Rotor Initial Position Estimation Using Learned Magnetic Sensor Signals
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Solution Overview
Problem
Existing position estimation methods for rotor position in motors, such as those used in robots and unmanned transport vehicles, face challenges in estimating the initial position without a preliminary rotation operation, especially when using absolute angle position sensors like optical encoders, which are large and costly.
Innovation Solution
A position estimation method using a combination of magnetic sensors and a signal processing device that estimates rotor position without requiring a preliminary rotation operation by learning the correspondence between sensor signals and rotor positions through a learning process, allowing for direct estimation of the initial position.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If an absolute angle position sensor such as an optical encoder or resolver is used to accurately control rotor position, then position estimation accuracy is improved, but device size and cost increase
Solution Approach 1:
The patent replaces mechanical/optical absolute angle position sensors with a magnetic sensor-based system. The motor control device uses magnetic sensors to detect rotor position and employs learning-based processing to estimate absolute position, substituting complex mechanical sensing systems with simpler magnetic field detection and computational methods.
Solution Approach 2:
The patent creates a learned model that copies the relationship between magnetic sensor signals and rotor positions. By learning the correspondence during a teaching phase and applying it during operation, the system reproduces absolute position estimation without requiring physical absolute position sensors, achieving accurate position control through informational copying rather than direct physical measurement.
2Measurement precision
If a preliminary rotation operation is performed to estimate initial rotor position, then position estimation accuracy is improved, but driving time and energy consumption increase
Solution Approach 1:
The patent performs preliminary learning action during a teaching phase where the rotor is rotated through all positions to establish the correspondence between magnetic sensor signals and rotor positions. This learned information is stored and reused during normal operation, eliminating the need for repeated preliminary rotations and enabling direct initial position estimation without time-consuming rotation operations.
Solution Approach 2:
The system uses its own magnetic sensor signals and learned correspondence to determine initial rotor position without requiring external intervention or preliminary rotation operations. The learning data stored in the device enables self-sufficient position estimation, allowing the motor control device to independently calculate initial position from current magnetic sensor readings combined with previously learned patterns.
3Measurement precision
If a preliminary rotation operation is performed to estimate initial rotor position, then position estimation accuracy is improved, but energy consumption increases
Solution Approach 1:
The patent performs preliminary learning action during a teaching phase where the rotor is rotated through all positions to establish the correspondence between magnetic sensor signals and rotor positions. This learned information is stored and reused during normal operation, eliminating the need for repeated preliminary rotations and enabling direct initial position estimation without time-consuming rotation operations.
Solution Approach 2:
The system uses its own magnetic sensor signals and learned correspondence to determine initial rotor position without requiring external intervention or preliminary rotation operations. The learning data stored in the device enables self-sufficient position estimation, allowing the motor control device to independently calculate initial position from current magnetic sensor readings combined with previously learned patterns.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate estimation of the rotor's initial position without the need for a preliminary rotation, reducing driving time and power consumption, and is suitable for applications like robots and unmanned transport vehicles.
Implementation Method 1
a plurality of magnetic sensors that generate rotor position signals on the basis of a magnetic field generated by the rotor
Data Source
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AI summary
One aspect of a position estimation method of the present invention includes: a learning step of acquiring learning data necessary for estimation of a rotational position of a rotor on the basis of an input sensor signal; and a position estimation step of estimating the rotational position of the rotor on the basis of the input sensor signal and the learning data. The learning step is performed, thereby acquiring, as the learning data, data indicating the correspondence relationship between a segment number associated with a section included in each of a plurality of quadrants and a pole pair number representing a pole pair position. The position estimation step is performed, thereby determining an initial position of the rotor on the basis of the input sensor signal and the learning data.