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Article

Analysis of the Future of Mobility: The Battery Electric Vehicle Seems Just a Transitory Alternative

by
Lázaro V. Cremades
* and
Lluc Canals Casals
Department of Project and Construction Engineering, Universitat Politècnica de Catalunya, 08028 Barcelona, Spain
*
Author to whom correspondence should be addressed.
Energies 2022, 15(23), 9149; https://doi.org/10.3390/en15239149
Submission received: 18 October 2022 / Revised: 24 November 2022 / Accepted: 29 November 2022 / Published: 2 December 2022
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Abstract

:
It is, undoubtedly, a widespread belief that the electric vehicle (EV) is considered sustainable. However, in the manufacturing and retirement phases, EVs do not appear to be as sustainable as internal combustion vehicles (ICVs) and during the use phase, the pollution produced by EVs depends on the source of electricity generation to recharge the batteries. From an economic point of view, EVs do not appear to be competitive compared to ICVs either. However, current market trends push hard on battery EVs (BEV) and plug-in hybrid vehicles (PHEV). This study aims to analyze which of the possible mobility alternatives has more sense to be considered as the option with higher penetration in the future. To this end, four known mobility technologies (ICVs, PHEVs, BEVs, and hydrogen fuel cell EVs or FCEVs) are compared for a mid-size car using published data, through environmental and techno-economic criteria, by applying the analytic hierarchy process method in an objective manner on multiple scenarios. Putting all criteria together, it seems that the ICV alternative is the one receiving the best results in most of the scenarios, except in the case where the environmental criteria have the greatest weight. The BEV solution has almost always turned out to be the worst alternative, but it is the only choice we have right now.

1. Introduction

The European Commission’s Sustainable and Smart Mobility Strategy states that at least 30 million electric cars should be operating on European roads by 2030 [1]. Making urban travel more sustainable is one of the greatest challenges we face as a society today. It is undoubtedly a widespread belief that mobility using electric vehicles (EVs) is considered sustainable mobility. To prove this statement, numerous studies in the literature have analyzed the life cycle of EVs regarding greenhouse gas emissions [2,3,4,5,6,7,8,9,10]. In addition, there are also studies comparing the life cycle of electric vehicles with that of conventional vehicles (i.e., those powered directly by fossil fuels or internal combustion vehicles, ICVs), such as [11,12,13,14], and/or between different types of electric vehicles (hybrid EVs or HEVs, plug-in hybrid EVs or PHEVs, battery EVs or BEVs, or hydrogen fuel cell EVs or FCEVs), such as [15,16,17,18]. These studies show that there are several determining factors for the sustainability of the EV regarding the manufacture, use, and retirement phases that might compromise its suitability in comparison to ICV.
In fact, the manufacturing phase is stated to have a higher impact on EVs than ICVs, which is calculated to be between 40 and 70% mainly due to the manufacture of the battery [19,20,21].
Nonetheless, it is said that, during the use phase, the EV is capable to counteract this higher impact caused in the manufacturing phase. Indeed, the main origin of pollution in the use phase is due to the generation of the electricity needed to recharge the batteries or to produce hydrogen in the case of FCEVs. If the origin comes from renewable energy sources, EVs can be considered “green”; otherwise, they are merely “clean” compared to ICVs [13] or, depending on the consumption of the vehicle, type of trips, and the electricity mix of each country, they could even be worse [22].
To reduce even more the environmental impact of the use phase, the automotive industry has continuously pursued weight reduction. However, the weight of batteries in BEVs and PHEVs is related to their energy capacity, on which the vehicle’s range depends. For example, 6 to 12 kWh batteries typically weigh between 100 and 150 kg, while 60 to 100 kWh batteries range from 350 to 600 kg. Therefore, their weight can be up to 25% of the vehicle’s weight [23].
Finally, the end-of-life (EoL) of EV batteries is also a critical phase in terms of sustainability. It is even more critical if the EoL is caused by the battery, lithium-ion batteries are said to be no longer functional for electric mobility when their state of health (SOH) is below 80% and they need to be replaced [24]. At this stage, a possible solution to increase the sustainability of such batteries might come from an extension of their useful life through applications that do not require such high SOH values, for example, as backup energy support in residential households or power variance in grid-scale photovoltaic plants [25,26]. These approaches are indeed aligned with circular economy streams, as the literature states that these environmental benefits are reached from being unnecessary to build new batteries for those purposes. However, it seems that this statement is not entirely correct, and doubts arise regarding the so-called benefits of battery reuse [27,28]. Be it as it may, at the very end, vehicles should be recycled, and the recycling of batteries is still in the early stages in comparison to the other alternatives, including FCEV [29].
In addition to the environmental aspect, sustainability also has an economic component. In that sense, an overview of the automotive market shows that EVs (not considering micro-mobility) are more expensive than ICVs. In fact, the literature has studied the costs involved in the construction and use of EVs, such as [30] in Germany or [31] in China. Some studies did a step forward comparing the costs of some EV alternatives with each other and/or with ICVs [32,33], indicating that BEVs are in the worst position considering the purchase cost.
For all these reasons, this study considers it necessary to delve into all existing (and expecting to be) possible mobility alternatives in the market in the coming years. To do so, this study analyzes which of them has more sense to be considered as the option with higher penetration in the future and if the current entrance of the BEV and PHEV is just a temporary situation or something that will, effectively, perpetuate for the next century.
This study compares four known mobility technologies (ICVs, PHEVs, BEVs, and FCEVs) for a mid-size car using published data. For this purpose, environmental and techno-economic criteria are used. Finally, a prioritization of the alternatives is presented by applying the analytic hierarchy process (AHP) method objectively.

