Air Conditioner Parameter Smoothing to Reduce Warm Air Oscillation
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Solution Overview
Problem
Air conditioners experience warm air oscillation due to sensor errors and control parameter hopping, leading to user discomfort and potential component degradation.
Innovation Solution
A method for controlling air conditioners by obtaining predicted and historical control parameter combinations, determining a target control parameter combination based on similarity, and operating the air conditioner according to this combination to stabilize parameter changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If Genetic Algorithm based on PID control theory combined with AI machine learning or deep learning is used as the main control logic, then energy efficiency and user comfort are improved, but warm air oscillation occurs due to sensor errors and control parameter hopping
Solution Approach 1:
The patent applies preliminary action by predicting future control parameters before they are needed. The prediction model forecasts control parameters in advance, and the optimization module pre-adjusts them to prevent oscillations before they occur, rather than reacting after temperature deviations happen.
Solution Approach 2:
The patent implements feedback by using historical control parameter data and actual temperature measurements to continuously refine predictions. The system compares predicted outcomes with actual results and adjusts the prediction model accordingly, creating a closed-loop control system that reduces oscillations.
2Ease of operation
If control parameters are frequently adjusted to maintain temperature, then user comfort is improved, but component lifespan is reduced due to compressor and internal fan oscillations
Solution Approach 1:
The system performs preliminary optimization of control parameters to find the most efficient settings before implementation. By predicting the optimal control sequence in advance and smoothing transitions between parameters, the system achieves good user comfort while minimizing frequent adjustments that would harm component lifespan.
3Adaptability or versatility
If control parameters change greatly to respond to environmental variations, then adaptability is improved, but warm air oscillation and user discomfort increase
Solution Approach 1:
The patent applies dynamics by making the control system adaptive and flexible. The prediction model dynamically adjusts control parameters based on real-time environmental conditions and historical data, allowing the system to adapt to variations while maintaining stability through optimized transition patterns.
Solution Approach 2:
The system uses feedback from environmental sensors and historical performance data to continuously refine its predictions. This allows the system to adapt to environmental variations while learning from past oscillation patterns to prevent future instability.
Data Source
AI summary
A method for controlling an air conditioner, an air conditioner and a computer-readable storage medium are provided. The method includes: obtaining at least two predicted control parameter combinations for a current cycle prediction of the air conditioner and obtaining a historical control parameter combination of the air conditioner from a previous cycle operation; determining a target control parameter combination for the air conditioner according to parameter similarities between each of the predicted control parameter combinations and the historical control parameter combination; and controlling the air conditioner to operate according to the parameter values in the target control parameter combination.