Electrification of transportation sharing economy business models: the ride- and carsharing cases

Electrification of urban transportation is on the rise. In April 2016, ridesharing company Teo Taxi launched a plug-in electric vehicle (PEV) fleet followed four months later by Uber. In 2020 Volkswagen will start a fully-electric carsharing platform, whereas other companies such as BMW already provide such a service. When driven, an electric vehicle garners profit for the platform through transportation. When parked, it can act as a controllable storage device either consuming surplus or injecting energy to the grid. Hence, managed PEV fleets provide unique grid-support opportunities, and added profits to the platform through vehicle-to-grid services. This thesis looks into two types of sharing economy business models with electric vehicles, namely the ride- and carsharing models. The former type of platform has transactional control over the vehicles, that is, private drivers respond to monetary incentives. The latter directly controls its fleet. This thesis develops a mathematical framework to analyze the aforementioned models through queuing theory. It characterizes viable control strategies for the platforms to co-optimize their revenues from both transportation and grid services. It develops profit maximization algorithms of the PEV fleet managers providing such services. Finally, variables of interest are plotted as a function of various platform parameters.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Electrical & Computer Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2019

Author dc:creator

• Mamalis, Theodoros

Contributors dc:contributor

• Bose, Subhonmesh

• electric vehicles, queuing networks, sharing economy, transportation, revenue maximization, vehicle-to-grid services, V2G

Statement dc:rights

• Copyright 2019 Theodoros Mamalis

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/104991

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/104991