Research On Multifractal Characteristics Of Hybrid Power System In Fuel Cell Vehicles

In recent years,fuel cell-based hybrid vehicles have become a research hotspot in the field of new energy vehicles with their low energy consumption,zero emissions and high safety features,combining the advantages of both electric and conventional vehicles.In order to clarify the complexity of FCHPS,this thesis innovatively uses fractal theory and entropy-related theoretical methods to comprehensively describe the complex characteristics of the system structure,driving conditions,energy flow and other dimensions(measures)of FCHPS,respectively.The research efforts in this thesis include the following:First,the data selection,data sources,and the modeling and simulation process of the data under each measurement are presented separately.Four configurations,pure fuel cell(PFC),fuel cell and battery hybridization(FC+B),fuel cell and ultracapacitor hybridization(FC+C),and fuel cell,battery,and ultracapacitor hybridization(FC+B+C)are selected for the study under the structure measure.Under the measurement of driving conditions,three sets of representative standard vehicle test conditions were selected:New European Driving Cycle(NEDC),World Light Vehicle Test Cycle(WLTC),China Light-duty Vehicle Test Cycle for Passenger Car(CLTC-P),and a set of Urban Road Real Driving Cycle(URRDC),of which URRDC conditions are driving data collected from a section of a real vehicle.The actual driving conditions are obtained by principal component analysis and K-means clustering analysis and are analyzed and processed according to the actual conditions of urban road driving.Under the energy flow measurement,the simulation output results of the three-energy source fuel cell vehicle configuration under power-following control are chosen to be further investigated,and the whole vehicle simulation of the three-energy source fuel cell vehicle in power-following mode is performed in the combined environment of MATLAB and the automotive simulation software ADVISOR platform to obtain the energy flow data required for this study.Secondly,the multifractal detrended fluctuation analysis(MF-DFA)method is used to explore the scale-invariance of the time series under driving conditions and energy flow measures,and by calculating the fluctuation function,generalized Hurst exponent,mass exponent spectra and multifractal singularity spectra of both time series,it is demonstrated that the time series under different measures exhibit long-range anticorrelation and significant multifractal characteristics,which provide a basis for the subsequent time series’ The correlation dimension and multifractal entropy of the time series are calculated.Finally,the fractal dimension of FCHPS with different measures is calculated.Subsequently,due to the superior classification ability of information entropy for different signals,which can truly reflect the complexity of information,the concept of multifractal entropy was defined using the concept of information entropy.Compared with the results of the calculation of the correlation dimension of time series under driving conditions and energy flow measures,the results obtained by the defined multifractal entropy were more optimal.Meanwhile,the Analytic Hierarchy Process(AHP)was introduced to achieve the characterization and quantification of the complexity of the entire FCHPS.In this thesis,we use fractal theory and entropy theory to quantitatively characterize the irregularity and complexity of FCHPS by characterizing the fractal dimension of different measures,the multifractal entropy and the overall measure of system complexity,and to provide a basis for the analysis of the complexity law of the hybrid power system of fuel cell vehicles.