2. Data and Methods

2.1. Basic Data

According to the market prospects and what currently is running our roads, this study analyzes four alternatives, which are:
  • Internal combustion vehicle (gasoline) (ICV)
  • Plug-in hybrid electric vehicle (gasoline and electricity) (PHEV)
  • Battery electric vehicle (electricity) (BEV)
  • Fuel cell electric vehicle (hydrogen and electricity) (FCEV)
This study assumes that the FCEV, in addition to the hydrogen fuel cell, resembles an electric battery that can be recharged to full charge via a plug, just like the PHEV.
The vehicle chosen for the comparison of the four alternatives is a car with a total power of 100 kW. Examples of representative cars of this power are: BMW 118i 2019 as ICV [34], Toyota Prius 2017 as PHEV [35], Hyundai Kona Electric 2018 [36], and Citroën ë-Jumpy Hydrogen [37]. Some significant characteristics of these cars are listed in Table 1.
Where “range” refers to the mileage that the vehicle can drive with a full energy storage system (i.e., fuel tank, battery, or fuel cell). In the case of PHEV and FCEV, the volume and capacity of the energy storage system refer to the overall volume and capacity of the two energy systems, respectively.

2.2. AHP Method

The process followed to discern which of these four alternatives has higher interest or chances to capture the automotive market in the long-term future is through the analytic hierarchy process (AHP) method, which is generally used to select alternatives objectively.
The AHP method, proposed by Thomas Saaty in 1980 [38], is a quantitative method for multi-criteria decision-making that facilitates the selection among different alternatives based on a series of criteria or selection variables and expert judgments expressed through pairwise comparisons using a preference scale [39,40,41]. Criteria and alternatives follow a hierarchical structure. This structure is described by the objective, criteria, and finally, the alternatives to be compared (see Figure 1). One of the fundamental aspects of the method is to choose the selection criteria well, to define them properly, and to ensure that they are mutually independent.
This study applies the AHP method to compare the four alternatives mentioned above through the following six criteria:
  • Global warming potential (GWP): total greenhouse gases emitted during the entire life of the vehicle.
  • Photochemical oxidant potential (POP): gases (NOx, CO, VOC) with the potential to form photochemical oxidants, such as ozone, in the presence of solar radiation emitted during the entire life of the vehicle.
  • Fueling time (FT): time to fill the energy storage system.
  • Fueling infrastructure (FI): cost of a fuel (gasoline and/or electricity, or hydrogen) station per vehicle.
  • Vehicle cost (VC): cost of the vehicle in mass production.
  • Fuel cost (FC): cost of fuel (gasoline and/or electricity, or hydrogen) per km driven.
Some of these criteria are used in other works (e.g., [33]), being considered relevant and mutually exclusive for the purpose of this study.
In the original AHP method, Saaty’s scale is used for the paired comparison (see Table 2). This is one of the keys to the success of this method, since this scale allows the transformation of qualitative aspects into quantitative ones, making the comparison between the different alternatives much easier and giving rise to more objective and reliable results.
Another of the strengths of the method is to assess the consistency of the decision to validate it as the best option [42].
The values assigned to each alternative are based on the six criteria, as shown in Table 3. These values correspond to the basic data in Table 1 and/or to values extracted from bibliographic sources as indicated in the same table.
Costs are referenced to USD 2019. For this purpose, the inflation indexes for the USA published in [44] have been used when necessary.
