Brushless DC Motor Error State Identification via Angular Deviation
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Solution Overview
Problem
Existing methods for detecting fault conditions in brushless DC motors are costly, provide low signal quality at low current intensities, and have long error detection times at low speeds or when the motor is stationary, due to high computational demands and limited information from voltage measurements.
Innovation Solution
A method that calculates angular deviation between the shaft angle and control angle, allowing for efficient fault detection with lower computational requirements, using a rule-based pattern recognition system that accounts for system parameters like direction of rotation and torque, and can detect errors at low speeds or when the motor is stationary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current measurement is used to detect fault conditions, then measurement precision is improved, but device complexity and cost increase due to high requirements for measuring circuitry
Solution Approach 1:
The patent replaces complex electrical measurement systems with a computational method based on voltage measurements and mathematical calculations. Instead of using sophisticated current sensing circuitry, the system calculates angular deviation from voltage measurements and control signals, substituting hardware complexity with software-based analysis.
2Device complexity
If voltage measurement is used to detect fault conditions, then device complexity is reduced, but measurement precision and fault detection capability are worsened due to limited information about current level
Solution Approach 1:
The patent introduces angular deviation as an intermediary parameter that bridges voltage measurements and fault detection. By calculating the angular deviation between the actual shaft position and the control angle, the system extracts meaningful fault information from voltage measurements without requiring direct current measurement, thus maintaining simplicity while improving precision.
3Reliability
If traditional fault detection methods are used at low speeds, then fault detection is possible, but loss of time increases due to long detection times requiring several complete electrical revolutions
Solution Approach 1:
The patent performs preliminary calculations of angular deviation continuously during motor operation, maintaining a ready state for fault detection. By continuously tracking the angular deviation between shaft angle and control angle, the system prepares fault detection data in advance, enabling immediate fault identification at low speeds without requiring multiple electrical revolutions to accumulate sufficient data.
4Measurement precision
If computationally intensive algorithms are used for voltage measurement analysis, then measurement precision is improved, but use of energy and computational resources increase
Solution Approach 1:
The patent extracts only the essential information needed for fault detection from the voltage measurements - specifically the angular deviation. By focusing calculations on this single key parameter rather than analyzing all aspects of the electrical signals, the system achieves adequate fault detection precision with minimal computational effort and energy consumption.
Data Source
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AI summary
The invention relates to a method for identifying an error state in a brushless direct current motor. For the purposes of this identification, an angle deviation between a shaft angle and a control angle is calculated and used to identify error states on the basis of characteristic patterns. This also works, in particular, for slowly-rotating or stationary brushless direct current motors and allows a clear reduction in the calculation capacities required, compared to the prior art.