Multifractal analysis vehicle’s in-use speed profile for application in driving cycles

Abstract

Time signals recorded by the on-board diagnostic system (OBD), describing the manner of vehicle’s movement in actual road conditions show non-stationarity and non-linearity, as well as statistical multiscalarity. In practice, it means that the analysis of registered time series requires modelling of non-linear phenomena. The aim of this study was to examine the nature of the vehicle speed profile in actual road conditions with the method of multifractal analysis. A number of studies indicates that the driving tests applied for many years have not been representative for the actual operating conditions of vehicles. For both the new Worldwide Harmonised Light duty Test Cycle (WLTC), a worldwide harmonised procedure of light vehicle testing, as well as in actual urban driving conditions along the measuring route, being subject to empirical research, confirmation of strong multifractal properties of the recorded vehicle speed time series have been obtained.

Verifying the Efficiency of a Diesel Particulate Filter Using Particle Counters with Two Different Measurements in Periodic Technical Inspection of Vehicles

“…One device used a DC and the other a CPC. A series of comparative tests was carried out on a group of 50 vehicles aimed at verifying the hypothesis that the technical solutions used in selected devices will allow for their use in a reliable diagnosis of DPFs, carried out on a large scale during periodic technical inspection, which would solve the common problem of excessive emissions of vehicles with defective filters [18].…”

CO2 Emission Costs Due to the Production and Use of Vehicles in the Context of Automotive Development

“…Each vehicle's drive through such a cycle therefore follows an identical course of speed, which allows representative comparisons of exhaust emissions from individual vehicles. The exhaust gases of the tested cars are sampled by analyzers and assessed in terms of the amount of individual pollutants (Wiśniowski et al, 2019;Puchalski et al, 2018;Chłopek, 2020).…”

Synthesis of naturalistic vehicle driving cycles using the Markov Chain Monte Carlo method

“…Papers where road traffic was analysed based on recorded vehicle speed signals indicate the multifractal properties of the dynamics of such traffic [3,16]. Multifractality can also be observed both in real and standard driving cycles [14]. Our research proposes to eliminate the acceleration signal from the multi-dimensional description of vehicle states using information about driving dynamics represented by multifractal parameters of the speed signal.…”

“…6). The analysis was carried out based on the time series of vehicle speed recorded with a sampling period of 1 s. The research has been described in the paper [14]. Due to the large share of "zero speeds" (idle periods) in the test, amounting to approx.…”