Brushless Winch Motor Sensorless Control for Accurate Positioning
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Solution Overview
Problem
Existing winch motors, particularly those using permanent magnet brushless motors, suffer from lower dynamic optimization accuracy and cannot satisfy requirements of high-accuracy control due to inaccuracy or real-time dynamic changes in motor parameters, affecting stability and convergence of sensorless FOC control algorithms.
Innovation Solution
A method involving a flux linkage observer-based sensorless observer model is used to dynamically obtain rotor position and rotational speed, calculate offsets, and perform feedback-based control to compensate for operating time and power offsets, enhancing accuracy and stability by adjusting motor parameters in response to load variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If sensorless FOC control is used to simplify installation and reduce cost, then device complexity and product cost are reduced, but measurement precision of rotor position and control accuracy deteriorate due to parameter inaccuracy
Solution Approach 1:
The system dynamically identifies and updates motor parameters (resistance, inductance, flux linkage) in real-time during operation, adapting to parameter variations caused by temperature, saturation, and other factors. This maintains high measurement precision without requiring physical sensors by continuously adjusting the mathematical model parameters used in the sensorless FOC algorithm.
Solution Approach 2:
The system employs iterative parameter identification where the identified parameters are fed back to update the motor model, which in turn improves the accuracy of rotor position estimation. This closed-loop feedback mechanism continuously refines the control accuracy by using the system's own operational data to correct and update parameter estimates.
2Device complexity
If fixed motor parameters are used in control algorithm, then device complexity is reduced, but control accuracy deteriorates due to real-time dynamic changes in motor parameters
Solution Approach 1:
The control system transitions from using fixed static parameters to dynamically updating parameters during operation. The system continuously identifies resistance, inductance, and flux linkage parameters based on real-time voltage and current measurements, allowing the control algorithm to adapt to changing operating conditions such as temperature variations, magnetic saturation, and load changes, thereby maintaining high operating accuracy.
Solution Approach 2:
The system performs self-identification of motor parameters using its own operational voltage and current data without requiring external calibration equipment or additional sensors. The parameter identification algorithm runs autonomously during normal motor operation, enabling the system to self-adjust and maintain optimal performance automatically.
3Measurement precision
If traditional self-calibration method is used, then electrical parameter accuracy is improved, but adaptability to load variations and dynamic performance deteriorate
Solution Approach 1:
Instead of performing parameter calibration only during initial setup or periodic maintenance, the system continuously identifies and updates motor parameters during normal operation. This continuous parameter identification ensures that the control algorithm always uses the most current and accurate parameters, enabling the system to adapt immediately to load variations and maintain high precision across different operating conditions.
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
The method ensures stable and accurate operation of the winch motor by compensating for real-time offsets, enabling high-accuracy control and preventing damage through real-time monitoring and protective measures, thus enhancing stability and reliability.
Implementation Method 1
dynamically obtaining a flux linkage variation via a flux linkage observer, calculating a dynamic rotor position
Implementation Method 2
building a motor model based on the basic parameter of the winch motor, and building a flux linkage observer-based sensorless observer model based on the motor model
Data Source
AI summary
A method for optimizing operating accuracy of a brushless winch motor includes outputting a d-axis reference current and a rotor position according to a winch motor startup signal using a flux linkage observer-based sensorless observer model and a motor model; obtaining a real-time rotational speed and a real-time winding/unwinding position of the winch motor according to an operating parameter of the winch motor using the flux linkage observer-based sensorless observer model and the motor model; and obtaining a first offset between the real-time winding/unwinding position of the winch motor and a preset position and a second offset between the real-time rotational speed of the winch motor and a preset rotational speed, performing closed-loop control of the operating parameter with the first offset and the second offset as feedback parameters, and adjusting the operating parameter to optimize operating accuracy of the winch motor.