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Life Cycle Assessment of Electric Vehicles – A Framework to Consider Influencing Factors


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The environmental impacts of electric vehicles (EVs) partially depend on the parameters of their site of operation. Variations of average driving patterns in different geographic locations and the use of heating and cooling due to local climate conditions have an impact on the energy consumption of EVs. In combination with the regional electricity mix these factors influence the environmental impact of EVs. Hence, these influencing factors must be included in an ecological assessment. The Life Cycle Assessment (LCA) method is used for the quantitative ecological assessment. An LCA can e.g. serve as a decisions support tool in vehicle engineering. This paper proposes a framework to consider influencing factors for the ecological assessment of EVs. A case study is used to demonstrate the capability of the framework.
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Procedia CIRP 29 ( 2015 ) 233 238
Available online at
2212-8271 © 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
Peer-review under responsibility of the scientifi c committee of The 22nd CIRP conference on Life Cycle Engineering
doi: 10.1016/j.procir.2015.02.185
The 22nd CIRP conference on Life Cycle Engineering
Life Cycle Assessment of Electric Vehicles – A Framework to Consider
Influencing Factors
Patricia Egedea,c*, Tina Dettmera,c, Christoph Herrmanna,c, Sami Karab,c
aChair of Sustainable Manufacturing & Life Cycle Engineering, Institute of Machine Tools and Production Technology (IWF), Technische Universität
Braunschweig, Langer Kamp 19b, 38106 Braunschweig, Germany
bSustainable Manufacturing & Life Cycle Engineering Research Group, School of Mechanical & Manufacturing Engineering, The University of New South
Wales, Sydney, NSW 2052 Australia
cJoint German-Australian Research Group on Sustainable Manufacturing and Life Cycle Engineering
* Corresponding author. Tel.: +49-531-391-7145; fax: +49-531-391-5842. E-mail address:
The environmental impacts of electric vehicles (EVs) partially depend on the parameters of their site of operation. Variations of average driving
patterns in different geographic locations and the use of heating and cooling due to local climate conditions have an impact on the energy
consumption of EVs. In combination with the regional electricity mix these factors influence the environmental impact of EVs. Hence, these
influencing factors must be included in an ecological assessment. The Life Cycle Assessment (LCA) method is used for the quantitative
ecological assessment. An LCA can e.g. serve as a decisions support tool in vehicle engineering. This paper proposes a framework to consider
influencing factors for the ecological assessment of EVs. A case study is used to demonstrate the capability of the framework.
© 2015 The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the International Scientific Committee of the Conference “22nd CIRP conference on Life Cycle
Keywords: Life Cycle Assessment; Electric Vehicles, Framework, User-specific, Regional
1. Introduction
Motorized vehicles have a significant impact on the global
greenhouse gas emissions. One option to reduce the
environmental impact is electric vehicles (EVs). Like all
reduction measures the implementation of EVs must be
evaluated carefully to avoid problem shifting or rebound
effects. Mostly Life Cycle Assessment (LCA) is used to
quantify the environmental impact along the entire life cycle
from raw material extraction to the end-of-life. However,
calculating the environmental impact with LCAs for EVs is
challenging. Results from different EV studies vary greatly
[1]. With these results it is possible to derive general
conclusion (e.g. “EVs can have lower environmental impacts
than conventional vehicles.”). Yet, more specific questions
are more challenging to answer. It is difficult to determine for
which situations and under which conditions these
conclusions apply. This makes it challenging to base decisions
on these results and to answer specific questions (e.g. “How
long is the ecological amortisation time for lightweight
materials for a specific market?”).
One reason for the difficulty of the calculation and the
variability of results is the lack of transparency of the
influencing factors of the LCA of EVs. The electricity mix,
use patterns and the material composition of the vehicles are
examples for important influencing factors of LCA results of
EVs. Usually the LCA practitioner does not have access to
primary data from the entire life cycle of the EV. Different
stakeholders are involved in the making, the use and the
disposal of the vehicle, which disperse the required
information over the entire supply chain and over time.
Confidentiality issues, complex supply chains, a variety of
possible use patterns and unknown future developments
increase the challenge of gathering the required data and
interdependencies, hence carrying out an LCA of an EV.
© 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
Peer-review under responsibility of the scientifi c committee of The 22nd CIRP conference on Life Cycle Engineering
234 Patricia Egede et al. / Procedia CIRP 29 ( 2015 ) 233 – 238
Figure 1 shows the array of results qualitatively. The x-axis
specifies the distance travelled; the y-axis marks the resulting
environmental impact. The travel distance underlies a certain
range (see ǻ3). The y-intercepts of the lines represent the
environmental impact of the raw material extraction and the
vehicle manufacturing. Depending on the assumptions made
for these first life cycle phases a range of values is possible
(see ǻ1). In this case two examples for a vehicle with a low
(see lower point of ǻ1) and high (see upper point of ǻ1)
environmental impact of raw material extraction and vehicle
manufacturing are shown. The slope of the line represents the
environmental impact which is caused in the use phase of the
vehicle in relation to the distance travelled. The slope is
defined by the energy consumption of the vehicle and the
environmental impact of the energy mix. Depending on the
scenario the values for the energy consumption and the energy
mix vary which results in a minimum (dotted line) and a
maximum (dashed line) slope. This leads to a range of final
results based on the assumptions of the use phase (see ǻ2).
When combining the ranges of raw material and
manufacturing phase, the use phase and driving distance, a
array is defined with possible outcomes of the LCA (shaded
area). The continuous line shows the ideal case using an
energy mix with (almost) no environmental impact. In this
case the consumption of the vehicle is irrelevant. For reasons
of clarity, the end-of-life phase is not considered in this
qualitative chart. The integration of the end-of-life phase adds
another set of parameters and enlarges the possible corridor of
results. A framework for the LCA of EVs clarifies the
different parameters and describes the system of the EV with
regard to LCA in detail. Depending on the goal and scope of a
study relevant influencing factors can be identified.
A framework clarifies the information that must be
collected and the relevant parameters which must be
considered. Hence, it increases the reproducibility and
transparency of LCAs of EVs.
Figure 1: Range of LCA results for EVs
2. Electric Vehicles and Life Cycle Assessment
2.1. Electric Vehicles
The term EV covers a range of vehicles types, e.g. hybrid
EVs and battery EVs. Hybrids have an electric and a
combustion engine. Depending on the type of hybrid the
vehicle can be charged from the grid such as Plug-In Hybrids.
