Multi-Level Thermal Modeling and Management of Battery Energy Storage Systems
With the accelerating global transition toward sustainable energy, the role of battery energy storage systems (ESSs) becomes increasingly prominent. This study employs the isothermal battery calorimetry (IBC) measurement method and computational fluid dynamics (CFD) simulation to develop a multi-dom...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
|
| Series: | Batteries |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2313-0105/11/6/219 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849521426287034368 |
|---|---|
| author | Zhe Lv Zhonghao Sun Lei Wang Qi Liu Jianbo Zhang |
| author_facet | Zhe Lv Zhonghao Sun Lei Wang Qi Liu Jianbo Zhang |
| author_sort | Zhe Lv |
| collection | DOAJ |
| description | With the accelerating global transition toward sustainable energy, the role of battery energy storage systems (ESSs) becomes increasingly prominent. This study employs the isothermal battery calorimetry (IBC) measurement method and computational fluid dynamics (CFD) simulation to develop a multi-domain thermal modeling framework for battery systems, spanning from individual cells to modules, clusters, and ultimately the container level. Experimental validation confirms the model’s accuracy, with the simulated maximum cell temperature of 36.2 °C showing only a 1.8 °C deviation from the measured value of 34.4 °C under real-world operating conditions. Furthermore, by integrating on-site calibrated thermodynamic parameters of the container, a battery system energy efficiency model is established. Combined with the battery aging engineering model, a coupled lifetime–energy efficiency model is constructed. Six different control strategies are simulated and analyzed to quantify the system’s comprehensive lifecycle benefits. The results demonstrate that the optimized control strategy enhances the overall energy storage station revenue by 2.63%, yielding an additional cumulative profit of CNY 13.676 million over the entire lifecycle. This research provides an effective simulation framework and decision-making basis for the thermal management optimization and economic evaluation of battery ESSs. |
| format | Article |
| id | doaj-art-00738fd673ca441997c6ac43e348cda8 |
| institution | Kabale University |
| issn | 2313-0105 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Batteries |
| spelling | doaj-art-00738fd673ca441997c6ac43e348cda82025-08-20T03:32:27ZengMDPI AGBatteries2313-01052025-06-0111621910.3390/batteries11060219Multi-Level Thermal Modeling and Management of Battery Energy Storage SystemsZhe Lv0Zhonghao Sun1Lei Wang2Qi Liu3Jianbo Zhang4Beijing HyperStrong Technology Co., Ltd., Building 2C, No. 9 Fenghao East Road, Haidian District, Beijing 100094, ChinaBeijing HyperStrong Technology Co., Ltd., Building 2C, No. 9 Fenghao East Road, Haidian District, Beijing 100094, ChinaBeijing HyperStrong Technology Co., Ltd., Building 2C, No. 9 Fenghao East Road, Haidian District, Beijing 100094, ChinaSchool of Material Science and Engineering, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Vehicle and Mobility, Tsinghua University, Beijing 100084, ChinaWith the accelerating global transition toward sustainable energy, the role of battery energy storage systems (ESSs) becomes increasingly prominent. This study employs the isothermal battery calorimetry (IBC) measurement method and computational fluid dynamics (CFD) simulation to develop a multi-domain thermal modeling framework for battery systems, spanning from individual cells to modules, clusters, and ultimately the container level. Experimental validation confirms the model’s accuracy, with the simulated maximum cell temperature of 36.2 °C showing only a 1.8 °C deviation from the measured value of 34.4 °C under real-world operating conditions. Furthermore, by integrating on-site calibrated thermodynamic parameters of the container, a battery system energy efficiency model is established. Combined with the battery aging engineering model, a coupled lifetime–energy efficiency model is constructed. Six different control strategies are simulated and analyzed to quantify the system’s comprehensive lifecycle benefits. The results demonstrate that the optimized control strategy enhances the overall energy storage station revenue by 2.63%, yielding an additional cumulative profit of CNY 13.676 million over the entire lifecycle. This research provides an effective simulation framework and decision-making basis for the thermal management optimization and economic evaluation of battery ESSs.https://www.mdpi.com/2313-0105/11/6/219battery energy storage systemsthermal modelcontrol strategy optimizationlife and energy efficiency coupled model |
| spellingShingle | Zhe Lv Zhonghao Sun Lei Wang Qi Liu Jianbo Zhang Multi-Level Thermal Modeling and Management of Battery Energy Storage Systems Batteries battery energy storage systems thermal model control strategy optimization life and energy efficiency coupled model |
| title | Multi-Level Thermal Modeling and Management of Battery Energy Storage Systems |
| title_full | Multi-Level Thermal Modeling and Management of Battery Energy Storage Systems |
| title_fullStr | Multi-Level Thermal Modeling and Management of Battery Energy Storage Systems |
| title_full_unstemmed | Multi-Level Thermal Modeling and Management of Battery Energy Storage Systems |
| title_short | Multi-Level Thermal Modeling and Management of Battery Energy Storage Systems |
| title_sort | multi level thermal modeling and management of battery energy storage systems |
| topic | battery energy storage systems thermal model control strategy optimization life and energy efficiency coupled model |
| url | https://www.mdpi.com/2313-0105/11/6/219 |
| work_keys_str_mv | AT zhelv multilevelthermalmodelingandmanagementofbatteryenergystoragesystems AT zhonghaosun multilevelthermalmodelingandmanagementofbatteryenergystoragesystems AT leiwang multilevelthermalmodelingandmanagementofbatteryenergystoragesystems AT qiliu multilevelthermalmodelingandmanagementofbatteryenergystoragesystems AT jianbozhang multilevelthermalmodelingandmanagementofbatteryenergystoragesystems |