Research on Multifractal Characteristics of Vehicle Driving Cycles

Vehicle driving cycles have complex characteristics, but there are few publicly reported methods for their quantitative characterization. This paper innovatively investigates multifractal characteristics using the fractal theory to characterize properties, laying foundation applications such as vehicle cycle feature identification, energy management strategies (EMS), and so on. To explore scale-invariance of cycles, four were analyzed Multifractal Detrended Fluctuation Analysis (MF-DFA) method, three which standard test cycles: New European Driving Cycle (NEDC), World-wide harmonized Light-duty Test (WLTC) China Passenger Car (CLTC-P), other is Urban Road Real (URRDC), was obtained by analyzing processing data collected in actual urban conditions. The fluctuation functions, generalized Hurst exponents, mass exponent spectra, singularity characteristic parameters calculated verify quantify singularities different time series. results show that fluctuations all long-range anticorrelations exhibit significant characteristics. can provide a basis analysis complexity cycles.