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Outline
Aimed at the problem that the prediction results of state-of-health (SOH) of lithium-ion batteries are inaccurate due to the failure to consider the capacity regeneration phenomenon, a nonlinear relationship method based on multi-time scale set empirical mode decomposition fusion time series mapping input and SOH is proposed. The battery capacity information considering capacity regeneration is decomposed into high-frequency main trend signals and low-frequency margin signals by an ensemble empirical mode decomposition (EEMD) algorithm, and the estimation of lithium-ion battery SOH is completed by the prediction results of the two types of signals. Results show that the proposed method can capture the phenomenon of capacity regeneration to improve the estimation accuracy and achieve the fitting of battery capacity degradation, and it is less affected by different prediction starting points. Both the predicted maximum RMSE (root mean square error) and MAE (mean absolute error) are not more than 1.5%, and the maximum MAPE (mean absolute percentage error) is not more than 2%.
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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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