method and system for identifying parameters of a servo motor. The method comprises the following steps: acquiring parameters of the servo motor; transmitting the parameters of the servo motor to a cloud identification engine and an edge identification engine; performing data processing and identification analysis, by the cloud identification engine, the parameters of the servo motor to obtain an internal resistance of the motor Rs, and sending an identification result to the edge identification engine through a network; identifying, by the edge identification engine, the cloud identification result and the parameters of the servo motor to obtain identification results of d-q axes inductances and a flux linkage. The system comprises a servo motor parameter acquisition unit, a sending unit, a cloud identification engine, and an edge identification engine.