Abstract:

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 short-time 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 steady-state operation of electric vehicles. Then， running fragments based on machine learning are regressed， and the short-time test cycle is constructed by fusion and splicing. Also， an improved braking safety detection method is proposed with short-time 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 short-time test cycle and detection method is verified by means of following test on a test bench.

Key words: electric vehicles, braking safety, short-time cycle, detection method, test bench