Laundry Drum Parameter Estimation to Remove Torque Fluctuation Effects
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Solution Overview
Problem
Laundry treating appliances face challenges in optimizing cycles of operation without sensors, as existing methods fail to accurately monitor and adjust parameters like torque fluctuations and load characteristics, leading to inefficiencies and increased costs.
Innovation Solution
A method involving a parameter estimator that rotates the drum during a cycle, determines the activation or deactivation of machine components, resets covariance, and repeatedly estimates parameters based on torque, acceleration, speed, and angular position to adjust cycle parameters, enabling sensor-less monitoring and optimization.
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 system uses the motor's own operational data (torque, speed, acceleration) to estimate load parameters and detect anomalies. The motor controller performs self-diagnosis by analyzing the relationship between commanded and actual motor responses, eliminating the need for external sensors to monitor load characteristics.
Solution Approach 2:
Physical sensors are replaced with a computational model that uses electrical motor parameters (current, voltage, speed) to infer mechanical load conditions. The parameter estimator algorithm substitutes direct mechanical measurement with indirect electrical measurement and mathematical estimation.
2Adaptability or versatility
If machine components are activated or deactivated during cycles, then adaptability and optimization are improved, but torque fluctuations and measurement reliability deteriorate
Solution Approach 1:
The system pre-identifies time intervals when drag-inducing components are activated or deactivated. By knowing these transition times in advance, the parameter estimator can adjust its estimation algorithm or weightings during these critical periods to maintain accuracy despite torque fluctuations.
Solution Approach 2:
The system continuously monitors motor torque, speed, and acceleration to detect anomalies caused by component transitions. This feedback is used to adjust the parameter estimation in real-time, compensating for the temporary reliability degradation during component activation/deactivation events.
3Productivity
If parameter estimation is performed continuously, then productivity and efficiency are improved, but use of energy and computational load increase
Solution Approach 1:
Instead of continuous high-computation parameter estimation, the system performs estimation at periodic intervals and uses simplified models between updates. The parameter estimator is activated at key moments (component transitions, anomaly detections) rather than running continuously at full computational intensity.
Solution Approach 2:
The system performs full parameter estimation only when necessary (when anomalies are detected or during critical cycle phases), and uses lighter monitoring otherwise. This partial action approach maintains productivity by focusing computational resources on the most critical moments rather than uniformly high computational load throughout.
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
This approach allows for real-time monitoring and optimization of washing machine cycles, improving efficiency, reducing energy consumption, and enhancing the accuracy of load characterization without the need for costly sensors.
Implementation Method 1
a motor operably coupled with the drum to rotate the drum
Implementation Method 2
determining a start time when a machine component is activated or deactivated during the cycle of operation, repeatedly estimating in a parameter estimator after the reset time, parameters of the rotating drum, based on the torque, acceleration, speed, and/or angular position of the drum
Data Source
AI summary
A method of removing effects of torque fluctuations caused by activation or deactivation of machine components in estimating inertia from a parameter estimator in a laundry treating appliance includes rotating the drum during a cycle of operation on a laundry load, determining a start time when a machine component is activated or deactivated during the cycle of operation, resetting covariance in a parameter estimator at a predetermined reset time after the start time, repeatedly estimating in the parameter estimator after the reset time, inertia of the laundry load, based on the torque, acceleration, speed, and/or angular position of the drum, processing estimated parameter values from the parameter estimator at a predetermined adjusting time after the predetermined reset time, and adjusting cycle parameters based on the processed estimated parameter values.