In the fueling infrastructure criterion, the cost per BEV is about USD 2550 for a higher Level 2 capacity outlet (240 V, 40 A). The same cost is estimated for a PHEV, as it can be understood that their owners will want to be able to recharge the vehicle as if it were a BEV. Therefore, they will need to install a similar charging station. In the case of ICVs, by analogy with BEVs, it has been considered that the cost of fueling infrastructure per vehicle would be the total cost of building a gas station equipped with 6 fuel pumps divided by the number of vehicles that can be filled in the time it takes to fill a BEV. This description can be mathematically calculated through Equation (1):
C F I I C V = C F I n · t I C V t B E V
where CFIICV is the cost of fueling infrastructure per ICV; CFI is the total cost of building a gas station; n is the number of fuel pumps; tICV is the fueling time for an ICV; tBEV is the fueling time for a BEV. The same considerations apply to FCEVs. In the case of the PHEV and the FCEV, this study does not consider adding the infrastructure cost of filling the PHEV gasoline tank nor the infrastructure cost of charging the FCEV batteries, respectively.
In the original AHP method, comparisons between pairs of alternatives are usually made based on judgments gained through experience [45]. However, in this work, these comparisons have been obtained mathematically from the data of the alternatives shown in Table 1 and Table 3. For each criterion, the ratios between the values of each alternative against the others are calculated. Then, an adjustment of these ratios to the preference scale (1 to 9 in Table 2) according to a linear relationship is completed. In this way, the comparison between alternatives is completely objective. That is, suppose that for a given criterion the value of alternative A is “a” and for alternative B it is “b”. Then, the ratio “a/b” will correspond to a value “p” in the preference scale as follows:
If a/b = 1 → p = 1
If   a / b   >   1   →   p = a b   −   1   ·   8 r m a x − 1 + 1
If   a / b   <   1   →   p = 1 a b   −   1   ·   8 r m a x − 1 + 1
where rmax = maximum value of all ratios in a given criterion.
The next step of the AHP method is to normalize the importance ratios so that the sum of the values in each column of the matrix equals 1, resulting in a standard matrix. Finally, the priority weights of each alternative are obtained by averaging the values of this matrix, referring to a given criterion. The same process is applied to all criteria.
Once the AHP method is applied to the alternatives, a sensitivity analysis is performed to determine the influence of the criteria weights on the prioritization of the alternatives by analyzing ten what-if scenarios (Table 4): in scenario 0 all criteria have the same importance, that is, they all have the same weight equal to wi = 100/6 = 16.67%. In scenarios 1 to 9, these weights vary giving more relevance to a group of criteria having similar concepts:
  • Environmental criteria (GWP and POP): scenarios 1 to 3.
  • Technical criteria (FT and FI): scenarios 4 to 6.
  • Economic criteria (VC and FC): scenarios 7 to 9.
To give higher relevance to these 3 groups separately, it has been assumed that the weight of each group (independently) increases by 30, 60, or 90% in front of scenario 0, while decreasing the weights of the remaining criteria accordingly. The resulting weights per criteria on each scenario are shown in Table 4. The increase in weights per criteria against scenario 0 is indicated in bold.
Lastly, the final priority order of the alternatives taking into account all the criteria is obtained through the weighted sum of the prioritization weights of each alternative by the weight of each criterion for each scenario, as shown in Equation (5):
W A = ∑ i = 1 6 w A i · w i
where WA is the overall weight of the alternative A; wAi is the weight of the alternative A for the criterion i obtained by the AHP method; wi is the weight of criterion i (i = 1 to 6).

