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| 3D Temperature Field Reconstruction Method for Energy Storage System Based on Improved MRF-KFCM Effective Region Segmentation |
| Pan Guobing1,2, Wang Jie1,2, Ouyang Jing1,2 |
1. Institute of Distributed Energy and Microgrid Zhejiang University of Technology Hangzhou 310023 China;
2. College of Mechanical Engineering Zhejiang University of Technology Hangzhou 310023 China |
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Abstract Energy storage system is one of the core components of microgrid, and its thermal management is of great significance to the safety and stability of microgrid. The Infrared Thermal Imager cannot monitor the internal temperature filed of the battery stack, which is more important. Aiming at this problem, a 3D temperature field reconstruction method based on surface temperature field and virtual heat source has been proposed. The effective region is extracted by the segmentation algorithm and mapped to the surface temperature field by calibration. Then, the 3D temperature field of the battery stack is preliminarily reconstructed, and then the temperature of sub-unit is modified by virtual heat source. In order to depress the influence on the 3D reconstruction which caused by the inaccurate region segmentation of infrared image of battery stack, the Kernel-Based Fuzzy C-Means Clustering algorithm under the constraint of Markov Random Field has been improved. In this method, the preliminary effective region of the battery stack in the visible light image can obtained by Otsu algorithm, and assigning pixels to cluster with different target information weight, then the accurate position in the infrared image is obtained by registration. Experimental results show that the proposed method can reflect the variation trend and local difference of the internal temperature of the battery stack, and the accuracy can meet the practical application requirements.
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Received: 25 November 2019
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2020, Vol. 35 
