DC varaiable speed compressor control method and control system
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Solution Overview
Problem
Current DC variable speed air conditioners do not effectively factor in energy consumption when adjusting compressor speed, leading to inefficient energy use during peak temperature periods.
Innovation Solution
A control system comprising a speed control calculation unit, data storage unit, information acquisition unit, network communication module, and speed control output unit that adjusts compressor operation based on outdoor temperature curves and peak energy consumption periods to minimize energy usage by modifying compressor-on and compressor-off timing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the compressor speed is adjusted based on basic matching principle (matching current output to current load), then the number of on/off cycles is reduced and comfort is improved, but energy consumption during peak temperature periods is not optimized
Solution Approach 1:
The system performs preliminary action by predicting future peak temperature periods using weather forecast data and temperature curve analysis. Before the peak temperature period arrives, the system pre-adjusts the compressor operation timing and speed to prepare for the upcoming high-load period, thereby optimizing energy consumption during the peak period rather than simply reacting to current conditions.
Solution Approach 2:
The system implements dynamic speed control by continuously adjusting the compressor speed based on real-time temperature data, predicted peak periods, and load conditions. Instead of fixed speed steps, the compressor operates at variable speeds that dynamically adapt to changing environmental conditions and energy consumption patterns, allowing optimization of both comfort and energy efficiency.
2Ease of operation
If the compressor operates continuously to maintain temperature, then comfort is maintained, but energy consumption increases during peak temperature periods
Solution Approach 1:
The system implements periodic action by analyzing temperature curves and identifying regular patterns in temperature fluctuations. It predicts peak temperature periods based on historical data and weather forecasts, then schedules compressor operation in periodic cycles that align with these predicted peaks. This allows the compressor to operate efficiently during high-demand periods while reducing operation during lower-demand periods, optimizing both temperature stability and energy consumption.
3Productivity
If the compressor speed is increased to meet high cooling demand during peak temperature, then cooling performance is improved, but energy consumption increases significantly
Solution Approach 1:
The system applies parameter changes by modifying the compressor operating parameters (speed, power output) based on predicted peak temperature periods and real-time temperature deviations. Instead of always operating at high speed during peak periods, the system dynamically adjusts parameters to match the actual cooling demand, using weather forecast data and temperature curve analysis to optimize the balance between cooling capacity and energy consumption.
Data Source
AI summary
The present disclosure relates to the field of air conditioning technology. In particular, it involves a control method and control device based on a DC variable speed AC compressor.