LOW VOLTAGE APPARATUS ›› 2025, Vol. 0 ›› Issue (8): 25-33.doi: 10.16628/j.cnki.2095-8188.2025.08.004

• Research & Analysis • Previous Articles     Next Articles

A Waveform Feature Extraction and Recognition Method for Electric Bicycle Charging Load

ZHAO Jie1, ZHANG Yanping1, DING Yuanyuan2   

  1. 1. Shanghai Hongtan Intelligent Technology Co., Ltd., Shanghai 201306, China
    2. Henan Zhengzhou Petroleum Branch, Sinopec Sales Co., Ltd., Zhengzhou 450000, China
  • Received:2025-03-25 Online:2025-08-30 Published:2025-09-26

Abstract:

In order to realize the identification of the electric bicycle charging load on the user side, the load current on the user side is collected in real time through the Internet of Things (IoT) circuit breaker.The disturbance time point of the current curve is quickly identified.The influence of the periodic load is filtered out, and the basic characteristics of the disturbance current curve are extracted to form the absolute value increment curve.According to the formation criteria of the initial transient pulse peak, time limit width of the charging current curve and the pulse peak, time limit width and symmetry of the current waveform at the beginning of steady-state charging, combined with the change of power increment and harmonic increment before and after charging, the charging load of the electric bicycle is identified to alarm or trip the circuit breaker, so as to ensure that the charging load of the electric bicycle is forbidden in the charging area of the non-electric bicycle.Experiments show that the proposed method is simple and effective, and can be implemented locally through the IoT circuit breaker.

Key words: electric bicycle, Internet of Things (IoT) circuit breaker, charging load identification, absolute value increment

CLC Number: