  Smart charging of Electric Vehicles (EVs) reduces operating costs, allows
more sustainable battery usage, and promotes the rise of electric mobility. In
addition, bidirectional charging and improved connectivity enables efficient
power grid support. Today, however, uncoordinated charging, e.g. governed by
users' habits, is still the norm. Thus, the impact of upcoming smart charging
applications is mostly unexplored. We aim to estimate the expenses inherent
with smart charging, e.g. battery aging costs, and give suggestions for further
research. Using typical on-board sensor data we concisely model and validate an
EV battery. We then integrate the battery model into a realistic smart charging
use case and compare it with measurements of real EV charging. The results show
that i) the temperature dependence of battery aging requires precise thermal
models for charging power greater than 7 kW, ii) disregarding battery aging
underestimates EVs' operating costs by approx. 30%, and iii) the profitability
of Vehicle-to-Grid (V2G) services based on bidirectional power flow, e.g.
energy arbitrage, depends on battery aging costs and the electricity price
spread.
