Abstract:
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The present document aims to analyze different types of Lithium-ion (Li-ion) batteries and
define which type is more suitable for a specific location, regarding the SOH (State of Health)
value after one year of operation.
Three batteries have been chosen for this comparison, each one having a different
performance according with mathematical models with different parameters. Two models are
based in the Lithium Iron Phosphate (LiFePO4) chemistry; with the difference that the Model
3 uses a carbon coated LiFePO4. The model 2 is based on the Lithium Manganese Nickel
Oxide (LiNiMnCoO2, known as NMC) chemistry. These models were selected based on the
existing studies available in the literature (many models have been developed for these types
of Li-ion), and most importantly, the LiFePO4 used to be the most used type of battery for
electrical vehicles and nowadays the NMC is becoming the new trend. LiFePO4 is used in
many electric cars manufactured in China and NMC is a type used in very popular brands
such as Tesla.
For each one of the models, the SOH calculation is presented and each equation is
developed according with the temperatures at three different locations: Oslo, Norway;
Barcelona, Spain and New Jersey in the US. For these places, the temperatures were
considered and configured into the models. The trail period was a year, and as the
temperatures were for the year 2016, the total cycle number was set to 366.
Results showed that the temperature plays a significant role in terms of the SOH rate of
change per cycle. Even though the final SOH value is not significantly changing for the same
model at different location, the set of values that the SOH takes is totally different. After
analyzing the graphs obtained, a modification was followed in order to consider the real
cases, where the mileage driven is not constant and is different at the three locations. Then a
higher difference in the SOH was identified comparing each place.
At the end, a market analysis is presented in order to estimate the annualized cost at each
place for each one of the three models. The cost-benefit is also a key indicator while making
the decision of the most suitable battery.
It can be concluded that using a battery outside the optimal temperature value then can
decrease its lifetime in the range of 1 to 3% only due to this variable. |