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In view of the problem that the variable window Adaptive Unscented Kalman Filter (AUKF) algorithm has a large mutation when the window changes, and the window sequence data decreases sharply, resulting in the increase of error, stability and accuracy decline in state estimation, this paper uses the Forgetting Factor Recursive Least Square (FFRLS) algorithm to identify parameters based on the second-order RC equivalent circuit model, combined with the improved variable window AUKF algorithm to estimate the State of Charge (SOC) of lithium battery, it is verified by the Urban Dynamometer Driving Schedule (UDDS) cycle test, and compared with Unscented Kalman Filter (UKF), AUKF and variable window AUKF algorithms. The test results show that the improved AUKF algorithm can control the average error within 0.38%, with higher accuracy and convergence.
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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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