This paper focuses on battery EVs which have an electric
motor and a battery which is charged externally (besides
recuperation). [1], [2]
EVs are seen as an option to reduce or eliminate the
downsides of using today’s fossil fueled vehicles. Their
characteristics offer advantages which solve problems caused
by conventional vehicles. These are the independence from
fossil fuels, the reduction of noise and the elimination of tail
pipe emissions. [3], [4] Their ability to run on many types of
energy sources via electricity storage in batteries provides the
opportunity for fossil fuel free mobility. The use of EVs
causes hardly any local emissions and causes little noise. In
mega cities which suffer from severe air pollution and high
noise levels these advantages are very valuable. The
disadvantages of EVs are mainly associated with the driving
range and the cost of the vehicles. [3], [4] Another concern is
the change of use of resources in comparison to conventional
vehicles due to use of Lithium-Ion batteries and electric
engines with permanent magnets. This leads to a more intense
use of metals like lithium, manganese or cobalt as well as rare
earth metals like neodymium. [2], [15] Currently, the driving
range of EVs is significantly lower than for conventional
vehicles. Even though this range is sufficient for the majority
of daily travel needs, many customers judge the driving range
of EVs as not sufficient. In addition the use of heating and
cooling devices can reduce the range significantly as these
auxiliaries are very energy intensive. The purchase price of
EVs is higher than for conventional vehicles of comparable
size. However, despite of their disadvantages EVs are
successful even in places with conditions which could be
considered unfavourable. An example is Norway which has a
climate that requires intensive heating which reduces the
range. However, due to incentives offered such as tax
reductions and a municipal charging infrastructure, EVs have
been adopted very well in the Scandinavian countries. [5]
As seen in figure 1 a high share of the environmental
impact of the EV occurs in the use phase and is directly linked
to the energy consumption during usage in combination with
the energy mix. The energy consumption of EVs depends on
different parameters which can be divided into three groups:
driving resistances, the use of auxiliaries and losses. Driving
resistances must be overcome to achieve and maintain a
certain velocity. Examples are the rolling, acceleration and
aerodynamic resistance. Vehicle characteristics like weight
and the frontal area influence the resistances. In addition the
use of auxiliaries such as heating, air conditioning and
ventilation increase the energy consumption. Also losses
occur in the process of converting electric energy into
mechanical energy due to the efficiencies of the different
components. [6], [7]
Patricia Egede et al. / Procedia CIRP 29 ( 2015 ) 233 – 238
2.2. Life Cycle Assessment
In order to identify the environmental impact of EVs, the
mass and energy fluxes of the respective product systems
need to be compared throughout their life cycles using the
LCA methodology according to ISO 14040 [8]. LCA has
proven to be a useful method for analysing and quantifying
the environmental impacts of products. It became generally
accepted in the last two decades and is internationally
approved and standardised (ISO 14040 [8], ISO 14044 [9]).
The LCA procedure consists of four successive steps: the
goal and scope definition, the inventory analysis, the impact
assessment and the interpretation of the results. The procedure
has to be understood as an iterative process rather than one
exercise. For instance intermediate results obtained from the
inventory analysis, impact assessment and interpretation may
require a modification of the goal and scope definition.
During goal and scope definition, the intended application
(i.e. the questions to be answered by the study), the
motivation for carrying out the study and the intended
audience have to be defined (ISO 14040 [8]). Furthermore,
the product system under study needs to be clearly described
including system boundaries and functional unit (the
quantified performance of the system). Furthermore, a number
of additional methodological details and choices have to be
documented for transparency reasons.
Life Cycle Inventory Analysis aims at understanding and
accounting for input and output flows within the observed
system and its interaction with the environment (elementary
flows). Petri-net based material flow nets can help to finally
calculate all incoming and outgoing flows crossing the system
boundaries. This input-output balance referenced to the
functional unit is called a Life Cycle Inventory.
Based on the Life Cycle Inventory, the potential
environmental impacts resulting from extracted resources and
from emitted pollutants are determined during Life Cycle
Impact Assessment. First, emissions are classified according
to their contribution to the different impact categories.
Second, their potential contribution is expressed in terms of
impact equivalents, e.g. in CO2-equivalents (CO2-eq) for
climate change.
In the interpretation phase, results of the study are plotted
to present the significant issues. Additionally, the reliability of
the study is scrutinized in sensitivity and uncertainty analyses
complemented by consistency and completeness checks.
Finally, recommendations are derived based on the findings of
the study.
2.3. Life Cycle Assessment of Electric Vehicles
As complexity of a product have a significant impact on
the complexity of the respective LCA study, LCA on EVs are
a challenging task. In recent years, a number of LCAs have
been published on EVs (e.g. [2], [10], [11], [12], [13]) or EV
specific components like Li-ion batteries (e.g. [12], [14], [15],
[16], [17]). Hawkins et al. [2] as well as Nordelöf et al. [1]
provided comprehensive reviews on LCAs of EVs. They
identified 55 and 79 relevant studies, respectively, including
full reports, journal papers and conference papers. They both
report widely diverging results which somehow have to be
expected for a complex product in an emerging market. The
divergence can be further explained by differences in
methodological choices and also by unavailability of primary
data. The guidelines of the project E-Mobility Life Cycle
Assessment Recommendations (eLCAr) [18] aim to
harmonise the methodological approach and to enhance
transparency of methodological choices.
As modern EVs have been introduced to the market
recently and there are plenty of ongoing research activities to
further develop the necessary key technologies (e.g. for
energy storage), most LCA studies focus on vehicle
production and related raw material acquisition. Therefore
and due to the lack of long-time measurements/ monitoring/
experiences, only few LCAs address the use phase in
particular (i.e. [19], [20]). Use profiles are mainly derived
from standard driving cycles and the associated energy
consumption is calculated generically as documented, e.g. in
the eLCAr guidelines [18]. Modelling of use phase scenarios
based on real life data and especially site specific
measurements have not been published yet.
3. Framework
The environmental impacts of EVs depend on various
parameters related to the vehicle’s characteristics, their
location of use and user influences. Variations of driving
patterns of different users and the use of heating and cooling
due to local climate conditions have an impact on the energy
consumption of EVs (see section 2.1.). In combination with
the regional electricity mix these parameters influence the
environmental impact of EVs. Therefore, the vehicles must be
seen as a part of the setting with which it interacts to answer
specific LCA questions. When neglecting these
interdependencies, important aspects might be missed and left
out. Connecting external influences with the use phase of the
vehicles assists the LCA practitioner to evaluate the influence
of parameters on the environmental impact. Setting up a
descriptive framework allows the LCA practitioner to
translate external influencing factors into environmental
impacts reducing the uncertainty of LCAs.
Figure 2 shows the proposed framework and illustrates the
EV as an element in a larger system of influencing factors and
highlights the connection of energy consumption and external
factors. The material and energy flows over the entire life
cycle necessary to manufacture and operate the vehicle define
the life cycle of the EV (mid-level). The setting of external
factors in which the EV is deployed (top level) influences the
life cycle and the LCA results. These external factors can be
divided into three groups: the user, the infrastructure and the
surrounding conditions. In this paper we focus on the
influence of these external factors on the use phase, i.e. the
energy consumption. External factors and also internal factors
(characteristics of the vehicle like the weight of the vehicle or
the size of the frontal area influencing the aerodynamic
resistance) affect the energy consumption in the use phase
(bottom level).
