Full
Outline
The analysis method based on incremental capacity (IC) achieves effective analysis of the aging mechanism of lithium-ion batteries by converting voltage plateaus into characteristic peaks. However, the immune capability of IC curves with respect to noise is poor, and the extracted health features are susceptible to interference from the noise peaks. To solve this problem, a state-of-health (SOH) estimation method based on noise immunity probability density function (PDF) feature extraction combined with an ensemble learning model is proposed. First, the PDF curve is obtained by calculating the PDF of the voltage curve, and different peak features extracted from the PDF and IC curves are analyzed and compared by setting different values of signal-to-noise ratio. Second, the learning speed and randomness of extreme learning machine are used to construct an ensemble learning model framework, so as to reduce the prediction error of a single model. Finally, SOH estimation experiments under different noise conditions were conducted on the CALCE dataset, and results demonstrated the high accuracy and reliability of the proposed method.
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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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