Amid electric cars are suggested as an alternative to fossil fuel depletion and for
improving environmental issues related to transportation, supply of such an alternative
is yet to be achieved. Some of the reasons would be due to its high prices
compared to internal combustion vehicles, the existing vehicles in the same category,
limitation to a shorter mileage per charge, insufficient charging infrastructure, unstable
operation, restriction of private businesses to enter the power market, including the
absence of affordable business services. To ensure economic feasibility of electric
cars in the existing transportation sector, it is necessary to deduce models for taxies,
car rental, car sharing, home delivery services, and bus mileage based on extremely
inexpensive electric fees compared to fossil fuel.
Today, each government enforces a subsidy system for electric cars in order to
boost electric car services. There is, however, limitation in funding for the subsidy,
and electric cars must be initiative in organizing its own sustainable business
ecosystem, considering falling prices due to the mass production of electric cars and
technical development. Of the various electric-car business ecosystems, the car sharing
service that claims to stand for economy of communion can solve both environmental
and traffic problems. This paper aims to study a methodology based on the electric
car-sharing business model.
Electric car-sharing business models have several variables. First, the price
fluctuation in car batteries of which forms the high prices of electric cars, different
daily mileage according to businesses, the actual purchase of electric cars according
to the size of the government subsides, and power charging fees, electric-car rental
fees, and driving-distance-based driving fees suggested by private electric car charging
operators.
This paper composed two types of integrated models of electric car-sharing service
businesses. The model 1 is electric car maintenance cost modeling compared to
internal combustion vehicles based on the net present value method and model 2 is car sharing simulation modeling. We can compare income and expenses of the
electric care sharing business based on the two models. In the model 1, we
compared the depreciation of an internal combustion vehicle, the same kind as that
of an electric car, car insurance, and vehicle tax using the net present value method.
We also analyzed the sensitivity of overall costs that varies according to the size of
subsidy and deduced a cost change chart of car sharing business operators according
to the subsidy. In the model 2, we carried out a simulation for the car-sharing
business that has the same O-D (Origin and Destination). For the simulation of
model 2, sub-modules are required to set the unit price of power charging in
advance. In the sub-model, the study reviewed the taxi business with most sensitivity
in the unit price computation of power charging. Taxi has the longest daily mileage
and is the first to face battery deterioration; therefore, the taxi business will need to
spend a large amount of money for battery replacement and profit availability is very
flexible in terms of the unit price of power charging. To apply costs according to
battery replacement demand, we estimated annual battery prices. In addition, we
conducted a sensitivity analysis for the unit price of power charging that reaches the
break-even point through an electric taxi simulation based on the daily mileage of
taxi.
The study suggests a design methodology based on battery price estimation and
mileages for a charging fee system that can generate profits for the electric car
service business and also an analysis methodology for the car sharing business. A
car-sharing operator can select electric cars or internal combustion vehicles for their
business and may verify profits from introducing electric cars compared to internal
combustion vehicles. The final goal of the research is to suggest sensitivity and
analysis methodology affecting car sharing providers according to the size of subsidy
and power charging fees based on travel time and distance.