Market Evolution Scenarios For Electric Vehicles. Summary
F R A U N H O F E R I N S T I T U T E F O R S Y S T E M S A N D I N N O VAT I O N R E S E A R C H I S IMARKET EVOLUTION SCENARIOS FOR ELECTRIC VEHICLESSUMMARYM A R T I N W I E T S C H E L , PAT R I C K P L Ö T Z , A N D R É K Ü H N A N D T I L L G N A N N
DisclaimerThis study was commissioned by acatech – German NationalAcademy of Science and Engineering and Working Group 7(AG 7) of the German National Platform for Electric Mobility(NPE). The assumptions, methodology, results and conclusionswere discussed extensively with representatives of WorkingGroup 7 and the NPE. The Fraunhofer ISI is solely responsiblefor the contents of the study. The study does not reflect theopinion of acatech or the NPE.ContactProfessor Martin WietschelFraunhofer Institute for Systems and Innovation Research ISIBreslauer Strasse 4876139 KarlsruheGermanye-mail: martin.wietschel@isi.fraunhofer.deTelephone: 49 (0) 721 6809 254
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CONTENTS1EXECUTIVE SUMMARY 42INTRODUCTION 73 METHODOLOGY, SCENARIOS AND IMPORTANT INPUT DATA 4RESULTS 9145 DISCUSSION AND CONCLUSIONS 25628REFERENCES
1EXECUTIVE SUMMARYWhat share of the market are electric vehicles (EVs) expected to have in Germany by 2020? Thiswas the question tackled by this study. The economic potential for electric cars was ascertainedby considering several thousand real-life driving profiles of conventional cars, as well as technical and economic data for different scenarios. Factors which can hinder the diffusion of electriccars, their restricted driving range, for example, or the limited range of models, are integrated asare supporting factors in the form of the willingness to pay more for an innovative technology.The main results of the study are: There is a great deal of uncertainty surrounding the market evolution of EVs because thisdepends heavily on external framework conditions such as price developments for batteries, crude oil and electricity. Under favorable conditions for electric cars, the joint target of the German governmentand the German National Platform for Electric Mobility (NPE) of one million electric cars by2020 can be reached without monetary support for the purchase of EVs. Even under less favorable conditions, a significant number of electric cars should be ableto enter the market by 2020 (about 150,000 to 200,000 in the total stock of cars). High electric driving shares (of more than 80 %) and simultaneously high annual mileages(more than 15,000 km) are essential prerequisites for electric cars to be economical. Asignificant share of driving profiles meets these premises. Vehicles with range extenders and plug-in hybrids will probably be able to reach largermarket shares than battery electric cars in the near future (approx. three quarters). Gasoline-fuelled cars will continue to dominate at low annual mileages in the future under cost-effectiveness aspects, and diesel cars at very high annual mileages. The private sector is a relevant market for electric cars. Especially full-time workers fromrural areas and small to medium-sized towns or the suburbs of larger cities show highpotentials for the switch to electric cars. These make up about one third of private carowners.4 5
The switch offers more economically to drivers with their own garage (approx. 60 % ofprivate car owners) or with private parking at home, than to so-called “on-street parkers”,because charging infrastructure costs strongly influence the economics. Moreover, thetotal number of on-street parkers is comparatively small compared to those with garagesor private parking at home (depending on the definition, between 3 and 20 %). Purely commercial fleets, which make up around 30 % of the market for new cars, showinteresting economic potential. This is due to their driving profiles which often featurepredictable routes, the specific economic framework conditions applying to commercialfleets such as the elimination of VAT with its positive impact, especially at the higher purchase prices of electric vehicles, and the high relevance of economic efficiency considerations in car purchasing decisions here. Different policy measures such as the introduction of special depreciation options, aflatrate subsidy or offering low interest loans could accelerate the market success of EVs.Significant market growth can be achieved in commercial fleets with comparatively modest financial support. Special depreciation allowances seem the most appropriate instrument here. However, a comprehensive evaluation of policy measures requires the analysisof macroeconomic effects, too. These