Washing Machine Motor Feedback for Sensorless Load Estimation
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Solution Overview
Problem
Washing machines lack efficient methods for real-time monitoring and optimization of laundry treatment cycles without relying on costly sensors, which affects performance and energy efficiency.
Innovation Solution
The implementation of parameter estimation algorithms in washing machines to estimate parameters like inertia, friction, and load imbalance, using motor torque, speed, and position data, allowing for adaptive control of cycles and improved operation without sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are used to monitor and optimize washing machine cycles, then measurement precision and control accuracy are improved, but device complexity and cost increase
Solution Approach 1:
The motor controller performs parameter estimation functions autonomously using existing motor data (current, voltage, speed, position) without requiring external sensors. The system self-monitors and self-optimizes by processing signals already present in the motor control circuitry, eliminating the need for additional measurement devices.
Solution Approach 2:
Physical sensors are replaced with a computational parameter estimation system that processes electrical signals from the motor controller. The estimation algorithm substitutes direct mechanical/electrical sensing with mathematical modeling and signal processing of existing motor operating parameters.
2Device complexity
If parameter estimation algorithms are implemented without sensors, then device complexity is reduced, but measurement precision may be affected
Solution Approach 1:
The parameter estimation algorithm continuously receives feedback from the motor controller regarding current draw, speed variations, and position data during different cycle phases. This real-time feedback enables dynamic adjustment of cycle parameters based on actual laundry load conditions, maintaining precision through continuous monitoring and adaptation.
Solution Approach 2:
The system performs preliminary parameter estimation during standardized phases of the washing cycle (such as acceleration phases or specific spin rates) to establish baseline characteristics before optimizing subsequent cycle parameters. This preliminary characterization enables more accurate predictions and adjustments during variable load conditions.
3Productivity
If real-time parameter monitoring is implemented, then productivity and energy efficiency are improved, but use of energy for data processing increases
Solution Approach 1:
The parameter estimation computations are performed within the existing motor controller hardware using processing capabilities already dedicated to motor control. By utilizing the same processor and computational resources for both motor control and parameter estimation, the system avoids additional energy-consuming processing units while achieving real-time monitoring and optimization.
Solution Approach 2:
The parameter estimation function is merged with the motor control operations, combining multiple functions (motor control, parameter monitoring, cycle optimization) into a single integrated control system. This consolidation shares computational resources and reduces redundant processing, thereby minimizing additional energy consumption while maximizing productivity benefits.
Data Source
AI summary
A laundry treating appliance includes a drum at least partially defining a treating chamber for receiving a laundry load for treatment according to a cycle of operation, a motor operably coupled with the drum to rotate the drum, a controller coupled to the motor for controlling the motor and for determining at least one input sensed from the motor, and a processor operably coupled with the controller and having a parameter estimator to estimate parameter values of a laundry load based upon the at least one input. The processor is configured to send an excitation signal to the controller that randomly fluctuates an acceleration command to affect acceleration of the motor while the parameter values of the laundry load are estimated. The cycle of operation can then be adjusted based on the estimated parameter values of the laundry load.