Motor Stall Detection Using Synchronous Current Sum Sampling
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Solution Overview
Problem
Sensorless multi-phase motors, such as BLDC and stepper motors, face challenges in detecting stall conditions due to limited torque, noise, and vibrations, especially when operating in micro-stepped modes without additional positioning means like back EMF measurements.
Innovation Solution
A method involving phase-shifted micro-stepped waveforms applied to motor windings, synchronous sampling of current sums, calculation of moving averages or sums over specific angular intervals, and adaptive threshold determination to detect stall conditions without relying on back EMF measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If back EMF measurement is used for stall detection in sensorless motors, then rotor position can be determined, but the method becomes complex and unreliable in micro-stepped mode with limited torque
Solution Approach 1:
The patent extracts the stall detection function from the complex back EMF measurement system and implements it through a simplified current monitoring approach. By measuring only the sum of currents through the phase windings and comparing it against a threshold, the system achieves reliable stall detection without requiring complex positioning means or back EMF measurements, directly resolving the contradiction between reliability and complexity
Solution Approach 2:
The motor's own current consumption serves as the detection parameter for stall condition. The system uses the sum of currents flowing through the phase windings during micro-stepped operation as a direct indicator of rotor movement status, eliminating the need for external sensing mechanisms and simplifying the overall detection system while maintaining reliability
2Manufacturing precision
If micro-stepped waveforms are applied to increase torque, then rotor displacement precision improves, but noise and vibrations increase
Solution Approach 1:
The patent applies periodic micro-stepped waveforms to the motor phase windings, dividing the rotation into discrete angular increments (e.g., 120° for three-phase motors). This periodic excitation allows precise control of rotor displacement while the systematic switching pattern helps reduce continuous vibrations and noise compared to traditional continuous waveforms
3Measurement precision
If moving average is calculated over even multiple of 60° intervals, then detection accuracy improves, but computational load increases
Solution Approach 1:
The patent segments the calculation window into specific angular intervals corresponding to even multiples of 60° (such as 120° or 240° for three-phase motors). This segmentation aligns with the electrical periods of the motor phases, allowing accurate stall detection by averaging current samples over complete electrical cycles while keeping the computational scope limited and manageable
4Reliability
If adaptive threshold is used for stall detection, then detection robustness against speed and load variations improves, but calculation complexity increases
Solution Approach 1:
The system performs preliminary calculation of the moving average of current samples over a defined angular interval before comparing against the threshold. This preliminary processing establishes a baseline current level that adapts to varying operating conditions (speed, load, aging), enabling robust stall detection without requiring complex real-time adjustments during operation
Data Source
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AI summary
A method of detecting stall of a multi-phase motor (2) operated in a micro-stepped mode, the method comprising: a) applying at least two phase-shifted micro-stepped waveforms to the phase windings of said motor; b) determining a sum of currents flowing through the phase windings, and taking samples of said sum of currents synchronously with the application of said micro-stepped waveforms; c) calculating a moving average or moving sum of said samples over one or more "full steps" of the phase-shifted waveforms; d) calculating an adaptive threshold based on said samples; e) detecting stall of the motor when the moving average is larger than said adaptive threshold. An electrical circuit (1) and a computer program for performing such method are also disclosed.