Improving electric vehicle utilization in carsharing: A framework and simulation of an e-carsharing vehicle utilization management system

Brendel, Alfred; Lichtenberg, Sascha; Brauer, Benjamin; Nastjuk, Ilja; Kolbe, Lutz M.

doi:10.1016/j.trd.2018.01.024

Cited by 68 publications

(26 citation statements)

References 52 publications

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“…Schneider et al studied electric vehicle (EV) battery charging and purchasing optimization [44]. Brendel et al and Xu et al studied EV-based car-sharing system optimization [45,46]. Gao et al studied battery capacity and recharging [47].…”

Section: Alternative Bus Technologies and Electric Busesmentioning

confidence: 99%

Electric Bus Selection with Multicriteria Decision Analysis for Green Transportation

Hamurcu

Eren

2020

Sustainability

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Multicriteria decision-making tools are widely used in complex decision-making problems. There are also numerous points of decision-making in transportation. One of these decision-making points regards clean technology vehicle determination. Clean technology vehicles, such as electric buses, have some advantages compared to other technologies like internal combustion engine vehicles. Notably, electric vehicles emit zero tailpipe emissions, thereby ensuring cleaner air for cities and making these clean technologies preferable to other technologies, especially in highly populated areas for better air quality and more livable cities. In this study, we propose a multicriteria decision-making process using analytic hierarchy process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) in the context of an electric bus in the center of Ankara. Six potential electric bus alternatives were evaluated under seven specific criteria. Overall, EV-2 electric buses outperformed other electric bus alternatives based on the chosen criteria. In addition, the stability of the results obtained under different scenarios using this method was established via sensitivity analysis.

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Section: Alternative Bus Technologies and Electric Busesmentioning

confidence: 99%

Electric Bus Selection with Multicriteria Decision Analysis for Green Transportation

Hamurcu

Eren

2020

Sustainability

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“…Simulations are commonly used in the general context of vehicle relocation research [27], while discrete event simulations are particularly common for carsharing simulations because they are able to identify system behavior changes when a set of different constraints is implemented. Furthermore, a carsharing system's state changes only through events such as rental requests, supply imbalances, relocations, and returns, which can be described through discrete-event simulation [28]. The developed simulation consists of individual users, vehicles, and stations.…”

Section: Iteration 2: Evaluation and Publicationmentioning

confidence: 99%

“…In this context, real-world data can be insufficient when it is collected from a realworld carsharing system as the data is incomplete and biased by the implemented relocation method. To account for such biases, we generated a data set following an established data generation approach [28]. The approach generates artificial rental data by training machine learning algorithms to learn the patterns within real-world data.…”

Section: Data Setmentioning

confidence: 99%

“…Charging EVs is an essential part of e-carsharing and therefore requires simulation within its logistic limitations. E-carsharing providers can either always charge their vehicles or use some kind of charging management service [28]. Continuous charging is the strategy used by the referenced e-carsharing system and is therefore implemented in the simulation.…”

Section: Charging Strategymentioning

confidence: 99%

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Adapting User-Based Vehicle Relocation for ECarsharing

Prinz¹,

Lichtenberg²,

Herrenkind³

et al. 2020

WI2020 Zentrale Tracks

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The mobility sector has been established as a prominent example for the sharing economy. E-carsharing offers a way to introduce and utilize electric vehicles as a sustainable mobility service to solve current and future mobility issues. Nonetheless, e-carsharing still faces several challenges that need to be overcome in order to act as a mainstream means of commute. In this article, we propose user-based relocation to improve the use and availability of electric vehicles within e-carsharing. It enables value co-creation by actively involving the user in value creation, e.g. increasing the positiondependent value of a shared vehicle. By simulating an e-carsharing system, we were able to analyze the capabilities of user-based relocation. The results indicate that user-based relocation has the potential to greatly improve electric vehicle use and demonstrates an example of successful value co-creation in the sharing economy. Furthermore, it strengthens e-carsharing as a part of everyday mobility.

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“…In addition, the results gained could be used for existing studies [33] to identify suitable car usage profiles for carsharing services and derive their potentials. Furthermore, the results can also be used in analysis to optimise carsharing fleets with different propulsion systems [34].…”

mentioning

confidence: 99%

Electric Factor—A Comparison of Car Usage Profiles of Electric and Conventional Vehicles by a Probabilistic Approach

Niklas

Behren

Chlond

et al. 2020

WEVJ

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To counteract climate change, electric vehicles are replacing vehicles with internal combustion engine on the automotive market. Therefore, electric vehicles must be accepted and used like conventional vehicles. This study aims to investigate to which extent electric vehicles are already being used like conventional vehicles. To do this, we present a supervised method where we combine usage data from conventional vehicles (from car use model based on survey data) and electric vehicles (from sensor data) in Germany and California. Based on conventional vehicles, eight car usage profiles were defined by hierarchical clustering in a previous study. Using a softmax regression, we estimate for each electric vehicle a probability of assignment for every car usage profile. Comparison of conventional and electric vehicles with a high probability reveals that electric vehicles are used similar for long-distance travel (>100 km) and different for short-distance travel (<10 km) to conventional vehicles. This implies that electric vehicles are indeed used for long-distance travel but are still not entirely used for everyday mobility. This could be because electric vehicles are not yet suitable for all trip purposes (e.g., transport of larger items).

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Improving electric vehicle utilization in carsharing: A framework and simulation of an e-carsharing vehicle utilization management system

Cited by 68 publications

References 52 publications

Electric Bus Selection with Multicriteria Decision Analysis for Green Transportation

Electric Bus Selection with Multicriteria Decision Analysis for Green Transportation

Adapting User-Based Vehicle Relocation for ECarsharing

Electric Factor—A Comparison of Car Usage Profiles of Electric and Conventional Vehicles by a Probabilistic Approach

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