236 Patricia Egede et al. / Procedia CIRP 29 ( 2015 ) 233 – 238
Figure 2: LCA framework for electric vehicles; Source of bottom picture see
3.1. Influencing factor: Vehicle
In the use phase specific characteristics of the vehicle
influence the energy consumption (as described in part 2.1).
These factors are considered internal in this framework as
they are inherent properties of the vehicle.
3.2. Influencing factor: User
The user of the EV influences the environmental impact of
the EV through the driving and charging behaviour as well as
through the intensity of the use of auxiliaries. A more
aggressive driving style leads to a higher energy consumption
whereas a more cautious driving style results in a more
efficient use of energy. Depending on the charging behaviour
and the willingness to install renewable energy specifically
for the EV (e.g. in the form of solar panels), the share of
renewable energy can be increased significantly compared to
the use of grid energy in many countries. Finally, the use of
heating and cooling to achieve the desired temperature has a
significant influence on the energy consumption. The
willingness to accept a warmer vehicle temperature in the
summer and a cooler temperature in the winter is directly
linked to a lower environmental impact.
3.3. Influencing factor: Infrastructure
The electricity mix is one of the most crucial parameters
for the LCA calculation. Using a mix based entirely on
renewable energies delivers a completely different result than
an energy mix based on fossil fuels. Choosing the adequate
mix which reflects the real world situation and leads to fair
and reliable results is challenging. [18] In many LCAs an
energy mix is used which is based entirely on renewable
energy. However, often it is not clear if this represents the
actual grid situation or if it is a case of crediting renewable
energy to the EV rather than a different use. In the latter case
it must be considered if the crediting can be justified. The
charging of EVs can in principle often be carried out at
regular household plugs. Yet, often more sophisticated
solutions are required at workplaces or in public areas to
allow adequate and safe charging. Depending on the
conditions of the site the installation of these charging stations
demands major building activities. These activities can be
significant for specific scenarios in which only one or a few
vehicles use one charging station. The available charging
infrastructure also influences the options of smart charging.
Smart charging applications can increase the share of
renewable energy used to charge the EV.
3.4. Influencing factor: Surrounding conditions
The surrounding conditions influence the environmental
impact of EVs. The climate, the topography and the type of
road are identified as significant factors for the energy
consumption. The climate influences the need for heating and
cooling appliances in the vehicle. The temperature varies both
on a seasonal as well as on a daily level leading to a
fluctuation of the energy consumption. Depending on the
interaction of temperature and humidity the wind shield of the
car can fog up and require ventilation or the use of the air
conditioning and/or heating. Currently, resistance heating is
mostly applied in EVs. Alternative technologies like a heat
pump can reduce the energy consumption for heating. A flat
topography leads to a lower energy demand, than a hilly
landscape. It is important also to consider the breaking
recuperation when calculating the energy consumption. The
type of road such as city streets or highways, define
parameters such as the speed limit and the frequency of stops
e.g. at traffic lights. These parameters influence the
3.5. Fields of application of framework
The framework serves as a support for LCA practitioners
by providing the necessary technical background on EVs. It
can be applied to various LCA studies. The influencing
factors have to be discussed in the goal and scope section of
External factors
Comfort requirements
Driving style
Charging behaviour
Internal factors
Vehicl e
Energy consumption
Energy mix
Charg ing system
Smart charging
Type of road
Patricia Egede et al. / Procedia CIRP 29 ( 2015 ) 233 – 238
the study. Examples for possible areas are comparative
assessments with other vehicle technologies and design
decisions. EVs compete with conventional vehicles as well as
vehicles with other alternative propulsion systems or fuels.
Analyzing the environmental impact in detail helps to identify
use cases and regions for which EVs are particularly useful.
This can allow policy makers or consumers to make robust
choices in increasingly diverse markets. Another decision
context is a design choice for EVs. When evaluating design
alternatives influencing factors can be significant for the
environmental sensitivity. Problem shifting can occur from
one phase to another or from one vehicle component to
another. To evaluate the possible environmental benefit of
design options a detailed analysis of the entire system and its
parameters is necessary to ensure robust results. This is
relevant for automotive manufacturers and their suppliers.
4. Case Study
The following case study shows the relevance of the
framework. The goal of the case study is to determine if and
how influencing factors impact the comparison of different
EV. A lightweight vehicle is evaluated with regard to its
ability to reduce the overall global warming potential (GWP)
in a range of countries with differing electricity mixes. The
results of Germany, Brazil and Spain are discussed in detail.
The purpose of using lightweight materials is to reduce the car
weight and consequently the energy consumption in the use
phase and/or to increase the driving range with the same
battery size. However, the use of lightweight materials usually
comes with higher environmental impacts during the raw
material and manufacturing phase compared to traditional
materials. The end-of-life phase is not considered for reasons
of clarity. Two vehicles are compared, one with a steel and
another with an aluminium chassis. To evaluate the impact of
the influencing factors three scenarios with differing external
factors are defined. The internal influencing factor vehicle
lifetime is analyzed by calculating results for driving
distances of 100,000 km, 150,000 km and 200,000 km.
The case study is performed as a delta analysis. The
relevant figures for the analysis are the weight reduction of
the aluminium vehicle and the CO2-eq of the material supply
of steel and aluminium. Following the LCA of Das [22] the
aluminium chassis achieves a weight reduction of 67%. The
CO2-eq/kg of steel is fixed as 5.7 based on [23] and the
Ecoinvent 3.01 database. [24] Ehrenberger et al. [25] show
the range of CO2-eq for primary aluminium production.
Based on this review and Das [22] the CO2-eq for aluminium
is set as 13 CO2-eq/kg. The CO2-eq of the electricity mixes
of 71 countries (and regions) are extracted from
Ecoinvent 3.01. [24]
4.1. Scenario descriptions of external factors
Three scenarios of external influencing factors are defined
for which the energy consumption is determined. Four
different influencing factors are considered: Driving
behaviour, desired temperature (both influencing factor user),
topography (influencing factor surrounding conditions) and
type of road (influencing factor infrastructure). Table 1 shows
the influencing factors and their specification for each
scenario. Scenario A depicts a rather cautious driver who
moves around in a flat city area. The need for heating and air
conditioning is low. The scenario characteristics result in a
rather low average velocity. Summed up, the average
consumption is therefore small at around 10 kWh/100km.
Scenario B shows a driver with an average driving behaviour
who mostly drives in a hilly city area. The requirement of
heating and cooling is medium. The scenario characteristics
result in a medium average velocity. Altogether, the average
consumption is therefore medium at around 15 kWh/100km.
Scenario C describes a dynamic driver travelling on highways
in a hilly area. The demand for heating and cooling is
medium. The scenario characteristics result in a rather high
average velocity. As a consequence of these characteristics,
the average consumption is therefore high at around
20 kWh/100km.
