Full
Outline
The curve of relationship between the state-of-charge (SOC) and open-circuit voltage (OCV) of lithium-ion batteries is the core factor affecting the SOC estimation accuracy. However, the traditional methods obtain the SOC-OCV curve through incremental OCV tests, which require a lot of time. Under this background, a method for reconstructing SOC-OCV curves at different temperatures is proposed in this paper, so as to improve the SOC estimation accuracy while reducing the experimental time. First, a small number of key OCV test points are determined by the SOC-OCV curve obtained from the traditional incremental OCV test at room temperature. At other temperatures, the particle swarm optimization algorithm is used to identify the OCV value in untested areas, with the determined key OCV test points as the boundary and 5% SOC as an interval. Based on the test and identified values of OCV, the SOC-OCV curves at different temperatures are reconstructed. This method improves the accuracy of SOC-OCV curves while reducing the OCV test points. Based on reconstructed SOC-OCV curves, the SOC is estimated by an adaptive extended Kalman filter. Results show that the root mean square error of SOC estimation decreased by at least 40% at different temperatures.
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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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