基于可重构热电阵列的动态电池温控系统——实现动态温度均匀化
Dynamic Battery Temperature Control System Based on Reconfigurable Thermoelectric Arrays—Achieving Dynamic Temperature Uniformity
DOI: 10.12677/sea.2025.142018, PDF,    国家自然科学基金支持
作者: 黄宏滔, 贾宏志*：上海理工大学光电信息与计算机工程学院，上海；张 磊, 徐舒喜, 刘 源：华东光电集成器件研究所，安徽 蚌埠
关键词: 可重构热电阵列；电池热管理；温度均匀性；能量收集；模糊PID；Reconfigurable Thermoelectric Arrays； Battery Thermal Management； Temperature Uniformity； Energy Harvesting； Fuzzy-PID
摘要: 基于热电效应的可逆性，本研究提出了一种动态可重构热电阵列系统，旨在解决电池组内部温度不均的问题，并实现快速收敛与能量收集。该系统通过动态切换每个热电模块(Thermoelectric Module, TEM)的工作模式——加热、冷却或发电，结合热点追踪技术及模糊PID (Fuzzy-PID)控制算法，实现了按需精准温控，不仅有效维持了电池工作环境的温度均匀性，还最大化利用了热差进行电力回收。实验验证表明，系统温度误差仅为1.77℃，系统超调损耗仅占整体功耗的0.11%，且在能量收集模式下能够达到319 mV的最大俘获电压。这项工作提供了高效绿色的温控解决方案。
Abstract: Leveraging the reversibility of the thermoelectric effect, this study introduces a dynamic reconfigurable thermoelectric array system designed to solve temperature imbalance within battery packs, enabling rapid convergence and energy harvesting. The system dynamically switches the operating mode of each thermoelectric module (TEM)—heating, cooling, or power generation —combined with hotspot tracking technology and a Fuzzy-PID control algorithm, achieving on-demand precise temperature control. This not only effectively maintains temperature uniformity within the battery operating environment but also maximizes the utilization of thermal gradients for power recovery. Experimental validation shows that the temperature error is only 1.77˚C, overshoot losses account for only 0.11% of the total power consumption, and the maximum captured voltage in the energy harvesting mode reaches 319 mV. This work presents an efficient and environmentally-friendly temperature control solution.
文章引用：黄宏滔, 张磊, 徐舒喜, 刘源, 贾宏志. 基于可重构热电阵列的动态电池温控系统——实现动态温度均匀化[J]. 软件工程与应用, 2025, 14(2): 189-200. https://doi.org/10.12677/sea.2025.142018

参考文献

[1] Yan, Y., Wang, B., Wang, C., Xiao, C. and Zhao, D. (2024) Adaptive Maximum Available Energy Evaluation for Lithium Battery in Hydrogen-Electric Hybrid Unmanned Aerial Vehicle Applications Considering Dynamic Ambient Temperature and Aging Level. Energy Conversion and Management, 314, Article 118685. [Google Scholar] [CrossRef] 
[2] Rizvi, S., Tahir, M.W., Ramzan, N. and Merten, C. (2024) Multiscale-Multidomain Model Order Reduction of Lithium-Ion Batteries for Automobile Application: A Review. Journal of Energy Storage, 99, Article 113390. [Google Scholar] [CrossRef] 
[3] Kumar, R.R., Bharatiraja, C., Udhayakumar, K., Devakirubakaran, S., Sekar, K.S. and Mihet-Popa, L. (2023) Advances in Batteries, Battery Modeling, Battery Management System, Battery Thermal Management, SOC, SOH, and Charge/Discharge Characteristics in EV Applications. IEEE Access, 11, 105761-105809. [Google Scholar] [CrossRef] 
[4] Fan, Q., Qu, D., Xu, C., Yang, H., Yang, S., Lin, D., et al. (2025) A Lithium-Ion Battery System with High Power and Wide Temperature Range Targeting the Internet of Things Applications. Journal of Power Sources, 630, Article 236070. [Google Scholar] [CrossRef] 
[5] Zhou, J., Shen, W., Ma, Z., Mou, X., Zhou, Y., Li, H., et al. (2024) Chebyshev-Galerkin-Based Thermal Fault Detection and Localization for Pouch-Type Li-Ion Battery. IEEE Transactions on Industrial Informatics, 20, 3436-3445. [Google Scholar] [CrossRef] 