are not taken into account in this study. So far, there are not many publicly available empirical data or studies on the group ofcompany car users, which makes up a relevant share of approximately 30 % of the newcar market and is particularly important for the large car segment. Not much research hasbeen done on how purchasing decisions are made here. This tends to be a complex process, because it has to balance the interests of both the companies and the car users. Thepotential to switch to EVs is probably limited here for purely economic reasons becauseusers have partially unfavorable driving profiles often characterized by long distances andindividual routes. More research is required on the company car sector. There are relevant uncertainties attached to the scenario analyses concerning the assumptions about the willingness to pay more for electric vehicles and the willingness toswitch to electrically-powered vehicles despite the currently still limited range of availablemodels. Both aspects have a strong influence on how the market develops. The drawbackof the limited model range will be offset to some extent in the next few months sinceGerman car makers have announced plans to introduce a wider variety of models(16 models until the end of 2014).www.isi.fraunhofer.de
2INTRODUCTIONElectric vehicles (EV) have been identified as key elements of sustainable transport in Germany’sNational Development Plan for Electric Mobility. An increasing shift towards electrically-poweredcars offers the chance to reduce the dependency of Germany on oil imports, minimize bothglobal (CO2) and local (pollutants, noise) emissions, contribute to conserving resources and further develop a multimodal transport system.1 Germany’s goal is to become an international leadsupplier and lead market for electric vehicles in order to retain its leading role in the automobileand automotive supplier industries as well as in the sciences. As a first milestone, the Germangovernment and the German National Platform for Electric Mobility 2 are striving to get one million electric cars onto Germany’s roads by 2020. However, the government can only implementtargeted and effective support measures if they can build on a well-founded understanding ofthe possible market evolution of electric vehicles. Here, it is important to develop empiricallyreliable models of the market evolution.Building on the previous work of the German National Platform for Electric Mobility (NPE), theoverall objective of this research project is therefore to develop a model to calculate the totalcosts of ownership of electric vehicles in a transparent way. In addition, different obstructivefactors (for example charging infrastructure availability or the insufficient range of models) andsupportive factors (for instance the willingness to pay more for an innovative and environmentallyfriendly vehicle) are considered and different market success scenarios are developed for electricvehicles up to 2020. The scenarios also illustrate several possibilities for how important influencing parameters could develop, including battery and crude oil prices and how these impact thediffusion of EVs. We also analyze the effect of different policy measures on market evolution.The next chapter outlines the methodology and the model used. The three scenarios are described, and the sensitivity analyses and important model input parameters explained. This isfollowed by a presentation of the results and their subsequent discussion and then conclusionsare derived. A detailed documentation presenting all the calculations, input data and equationsis given in the long version of this report, which is only available in German “Markthochlaufszenarien für Elektrofahrzeuge – Langfassung”.3123www.isi.fraunhofer.decf. Bundesregierung 2009.cf. NPE 2010.Plötz et al. 2013.
Important factors for the decision to buy a carCriterion ranked first in the decision process50%Vehicle SizeSmall40%Share of answersMedium30%Large20%Included in the model:— Vehicle size— Purchase price— Brand— Fuel consumption— Fuel type— Emission gwasdawpoivnedrgiFoAssumed to be of equalvalue:— Safety— Design— ripertur-wFuTreff eseKichlefauPuscVehBegicsizeunleigunpr0%d10%Not included:— Gear shift— Engine power— Four wheel drive4Figure 3–1: Important factors in private consumers’ vehicle purchase decision and their consideration in the ALADIN modelMarketevolutionExtensionscustomer behaviorTCO-modelDriving profilesCa. 