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小米科技(武汉)有限公司 武汉 430010
李倍宇,男,中级工程师,小米科技(武汉)有限公司,18777357765,E-mial:libeiyu@xiaomi.com。研究方向:家用空调智能控制,空气源热泵空调节能运行研究。
收稿:2026-07-07,
修回:2026-08-19,
录用:2026-08-19,
网络首发:2026-09-24,
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李倍宇,廖敏,赵倩,等. 基于动态过热度驱动多联式空调精准控温关键技术[J]. 制冷学报,XXXX,XX(XX):1-9.
Li Beiyu,Liao Min,Zhao Qian,et al. Dynamic Superheat-Driven Key Technology for Precise Temperature Control in Multi-Split Air Conditioning Systems[J]. Journal of Refrigeration,XXXX,XX(XX):1-9.
李倍宇,廖敏,赵倩,等. 基于动态过热度驱动多联式空调精准控温关键技术[J]. 制冷学报,XXXX,XX(XX):1-9. DOI: 10.12465/issn.0253-4339.20260707002.
Li Beiyu,Liao Min,Zhao Qian,et al. Dynamic Superheat-Driven Key Technology for Precise Temperature Control in Multi-Split Air Conditioning Systems[J]. Journal of Refrigeration,XXXX,XX(XX):1-9. DOI: 10.12465/issn.0253-4339.20260707002.
为解决现有多联机控温效果无法满足家用复杂使用场景舒适性的问题,本文基于多智能体强化学习算法,提出动态过热度驱动的自适应精准控温方法,综合考虑机组启动、快速降温及稳态运行3个不同温控阶段的机组运行特征及房间温度响应特征,分阶段差异化适配电子膨胀阀开度与室内机过热度的调控方案,并进行了实验验证分析。结果表明:搭载本文控温技术的受试样机,降温响应速度≥0.45 ℃/min、控温波动<0.3 ℃,在室温达标时长与稳态控温稳定性上,均较定蒸发温度和定过热度2类传统算法表现出显著性能优势,综合降温速率提高38.4%,控温精度提高42.2%。
Existing multi-split air conditioning systems fail to provide satisfactory thermal comfort in complex residential operating scenarios. To address this limitation, this study proposes a dynamic superheat-driven adaptive precision temperature control strategy employing a multi-agent reinforcement learning (MARL) algorithm. The strategy accounts for system operational characteristics and room temperature dynamics across three distinct control stages, namely, start-up, rapid cool-down, and steady-state operation, and implements a stage-specific control scheme for electronic expansion valve (EEV) opening and indoor-unit superheat. Experimental validation demonstrates that the prototype incorporating the proposed strategy achieves a cool-down response rate of ≥0.45 ℃/min and a temperature fluctuation of <0.3 ℃. Compared with two conventional control strategies—fixed evaporation temperature and fixed superheat—the proposed strategy exhibits significant advantages in both setpoint attainment time and steady-state stability, with an improvenet of overall cool-down rate by 38.4% and temperature control accuracy by 42.2%.
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