[6] Sadeghi, H. and Restuccia, F. (2025) Kinetic Modelling of Thermal Decomposition in Lithium-Ion Battery Components during Thermal Runaway. Journal of Power Sources, 629, Article 236026. [Google Scholar] [CrossRef] 
[7] Mousavi, S., Zadehkabir, A., Siavashi, M. and Yang, X. (2023) An Improved Hybrid Thermal Management System for Prismatic Li-Ion Batteries Integrated with Mini-Channel and Phase Change Materials. Applied Energy, 334, Article 120643. [Google Scholar] [CrossRef] 
[8] Singh, L.K., Gupta, A.K. and Sharma, A.K. (2022) Hybrid Thermal Management System for a Lithium-Ion Battery Module: Effect of Cell Arrangement, Discharge Rate, Phase Change Material Thickness and Air Velocity. Journal of Energy Storage, 52, Article 104907. [Google Scholar] [CrossRef] 
[9] Sun, Z., Guo, Y., Zhang, C., Xu, H., Zhou, Q., Wang, C. (2023) A Novel Hybrid Battery Thermal Management System for Prevention of Thermal Runaway Propagation. IEEE Transactions on Transportation Electrification, 9, 5028-5038. [Google Scholar] [CrossRef] 
[10] Hong, J., Wang, Z., Qu, C., Ma, F., Xu, X., Yang, J., et al. (2023) Fault Prognosis and Isolation of Lithium-Ion Batteries in Electric Vehicles Considering Real-Scenario Thermal Runaway Risks. IEEE Journal of Emerging and Selected Topics in Power Electronics, 11, 88-99. [Google Scholar] [CrossRef] 
[11] Yang, H., Yang, G., Liu, N., Zhang, S. and Gao, Q. (2025) Investigating the Impact of Inlet Angle on the Performance of Air-Cooling Lithium-Ion Battery Pack. Applied Thermal Engineering, 263, Article 125314. [Google Scholar] [CrossRef] 
[12] Vashisht, S., Rajat, and Rakshit, D. (2024) Recent Advances and Perspectives in Enhancing Thermal State of Lithium-Ion Batteries with Phase Change Materials: Internal and External Heat Transfer Enhancement Factors. E Transportation, 22, Article 100381. [Google Scholar] [CrossRef] 
[13] Gu, X., Ding, P., Chao, G. and Cui, Y. (2024) Analysis and Prediction of Battery Temperature in Thermal Management System Coupled Sic Foam-Composite Phase Change Material and Air. Journal of Energy Storage, 104, Article 114503. [Google Scholar] [CrossRef] 
[14] Gharehghani, A., Rabiei, M., Mehranfar, S., Saeedipour, S., Mahmoudzadeh Andwari, A., García, A., et al. (2024) Progress in Battery Thermal Management Systems Technologies for Electric Vehicles. Renewable and Sustainable Energy Reviews, 202, Article 114654. [Google Scholar] [CrossRef] 
[15] Lin, J., Liu, D., Liu, X., Liu, M. and Cui, Y. (2025) Cnt@mxene Porous Composite PCM Based Thermal Management for Lithium-Ion Battery System. Applied Thermal Engineering, 262, Article 125240. [Google Scholar] [CrossRef] 
[16] Xie, Y., Li, B., Hu, X., Lin, X., Zhang, Y. and Zheng, J. (2021) Improving the Air-Cooling Performance for Battery Packs via Electrothermal Modeling and Particle Swarm Optimization. IEEE Transactions on Transportation Electrification, 7, 1285-1302. [Google Scholar] [CrossRef] 
[17] Hasan, H.A., Togun, H., Abed, A.M., Biswas, N. and Mohammed, H.I. (2023) Thermal Performance Assessment for an Array of Cylindrical Lithium-Ion Battery Cells Using an Air-Cooling System. Applied Energy, 346, Article 121354. [Google Scholar] [CrossRef] 
