Full
Outline
Due to the magnetic saturation effect, there is a difference between the apparent inductance and incremental inductance of a permanent magnet synchronous motor (PMSM), resulting in a deviation in the description of the motor model. With the consideration of the influence of magnetic saturation effect, a new PMSM model is established in this paper by introducing apparent inductance and incremental inductance, and the model parameters are further identified by the particle swarm optimization (PSO) algorithm. To solve the problem that the PSO algorithm is easy to fall into local optimum and its convergence speed is slow, an adaptive particle swarm optimization (APSO) algorithm combined with reverse learning is proposed. To overcome the influence of inverter nonlinearity on the identification results, the error voltage caused by inverter nonlinearity is taken as a new parameter to be identified, and it is identified online. Experimental results verified the accuracy of the APSO algorithm when it was used in identifying the d- and q-axis apparent inductance, d- and q-axis incremental inductance, permanent magnet flux linkage and inverter nonlinearity error voltage of PMSM.
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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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