3. Results

To facilitate the comprehension of the process, an example of the steps followed is presented for the GWP criterion only. Therefore, Table 5, Table 6 and Table 7 show the GWP intermediate and consecutive results of applying the AHP method based on the values in Table 3. Table 5 presents the ratios of the GWP criterion values shown in Table 3 for the four alternatives against each other. Table 6 shows the adjustment of these ratios in Table 5 to Saaty’s scale (1 to 9). Finally, based on the values in Table 6, Table 7 shows the resulting normalization by the sum of their column (the final sum of each column should be equal to 1).
The last column in Table 7 shows the priority vector of the alternatives, calculated as the average of the values of the other columns. In the case of the GWP criterion, the FCEV alternative is the one that offers the largest value prominently (in bold).
Following the same process to obtain the priority values in Table 7 for the GWP, Table 8 shows the equivalent results for the other criteria (POP, FT, FI, VC, and FC). Note that, being a repetitive method, the initial steps (those that would correspond to Table 5 and Table 6 for these other criteria) are not presented to ease the reading of the document.
All matrices have successfully passed the AHP consistency test, which ensures that the values of the ratios used in the method are neither random nor illogical in their pairwise comparisons [38,46].
According to these results, FCEV would be the priority alternative for the GWP (weight = 67.1%) and POP criteria (56.1%); ICV would be the priority alternative for the FI (35.6%), FT (58.0%), and VC (42.3%) criteria, while the PHEV alternative would be the priority alternative for the FC criterion (55.6%).
However, to know the overall priority of alternatives, all criteria must be considered at the same time. This is completed by applying the weights from the ten scenarios shown in Table 4. Figure 2 presents the results of applying the decision matrices resulting from multiplying the priority vectors in Table 7 and Table 8 by the weight vectors of the six criteria from Table 4 according to these scenarios.
When including all criteria to take a decision (Figure 2), it seems that the ICV alternative is the one receiving the best results in most scenarios. However, in the cases where the environmental criteria (GHP and POP) have the greatest weight (scenarios 1 to 3), the FCEV alternative takes the lead and the ICV decreases linearly as the relevance of the environmental criteria increases. Nonetheless, as FCEVs are not fully developed and available in the market, BEVs and PHEVs are the ones entering now into the market.
It should be observed, though, that the BEV alternative results to be the least interesting in almost all scenarios.