[18] Chen, K., Zhang, Z., Wu, B., Song, M. and Wu, X. (2024) An Air-Cooled System with a Control Strategy for Efficient Battery Thermal Management. Applied Thermal Engineering, 236, Article 121578. [Google Scholar] [CrossRef] 
[19] Huang, G., Zhao, P. and Zhang, G. (2022) Real-Time Battery Thermal Management for Electric Vehicles Based on Deep Reinforcement Learning. IEEE Internet of Things Journal, 9, 14060-14072. [Google Scholar] [CrossRef] 
[20] Verma, A., Saikia, T., Saikia, P., Rakshit, D. and Ugalde-Loo, C.E. (2023) Thermal Performance Analysis and Experimental Verification of Lithium-Ion Batteries for Electric Vehicle Applications through Optimized Inclined Mini-Channels. Applied Energy, 335, Article 120743. [Google Scholar] [CrossRef] 
[21] Gan, H., Tian, J., Qiu, H., Li, G., Liu, C. and Zhao, J. (2025) Thermal Performance of Symmetrical Double-Spiral Channel Liquid Cooling Plate Based Battery Thermal Management for Energy Storage System. Applied Thermal Engineering, 263, Article 125399. [Google Scholar] [CrossRef] 
[22] Zhang, S., Chen, Z., Bai, Q., Li, W. and Pei, Y. (2022) Individualization of Optimal Operation Currents for Promoting Multi-Stage Thermoelectric Cooling. Materials Today Physics, 26, Article 100746. [Google Scholar] [CrossRef] 
[23] Park, S.J., Bang, K.M., Kim, B., Ziolkowski, P., Jeong, J. and Jin, H. (2022) Adaptive Thermoelectric Cooling System for Energy-Efficient Local and Transient Heat Management. Applied Thermal Engineering, 216, Article 119060. [Google Scholar] [CrossRef] 
[24] Buchalik, R., Nowak, G. and Nowak, I. (2022) Comparative Analysis and Optimization of One and Two-Stage Cooling Systems with Thermoelectric Cells with Respect to Supercooling. Energy Conversion and Management, 259, Article 115587. [Google Scholar] [CrossRef] 
[25] Ang, E.Y.M., Ng, P.S., Soh, C.B. and Wang, P.C. (2022) Multi-Stage Thermoelectric Coolers for Cooling Wearables. Thermal Science and Engineering Progress, 36, Article 101511. [Google Scholar] [CrossRef] 
[26] Luo, D., Zhao, Y., Cao, J., Wu, Z., Yang, X. and Chen, H. (2024) Effective Temperature Control of a Thermoelectric-Based Battery Thermal Management System under Extreme Temperature Conditions. Journal of Energy Storage, 103, Article 114344. [Google Scholar] [CrossRef] 
[27] Wang, N., Tang, J., Shan, H., Jia, H., Peng, R. and Zuo, L. (2023) Efficient Power Conversion Using a PV-PCM-TE System Based on a Long Time Delay Phase Change with Concentrating Heat. IEEE Transactions on Power Electronics, 38, 10729-10738. [Google Scholar] [CrossRef] 
[28] Kwan, T.H., Wu, X. and Yao, Q. (2020) Complete Implementation of the Combined TEG-TEC Temperature Control and Energy Harvesting System. Control Engineering Practice, 95, Article 104224. [Google Scholar] [CrossRef] 
[29] Wang, N., Liu, Z.X., Ding, C., Zhang, J., Sui, G., Jia, H., et al. (2022) High Efficiency Thermoelectric Temperature Control System with Improved Proportional Integral Differential Algorithm Using Energy Feedback Technique. IEEE Transactions on Industrial Electronics, 69, 5225-5234. [Google Scholar] [CrossRef] 
[30] Kluska, J. and Zabinski, T. (2020) Pid-Like Adaptive Fuzzy Controller Design Based on Absolute Stability Criterion. IEEE Transactions on Fuzzy Systems, 28, 523-533. [Google Scholar] [CrossRef] 

为你推荐