集成技术2025，Vol.14Issue(6)：117-126,10.DOI:10.12146/j.issn.2095-3135.20250629001
基于功率分层的PPO-PID薄膜热电冷却芯片的精准控温算法
Precise Temperature Control Algorithm of PPO-PID Thin Film Thermoelectric Cooling Chip Based on Power Stratification
摘要
Abstract
The thin film thermoelectric cooler has problems such as excessive energy consumption,low temperature control accuracy and chip overtemperature due to the mismatch between the current and the hot spot heat flux density of the chip in the process of integrated cooling chip.To solve these problems,a PPO-PID temperature control algorithm based on power stratification is proposed.The power stratification strategy is used to control the hierarchical current of thin film thermoelectric cooler with different cooling capacity requirements,and the proximal policy optimization(PPO)algorithm is used as the main control algorithm.By means of deep reinforcement learning,the parameters of proportional-integral-derivative control(PID)controller are automatically adjusted according to real-time temperature deviation and rate of change,and the current is fine-tuned,which almost eliminates the large temperature fluctuations in the PID temperature control process.The simulation results show that in the process of realizing the temperature control target of thin film thermoelectric cooler cold end,the temperature control accuracy of PPO-PID temperature control algorithm can reach±0.95℃,which is 79.35%higher than that of traditional PID control.In addition,filtering the output current of the hierarchical PPO-PID can improve the stability of the output current,but the average temperature difference between the cold end temperature and the target temperature rises to±1.15℃,so whether to add filtering can be considered according to the requirements of accuracy and current stability.关键词
薄膜热电制冷器/芯片热点/PID控制/近端策略优化算法/温度控制Key words
thin film thermoelectric cooler/chip hotspots/PID control/proximal policy optimization algorithm/temperature control分类
能源科技引用本文复制引用
王云艺,李美勇,张怡景,申利梅..基于功率分层的PPO-PID薄膜热电冷却芯片的精准控温算法[J].集成技术,2025,14(6):117-126,10.基金项目
国家自然科学基金项目(52176007) This work is supported by National Natural Science Foundation of China(52176007) （52176007）