Table 1: Description of scenarios A, B and C
Influencing factor Scenario A Scenario B Scenario C
Driving behaviour Cautious Average Dynamic
Desired temperature Low Medium Medium
Topography Flat Hilly Hilly
Type of road City City Highway
Energy consumption
[kWh/100km] ~10 ~15 ~20
4.2. Results
The results of the case study are presented in figure 3. The
chart shows for which number of countries the material choice
steel has a lower environmental impact than aluminium (blue
bars) and vice versa (orange bars). The three scenarios A, B
and C are calculated for the three lifetime expectancies of the
vehicles. The comparison of the scenarios reveals that the
lower environmental impact of one material in comparison to
another depends not only on the electricity mix but also on the
energy consumption in the use phase. For the medium life
time expectancy the advantageousness switches in 17
countries from steel to aluminium as the consumption
increases. With a shorter life span of the vehicle the number
increases to 36. In the last example with the longest life span
the result changes for 11 countries. As the life time of the
vehicle increases the differences between the scenarios A, B
and C diminish. Eventually the higher impact of the
production of the aluminium pays off regardless of the energy
consumption per kilometre. The lightweight design becomes
more and more relevant as the vehicle is used longer and
For the countries Brazil, Germany and Spain the results are
is exemplified. Brazil has an energy mix with rather low CO2
emissions as it is mainly based on hydro power. Germany has
an energy mix with medium CO2 emissions with a rather
divers mix of energy sources. The CO2 emissions of the
Spanish energy mix lie in between the other two countries. In
Brazil the material choice of steel causes lower emissions than
the choice of aluminium. Only in the case of a 200,000 km
238 Patricia Egede et al. / Procedia CIRP 29 ( 2015 ) 233 – 238
driving distance and a high consumption in scenario C the
choice of aluminium pays off. For Germany, the opposite is
the case. Aluminium is the better choice except for the case of
a low consumption (Scenario A) and a short driving distance
(100,000 km). In the case of Spain, the result is not as clear.
For a long driving distance the choice of aluminium pays off.
In the other two cases of medium and low driving distances
(150,000 km and 100,000 km) aluminium only pays off for a
high consumption (Scenario C) or for a medium and high
consumption (Scenarios B and C). It becomes clear that the
external factors can influence whether a material choice pays
off in a specific country or not. Considering average values
for the consumption can lead to misleading results of a study.
Sensitivity analysis can reveal the robustness of results.
However, including external factors systematically can help to
reduce the uncertainty of the use phase by narrowing down
the possible energy consumption and increase the reliability
of LCAs for EVs.
Figure 3: Analysis of lower GWP of steel and aluminium vehicle
Summary and Outlook
This paper presents a framework for the LCA of EVs to
consider influencing factors of the use phase. The vehicle was
identified as an internal factor; the user, infrastructure and
surrounding conditions were defined as external factors. In a
case study the relevance of the identified factors was shown.
The advantageousness of an aluminium lightweight design
changed for a number of countries depending on the
parameter value of the influencing external factors and the
resulting energy consumption per kilometre. Following the
(approach of the) framework, e.g. car manufacturers could
more precisely define design strategies for their different
target markets and governments could include their countries’
characteristic to environmentally meaningful tailor respective
regulation and policies.
The necessity to include or exclude these influencing
factors in an LCA study depends on the defined goal and
scope. Improvements of the framework can be achieved by
determining quantitative relations between the influencing
factors and the energy consumption. Furthermore, the impact
of the external factors on the remaining life cycle phases can
be analyzed.
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Vehicle Construction, German Aerospace Centre e.V, 2013.
Steel Aluminium
100,000km 150,000km 200,000km
... Therefore, a life cycle perspective is required to avoid shifting the problem. Egede et al. (2015) proposed a framework to consider all the influencing factors for the LCA of EVs. The aim was for this paper to be a guide for all future LCAs regarding EVs. ...
... Also, the energy consumption in the vehicle was separated into the different devices in the EV. All these factors and components combine to create the proposed framework to be used for the LCA. Figure 1 depicts the suggested LCA framework (Egede et al., 2015). The focus is more on the use phase, and the environmental aspect to be more precise. ...
... The first internal factor is the vehicle itself. These are the characteristics of the vehicle like weight, frontal area, aerodynamics, efficiencies of components and the use of impactful materials like lithium, manganese, cobalt, and neodymium (Egede et al., 2015). The next factor is the user of the vehicle. ...
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The Advanced Manufacturing Student Conference (AMSC) represents an educational format designed to foster the acquisition and application of skills related to Research Methods in Engineering Sciences. Participating students are required to write and submit a conference paper and are given the opportunity to present their findings at the conference. The AMSC provides a tremendous opportunity for participants to practice critical skills associated with scientific publication. Conference Proceedings of the conference will benefit readers by providing updates on critical topics and recent progress in the advanced manufacturing engineering and technologies and, at the same time, will aid the transfer of valuable knowledge to the next generation of academics and practitioners.
... The LCA of BEVs represents an ongoing challenge due to the complexity of the system (Tintelecan et al. 2020). Moreover, the deployment of BEVs must be evaluated carefully to avoid problem shifting or rebound effects (Egede et al. 2015). Thus, to analyze the environmental benefits of BEVs, numerous studies have examined their environmental performances in comparison to internal combustion vehicles (ICVs) (Boureima et al. 2009;Girardi et al. 2015;Hawkins et al. 2013;Lombardi et al. 2017;Vargas et al. 2019). ...
... Hawkins et al. (2012) andNordelöf et al. (2014) have provided a comprehensive review of research on the LCA of BEVs. They identified 55 and 70 relevant studies, with varying scopes and analyses, and reported widely diverging results, which is to be expected for a complex product in an emerging market (Egede et al. 2015). The scope of studies varied from complete life cycles to well-to-wheel life cycles to the LCA of the battery alone; generally, more studies included the life cycle inventory (LCI) of fuels and electricity than addressed the LCI of the vehicle itself (Hawkins et al. 2012). ...
... Another reason that the LCA determined in BEV studies varies tremendously is the lack of transparency for the influencing factors (Egede et al. 2015). Due to data confidentiality and the dispersion across the multiple stakeholders involved in the making of BEVs, LCA practitioners usually have limited access to primary data from the entire life cycle of the vehicles (Egede et al. 2015;Vargas et al. 2019). ...