6,500 for private,fleets & company carsVehicle dataCalculation in TCO basic model Techno-economicparameters, pricesCharginginfrastructureSimulation electric driving sharesSimulation technical substitutabilityIndividual TCO Market dataAnalysis of planned modelsCustomer behaviorResults of purchase &acceptance researchMarket dataNewly registered vehiclesper segment and group,scrapped carsIndividual TCO of all drive trainsInfrastructure & customer behaviorScenarios of costs,availability & capacityon/offLimited availability of EVon/offCustomers‘ willingness to pay moreon/offAggregation and market evolution Extrapolation of the EV shares of drivingprofiles in newly registered vehiclesStock model Market evolution of EVFigure 3–2: Overview of the approach taken in the ALADIN model8 93 options:Costs charging infrastuctureEV shares of driving profiles Basic model:TCO calculation 23 8 variantsResult:TCO calculation– Infrastucture costs– Limited availability Willingness to pay more
3 METHODOLOGY, SCENARIOS ANDIMPORTANT INPUT DATA3.1METHODOLOGYIn a first step, therefore, the costs of total use, referred toas TCO (Total Cost of Ownership), are ascertained for electricThis section describes the methodology for calculating the mar5and conventional vehicles in Germany. The TCO comprise theket evolution of electric vehicles. The simulation model ALADINpurchasing and running costs for the respective vehicle and(Alternative Automobiles Diffusion and Infrastructure) is theare calculated from the user’s perspective. Table 3–1 shows a6key element here. The evolution of the market is calculatedsummary of the economic variables included. Three user groupssuccessively based on a comparison of the economic efficiencyare distinguished – private, commercial (only fleet vehicles) andof different drive systems and taking obstructive and supportivecompany cars – because of their different rates of taxation andfactors into account for approximately 6,500 driving profiles.depreciation options as well as their deviating patterns of utiliza-One driving profile covers all the trips made by one vehicle in attion. Because the TCO are also strongly influenced by the sizeleast one representative week. The successive approach allowsof the vehicle, different car segments are also distinguished.the effects of individual influencing factors on market evolutionTable 3–2 shows the distribution of newly registered cars byto be plotted separately and thus makes it more transparent.user group and segment.Figure 3–1 gives an overview of the most important factorsThe drive technologies analyzed included battery electric ve-which play a role in the decisions of private consumers whenhicles (BEV), range-extended vehicles (REEV) and plug-in hybridsbuying a vehicle and which of them are considered in the model.(PHEV)10 as EVs as well as conventional gasoline and dieselFigure 3–2 shows the general approach taken in the ALADINcars. For the TCO calculations, the cheapest respective drivemodel.technology was selected.The costs of buying and using a vehicle obviously play an important role for potential buyers when making a purchasingdecision.7 In commercial fleets, the economic aspects are evenmore important.8 Compared to conventional cars, electric carsare generally more expensive to purchase, but they are oftencheaper to run on account of lower fuel and maintenance costs,among other things. It is therefore essential to look at costs interms of the total costs of use, in order to determine for whichutilization or driving profiles electric cars are more economicalthan conventional ones. Total cost calculations for vehicles arecorrespondingly a common component of models of the marketpenetration of electric vehicles.9456789Own assessment based on Peters and de Haan 2006.Detailed documentation is found in the full report (Plötz et al. 2013).Although the ALADIN model has not yet been published in its entirety,individual databases and calculations for certain owner groups havebeen published several times (see among others Wietschel et al. 2012,Gnann et al. 2012a and 2012b, Plötz et al. 2012, Dütschke et al. 2012,Kley 2011).See e. g. Peters et al. 2011 for private owners and Dataforce 2011for commercial owners.See Öko-Institut 2011a and Dataforce 2011.See Fraunhofer ISI 2012; ESMT 2011; Kley 2011; McKinsey 2011; NPEwww.isi.fraunhofer.de2011a, 2011b; Plötz et al. 2012; Wietschel et al. 2009 and 2011;Schmid 2012; Mock 2010, among others.10 If the option to power the vehicle directly using the combustion engineis realized in hybrid vehicle concepts, these are called Plug-in HybridElectric Vehicles (PHEV). Range-extended electric vehicles (REEV) havea combustion engine in addition to the battery with a generator toextend the driving range. This provides additional power for the battery, but does not directly power the vehicle.
