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There may be inconsistencies in temperature， charge state， aging state （capacity and internal resistance） between individual cells in a battery module. Due to the existence of the "short board effect"， the inconsistencies will affect the overall performance of the battery module， so timely and accurate inconsistencies diagnosis is very necessary. Considering that the above-mentioned inconsistencies will affect the electrode process characteristics， which will be reflected in the Electrochemical Impedance Spectroscopy （EIS） and Distribution of Relaxation Time （DRT）， in this paper， after clarifying the effect of several kinds of inconsistencies on EIS and DRT by combining the equivalent circuits， an inconsistencies diagnosis method for battery modules based on EIS and DRT is innovatively proposed. The performance of unsupervised clustering algorithms such as K-means， AP （Affinity Propagation） and DBSCAN （Density Based Spatial Clustering of Applications with Noise） is comparatively analyzed by mixing the abnormal batteries into a group of batteries with good consistency. The results show that the DBSCAN diagnostic accuracy is 99.2%， which can realize the accurate diagnosis of the inconsistency difference of single cells within the battery module.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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