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To obtain the state-of-charge (SOC) estimation value well, a second-order equivalent circuit model is selected as the research object. Aimed at the disadvantage that the recursive least squares method with a forgetting factor is easy to be disturbed by environmental factors such as noises in the parameter identification, a bias compensation recursive least squares method is proposed to realize the accurate identification of model parameters, and the SOC is estimated combined with the unscented Kalman filter algorithm. In view of the disadvantages of the unscented Kalman filter algorithm such as poor stability, the weight vectors are used to update the Kalman filter gain in the filter algorithm. Experimental results show that the total error of the proposed algorithm in estimating SOC was controlled within 2.7%, which verified the robustness and effectiveness of the algorithm.
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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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