Stochastic simulation and validation of Markov models of real driving cycles
University of Technology and Humanities in Radom
Andrzej Puchalski   

University of Technology and Humanities in Radom
Data nadesłania: 08-03-2019
Data akceptacji: 13-06-2019
Data publikacji online: 17-06-2019
Data publikacji: 17-06-2019
Diagnostyka 2019;20(3):31–36
The driving cycle is a time series of the vehicle speed reflecting its movement in real road conditions. The WLTC (Worlwide harmonized Light duty Test Cycle) valid from August 2017 is based on real driving profiles derived from research and statistical analysis of road traffic in Europe, the USA and Asia. In addition to certification and comparative research, driving cycles are used in the process of virtual design of drive systems and embedded control algorithms, traffic management or intelligent road transport. Regardless of the intended use, the standard test does not guarantee the correctness of the results obtained. There is a need to generate many different driving cycles that meet the established equivalence conditions. The article discusses the methods of stochastic simulation and assessment of equivalence of obtained traffic models. The Monte Carlo method of Markov chains was used in the research. The comparative criteria are defined using the statistical parameters of the vehicle speed time series and the corresponding multifractal spectra. The synthesis was carried out at predetermined length of time series. The experiment carried out involved the study of traffic in real road conditions of urban driving and extra-urban large agglomerations during working days.
Zhao B, Hofman T, Lv C, Steinbuch M. Intelligent Synthesis of Driving Cycle for Advanced Design and Control of Powertrains. In: 2018 IEEE Intelligent Vehicles Symposium (IV). IEEE/ 2018: 1608–1613.
Brady J, Margaret O, Brady J, Margaret O. Development of a driving cycle to evaluate the energy economy of electric vehicles in urban areas. Applied energy/ 2016; 177: 165–178.
Chłopek Z. Synthesis of driving cycles in accordance with the criterion of similarity of frequency characteristics. Eksploatacja i Niezawodność – Maintenance and Reliability. 2016;18(4):572–577.
Dai M, Zhang C, Zhang D. Multifractal and singularity analysis of highway volume data. Physica A. 2014; 407: 332–40.
Hongwen H, Jinquan G, Jiankun P, Huachun T, Chao S. Real-time global driving cycle construction and the application to economy driving pro system in plug-in hybrid electric vehicles. Energy. 2018;152:95–107.
Hung WT, Tong HY, Lee CP, Ha K, Pao LY. Development of a Practical Driving Cycle Construction Methodology: A Case Study in Hong Kong. Transportation Research Part D. 2007; 12: 115-128.
Hereijgers K, Silvas E, Hofman T, Steinbuch M. Effects of using Synthesized Driving Cycles on Vehicle Fuel Consumption. IFAC-PapersOnLine. 2017; 50(1): 7505–10.
Mayakuntlaa SK, Vermab A. A novel methodology for construction of driving cycles for Indian cities, Transportation Research Part D. 65, 2018: 725–735.
Mock P, Kühlwein J, Tietge U, Franco V, Bandivadekar A, German J. The WLTP: How a new test procedure for cars will affect fuel consumption values in the EU. In: The International Council on Clean Transpotration, Workink paper. 2014.
Nyberg P, Frisk E, Nielsen L. Generation of Equivalent Driving Cycles Using Markov Chains and Mean Tractive Force Components. Proc. of IFAC, 2014: 8787–8792.
Nyberg P, Frisk E, Nielsen L. Driving Cycle Adaption and Design Based on Mean Tractive Force. Proc. of IFAC. 2013;46(21):689–694.
Puchalski A, Ślęzak M, Komorska I, Wiśniowski P. Multifractal analysis vehicle’s in-use speed profile for application in driving cycles. Eksploatacja i Niezawodność – Maintenance and Reliability 2018;20(2):177–181.
Puchalski A, Komorska I. Binomial multifractal features of worldwide harmonized light duty vehicles test cycle. Vibroengineering Procedia. 2017;13:175-179.
Sileghem L, Bosteels D, May J, Favre C, Verhelst S. Analysis of vehicle emission measurements on the new WLTC, the NEDC and the CADC. Transp Res Part D. 2014;32:70–85.
Silvas E, Hereijgers K, Peng H, Hofman T, Steinbuch M. Synthesis of Realistic Driving Cycles with High Accuracy and Computational Speed, Including Slope Information. IEEE Trans Veh Technol. 2016;65(6):4118–4128.