基于温度特征与占用预测的供热自适应控制方法及系统
By combining ensemble empirical mode decomposition and hidden Markov models, the heating control strategy is dynamically adjusted, solving the problem of the inability to accurately sense indoor occupancy status in existing technologies. This achieves both comfort during occupied periods and energy-saving effects during unoccupied periods.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- JINAN INSTITUTE OF SUPERCOMPUTING TECHNOLOGY
- Filing Date
- 2026-04-23
- Publication Date
- 2026-07-17
AI Technical Summary
Existing indoor temperature control methods cannot accurately sense indoor occupancy status, making it difficult for heating control to balance comfort and energy saving. Traditional constant temperature control results in energy waste, and timed control cannot cope with dynamic changes in users.
By combining ensemble empirical mode decomposition algorithm and hidden Markov model, the occupancy status is predicted through temperature fluctuation feature sequence, and adaptive heating control command is generated by combining model predictive control algorithm to dynamically adjust heating strategy.
It achieves non-intrusive occupancy status perception based on low-cost temperature sensors, accurately extracts human activity characteristics, and ensures comfort during periods when people are present and promotes energy conservation during periods when no one is present.
Smart Images
Figure CN122083400B_ABST