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Outline
To ensure the long-term safe and stable operation of electric vehicles and reduce the failure rate of lithium-ion batteries, aimed at the issue of whether the battery management system of electric vehicles can accurately and effectively detect the two important parameters of batteries, i.e., state-of-charge (SOC) and state-of-health (SOH), an improved convolutional neural networks-sequence-to-sequence (CNN-Seq2Seq) neural networks joint estimation method for the SOC and SOH of lithium-ion batteries based on CNN-long short-term memory (CNN-LSTM) neural networks was proposed. The results of comparative experiments on the public data set show that the proposed method improves the stability and accuracy of SOC and SOH estimation results for lithium-ion batteries.
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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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