TY - CHAP

T1 - Station-Based Electric Carsharing

T2 - A Decision Support System for Network Generation

AU - Sonneberg, Marc Oliver

AU - Breitner, Michael H.

PY - 2022/1/1

Y1 - 2022/1/1

N2 - Electric carsharing is a mobility alternative addressing the world’s growing need for sustainability and allowing to reduce pollution, traffic congestion, and shortage of parking in cities. Since electric vehicles cut down carbon emissions through the use of renewable energy and reduce noise exposure compared to conventionally powered vehicles, they further enhance ecological sustainability within an even sustainable concept. For carsharing services, electric vehicles are a suitable fit for carsharing because typical carsharing trips are comparatively short, resulting in uncritical range restrictions for the trips itself. Yet, only station-based approaches can appropriately accommodate charging infrastructures and suitably account for range limitations and charging cycles. The positioning and sizing of carsharing stations are critical success factors for reaching many potential users. This represents a multi-dimensional challenge that requires decision makers to address the conflicting goals of fulfilling demands and maximizing profit. To provide decision support in anticipating optimal locations and to further achieve profitability, an optimization model is developed in this chapter. The integration of the model into a decision support system (DSS) enables easy operability by assisting the user to import, edit, export, and visualize data. Solutions are illustrated, discussed, and evaluated using the city of Portland (OR) as a computational study. Results demonstrate the applicability of the DSS indicating that profitable operation of electric carsharing is possible.

AB - Electric carsharing is a mobility alternative addressing the world’s growing need for sustainability and allowing to reduce pollution, traffic congestion, and shortage of parking in cities. Since electric vehicles cut down carbon emissions through the use of renewable energy and reduce noise exposure compared to conventionally powered vehicles, they further enhance ecological sustainability within an even sustainable concept. For carsharing services, electric vehicles are a suitable fit for carsharing because typical carsharing trips are comparatively short, resulting in uncritical range restrictions for the trips itself. Yet, only station-based approaches can appropriately accommodate charging infrastructures and suitably account for range limitations and charging cycles. The positioning and sizing of carsharing stations are critical success factors for reaching many potential users. This represents a multi-dimensional challenge that requires decision makers to address the conflicting goals of fulfilling demands and maximizing profit. To provide decision support in anticipating optimal locations and to further achieve profitability, an optimization model is developed in this chapter. The integration of the model into a decision support system (DSS) enables easy operability by assisting the user to import, edit, export, and visualize data. Solutions are illustrated, discussed, and evaluated using the city of Portland (OR) as a computational study. Results demonstrate the applicability of the DSS indicating that profitable operation of electric carsharing is possible.

UR - http://www.scopus.com/inward/record.url?scp=85143459483&partnerID=8YFLogxK

U2 - 10.1142/9781800611429_0008

DO - 10.1142/9781800611429_0008

M3 - Contribution to book/anthology

AN - SCOPUS:85143459483

SN - 9781800611412

SP - 173

EP - 192

BT - Electric Vehicles in Shared Fleets

A2 - Degirmenci, Kenan

A2 - Cerbe, Thomas M.

A2 - Pfau, Wolfgang E.

PB - World Scientific Publishing Co. Pte Ltd

ER -