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Purpose The electrification of transport has been generally identified as a leading trend in sustainable transportation, but the transition to electromobility has not been widely embraced in the Gulf Cooperation Council (GCC) region. This study aims to identify the optimal vehicle choice for a rentier arid state in the GCC, Kuwait, while considering the environmental, economic, and social pillars of sustainability and the challenges posed in the region. Method The core of this framework is a mathematical model that integrates the three pillars of sustainability—environmental, economic, and social—with the associated practical constraints and logistics. The parameters derived from each perspective were aggregated through a weighting and normalization scheme to derive a composite sustainability index. The environmental aspect was evaluated through a life cycle assessment (LCA) of battery electric vehicles (BEVs) and internal combustion vehicles (ICVs), the financial aspect was calculated using net present value (NPV) formulas with a nominal discount rate, and the social aspect was evaluated based on a stakeholder and public perspective. An optimization model was formulated with a mixed integer program (MIP), and then, a sensitivity analysis was applied to evaluate the impact of altering key model assumptions. Results and discussion Overall, ICVs displayed worse environmental performance than BEVs across most impact categories: 74.2% of the total environmental burden of BEVs was traced back to electricity generation and 96.8% of ICV environmental impacts were attributed to the use of fossil fuels. The total annual equivalent cost was 549.55 USD higher for BEVs. High battery costs account for the high vehicle prices; however, a dramatic reduction in battery pack costs is expected in the upcoming decades. Moreover, the shift towards electric motors will lead to notable annual subsidy savings on both, the government and user, in oil-rich countries. Finally, the social impact will be favorable for ICVs in the immediate future until suitable infrastructure is implemented. Conclusions The electrification of transport has been identified as a leading trend in sustainable transportation, but the transition to electromobility has not been as widely embraced in the GCC region. Although BEVs are both environmentally and economically viable even in oil-rich countries, social barriers and policy change are the greatest challenges, including family size, lowering gasoline subsidies, imposing taxes on ICVs and vehicle emissions, and the adoption of BEVs for government and commercial fleets.
... Developed countries have shifted to using EVs in order to reduce environmental pollution in recent years. As a result, numerous researchers have studied the effects of EVs on the environment (e.g., Fuinhas et al. [2]; Peng et al. [11]; Plötz et al. [23]; Zhao et al. [24]; Kazemzadeh et al. [25]; Vilchez and Jochem [27]; Franzò and Nasca [29]; Petrauskienė et al. [30]; Bekel and Pauliuk [31]; Egede et al. [32]; and Rangaraju et al. [33]). ...
... This section will examine possible explanations for the results. The ability of BEVs and PHEVs to mitigate CO 2 emissions and/or air pollution was found by several authors (e.g., Fuinhas et al. [2]; Bekel and Pauliuk [31]; Del Pero et al. [10]; Peng et al. [11]; Andersson and Börjesson [16]; Plötz et al. [23]; Zhao et al. [24]; Kazemzadeh et al. [25]; Vilchez and Jochem [27]; Franzò and Nasca [29]; Petrauskienė et al. [30]; Egede et al. [32]; and Rangaraju et al. [33]; Ajanovic and Haas [34]; Burchart-Korol et al. [35]; Tagliaferri et al. [36]; and Hootman et al. [37]). According to Kazemzadeh et al. [25], the capacity of EVs (BEVs and PHEVs) to mitigate air pollution could be related to the increase in the energy efficiency of EVs that consequently reduces the consumption of electricity. ...
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The decarbonisation of the transportation sector is crucial to reducing carbon dioxide (CO2) emissions. This study analyses evidence from European countries regarding achievement of the European Commission’s goal of achieving carbon neutrality by 2050. Using panel quantile econometric techniques, the impact of battery-electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs) on CO2 emissions in twenty-nine European Union (EU) countries from 2010–2020 was researched. The results show that BEVs and PHEVs are capable of mitigating CO2 emissions. However, each type of technology has a different degree of impact, with BEVs being more suited to minimizing CO2 emissions than PHEVs. We also found a statistically significant impact of economic development (quantile regression results) and energy consumption in increasing the emissions of CO2 in the EU countries in model estimates for both BEVs and PHEVs. It should be noted that BEVs face challenges, such as the scarcity of minerals for the production of batteries and the increased demand for mineral batteries, which have significant environmental impacts. Therefore, policymakers should adopt environmentally efficient transport that uses clean energy, such as EVs, to reduce the harmful effects on public health and the environment caused by the indiscriminate use of fossil fuels.
... Auxiliary components include the vehicle's lighting, radio, navigation, and optional seat heating. These devices don't require any form of propulsion at all (Egede, P., 2015). These devices are powered by a 12 Volt battery and a traction battery. ...
... policies In order to better understand how public policy affects consumer, producer, and market development there have been a number of studies undertaken it was shown that changes in state and federal public policy were closely linked to changes in the US car industry between 2000 and 2006. Due to their apparent immediate monetary return, sales tax incentives have the biggest impact of all policy interventions (Egede, P., 2015). Sales tax incentives would be prohibitively expensive to execute and would impair the fuel economy of new conventional autos, according to Morrow et al. ...
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Electric vehicles are being promoted in a number of countries as a way to reduce greenhouse gas emissions and fossil fuel depletion. The rate of adoption of electric vehicles, on the other hand, varies per country. The study's goals were to compare factors that influence electric car uptake and to generate policy suggestions. The design of electric vehicles(EVs) is an example of a successful policy. It has been demonstrated that there is no single appropriate policy or country-specific scenario for supplying electric vehicles. Because electric vehicles are becoming more popular, a policy mix that promotes their proliferation in many countries is required. Government support for EV and charging station adoption appears to dwindle when EV and charging station designs advance beyond a certain point, maybe due to dwindling customer demand. Reduce the cost of electric car charging as well as the cost of license plate registration is one of the most essential things the many countries can do.
... 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]. ...
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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.
... Several LCA studies have been investigated to evaluate the environmental performances of EVs and ICEVs in different countries. The environmental impact in the life cycle of EVs is strongly influenced by regional electricity mix in combination with the specific conditions of their production site, different driving conditions in various geographical locations and local climate conditions [16,35]. The effect of electricity mix for more than 70 countries in the world was investigated by J. Woo et al. [16]. ...
Ethiopia’s transportation sector is currently dominated by internal combustion engine vehicles running using imported petroleum oil. Due to shortages in hard currency, a rising economy and population growth, and rapid industrialization, energy security to meet the national demand for transport is a quite severe problem. As a result, Ethiopia is strengthening its effort to look for clean alternative energy sources, such as biofuels and electricity. Ethiopia’s biofuel program relies on cane molasses-based ethanol and jatropha based biodiesel for blending into conventional petroleum fuels. In order to investigate the sustainability of Ethiopian biofuel production and use in transportation fuels in terms of their energy balance and environmental impacts, well-to-wheel (WTW) analysis was conducted. The WTW energy saving, greenhouse gas (GHG) emission reduction benefits and criteria air pollutants of blending different commonly used ratios of ethanol with gasoline, biodiesel with diesel and electricity mix (mostly (90%) from hydropower) were analysed in the Ethiopian situation. It is found that both ethanol and biodiesel production has shown net energy gain and reductions in GHG emissions which indicates sustainability and, therefore, could be good substitutes for petroleum fuels if their production pathways are properly managed and implemented. Flexible fuel vehicles (FFVs) fuelled with a blend of 85% ethanol and 15% gasoline (E85) could save 65% fossil fuels and 29% of GHG emission reductions compared to neat gasoline vehicles. Compared to neat diesel vehicles, a blend of 20% biodiesel and 80% diesel (B20) powered vehicles could save 15% fossil energy and could remove 12% of GHG emissions per kilometre driven. Hybrid electric vehicles (HEV) and plug-in hybrid electric vehicles (PHEV) with biofuels (ethanol and biodiesel), gasoline, and diesel showed higher savings of fossil fuel energy and less GHG emissions in every scenario.
