In this section, the results related to the one-year simulations developed at different scenarios and case studies are presented and discussed in detail. In order to quantify the effect of fast charging in the different scenarios and case studies, the results will be focused on the analysis of the degradation suffered by the battery. The degradation can be measured by the CF
y value returned by the simulation model (capacity fade after 1 year), or the expected battery lifetime (y
BT), which is calculated as follows:
where CF
EOL is the capacity fade at battery End of Life (EOL), typically defined at 20%.
For each case study being analysed, two graphs are presented. On the one hand, the absolute degradation (represented by CF
y) is given in relation to the absolute value of the parameter whose sensitivity is being analysed (P
ch or E
BT). The aim of this representation is to compare the degradation suffered in the different case studies (different battery chemistries, BEB lines, charger powers, and battery capacities) in absolute figures. On the other hand, in a second graph, the increase/decrease of the battery lifetime (represented by Δy
BT) is given in relation to the increase/decrease of the analysed parameter (ΔP
ch or ΔE
BT). The aim of this second representation is to analyse the relative increase/decrease of the degradation or battery lifetime in relation to the relative increase/decrease of the analyzed parameter. The relative parameters Δy
BT, ΔP
ch, and ΔE
BT are obtained in relation to the BC, therefore:
where the variables with the suffix
_BC refer to the values in the BC, and the variables with the suffix _x to the values in the case being analyzed (which can be the LC, MC, or HC).
3.1. Sensitivity to Charger Power
In this first sensitivity analysis, the impact of the charger power in the battery lifetime is evaluated.
Figure 8 and
Figure 9 show the two graphs previously explained.
Figure 8 represents the CF
y values in relation to the absolute charger power values for the different battery chemistries and BEB lines, while
Figure 9 represents the battery lifetime change (
) in relation to the relative charger power (
) for the different battery chemistries and BEB lines. In addition,
Figure 10 depicts the SoC evolution graphs obtained from the simulation. These graphs represent simulation results from the BC on 1 January and help obtain the conclusions regarding battery degradation.
On the one hand, the results of
Figure 8 allow the comparison of the degradation suffered by LTO, LFP, and NMC batteries in the various proposed scenarios and case studies. In the three scenarios, LTO batteries exhibit the lowest degradation, with capacity fades always under 1.5%/year (lifetimes higher than 13 years). LFP batteries showcase CF values around 2.5–3%/year (lifetimes of around 6–8 years), and in all cases the degradation is doubled compared to LTO. Finally, NMC batteries exhibit the highest degradation, with CF values between 5.1–8.7%/year (lifetimes of around 2.3–4 years). In almost all the cases, it is observed that the degradation is doubled compared to LFP chemistry. Compared to LTO, the degradation is even 4 times higher.
The results can be also analysed scenario by scenario. In BCN, it is important to highlight that deploying a charger of 200 kW turns out to be unfeasible. The reason is that BCN is the scenario where the BT is most discharged between consecutive charging activities (see
Figure 8a). Therefore, a charger of more than 200 kW is required in order to recover that energy in the considered stop time. NMC suffers the highest degradation in this scenario, which demonstrates that its degradation is sensitive to high DODs (see graphs in
Figure 8).
Regarding the scenario in OSN, the power of the charger can be reduced up to 200 kW. For LFP and LTO chemistries, OSN is the scenario where the batteries are most degraded. This evidences that the feature that most degrades these chemistries is not the realized DOD, as the highest DOD is obtained in BCN (see
Figure 8a,b). OSN is characterized as being a demanding scenario, which can cause the higher degradation of these chemistries.
Finally, in GOT the charging power can be also reduced up to 200 kW. The degradation is lowest in this scenario. This demonstrates that increasing the charging frequency does not directly accelerate the degradation suffered by the batteries and that therefore, reducing the DOD realized by the battery can efficiently increase its lifetime (see
Figure 8c). The obtained results are summarized in
Table 9.
On the other hand, the graphs in
Figure 9 permit evaluation of the impact of reducing the charger power (P
ch) in relation to the defined BC. The first conclusion obtained when analyzing the depicted results is that the chemistry that most benefits from the P
ch reduction is NMC. As this chemistry is close to its maximum charging C-rate in the BC, this high degradation reduction becomes reasonable. The lifetime gain reaches 25% in BCN (when reducing the charging power by 25%), 30% in OSN, and 22% in GOT (in these two scenarios when reducing the charging power by 50%). Therefore, in NMC the lifetime gain is sensitive to the scenario.
