Research on Markov Property Analysis of Driving Cycle

Shi, Shuming; Nie, Lin; Zhang, Yan; Huang, Chaosheng; Liu, Li; Lu, Biao; Cheng, James

doi:10.1109/vppc.2013.6671737

Cited by 12 publications

(3 citation statements)

References 9 publications

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“…It is also worth emphasizing that the use of the Markov, Semi-Markov or Hidden-Markov model requires the fulfilment of the assumptions authorizing their use. This is noted, for example, in [4,76,64,15]. These include, first of all, the fulfilment of the Markov property.…”

Section: Introductionmentioning

confidence: 98%

Evaluation of the maintenance system readiness using the semi-Markov model taking into account hidden factors

Kozłowski,

Borucka,

Oleszczuk

et al. 2023

Eksploatacja i Niezawodność – Maintenance and Reliability

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Modelling the time that the system remains in a given state using classical distributions is not always possible. In many cases, empirical distributions are multimodal due to the influence of external, hidden factors and the selection of the best classical distributions may lead to erroneous results. In the article the method of diagnosis of influence of hidden factors into sojourn time of semi-Markov models was presented. In order to capture hidden factors, the authors proposed to model the distributions of the sojourn time with a mixture of distributions, which is a significant novelty in relation to the studies presented in the literature. Hidden factors directly affect the reliability of technical systems. Detecting the existence of these factors enables more accurate modeling of system readiness. Paying attention to irregularities caused by hidden factors makes it possible to reduce system maintenance costs. Such a system model provides complete information and enables a reliable assessment of the system readiness and maintenance.

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Section: Introductionmentioning

confidence: 98%

Evaluation of the maintenance system readiness using the semi-Markov model taking into account hidden factors

Kozłowski,

Borucka,

Oleszczuk

et al. 2023

Eksploatacja i Niezawodność – Maintenance and Reliability

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“…The authors used a stochastic and statistical methodology employing MC process in order to match the mean values of the statistical variables calculated by the regression analysis within the ±10% of the real-world DCs. Shi et al proofed the Markov property of DC from 2 aspects of experiment and theory reveling the relationship between state transition matrix and probability (9) . The authors proved that the transition matrix can be used as an alternative to the speed vs. time data sequence.…”

Section: Introductionmentioning

confidence: 99%

Kuwait Driving Cycle Generation Using Micro-Trip Combination Optimization Method Based on WLTC

Ötkür¹,

Doust²

2023

IJAE

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Albeit the low population of Kuwait (World Ranking 129), vehicle ownership percentage is the highest in the Gulf Cooperation Council (GCC) countries and 29th in world raking. Therefore, transport vehicle emissions effect is importantly high and must be taken into consideration in order to fight with the Global Warming and pollution effects. For Internal Combustion Engine (ICE) propelled vehicles, generated emissions strongly depend on the driving profile. Despite the low surface area of Kuwait, percentage of dessert areas with no / limited road infrastructure is significantly high resulting to extreme traffic jam conditions especially in the Capital Governate (Kuwait City). Considering the peculiar traffic conditions in Kuwait, in order to make valuable emissions analysis research, there is a clear need for driving cycle generation for Kuwait. Within this study, more than 1200 km of data is measured using Matlab Mobile in 3 different vehicles and analyzed using Matlab software. Kuwait driving cycle is generated employing Worldwide Harmonized Light Vehicles Test Cycle (WLTC), based on targeting to achieve similar vehicle speed vs acceleration profiles via making vehicle speed scaling for each phase of the WLTC. Total length of the cycle is kept constant. Generated Kuwait driving cycle profile can be used for emissions and fuel economy analysis as a future work.

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“…The review of available literature has shown that not all authors using Markov processes bear in mind the assumptions for their application. This is noted for example in papers by Kozłowski et al (2020), Shi et al (2013), Zhang et al (2010). The first requirement is to meet the Markov property.…”

Section: Introductionmentioning

confidence: 99%

Method of Testing the Readiness of Means of Transport With the Use of Semi-Markov Processes

Borucka

2021

Transport

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In the analysis of the readiness of means of transport, the Markov and semi-Markov processes are particularly applicable, allowing for the description of the usage process over long periods of time, determination of indicators of the exploitability and readiness of the used set of objects, as well as simulation of long-term forecasts of the usage process results. The studies presented in the literature usually concern the theoretical side of the matter, mainly the construction of formal models of the process of changing the operating states of a vehicle. Less attention is paid to the empirical side, especially with regard to the actual conditions of use. Examples of experimental observations presented in the literature most often concern individual cases. This paper lists selected irregularities and presents an example of a study of a real transport system based on semi-Markov processes.

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Research on Markov Property Analysis of Driving Cycle

Cited by 12 publications

References 9 publications

Evaluation of the maintenance system readiness using the semi-Markov model taking into account hidden factors

Evaluation of the maintenance system readiness using the semi-Markov model taking into account hidden factors

Kuwait Driving Cycle Generation Using Micro-Trip Combination Optimization Method Based on WLTC

Method of Testing the Readiness of Means of Transport With the Use of Semi-Markov Processes

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