Development of a driving cycle for Istanbul bus rapid transit based on real-world data using stratified sampling method

Kaymaz, Habib; Korkmaz, Hayriye; Erdal, Hasan

doi:10.1016/j.trd.2019.08.023

Cited by 31 publications

(18 citation statements)

References 12 publications

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“…Estudios también afirman que los factores medioambientales y financieros obligan a desarrollar vehículos limpios, eficientes y sostenibles, siendo la transición a la electrificación e hibridación una posible solución a estos problemas. Sin embargo, los ciclos de conducción también son soluciones, ya que representan las condiciones reales de conducción para las pruebas de emisiones de vehículos y estimación, por lo tanto, crear un ciclo de conducción práctico para vehículos con parámetros característicos como velocidad, distancia, tiempo y aceleración se convirte en algo muy importante, puesto que implica determinar la ruta y luego analizar los datos utilizando técnicas de muestreo estratificado (Kaymaz et al, 2019).…”

Section: Introductionunclassified

Influencia del estado de conducción, tipo de vehículo y condiciones de viaje en las variables cinemáticas de las rutas en autobuses urbanos. Caso de estudio Ibarra-Ecuador

et al. 2022

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Las ciudades de Latinoamérica tienen problemas de contaminación y tráfico por la falta de investigación y planificación del sector de transporte. En Ecuador, las características de las flotas de transporte y su cinemática en la ciudad no se han determinado. El presente estudio analiza detalladamente las características cinemáticas de cada ruta de transporte público de la ciudad de Ibarra-Ecuador mediante el uso de equipos de georreferenciación GPS para cada segundo de recorrido. Se monitoreó 22 rutas de autobuses urbanos, evaluando 186 autobuses en 832 viajes, en los que se determinó que la velocidad promedio, la aceleración y desaceleración dependen, principalmente, de tres factores: ruta, sector de la ciudad y modelo de vehículo. Otros factores como operadora, edad de conductor, tiempos de viaje y la franja horaria no presentaron mayor significancia en la influencia a las variables cinemáticas en estudio, por lo que no se consideran dentro del estudio de investigación.

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Section: Introductionunclassified

Influencia del estado de conducción, tipo de vehículo y condiciones de viaje en las variables cinemáticas de las rutas en autobuses urbanos. Caso de estudio Ibarra-Ecuador

et al. 2022

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“…Ample research has been conducted on developing non-legislative cycles in various regions for different aims. For instance, cycles of Dublin [4], Istanbul [12], Tianjin [13], Florence [5], and Hefei [14] were established to study energy consumption and driving range. Cycles of Mexico [15], Hanoi [16], Aleppo [17], and Taipei [18] were mainly used to research emissions.…”

Section: Introductionmentioning

confidence: 99%

Development of a Typical Urban Driving Cycle for Battery Electric Vehicles Based on Kernel Principal Component Analysis and Random Forest

Wang

Zhao

et al. 2021

IEEE Access

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Great concerns have been raised on the driving cycle due to its critical importance in vehicle design, energy management strategy, and energy consumption forecast of new energy vehicles. Taking Xi'an city as a case, a novel method of driving cycle development for battery electric vehicles is proposed in this paper. First, the chase car method and on-board measurement method are combined to collect sufficient real driving data, which are randomly divided into two parts for developing and validating the target cycle. Then the nonlinear dimension reduction of characteristic parameters with respect to the micro-trips is achieved by employing kernel principal component analysis, and an improved clustering method is developed for constructing candidate cycles, in which the K-means clustering algorithm is applied in the training of random forest. The target cycle is selected from the candidate cycles by determining the assessment criteria with consideration of the characteristic parameters and the speed-acceleration distribution probability. Finally, a comparative study of different methods is implemented to illustrate the effectiveness of the proposed method. The typicality of the target cycle is revealed by analyzing the discrepancies between the target cycle and other legislative cycles.INDEX TERMS Urban driving cycle, battery electric vehicles, random forest, kernel principal component analysis.

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“…34,35 Lastly, some efforts relied on fuel consumption or emissions prediction as the sole test for representativeness. 24 After constructing a cycle that is representative of the original data-set, it is usually compared to existing cycles in the literature 27,28 or to legislative cycles, 15,18,25,30 or to both. 29,33,36 This is performed to highlight the similarities and differences between the existing cycles and the newly proposed one demonstrating the scientific contribution of the new cycle.…”

Section: Introductionmentioning

confidence: 99%

“…In the on-board measurement method the target vehicle is instrumented with a variety of sensors and real-time data is collected. 25 The chase-car method relies on an instrumented vehicle to randomly follow other vehicles in traffic in an attempt to replicate their behavior. 26 GPS data is usually sufficient to build velocity profiles, and in some studies GPS data from passengers’ cellphones is collected.…”

Section: Introductionmentioning

confidence: 99%

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The development of a representative multidimensional transient duty cycle for in-service switcher locomotives

Hegazi

Hoffrichter²,

Andrews

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part F:

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Switcher locomotives operate in railway yards where they shunt railcars and assemble trains. Shunting railcars requires frequent aggressive acceleration and deceleration events in order for the locomotive to push or pull railcars onto specific tracks. As a result, switcher locomotives rarely sustain tractive power for any significant period of time. Given that all switchers in North America rely on diesel-electric propulsion; the result is rapid and frequent transitions in engine power leading to a very low engine efficiency and high levels of emissions. Any attempt to quantify or remedy these issues will face a lack of a representative profile or test cycle. A locomotive duty cycle is a breakdown of time spent at each power level of the locomotive’s engine. A major drawback of current duty cycles is that they only account for steady power. Such cycles are not representative of real switcher locomotive operation. This paper presents a real-world transient duty cycle for switcher locomotives that accounts for the rapid power transitions and is argued to be more statistically representative of actual operations. The methodology adopted relies on real-time data collection, microtrip based trip segmentation, and a finite mixture model-based clustering algorithm. Measurements were collected on a EMD 16-645 GP9 locomotive. The duty cycle developed herein is representative of switching operations in Southern Railway of British Columbia’s New Westminster Yard as an example of the methodology which can be repeated in other cases as well.

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Development of a driving cycle for Istanbul bus rapid transit based on real-world data using stratified sampling method

Cited by 31 publications

References 12 publications

Influencia del estado de conducción, tipo de vehículo y condiciones de viaje en las variables cinemáticas de las rutas en autobuses urbanos. Caso de estudio Ibarra-Ecuador

Influencia del estado de conducción, tipo de vehículo y condiciones de viaje en las variables cinemáticas de las rutas en autobuses urbanos. Caso de estudio Ibarra-Ecuador

Development of a Typical Urban Driving Cycle for Battery Electric Vehicles Based on Kernel Principal Component Analysis and Random Forest

The development of a representative multidimensional transient duty cycle for in-service switcher locomotives

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