4. Discussion

Results show how dramatically the ICV is best evaluated in half of the scenarios analyzed. These results are in accordance with the market trends through a time when the choice was taken mostly based on cost-effectiveness. When this occurs (scenarios 7–9), Figure 2 shows that the choice would still be the same, as petrol fuel-based alternatives take the lead because the different costs of these new technologies make them less attractive [47]. The history of cars relates the competition between EVs and ICVs from the early stages (1890) until the arrival of petrol-based fuels at the beginning of the 20th century, the moment in which the ICV became widely adopted due to its practical advantages [48]. ICVs spread worldwide and became the choice of mobility technology, becoming one of the most powerful industries in the world. However, the side effects of ICVs, which were initially neglected, are nowadays more visible than ever. On one side, greenhouse gas emissions are causing an increase in the temperatures on Earth, while NOx, CO, and VOC are polluting the air in urban areas that begin to take measures to avoid the entrance of older vehicles or to dramatically restrict the mobility of polluting vehicles.
These side effects are the main cause of change in regulations. The regulatory new framework together with the improvement of batteries (with the apparition, in 1990, of the first commercialization of Li-ion batteries [49]) somehow forced the entrance of electrified mobility. This relatively new technology opened the path to the third awakening of the EV (the second one took place in 1990 with the arrival and sudden death of the Impact, a model from GM [50]). Nissan Leaf (2010) was the first worldwide sold BEV model and, since then, Li-ion batteries have been the choice for electrification for almost all EV models in the market. However, since the very beginning, researchers are looking for a substitute for these batteries due to their many drawbacks, such as a still poor energy density to satisfy the range anxiety without causing an increase in weight, size, the extensive use of materials, or safety among others [51].
It has sense, then, that results show how the ICV is not the first choice when environmental issues are prioritized. However, even in these scenarios dominated by environmental concerns (1–3), the BEV is not very well placed, having to compete with PHEV (which is what one can see in the automotive market nowadays). Indeed, there is one alternative having a better result than BEV (in fact, up to twice better): the FCEV.
FCEVs eliminate most of the drawbacks of BEV and PHEV batteries with the use of fuel cells. However, original equipment manufacturers (OEM) do not yet consider them as a choice for electrified models due to technology readiness. FCEV technology is yet not sufficiently mature, having much lower efficiencies than lithium-ion batteries (50% vs. 98%) [52] while the compression of gas is still too expensive and the fueling infrastructure is almost inexistent. It is noteworthy to mention that BEV is better positioned than FCEV in only two scenarios (6 and 9), being those in which costs and infrastructure gain more relevance.
The results obtained in this work are in line with those obtained in comparisons made in previous studies, such as between BEVs and ICVs [53,54,55] or between BEVs and FCEVs [33], or between BEVs, PHEVs and FCEVs [56].
Through this argumentation, this study corroborates, that, this third rise of BEVs and PHEVs seems to be just a transitory phase until OEMs find another alternative, which seems to be related to FCEV powered by hydrogen in the best cases. The duration of this phase relies on the advancements in both batteries (which are dealing with new materials and chemistries) and fuel cell technologies. Depending on the velocity of one or another, this phase will be longer or shorter but, in the end, batteries do not seem to be the final choice and will be most surely substituted by FCEV, which is aligned with previous research that states that PHEV and BEV are just a bridge to hydrogen fueled vehicles [57] that FCEV are the next step of EV [58]. Nonetheless, the final choice is not that clear, as uncertainty seems to be the reason for disagreement, and therefore all technologies should still develop before deciding for one option only [59].
From the results, it is also interesting to see that, PHEV, being a merge of ICV and BEV, has a behavior between these two alternatives in most scenarios. When environmental criteria are enhanced, the relevance of PHEV decreases with a lower slope than that of an ICV, taking the second position after FCEV in scenario 3. Similarly, when considering fueling time and infrastructure, it is stable in the second position and, when analyzing costs, it behaves almost as an ICV, being capable of even taking the lead as it has the best of an ICV and BEV. It is interesting to note that, in all scenarios, PHEV is better positioned than BEV.
This study presents how the higher the environmental concern higher is the interest in FCEV and BEV while the chances to select the ICEV and PHEV decrease. These results are aligned with other research, indicating that, in the mid-term future, several technologies will be chosen depending on the passenger car market segment, where there is space for PHEVs if they include biofuels [60].
This study considers six long-term criteria (GWP, POP, FT, FI, VC, and FC) and discards technology readiness (as something that can be reached with sufficient time) to identify, with an objective approach, which is the best choice for the future of private mobility. Results indicate that battery-based vehicles are not very well evaluated in none of the scenarios analyzed and, consequently, they will not be the choice of the century. Somehow, results are relatively frustrating, as ICVs lead most of the possible scenarios except the one considering environmental burdens, which is led by FCEVs, although they might change if hydrogen-related costs decrease and fuel cost increase in the future, as some researchers point out to be the case [61].
This study opens a new path of discussion, as it focuses on privately driven vehicles only, leaving space for improvements in public transportation or substantial changes in social mobility habits, which are gaining relevance in these last years and could change the numbers in case of consideration.

Author Contributions

Conceptualization, L.V.C. and L.C.C.; methodology, L.V.C.; software, L.V.C.; validation, L.V.C. and L.C.C.; formal analysis, L.C.C.; investigation, L.V.C. and L.C.C.; resources, L.V.C.; data curation, L.V.C. and L.C.C.; writing—original draft preparation, L.V.C. and L.C.C.; writing—review and editing, L.V.C. and L.C.C.; visualization, L.V.C. and L.C.C.; supervision, L.V.C. and L.C.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Not applicable.

Acknowledgments

Lluc Canals Casals is a Serra Hunter Fellow from the Generalitat de Catalunya.

Conflicts of Interest

The authors declare no conflict of interest.