... Nansai et al. [9] performed an LCA of a charging station in the production, transportation, and installation phase, but the operations and decommissioning phases were neglected from the analysis. Studies have conducted comparative LCAs of ICEVs and BEVs that considers the production, operations, and disposal stages in both of the vehicle's entire life cycle [2,3,[10][11][12][13][14]. BEVs were reported to have lower operations impact compared to ICEVs due to the absence of tailpipe emissions, lower environmental loads involving electricity generation from low carbon-intense fuel sources, higher powertrain efficiencies, and regenerative braking capabilities. ...
This paper evaluates and calculates the magnitude of greenhouse gases produced from the implementation of electric bus charging stations into existing bus depots concurrent with the transitioning of the commuter bus fleets into electrified powertrains. To achieve this, a comprehensive and in-depth emissions life cycle assessment is conducted and utilises the Australian based fleets as a case study, focusing particularly on Sydney city and Inner West regions. To define the scope and system boundary for this type of study, the authors have chosen bus routes that take into account city, suburban, and highway driving. The study conducts a life cycle assessment of electric bus charging stations that incorporates the greenhouse gas emissions produced from the production, transportation, installation, operations, and decommissioning phases. Additionally, three alternate scenarios are explored: time variance, high shares of renewables, and net-zero emissions by 2050. Results show that contributions from infrastructure development and the transition to electrified buses are substantially outweighed by operation emissions. The operations phase is heavily dependent on the electricity grid-mixes carbon intensity and contributes the most greenhouse gas emissions (98.8%), followed by production (0.69%), recycling and disposal (0.48%), installation (0.01%), and transportation (0.01%). The current Australian electricity grid-mix produces approximately 1.2 ∼ 1.4 times more greenhouse emissions than when combusting diesel fuel. Thus, net-zero emissions will not be achieved without substantial grid-mix decarbonisation. This study also finds that regional-specific parameters heavily influences the final life cycle emissions calculations. For the case-specific scenario, it is found that transitioning the existing transport bus fleet into electric powertrains has the potential to significantly reduce the impact on climate change compared to diesel buses. However, it can only be made possible if the electricity used to charge the electric buses is generated from low carbon-intensive sources, such as renewable energy.
Electric mobility is emerging all around the world to minimize environmental impacts, reduce dependency on petroleum, and diversify energy sources for transportation. Any emerging technology comes with uncertainties in terms of its environmental, economic, and social impacts on the global society, and history has shown that some technological changes have led also to great societal transformation thus shaping our future as humanity. Understanding, perceiving, and anticipating the potential changes are essential to managing as well as internalizing maximum benefits out of these technological advancements for a sustainable global community. In the literature, life cycle assessment approaches are mainly used to assess the potential environmental impacts of electric vehicles. Considering the potential impacts of emerging transportation technologies, traditional life cycle assessment is not sufficient to analyze economic and social impacts, ripple, side, or rebound effects, macro-economic impacts, and global-supply chain related impacts. In response to these knowledge gaps, traditional environmental life cycle assessment approaches are evolving into new more integrated, and broader approaches (e.g., life cycle sustainability assessment). This research aims to reveal research gaps in the sustainability assessment of electric vehicles and provide an outlook of the current state of knowledge, perspectives on research gaps, and potential ways for the adoption of integrated life-cycle modeling approaches. We conducted a comprehensive literature review focusing on sustainability assessment studies for emerging electric vehicle technologies for the period between 2009 and 2020 using the Scopus database. A total of 138 life cycle assessment studies focusing on electric and autonomous (electric) vehicles are analyzed. The reviewed studies are classified and analyzed based on sustainability indicators, life cycle approaches, life cycle phases, data sources and regions, and vehicle technology and class. We also compared the global warming potential of battery electric vehicles of different class sizes. According to the literature review, five major knowledge gaps are identified; 1) lack of socio-economic assessment, 2) lack of integrated modeling approaches and macro-level assessment; 3) limited consideration of end-of-life management and circular economy applications, 4) underrepresented developing world; 5) underrepresented emerging technologies. The findings of this review can help researchers worldwide to overview the state-of-art and state-of-practice in the field of sustainability assessment of emerging technologies and electric vehicles.
The electrification of the car fleet is an essential transformation to a meaningful reduction of greenhouse gas emissions in road transport. This has been a major goal of European transport policies, but other actions can also enhance the effectiveness of EVs to reduce emissions. In this paper we analyse four key European and German transport policies and assess how these could be improved to increase their potential to reduce emissions. Using iterative feedback from 12 interviews across various stakeholder groups, we have developed proposals for revised policies on electric vehicles. The results show that current policies in the EU and Germany are not making use of the full environmental potential of EVs, because they do not differentiate sufficiently between different EVs, and have been designed for the era of combustion vehicles. We suggest that the introduction of a new Bonus-Malus Registration Scheme and the overhaul of the existing Road Tax System are the most promising changes both in terms of their potential to reduce emissions and their likelihood of adoption.
This paper critically reviewed an overall of 76 available life cycle studies that have assessed the environmental impact of lithium-ion batteries and have also provided detailed contribution analyses and transparent inventories. A total of 55 studies were identified that investigated the four notable product life cycle phases: (1) materials and parts production, (2) cell manufacturing, (3) battery pack assembly, and (4). end-of-life decommissioning. Based on the results from the reviewed studies, the average values for global warming potential and cumulative energy demand from lithium-ion battery production were found to be 187.26 kgCO2e/kWh or 19.78 kgCO2e/kg, and 42.49 kWh/kg, respectively. This provides evidence to expose the fact that from a life cycle perspective electric vehicles are not emissions-free and contribute to climate change. An examination into the disparity in global warming potential and cumulative energy demand estimates revealed that the results were influenced by battery chemistry, active materials, production volume, regional manufacturing, and various assumptions adopted by the life cycle studies. Most studies claimed that the magnitude of end-of-life contributions to total environmental impact is relatively small and consequently omitted the end-of-life phase from their investigation. Further investigations into battery second-life applications presented the argument that repurposing lithium-ion batteries into mobility or utility applications extend their service lives and yield environmental, social, and economical benefits. Also, recycling reduces landfill waste and materials shortage. Therefore, this article recommends more research efforts and implementation of industrial practices on lithium-ion batteries decommissioning through repurposing and recycling.
