Data processing: measuring – calibrating – or testing – Calibration or correction system
Reexamination Certificate
2002-08-30
2004-11-30
Barlow, John (Department: 2863)
Data processing: measuring, calibrating, or testing
Calibration or correction system
Reexamination Certificate
active
06826499
ABSTRACT:
BACKGROUND
Brushless motors and controllers of various types are commonly employed in motion control. Typically, brushless motors employ two methods or types of control. Sinusoidal control technology, that is, they are commanded with a sinusoidal voltage command and maintain sinusoidal flux. Commonly, proper control of such a motor also requires the use of a high-resolution position sensor to detect the rotor position throughout the entire angular rotation. Such a sensor, and the electronics to decode and condition it are often complex and expensive. Another common method for controlling brushless motors is with trapezoidal control. With trapezoidal control, the excitation is commonly three-phase square waves, yielding trapezoidal flux wave-shapes. However, because of the inherent characteristics of the motor, the flux typically will not be exactly trapezoidal. This distortion of the flux wave shape results in the motor exhibiting torque fluctuations at each phase commutation point. Such torque fluctuations are generally undesirable.
A motor control system is depicted in FIG.
1
. Accurate measurement of the position of the motor rotor is desirable to facilitate motor control. In order to measure and determine the absolute position of a motor shaft, a motor is typically equipped with a position sensor operatively coupled to the motor shaft to monitor a relative rotational position of a shaft. The position sensor may include, but not be limited to, potentiometers, synchros, Hall-effect, or variable-reluctance sensor, and the like, including combinations of the foregoing. Moreover, the position sensor generates a signal that must be accurately determinable for calibrating and initializing an electronically commutated motor.
A set of sensors may be used to determine which phase of the motor must be excited at any given time. For example, in the case of trapezoidal control, high accuracy may not be necessary and a simple set of sensors is all that is needed regarding position information. Therefore, a set of 3 sensors that yield 3 signals, typically 120 electrical degrees apart are sufficient. Electrical degree is defined as a physical rotation in mechanical degrees of the rotor divided by the number of pole pairs of the motor. In order to generate 3 signals that are each differentiated by 120 electrical degrees apart, necessitates assembling each of the sensors 120 electrical degrees apart from each other. Mechanically aligning the sensor's switch point or zero position with that of the motor may be cost prohibitive. Such position sensors are often called “commutation” sensors, because they are used to signal the controller when to commutate the motor currents from one phase to another.
Turning now to sinusoidal motor control implementations. This control technology requires knowledge of the rotor position with relationship to the motor's electromotive force (EMF). This is usually accomplished by mechanically aligning an absolute rotor position sensor with resolution on the order of a few electrical degrees, or less, to the motor's EMF. Absolute position sensors, however, are more complex to integrate and only become acceptable for applications without stringent cost restrictions. Moreover, absolute positions sensor require alignment and/or a bias calibration. This alignment process can be problematic in a high volume, manufacturing environment. The waveforms for a motor including ideally aligned low-resolution (or commutation) sensor signals are shown in FIG.
2
.
BRIEF SUMMARY
Disclosed herein is a method for calibrating and initializing position for a rotating device. The method comprises: establishing a sensor subsystem datum indicative of a measurement reference point for a sensor subsystem; obtaining a calibration value corresponding to a distance to a selected magnetic reference position for the rotating device, relative to the sensor subsystem datum; and measuring a position and calculating a position delta relative to an initial reference. The method also includes: estimating an offset from the sensor subsystem datum to an initial reference; determining an absolute position estimate of the rotating device relative to the magnetic reference position. The absolute position estimate is responsive to the calibration value, the position delta, and the offset from the sensor subsystem datum to the initial reference.
Also disclosed herein is a system for calibrating and initializing an electronically commutated electric machine. The system comprising: an electric machine; a position sensor subsystem operatively connected to the electric machine configured to measure a position and transmit a position signal to a controller; an absolute position sensor operatively connected to the controller and transmitting a position signal indicative of an absolute position of the electric machine. The system also includes a relative position sensor operatively connected to the controller and transmitting a position signal indicative of a position of the electric machine. The controller executes a process implementing a method for calibrating and initializing position for the electric machine, the method comprising: establishing a sensor subsystem datum indicative of a measurement reference point for a sensor subsystem; obtaining a calibration value corresponding to a distance to a selected magnetic reference position for the electric machine, relative to the sensor subsystem datum; and measuring a position and calculating a position delta relative to an initial reference. The method also includes: estimating an offset from the sensor subsystem datum to an initial reference; determining an absolute position estimate of the electric machine relative to the magnetic reference position. The absolute position estimate is responsive to the calibration value, the position delta, and the offset from the sensor subsystem datum to the initial reference.
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Materials downloaded from web under hyperphysics.phy-astr.gsu.edu and mag-net.ee.unist.ac.uk.
Collier-Hallman Steven J.
Colosky Mark P.
McCann Roy
Tallant, II James Charles
Weilhammer Phillip
Delphi Technologies Inc.
Lau Tung S
Smith Michael D.
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