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Conventional braking safety detection usually uses long and extreme working conditions but may result in a loss of accurate working range. To address this deficiency, firstly, a shorttime test cycle for stabilizing pedal mode test method is developed, which incorporates existing test standards , not limited to a single extreme braking mode but taking into consideration of fast steadystate operation of electric vehicles. Then, running fragments based on machine learning are regressed, and the shorttime test cycle is constructed by fusion and splicing. Also, an improved braking safety detection method is proposed with shorttime test cycle, which reduces the dimension of the characteristic parameters of the braking segments by the principal component analysis, while the hidden danger is judged by calculating the repeatability distance of braking segments based on the characteristic parameters. Finally, the effectiveness of the proposed shorttime test cycle and detection method is verified by means of following test on a test bench.
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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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