Torque Ripple Suppression in Rotating Electrical Machines
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Solution Overview
Problem
Existing torque ripple suppression methods face challenges in accurately handling high-frequency disturbances and multi-inertia systems, leading to reduced performance and difficulty in generating desired compensating currents, especially in varying speed operations.
Innovation Solution
A periodic disturbance observer is used to estimate the real and imaginary parts of the torque ripple frequency component, allowing for the generation of feedback compensating currents that cancel periodic disturbances, employing a one-dimensional complex vector model for system identification and adaptive control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If feedback suppression control is used to accurately suppress torque ripple, then torque ripple suppression performance is improved, but control response deteriorates due to calculation dead time in high frequency range
Solution Approach 1:
The control system segments the torque ripple suppression into two distinct paths: a fast feedforward path using a periodic disturbance observer for high-frequency components, and a slower feedback path using a shaft torque meter for overall accuracy. This segmentation allows each path to optimize for its specific frequency range, resolving the contradiction between accuracy and response speed.
Solution Approach 2:
The periodic disturbance observer performs preliminary action by estimating and compensating for torque ripple before the shaft torque meter can measure and respond to it. The observer uses system identification models to predict disturbance characteristics in advance, providing proactive compensation that reduces the impact of calculation dead time in the feedback path.
2Adaptability or versatility
If system identification with complex vector model is used to handle multi-inertia systems, then adaptability to varying speed operations is improved, but device complexity increases
Solution Approach 1:
The system uses parameter changes by adapting the complex vector model parameters (magnitude and phase) according to operating conditions. The periodic disturbance observer adjusts its parameters based on system identification results that vary with speed, allowing the controller to maintain accuracy across different operating points without requiring a completely different control structure for each condition.
Solution Approach 2:
The complex vector model acts as an intermediary that simplifies the representation of multi-inertia system dynamics. Instead of directly controlling each inertia element, the model provides a unified mathematical representation that captures the essential frequency characteristics, making the system adaptable to varying conditions while keeping the control structure manageable.
3Loss of time
If periodic disturbance observer is used to estimate torque ripple frequency components, then response time is improved, but measurement precision may be affected by model accuracy
Solution Approach 1:
The system employs feedback by using the shaft torque meter to measure actual torque ripple and comparing it with the periodic disturbance observer's estimates. This feedback loop allows the system to verify and refine the observer's performance, ensuring that the fast response of the observer does not compromise measurement precision. The feedback mechanism compensates for model inaccuracies by adjusting the control based on actual measurements.
Data Source
AI summary
A periodic disturbance observer determines real part I^An and imaginary part I^Bn of an estimated current including a periodic disturbance, from value of identification identifying a system transfer function of an nth order torque ripple frequency component from a command torque to a detected torque value, with a one-dimensional complex vector having a real part P^An and an imaginary part P^Bn, a cosine coefficient TAn, a sine coefficient TBn, and the real part P^An and imaginary part P^Bn of the system transfer function; subtracts command compensating current IAn* and IBn* obtained through pulsation extracting filter GF, respectively, from the real part I^An and imaginary part I^Bn of the estimated current, and thereby determines estimated periodic disturbance current real part dI^An and imaginary part dI^Bn to cancel the periodic disturbance current.