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Purpose The purpose of this review article is to investigate the usefulness of different types of life cycle assessment (LCA) studies of electrified vehicles to provide robust and relevant stakeholder information. It presents synthesized conclusions based on 79 papers. Another objective is to search for explanations to divergence and “complexity” of results found by other overviewing papers in the research field, and to compile methodological learnings. The hypothesis was that such divergence could be explained by differences in goal and scope definitions of the reviewed LCA studies. Methods The review has set special attention to the goal and scope formulation of all included studies. First, completeness and clarity have been assessed in view of the ISO standard’s (ISO 2006a, b) recommendation for goal definition. Secondly, studies have been categorized based on technical and methodological scope, and searched for coherent conclusions. Results and discussion Comprehensive goal formulation according to the ISO standard (ISO 2006a, b) is absent in most reviewed studies. Few give any account of the time scope, indicating the temporal validity of results and conclusions. Furthermore, most studies focus on today’s electric vehicle technology, which is under strong development. Consequently, there is a lack of future time perspective, e.g., to advances in material processing, manufacturing of parts, and changes in electricity production. Nevertheless, robust assessment conclusions may still be identified. Most obvious is that electricity production is the main cause of environmental impact for externally chargeable vehicles. If, and only if, the charging electricity has very low emissions of fossil carbon, electric vehicles can reach their full potential in mitigating global warming. Consequently, it is surprising that almost no studies make this stipulation a main conclusion and try to convey it as a clear message to relevant stakeholders. Also, obtaining resources can be observed as a key area for future research. In mining, leakage of toxic substances from mine tailings has been highlighted. Efficient recycling, which is often assumed in LCA studies of electrified vehicles, may reduce demand for virgin resources and production energy. However, its realization remains a future challenge. Conclusions LCA studies with clearly stated purposes and time scope are key to stakeholder lessons and guidance. It is also necessary for quality assurance. LCA practitioners studying hybrid and electric vehicles are strongly recommended to provide comprehensive and clear goal and scope formulation in line with the ISO standard (ISO 2006a, b).
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The study analyses the entire life cycle of magnesium components for two exemplary transport applications. This includes the production of primary magnesium, alloying, component production, use phase and the end-of-life of magnesium components. For the use phase, examples for vehicle and aircraft components are selected to show benefits compared to aluminium. The results of the study provide up-to-date information about potentials concerning energy and emissions for the use of magnesium.
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Electric vehicles (EVs) have no tailpipe emissions, but the production of their batteries leads to environmental burdens. In order to avoid problem shifting, a life cycle perspective should be applied in the environmental assessment of traction batteries. The aim of this study was to provide a transparent inventory for a lithium-ion nickel-cobalt-manganese traction battery based on primary data and to report its cradle-to-gate impacts. The study was carried out as a process-based attributional life cycle assessment. The environmental impacts were analyzed using midpoint indicators. The global warming potential of the 26.6 kilowatt-hour (kWh), 253-kilogram battery pack was found to be 4.6 tonnes of carbon dioxide equivalents. Regardless of impact category, the production impacts of the battery were caused mainly by the production chains of battery cell manufacture, positive electrode paste, and negative current collector. The robustness of the study was tested through sensitivity analysis, and results were compared with preceding studies. Sensitivity analysis indicated that the most effective approach to reducing climate change emissions would be to produce the battery cells with electricity from a cleaner energy mix. On a per-kWh basis, cradle-to-gate greenhouse gas emissions of the battery were within the range of those reported in preceding studies. Contribution and structural path analysis allowed for identification of the most impact-intensive processes and value chains. This article provides an inventory based mainly on primary data, which can easily be adapted to subsequent EV studies, and offers an improved understanding of environmental burdens pertaining to lithium-ion traction batteries.
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Electric vehicles (EVs) coupled with low‐carbon electricity sources offer the potential for reducing greenhouse gas emissions and exposure to tailpipe emissions from personal transportation. In considering these benefits, it is important to address concerns of problem‐shifting. In addition, while many studies have focused on the use phase in comparing transportation options, vehicle production is also significant when comparing conventional and EVs. We develop and provide a transparent life cycle inventory of conventional and electric vehicles and apply our inventory to assess conventional and EVs over a range of impact categories. We find that EVs powered by the present European electricity mix offer a 10% to 24% decrease in global warming potential (GWP) relative to conventional diesel or gasoline vehicles assuming lifetimes of 150,000 km. However, EVs exhibit the potential for significant increases in human toxicity, freshwater eco‐toxicity, freshwater eutrophication, and metal depletion impacts, largely emanating from the vehicle supply chain. Results are sensitive to assumptions regarding electricity source, use phase energy consumption, vehicle lifetime, and battery replacement schedules. Because production impacts are more significant for EVs than conventional vehicles, assuming a vehicle lifetime of 200,000 km exaggerates the GWP benefits of EVs to 27% to 29% relative to gasoline vehicles or 17% to 20% relative to diesel. An assumption of 100,000 km decreases the benefit of EVs to 9% to 14% with respect to gasoline vehicles and results in impacts indistinguishable from those of a diesel vehicle. Improving the environmental profile of EVs requires engagement around reducing vehicle production supply chain impacts and promoting clean electricity sources in decision making regarding electricity infrastructure.
Die Automobilindustrie befindet sich in einem tiefgreifenden Wandel. Mit der Elektromobilität verändern sich bisherige Fahrzeug- und Antriebskonzepte grundlegend – und damit auch der gesamte Wertschöpfungsprozess. Das Buch liefert einen umfassenden Überblick über die Herausforderungen und die Lösungen zu allen Aspekten der Elektromobilität: von der Produktentwicklung über die Produktion von Elektrofahrzeugen mit Hinweisen für die Konstruktion des Antriebsstrangs bis hin zum Aufbau einer Infrastruktur und zu Geschäftsmodellen. Für die zweite Auflage wurden sämtliche Inhalte auf den aktuellen Stand der technologischen Entwicklung gebracht. Das Thema Batterieproduktion wurde ebenso erweitert wie die damit verknüpfte Frage des Remanufacturings als Teil des Recycling-Kreislaufes. Das Buch gliedert sich in fünf Kapitel. Im Grundlagenkapitel werden die Herausforderungen der Elektromobilität beschrieben und die Ansätze für eine integrierte Produkt-, Prozess- und Infrastrukturentwicklung skizziert. Darüber hinaus bietet es umfassende Einblicke in die Montage von Elektrofahrzeugen. In den folgenden Kapiteln werden Konzepte für den Städtebau und für den Aufbau eines Servicenetzes vorgestellt sowie Geschäftsmodelle, ihre Entwicklung und Rechtsgrundlagen erläutert. Im Kapitel Fahrzeugkonzeption geht es um den Prozess der Industrialisierung und Fragen der Batterieproduktion. Die Entwicklung von elektrofahrzeugspezifischen Komponenten wie der des Antriebsstrangs wird im abschließenden Kapitel „Entwicklung von elektrofahrzeugspezifischen Systemen“ beschrieben. Die Herausgeber Prof. Dr.-Ing. Achim Kampker ist seit April 2009 Universitätsprofessor für das Fach Produktionsmanagement in der Fakultät für Maschinenwesen der RWTH. Von 2009 bis 2013 leitete er den Lehrstuhl für Produktionsmanagement am Werkzeugmaschinenlabor WZL. Seit Januar 2014 ist er Leiter des neu gegründeten Lehrstuhls Production Engineering of E-Mobility Components (PEM). Prof. Dr.-Ing. Dirk Vallée war seit 2008 Lehrstuhlinhaber und Institutsdirektor am Institut für Stadtbauwesen und Stadtverkehr der RWTH Aachen University. Zudem war er von 1995 bis 2002 Referent für die Verkehrsplanung und Projektleiter S-Bahn-Erweiterung beim Verband Region Stuttgart und arbeitete anschließend bis 2008 als leitender technischen Direktor beim Verband Region Stuttgart. Im Jahr 2017 ist Prof. Dr.-Ing. Dirk Vallée verstorben. Prof. Dr.-Ing. Armin Schnettler ist seit 2001 Institutsleiter des Instituts Hochspannungstechnik der RWTH Aachen University. Von 2003 bis 2013 war er Vorstand der Forschungsgemeinschaft für Elektrische Anlagen und Stromwirtschaft e.V. Zudem ist Prof. Dr.-Ing. Armin Schnettler Herausgeber des „Archiv für Elektrotechnik – Electrical Engineering“, Springer Verlag, Heidelberg.
