Sensorless Laundry Drum Friction Monitoring From Motor Parameters
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Solution Overview
Problem
Laundry treating appliances, such as washing machines, face challenges in optimizing cycles of operation without sensors, which are costly, and in detecting high friction events that can impact performance and efficiency.
Innovation Solution
The implementation of parameter estimation algorithms to monitor and estimate parameters like torque, acceleration, speed, and angular position of the drum to detect high friction events and optimize cycle operations, including real-time monitoring of inertia and friction values, and using excitation sequences to improve parameter estimation signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are used to monitor and optimize cycles of operation, then measurement precision and reliability are improved, but device complexity and cost increase
Solution Approach 1:
The motor controller performs parameter estimation functions internally using existing motor measurements (current, voltage, speed) without requiring external sensors. The system serves itself by utilizing the motor's own operational data to estimate torque, friction, and load parameters, eliminating the need for separate sensing hardware while maintaining monitoring capabilities
Solution Approach 2:
The motor controller is designed to perform multiple functions: it controls motor operation, estimates mechanical parameters (torque, friction, inertia), detects high friction events, and optimizes wash cycles. This multi-functional approach consolidates what would traditionally require separate sensors and control systems into a single integrated controller, reducing overall system complexity while maintaining measurement precision
2Reliability
If parameter estimation algorithms are implemented to detect high friction events, then reliability and efficiency are improved, but device complexity increases
Solution Approach 1:
The parameter estimation algorithm continuously monitors motor operational parameters and provides feedback about friction conditions to the controller. This feedback mechanism enables real-time detection of high friction events and automatic adjustment of motor operation to maintain reliability while preventing damage, with the complexity managed through iterative estimation rather than complex hardware systems
Solution Approach 2:
The patent replaces mechanical friction detection systems (which would require physical sensors and mechanical linkages) with computational parameter estimation algorithms. The controller uses electrical measurements and mathematical models to estimate mechanical friction parameters, substituting a software-based solution for what would traditionally require complex mechanical sensing systems
Data Source
AI summary
A method of detecting high friction events in a laundry treating appliance includes rotating the drum, determining, during the rotation, a torque of the motor, an acceleration of the drum, a speed of the drum, and/or an angular position of the drum at each of multiple speeds, and repeatedly estimating with a parameter estimator, during the rotation, viscous friction, coulomb friction, and total friction based on the torque, acceleration, speed, and/or angular position of the drum. A high friction even is determined based on the estimated viscous friction, coulomb friction and/or total friction.