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Energies 15 09149 g001 550
Figure 1. The hierarchical structure of the AHP method followed in this study.
Figure 1. The hierarchical structure of the AHP method followed in this study.
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Energies 15 09149 g002 550
Figure 2. Overall priority of the alternatives for the ten scenarios.
Figure 2. Overall priority of the alternatives for the ten scenarios.
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Table
Table 1. Car characteristic data used in the analysis.
Table 1. Car characteristic data used in the analysis.
AlternativePower (kW)Weight (kg)Energy Consumption (L Gasoline-eq/100 km)Range (km)Energy Storage (L)Capacity
(kWh)
IntervalAverageIntervalAverage
ICV10013655–107.5420–84063042373.8 4
PHEV10014453.4–4.6 14757–113594666 2391.5 5
BEV10016101.6–4.43109–30020430039.2 6
FCEV10013006.6–8.87.7350–490420200 3248.1 7
1 The 8.8 kWh battery allows traveling about 40 km at full load with an equivalent consumption of 1 L gasoline-eq/100 km. The combustion engine, which consumes 4–6 L gasoline/100 km, is used to cover the remaining 60 km. Equivalence ratio: 1 L gasoline = 8.9 kWh. 2 Volume of fuel tank plus batteries. 3 Volume of 70 MPa H2 tanks plus batteries. 4 Equivalence ratio: 1 L gasoline = 8.9 kWh. 5 Energy contained in 43 L gasoline (tank) plus 8.8 kWh battery. 6 Battery capacity. 7 Energy contained in 4.4 kg H2 (tanks) plus 10.5 kWh battery. Equivalence ratio: 1 kg H2 = 54 kWh.
Table
Table 2. Saaty’s scale of preference for the comparison of two elements (based on [42]).
Table 2. Saaty’s scale of preference for the comparison of two elements (based on [42]).
ImportanceMeaning
1Equal importance (both elements contribute equally to the objective)
3Moderate importance (an element is slightly more important than the other)
5Strong importance (an element is more important than the other)
7Very strong importance (an element is muchmore important than the other)
9Extreme importance (there is clear evidence that an element is far more important than the other)
Reciprocals of aboveIf the element “a” has an importance value “x” with respect to the element “b”, then “b” has an importance value “1/x” with respect to “a”
Rationals (x.1–x.9)Ratios arising from the scale
Table
Table 3. Values of each criterion for each alternative.
Table 3. Values of each criterion for each alternative.
CriterionAlternativeCriterion ValueRemarks
GWP: Global warming potential (kg CO2 eq/km)ICV0.291Vehicle production is responsible for 21% of the GWP impact [17].
PHEV0.24226% in vehicle production [17].
BEV0.26542% in vehicle production [17].
FCEV0.18[33].
POP: Photochemical oxidant potential (kg C2H4 eq/km)ICV5.21 × 10−521% in vehicle production [17].
PHEV4.23 × 10−527% in vehicle production [17].
BEV1.75 × 10−564% in vehicle production [17].
FCEV1.19 × 10−5Estimated.
ICV2Estimated.
FT: Fueling time (minutes)PHEV70.52 min to fill gasoline tank + 68.5 min for recharging the battery using a 240 V, 40 A, 7.7 W charger.
BEV305Idem as PHEV.
FCEV875 min to fill the H2 tank + 82 min for recharging the battery as PHEV.
FI: Fueling infrastructure (2019 USD per vehicle-eq)ICV2430Cost of building a gas station: USD 2,448,000 (2022); 6 fuel pumps [43].
PHEV2550Idem as BEV.
BEV2550Cost for a higher Level 2 capacity outlet (240 V, 40 A): USD 2150 (2008) [33].
FCEV7130Cost of building a hydrogen station in mass production: USD 2,200,000 (2008); 6 hydrogen intakes [33].
VC: Vehicle cost (2019 USD)ICV33,830[34]
PHEV37,950[35]
BEV43,830[36]
FCEV108,900[37]
FC: Fuel cost (2019 USD per km)ICV0.0102Gasoline price: USD 2.6 (2019) per gallon; 1 gallon = 3.785 L.
