Method and device for adjusting operation of washing machine based on system modeling
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Solution Overview
Problem
Conventional washing machine control systems are reactive and may abruptly interrupt operations, leading to noticeable user experiences and inefficiencies, such as excessive current consumption and temperature exceedance, without proactive adjustments to maintain safe operating conditions and efficiency goals.
Innovation Solution
A method that models and adjusts wash cycle programs based on predicted operating temperatures and current consumption, using sensors for load and ambient data to modify duty cycles of the motor and heater, ensuring safe and efficient operation by recalibrating system models with controllers like proportional-integral or neural networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the motor and heater are both turned on at the same time to improve washing performance, then the washing effectiveness is improved, but the current consumption exceeds the maximum current consumption
Solution Approach 1:
The control system predicts future current consumption and operational temperatures before they occur, allowing it to preemptively adjust the duty cycles of the motor and heater to prevent current consumption from exceeding maximum limits while maintaining washing effectiveness
2Reliability
If the control system monitors and responds to operational parameters in real-time, then safety is improved, but the control system abruptly interrupts operation leading to noticeable user experience degradation
Solution Approach 1:
The control system uses predictive modeling to anticipate when operational parameters will exceed safe thresholds, allowing it to gradually adjust duty cycles before limits are reached, thereby maintaining safety without abrupt interruptions that degrade user experience
Solution Approach 2:
The control system continuously monitors operational parameters and uses this feedback to dynamically adjust duty cycles in real-time, maintaining safe operation while providing smooth, continuous control adjustments rather than abrupt interruptions
3Temperature
If the duty cycle of the motor is reduced to lower operating temperature, then the motor temperature is controlled within safe limits, but the washing performance deteriorates
Solution Approach 1:
The control system dynamically adjusts the motor duty cycle based on real-time predictive modeling of temperature and current consumption, optimizing the balance between temperature control and washing performance by continuously adapting to changing operational conditions
4Loss of energy
If the control system uses predictive modeling to adjust duty cycles, then energy efficiency is improved, but the device complexity increases
Solution Approach 1:
The control system replaces complex hardware-based temperature and current monitoring with software-based predictive modeling that uses mathematical algorithms to forecast operational parameters, reducing the need for additional sensors and complex control hardware while improving energy efficiency
Data Source
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AI summary
Devices and methods to adjust the operation of a washing machine based on system modeling include a motor, a control board, a heater, a number of sensors, and an electronic controller. The controller receives a selected wash cycle program and determines an operating condition of the selected wash cycle program, using data from the sensors. The motor may be used as a sensor. Based on the operating condition, the controller predicts an operational parameter of the washing machine using a system model. The controller may adjust the wash cycle program to keep the operational parameter in bounds or increase efficiency. The operational parameter may be temperature, electrical current consumption, wash efficiency, or energy consumption. The wash cycle program may be adjusted by modifying the duty cycle of the motor or the heater. The system model may be recalibrated upon use to adapt to the particular characteristics of the washing machine.