Simulation methods commonly used throughout the design and verification process of various types of motor vehicles require
development of naturalistic driving cycles. Optimization of parameters, testing and gradual increase in the degree of autonomy of
vehicles is not possible based on standard driving cycles. Ensuring representativeness of synthesized time series based on collected
databases requires algorithms using techniques based on stochastic and statistical models. A synthesis technique combining the
MCMC method and multifractal analysis has been proposed and verified. The method allows simple determination of the speed
profile compared to classic frequency analysis.
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Mechanical Coupling Devices to Various Types of Vehicles under Cyclic Loading Tadeusz Szymczak, Sławomir Cholewiński, Adam Brodecki, Jacek Łączyński International Journal of Automotive Technology
A driving cycle construction methodology combining Markov chain with variation parameters and Monte Carlo Jiaming Xing, Yuanjian Zhang, Chong Guo, Zhuoran Hou, Peng Liu, Shibo Li 2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)
Adaptive Driving Cycles of EVs for Reducing Energy Consumption Iwona Komorska, Andrzej Puchalski, Andrzej Niewczas, Marcin Ślęzak, Tomasz Szczepański Energies
Customer-centric aging simulation for 48 V lithium-ion batteries in vehicle applications Valentin Steininger, Peter Hüsson, Katharina Rumpf, Dirk Sauer eTransportation
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