Constructing representative driving cycle for heavy duty vehicle based on Markov chain method considering road slope

Jia, Xinyi; Wang, Hewu; Xu, Liangfei; Wang, Qing; Li, Hang; Hu, Zunyan; Li, Jianqiu; Ouyang, Minggao

doi:10.1016/j.egyai.2021.100115

Cited by 14 publications

(7 citation statements)

References 29 publications

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“…The slope value is an important parameter, for example, when calculating loads on transmission units and aggregates [3]. Due to the available qualitative data on vehicle mileage and altitude (processed in the previous paragraphs), the slope of the road can be calculated using formula 3, similar to how similar calculations were performed in [14].…”

Section: Processing Height Datamentioning

confidence: 99%

Improving the quality of the driving cycle by processing statistical data of vehicle movement

Potashnikov,

Muravev,

Kartashov

et al. 2023

E3S Web Conf.

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The article describes the process of analyzing and processing statistical data on the movement of freight transport obtained using navigation equipment installed on the vehicles in question. A detailed analysis of the source data, as well as all stages of their processing, was carried out using specialized Python tool packages such as Pandas, Numpy and Sklearn. The effectiveness of the proposed approach to data processing is shown by comparing the driving cycles of vehicles generated on the basis of the original and modified data. The topic of data analysis and processing is not new, but the relevance of the article lies in the successful application of common and effective processing methods to statistical data on the movement of vehicles, work with which is complicated by the fact that they are obtained using widespread, but focused on other tasks equipment. Thus, the work opens up new opportunities for statistical analysis of the movement of freight transport without the need to replace navigation equipment.

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Section: Processing Height Datamentioning

confidence: 99%

Improving the quality of the driving cycle by processing statistical data of vehicle movement

Potashnikov,

Muravev,

Kartashov

et al. 2023

E3S Web Conf.

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“…The transition probability describes the probability of moving from one state to another (Khadijat et al, 2021). In other words, it describes the probability of a process being in one state if the state of the process is known at one time in advance (Jia et al, 2021) (Sylvester, 2022). Mathematically, the probability of the transition can be written as follows:…”

Section: Transition Opportunity Matrixmentioning

confidence: 99%

Implementation of markov chain in predicting regeneration agricultural in Pasuruan district

Wahid

Pusakaningwati

Masud

2022

Int.J.Trends.Math.Edu.Research

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The Industrial Era 5.0 has made many positive and negative changes in various sectors, one of the negative impacts is the agricultural sector related to the lower portion of young farmers so that it must be a serious concern for the government in future agricultural development programs, especially in agricultural base areas such as in Pasuruan Regency. This situation encourages the importance of finding solutions to realize the regeneration of farmers. This study aims to analyze the transformation between generations of agricultural workers in Pasuruan Regency through the Marcov Chain model approach. The final result of this study is the analysis of transformations between generations of agricultural workers in Pasuruan Regency so that it can be used as a basis for formulating future policies for better future generations of agriculture.

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“…A driving cycle consists of a sequence of vehicle operating conditions (idle, acceleration, cruise, and deceleration) [6]. However, operating conditions may vary across cities due to variations in topography, vehicle type under consideration, vehicle composition, and road type [7]. A driving cycle is a common test process used to assess a vehicle's performance and emissions under particular driving circumstances.…”

Section: Introductionmentioning

confidence: 99%

Data Collection and Data Management Approach for Developing a Driving Cycle: A Review

Nurru Anida Ibrahim,

Arunkumar Subramaniam,

Siti Norbakyah Jabar

et al. 2024

ARASET

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Driving cycles were first proposed and developed for standard emission measurements used by legislative bodies to approve newly developed vehicles. There are many driving cycles that have been developed over the past few years. Most of the research on driving cycles is based on the condition of the vehicle in a specific location, such as the United States FTP75, European ECE 15, Japan 10115, and others. A driving cycle is a representative speed-time profile that reflects the typical driving pattern of a given city or region. A driving cycle consists of a sequence of vehicle operating conditions (idle, acceleration, cruise, and deceleration). The basic methodologies to construct a driving cycle are route selection, data collection, and the development of the driving cycle. However, as far as we know, detailed reviews and in-depth discussions of data collection instruments and data management are rarely present. As a result, this paper reviews and discusses the recent data collection approach, as well as providing a thorough analysis of the mechanisms that they employ. Furthermore, the disadvantages and advantages of the reviewed mechanisms have also been discussed.

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Constructing representative driving cycle for heavy duty vehicle based on Markov chain method considering road slope

Cited by 14 publications

References 29 publications

Improving the quality of the driving cycle by processing statistical data of vehicle movement

Improving the quality of the driving cycle by processing statistical data of vehicle movement

Implementation of markov chain in predicting regeneration agricultural in Pasuruan district

Data Collection and Data Management Approach for Developing a Driving Cycle: A Review

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