PHEV0.0052Gasoline price as for ICV; electricity price: USD 0.1301 (2019) per kWh.
BEV0.0319Electricity price as for PHEV.
FCEV0.0491Hydrogen price: USD 4.25 per kg; electricity price as for PHEV.
Table
Table 4. Criteria weights assumed for the ten scenarios of the sensitivity analysis.
Table 4. Criteria weights assumed for the ten scenarios of the sensitivity analysis.
GWPPOPFTFIVCFCSum
Scenario 00.1670.1670.1670.1670.1670.1671
Scenario 10.2170.2170.1420.1420.1420.1421
Scenario 20.2670.2670.1170.1170.1170.1171
Scenario 30.3170.3170.0920.0920.0920.0921
Scenario 40.1420.1420.2170.2170.1420.1421
Scenario 50.1170.1170.2670.2670.1170.1171
Scenario 60.0920.0920.3170.3170.0920.0921
Scenario 70.1420.1420.1420.1420.2170.2171
Scenario 80.1170.1170.1170.1170.2670.2671
Scenario 90.0920.0920.0920.0920.3170.3171
Table
Table 5. Ratios between alternatives for the global warming potential (GWP) criterion from Table 3 values.
Table 5. Ratios between alternatives for the global warming potential (GWP) criterion from Table 3 values.
ICVPHEVBEVFCEV
ICV1.0000.8320.9110.619
PHEV1.2021.0001.0950.744
BEV1.0980.9131.0000.679
FCEV1.6171.3441.4721.000
Table
Table 6. Importance ratios between alternatives for the GWP criterion fitted to the preference scale (1–9).
Table 6. Importance ratios between alternatives for the GWP criterion fitted to the preference scale (1–9).
ICVPHEVBEVFCEV
ICV1.0000.2760.4400.111
PHEV3.6271.0002.2330.183
BEV2.2730.4481.0000.140
FCEV9.0005.4687.1261.000
Sum15.9007.19210.7991.434
Table
Table 7. Standard matrix of importance ratios between alternatives for the GWP criterion.
Table 7. Standard matrix of importance ratios between alternatives for the GWP criterion.
ICVPHEVBEVFCEVPriority
ICV0.0630.0380.0410.0770.055
PHEV0.2280.1390.2070.1270.175
BEV0.1430.0620.0930.0980.099
FCEV0.5660.7600.6600.6970.671
Sum1.0001.0001.0001.0001.000
Table
Table 8. Standard matrix of importance ratios between alternatives for the POP, FT, FI, VC, and FC criteria.
Table 8. Standard matrix of importance ratios between alternatives for the POP, FT, FI, VC, and FC criteria.
CriterionAlternativeICVPHEVBEVFCEVPriority
Photochemical oxidant potential (POP)ICV0.0580.0500.0500.0640.055
PHEV0.0900.0770.0650.0820.078
BEV0.3300.3330.2840.2740.305
FCEV0.5230.5400.6010.5800.561
Fueling time (FT)ICV0.5630.4970.7310.5280.580
PHEV0.2010.1770.0960.1650.160
BEV0.0630.1510.0810.1440.110
FCEV0.1740.1750.0920.1630.151
Fueling infrastructure (FI)ICV0.3620.3640.3640.3360.356
PHEV0.2990.3000.3000.3140.303
BEV0.2990.3000.3000.3140.303
FCEV0.0400.0360.0360.0370.037
Vehicle cost (VC)ICV0.4370.4480.4320.3740.423
PHEV0.3030.3120.3260.3210.316
BEV0.2110.2000.2090.2640.221
FCEV0.0490.0400.0330.0420.041
Fuel cost (FC)ICV0.2890.2890.2850.2860.287
PHEV0.5530.5540.5570.5590.556
BEV0.0960.0950.0950.0940.095
FCEV0.0630.0620.0630.0620.062
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Cremades, L.V.; Canals Casals, L. Analysis of the Future of Mobility: The Battery Electric Vehicle Seems Just a Transitory Alternative. Energies 2022, 15, 9149. https://doi.org/10.3390/en15239149

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Cremades LV, Canals Casals L. Analysis of the Future of Mobility: The Battery Electric Vehicle Seems Just a Transitory Alternative. Energies. 2022; 15(23):9149. https://doi.org/10.3390/en15239149

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Cremades, Lázaro V., and Lluc Canals Casals. 2022. "Analysis of the Future of Mobility: The Battery Electric Vehicle Seems Just a Transitory Alternative" Energies 15, no. 23: 9149. https://doi.org/10.3390/en15239149

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