Table 3–1: Economic variables considered in the ALADIN modelParameterPrivateCommercialCompany carsPurchase price Discounting of future costs Residual value at the end of the ownership period Fuel prices (gasoline, diesel, electricity) Repair and maintenance costs VAT Vehicle taxTaxation of benefit in kind11 Willingness to pay moredepending on variantCharging infrastructure costsdepending on variantTable 3–2: Analyzed combinations of user group and car segmentSegmentPrivateCommercialCompany carsSmall Medium Large Light-duty commercial vehiclesOne of the key innovations compared to previous TCO analysesespecially relevant for PHEV and REEV. The first step is to makeis that the calculations are not made based on average annualTCO calculations on this basis.mileages but are instead based on real-life driving profiles.12In the second step, the TCO calculations are extended by includA driving profile covers all the trips including the purpose,ing the costs of the main charging infrastructure. This is donelength of route, departure and arrival time, duration as wellin order to put the assessment of the economic efficiency inas information about the vehicle over an observation periodthe TCO calculations on a broader basis. Charging infrastruc-of at least one week. Profiles vary widely by user even withinture costs vary widely depending on the charging type andthe different groups and have a very strong influence on thelocation. For instance, using private charging infrastructure iseconomic efficiency of electric vehicles. The barrier presentedgenerally cheaper for drivers with a garage than the use ofby BEV’s limited range is explicitly considered in the analyses.public charging infrastructure on which on-street parkers haveEach individual driving profile is analyzed according to whetherto rely.13 Because the methodology is a simulation which doesthe driver is able to make all the trips with a BEV. In addition,not represent spatial modeling but only trip purposes (such asthe electric driving share of plug-in hybrids or range-extendedfor example “going home”, “going to work”, “going shop-electric vehicles is simulated individually for each driving profile.ping”), statements about the infrastructure are only possibleThis is important to obtain realistic results for the economic ef-to a limited extent. The infrastructure assumption made is theficiency, which depends on the share of electric driving and issame for all users in the respective user group. Depending onthe scenario, car users are provided with a different amount of11 The scenarios were based on calculations using the former regulation with taxation of benefits in kind for company cars. Towards theend of the project, this regulation was altered and EVs were placedon a better footing tax-wise, but this could no longer be taken intoaccount in the calculations made here. But the current legal status isconsidered in the calculations for the policy measures (chapter 4.5).12 The driving profiles used are described in the detailed report (Plötz etal. 2013).10 11charging infrastructure (for example, only charging at home forprivate users and only charging at work for commercial users).In terms of costs, however, only the primary charging point(e.g. the private wall box of garage owners) is classified.13 See Gnann et al. 2013 and Kley 2011.
The brand and size of a vehicle are also important factors in14costs of company cars. The drivers therefore do not necessar-fluencing the decision to buy. For instance, many buyers areily profit from low costs in this area. Furthermore, company-extremely loyal to a particular brand or, conversely, would notinternal stipulations play a role. The details can vary widely, buteven consider buying other brands. There will continue to be athey probably have a large influence on the selection of therestricted range of models and brands of electric vehicles avail-vehicle (e. g. exclusive contracts with specific manufacturers,able in the near future, which represents a limiting factor forleasing contracts). A company’s policy concerning its publicthe market evolution of electric vehicles. The restricted choiceimage and environmental performance can also influence theand availability of brands are therefore taken into account inprovision of vehicles. For this reason, it is necessary to take allthe model. This is done by analyzing currently offered models ofthe stakeholders’ considerations into account: the company’selectric vehicles and the announcements made about plannedmanagement, its fleet administrator and its drivers. There arenew ones. Logistic growth in the number of available makesno comprehensive publicly accessible surveys available of thesewith BEV drives or REEV/PHEV is then determined on this basiscomplex decision processes and there is the corresponding needusing ordinary least squares regression. It is also assumed thatfor further research here. It was therefore not possible to includesome buyers decide in favor of an EV of a different brand (ifthe willingness to pay more for company car users.an EV has ideal TCO) and the rest for a conventional vehicle ofthe original brand.The existing studies in the commercial transport sector showthat some commercial users definitely have the willingness toThe most important factors obstructing the market diffusionpay more, but that this is still lower overall in comparison toof electric vehicles are taken into account with the economicprivate users.19 A willingness to pay more for commercial usersefficiency, range anxiety and the limited offer of electric vehicles.is included based on the results of Dataforce 2011.The fourth and final step then integrates other aspects of electricvehicles which tend to support th
This study was commissioned by acatech – German National Academy of Science and Engineering and Working Group 7 (AG 7) of the German National Platform for Electric Mobility (NPE). The assumptions, methodology, results and conclusions were discussed extensively with representatives of Working Group 7 and the NPE. The Fraunhofer ISI is solely responsible for the contents of the study. The .
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