Advanced lightweight materials are increasingly being incorporated into new vehicle designs by automakers to enhance performance and assist in complying with increasing requirements of corporate average fuel economy standards. To assess the primary energy and carbon dioxide equivalent (CO2e) implications of vehicle designs utilizing these materials, this study examines the potential life cycle impacts of two lightweight material alternative vehicle designs, i.e., steel and aluminum of a typical passenger vehicle operated today in North America. LCA for three common alternative lightweight vehicle designs are evaluated: current production ("Baseline"), an advanced high strength steel and aluminum design ("LWSV"), and an aluminum-intensive design (AIV). This study focuses on body-in-white and closures since these are the largest automotive systems by weight accounting for approximately 40% of total curb weight of a typical passenger vehicle. Secondary mass savings resulting from body lightweighting are considered for the vehicles' engine, driveline and suspension. A "cradle-to-cradle" life cycle assessment (LCA) was conducted for these three vehicle material alternatives. LCA methodology for this study included material production, mill semi-fabrication, vehicle use phase operation, and end-of-life recycling. This study followed international standards ISO 14040:2006 [1] and ISO 14044:2006 [2], consistent with the automotive LCA guidance document currently being developed [3]. Vehicle use phase mass reduction was found to account for over 90% of total vehicle life cycle energy and CO2e emissions. The AIV design achieved mass reduction of 25% (versus baseline) resulting in reductions in total life cycle primary energy consumption by 20% and CO2e emissions by 17%. Overall, the AIV design showed the best breakeven vehicle mileage from both primary energy consumption and climate change perspectives.
Battery electric vehicles Plug-in hybrid electric vehicles Life-cycle assessment Greenhouse gas emissions Well-to-wheel balances Total costs of ownership a b s t r a c t This paper presents an environmental and an economic Life-Cycle Assessment (LCA) for conventional and electric vehicle technologies, focusing mainly on the primary energy source and the vehicle operation phase Greenhouse Gas (GHG) emissions. A detailed analysis of the electricity mix was performed, based on the contribution of each type of primary energy source and their variation along a year. Three mixes were considered, with different life cycle GHG intensity: one mainly based in fossil sources, a second one with a large contribution from nuclear and a third one with a significant share of renewable energy sources. The conventional vehicle technology is represented by gasoline and diesel International Combustion Engine Vehicles (ICEVs), while the electric technology is represented by Plug-in Hybrid Electric Vehicles (PHEVs) and Battery Electric Vehicles (BEVs). Real world tests were performed for representative compact and sub-compact EVs. The use profile of the vehicle was based on data acquired by a real time data acquisition system installed in the vehicles. The results show that a mix with a large contribution from Renewable Energy Sources (RESs) does not always translate directly into low GHG emissions for EVs due to the high variability of these sources. The driving profile under different scenarios was also analyzed, showing that an aggressive style can increase the energy consumption by 47%. The tests also showed that the use of climate control can increase the energy consumption between 24 and 60%. Compared with other technologies, EVs can be more sustainable from an environmental and economic perspective; however, three main factors are required: improvement of battery technology, an eco-driving attitude and an environmental friendly electricity mix.
Life-cycle assessment is basically the assessment of a product from the cradle to the grave. Ideally, a product is recycled after its useful life is complete and the end-of-life of the first life cycle leads to the beginning of a new product system. For the end-of-life of magnesium vehicle parts, there are various possible paths to a second life cycle. When magnesium parts are dismantled or magnesium is separated after shredding, the resulting magnesium alloys can be used for secondary, noncritical applications. However, the typical case for magnesium components is that the magnesium postconsumer scrap ends up in the nonferrous metals fraction that consists primarily of aluminum, magnesium, and heavy metals. Today, aluminum is typically fed into a second life cycle as a secondary alloy, and magnesium becomes part of the aluminum cycle as an alloy addition. In this article, we evaluate the environmental effects of using magnesium in the aluminum cycle. We also assess the influence of end-of-life scenarios on the overall environmental impact of a component's life cycle. The primary focus of our analysis is the evaluation of the effects of magnesium vehicle components on greenhouse gas emissions.
This study reviews existing life-cycle inventory (LCI) results for cradle-to-gate (ctg) environmental assessments of lead-acid (PbA), nickel–cadmium (NiCd), nickel-metal hydride (NiMH), sodium-sulfur (Na/S), and lithium-ion (Li-ion) batteries. LCI data are evaluated for the two stages of cradle-to-gate performance: battery material production and component fabrication and assembly into purchase ready batteries. Using existing production data on battery constituent materials, overall battery material production values were calculated and contrasted with published values for the five battery technologies. The comparison reveals a more prevalent absence of material production data for lithium ion batteries, though such data are also missing or dated for a few important constituent materials in nickel metal hydride, nickel cadmium, and sodium sulfur batteries (mischmetal hydrides, cadmium, β-alumina). Despite the overall availability of material production data for lead acid batteries, updated results for lead and lead peroxide are also needed. On the other hand, LCI data for the commodity materials common to most batteries (steel, aluminum, plastics) are up to date and of high quality, though there is a need for comparable quality data for copper. Further, there is an almost total absence of published LCI data on recycled battery materials, an unfortunate state of affairs given the potential benefit of battery recycling. Although battery manufacturing processes have occasionally been well described, detailed quantitative information on energy and material flows are missing. For each battery, a comparison of battery material production with its manufacturing and assembly counterpart is discussed. Combustion and process emissions for battery production have also been included in our assessment. In cases where emissions were not reported in the original literature, we estimated them using fuels data if reported. Whether on a per kilogram or per watt-hour capacity basis, lead-acid batteries have the lowest cradle-to-gate production energy, and fewest carbon dioxide and criteria pollutant emissions. The other batteries have higher values in all three categories.