Regarding LTO chemistry, the lifetime gain is 12% when reducing the charging power by 33%, and 24% when reducing the charging power by 67%. In contrast to NMC, in this case, the degradation variation is not sensitive to the scenario. Finally, the degradation of LFP chemistry remains unaltered when reducing the charger power. Therefore, it can be concluded that from the degradation point of view, in the case of NMC and LTO, reducing the charger size below 600 kW can be a good practice. Depending on the scenario, this reduction can be higher or lower, as enough room must be left to ensure the full SOC recovering at the charging point. As LFP is not affected by high charging C-rates, the 600 kW charger becomes an appropriate option.
The obtained results are summarized in
Table 10. The variable lifetime improvement ratio defines how much the BT lifetime is improved when downsizing the charger (value 1 defines that the lifetime is improved by 25% when downsizing the charger by 25%).
3.2. Sensitivity to Battery Capacity
In this second sensitivity analysis, the effect of increasing the battery capacity is analyzed. The battery capacity effect is more complex than the effect analysed in the previous sensitivity analysis. In this case, the analyzed variable affects both the C-rate in which the battery is charged and the DOD that it performs (in the previous analysis only the C
ch value was altered).
Figure 11 represents the CF
y values in relation to the absolute battery capacity values for the different battery chemistries and BEB lines, while
Figure 12 represents the battery lifetime change (
) in relation to the relative battery capacity (
) for the different battery chemistries and BEB lines.
Figure 13 depicts some representative SoC profiles obtained from simulation. These graphs help understand the results depicted in the previous figures.
Regarding the results depicted in
Figure 11, the same patterns identified in the previous sensitivity analysis are noticed. In all scenarios, LTO is the chemistry showing the lowest degradation, while NMC is the most degraded chemistry. Comparing the different scenarios, NMC degrades the most in BCN and the least in GOT, while LFP and LTO degrade the most in OSN and the least in GOT. The degradation reduction induced by the battery capacity increase allows LTO to reach CF
y values up to 0.6–0.75%/year (lifetimes up to 30 years), NMC to reach CF
y values around 1.3–1.5%/year (lifetimes up to 15 years), and LFP to reach CF
y values around 3.25–3.62%/year (lifetimes up to 6.15 years). Therefore, and as will be further analysed with the help of
Figure 11, it can be deduced that the degradation is reduced more with the capacity increase than with the charger power downsizing. The obtained results are summarized in
Table 11.
Focusing on the relative lifetime increases depicted here, further observations can be obtained. First of all, it is confirmed that, compared to
Figure 9, the lifetime improvements are higher. However, it has to be considered that reducing the charger size does not involve an additional cost while increasing the battery capacity requires an additional investment. The obtained lifetime increase has to be higher than the capacity increase in order to be a cost-efficient option. This is represented by the dotted lines depicted in the graphs: below the dotted lines, increasing the battery capacity is not cost-efficient; and above the dotted lines, increasing the battery capacity becomes cost-efficient.
The chemistry most benefiting from the capacity increase turns out to be LTO, mainly when the capacity is increased more than 25%. In the three scenarios (BCN, GOT, and OSN) similar tendencies are observed: 30% lifetime increase with a 25% capacity increase, and 92% lifetime increase with a 67% capacity increase.
Regarding LFP, it is at the borderline of the cost-efficiency in all the cases: 50% lifetime increase with a 50% capacity increase and a 96% lifetime increase with a 100% capacity increase. Therefore, it can be concluded that LFP is not much benefited by the capacity increase.
Finally, the graphs from
Figure 12 show that the cost-efficiency of increasing NMC capacity depends on the scenario. In BCN and OSN, increasing the capacity becomes cost-efficient: with a 33% capacity increase, the lifetimes are increased by 50% (BCN) and by 43% (OSN), and with a 100% capacity increase the lifetimes are increased by 135% (BCN) and by 106% (OSN). However, in the GOT scenario, cost efficiency is only obtained when increasing the capacity by 33% (38% lifetime increase), as with a 100% capacity increase the lifetime is only increased by 93%. This reinforces the idea that NMC is more sensitive to the scenario characteristics than LTO and NMC, as was already concluded in the previous sensitivity analysis.
The obtained results are summarized in
Table 12. The variable lifetime improvement ratio defines how much the BT lifetime is improved when oversizing it (value 1 defines that the lifetime is improved by 25% when increasing the BT size by 25%).
In short, increasing the battery capacity is appropriate for LTO, especially the more the capacity is increased. In NMC the capacity increase is also appropriate, but in this case, the oversizing should not be very high. And for LFP, the recommendation is not to increase the battery capacity very much, as the benefit is barely visible.