Laundry drying machine and control method thereof
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Solution Overview
Problem
Current laundry drying machines, especially rotatable drum washer-dryers, face challenges in accurately estimating laundry moisture due to the inability to arrange moisture sensors within the drum, leading to time-consuming calibration procedures and inefficiencies in determining the end of the drying cycle.
Innovation Solution
A method that controls the laundry drying machine by collecting physical quantities such as inertia, temperature, static unbalance, fan speed, air temperature, motor torque, and motor torque variation during an initial phase of the drying cycle, using a cubic polynomial model to estimate moisture levels and determine the optimal end time of the cycle based on these parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If moisture sensors/electrodes are arranged inside the drum to contact the laundry for direct measurement, then measurement precision is improved, but device complexity increases and the architecture becomes unsuitable for rotatable drum washer-dryers
Solution Approach 1:
The patent uses motor torque as an intermediary parameter to indirectly measure laundry moisture. Instead of directly contacting the laundry with sensors, the system measures the torque required to rotate the drum, which varies with laundry moisture content. This mediator approach enables moisture estimation without complex internal sensor arrangements.
Solution Approach 2:
The patent replaces the mechanical/electrical sensor system with a mechanical measurement approach using the existing motor. By measuring motor torque through electrical parameters (current, voltage, power), the system substitutes dedicated moisture sensors with the motor's inherent measurement capabilities, simplifying the overall device architecture.
2Measurement precision
If algorithms use multiple physical quantities and thresholds for each load size and temperature, then measurement precision is improved, but loss of time increases due to time-consuming calibration procedures
Solution Approach 1:
The patent changes the approach from using multiple thresholds for different conditions to using a single dynamic torque threshold. By continuously monitoring motor torque and comparing it against one adaptive threshold, the system eliminates the need for extensive calibration across multiple load sizes and temperatures, significantly reducing setup time while maintaining precision.
Solution Approach 2:
The system performs self-calibration by automatically adapting the torque threshold based on real-time motor characteristics and loading conditions. The controller learns the appropriate threshold during initial operation without requiring manual calibration procedures, enabling the system to serve itself and eliminate time-consuming setup steps.
3Productivity
If the drying cycle is controlled based on torque and temperature signals with thresholds, then productivity is improved, but measurement precision deteriorates due to noise from laundry tumbling
Solution Approach 1:
The patent implements feedback by continuously monitoring motor torque and dynamically adjusting the drying process. The system uses real-time torque measurements with hysteresis comparison (different thresholds for increasing and decreasing torque) to detect moisture changes, providing feedback control that improves both productivity and precision despite tumbling noise.
Solution Approach 2:
The system performs preliminary filtering and signal processing of torque data before making control decisions. By pre-processing the torque signals to remove noise and validate measurements, the system ensures accurate moisture detection while maintaining efficient drying cycle control.
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 a precise and automatic end-of-cycle detection without the need for dedicated moisture sensors, improving the robustness and efficiency of the drying process across various laundry compositions.
Implementation Method 1
performing an estimation of polynomial coefficients of a cubic polynomial model indicative of an estimated change of the laundry moisture over the time, based on respective linear polynomial models comprising said collected physicals quantities
Implementation Method 2
hot air generator means for supplying a drying airflow to the laundry drum
Implementation Method 3
hot air generator means for supplying a drying airflow to the laundry drum
Implementation Method 4
an electric motor for rotating said rotatable laundry drum about its axis
Implementation Method 5
a moisture sensor system comprising measuring electrodes positioned inside the drum for contacting the laundry measure the impedance of the laundry
Data Source
Figure 1~2
Figure 3
Figure 4a
AI summary
Method to control a laundry drying machine (1), which comprises: a rotatable laundry drum (3) designed to rotate about an axis (6) and adapted to be loaded with laundry, an electric motor (9) for rotating said rotatable laundry drum (3) about its axis (6), hot air generator means (11) for supplying a drying airflow to the laundry drum (3). The comprising the step of controlling said electric motor (9) and said hot air generator means (11) during a drying cycle, based on one or more physicals quantities being associated with said rotatable laundry drum (3) loaded with laundry, said electric motor (9) and said hot air generator means (11). The method comprising: collecting said physicals quantities during a initial phase of said drying cycle, performing an estimation of polynomial coefficients of a cubic polynomial model indicative of an estimated change of the laundry moisture over the time, based on respective linear polynomial models comprising said collected physicals quantities, performing an estimation of the laundry moisture by said cubic polynomial model based on said estimated polynomial coefficients.