KOTI - Korea Transport institute

Introduction
Since 2005, Korea has been pursuing EV policy and running various pilot projects to find appropriate measures to increase EV stocks. In 2010, Korea set its target volume for EVs and charging infrastructure on roads as 200 thousand units by 2020. Since the announcement for target volume of EV deployment, Korean central and local governments have started to appropriate funds to support R&Ds for vehicle and battery technologies and to deploy EVs and charging infrastructure. In pursuant to EV policies, Korea launched a five year pilot project for Smart Grids test bed at Jeju Island that included renewable energy technologies, ICT, energy grids, and smart transportation (a.k.a. Electric Vehicles).
In addition to such a grand pilot project, local governments of major large cities are pursuing EV pilot projects. Especially, Seoul has been supporting new mode of EVs in public transport including EV Car-sharing, BEV buses, OLEV, and EV taxis. Also, Seoul has been supporting EVs for logistics including small motorbikes for food delivery and EV truck development.
Jeju municipal government has been focusing on deploying EVs for tourists such as EV taxis and for private users. Furthermore, Jeju is pursuing a policy to utilize renewable energy including wind power thanks to its climate condition and set up a test bed at a small Island, Gapa-do, for testing the system connection between wind power generation grid and EVs.
Even though such various efforts were made to stimulate EV deployment, the results have not been returned yet. Rather than success, Korea is still situated in the initial stage of EV deployment and challenged by various barriers.
The most important barrier is the consumers’ perception on EVs and their technical limitation in terms of driving ranges as well as uncompetitive price scheme compared to ICE vehicles. While EVs are superior to ICE in the environmental aspect by emitting zero pollutants, consumers are tend to choose ICE over EVs for price competitiveness. In other words, economic incentives win over moralities.
Actually, when considering average trip distance per day for urban resident which is about 43km on average for seven mega cities in Korea in 2012, currently available EVs in the market could meet their daily transport needs. However, consumer’s perception on driving range is relatively negative and exacerbated by huge price difference between the two types of vehicles.
Several surveys have been done to examine preferred driving ranges for EV users and the most preferred ranges are from 200㎞ to 437㎞ in European countries (Bunzeck et al., 2011, VDE, 2010, Bronchard et al., 2011). However, actual average trip distance per day for Germany is less than 100㎞ (Bunzecket et al., 2011). Also, in a survey done for Seoul, average trip distance per day showed 37.3㎞ while one of their most concerns for purchasing an EV was the short driving range per charge.
The difference between preferred driving range for EVs and actual average trip distance is called EV Range Paradox. Several researches done to understand the EV Range paradox and some of the research results showed that the driver’s perceptions on range paradox have been shorten as their EV experiences increased. (Franke et al., 2013, 2014) Furthermore, their recharging strategies become stable, as their EV experiences increased (Franke et al., 2013).
However, such researches were focused on drivers’ behavior adapting to the new environment in which they drove EVs and could not explain how far their behaviors were deviated after experiencing EVs compared to driving ICEs. Therefore, a research question arises how far the drivers’ transport behavior deviated after experiencing EVs.
Over a series of surveys and GPS tracking experiments for residents in Jeju Island in Korea, this research tries to observe the degrees of deviation for driver’s opinion and travel behaviors after experiencing EVs.
Prior to plunging into explaining surveys and experiments, this research overviewed current status of EVs and charging infra development in other countries to select a few model countries for case studies. For comparison of current numbers of deployed EVs, numbers of EV developers, dependency on fossil fuels for transport, and degrees of government determination, four countries are selected including Germany, French, Norway, and Netherlands. Then it compares governing structures for deploying EVs and provisions of policy measures and incentives for stimulating EV deployment for each country to draw some implications.
Therefore, this research is composed of two parts. The first part discusses current status of EV deployment in European countries and their policy measures. The second part discusses surveys and experiments done in Korea. Lastly, it concludes with suggestions for further researches and policy recommendations.
Current Status of EV Deployment and Policy Framework in Europe
Selection Criteria for Case Study
To select model countries for case study, this research first looked at the number of vehicles on roads for European countries including Germany, France, Norway, Netherlands, Denmark, UK, Sweden, and Portugal. Comparing rates of EVs on roads out of total number of registered vehicles, Norway has the highest rates and Netherlands the next. Germany has the lowest rates among the European countries we looked into.
However, Germany is known for a country that rigorously pursues EV development and deployment policies and the volume of CO2 emission explains the rationale behind it. Looking into CO2 volume emitted from households for transport activities, Germany ranked the first and France ranked the second.
Furthermore, Germany and France have automobile developers who take large share of world automobile market and they seem preparing for the future automobile market that is expected to be dominated by EVs. Therefore, to foster competitiveness in EV market, automobile companies are taking their part by investing in EV development and by participating in experiments in collaboration with their own governments as well as with other countries.
Looking at the number of EV developers that are in operation, Germany has four EV developers and France has three. Norway has an EV manufacture and produced some of small EVs, however, the company is not in business in 2014.
Another factor to consider is how strong the governments’ determinations on deploying EVs and it could be reflected in the government budgets for EV policies. Comparing monetary incentives including tax benefits per EV purchase, Netherlands and Norway provide higher incentives compared to other countries among European countries. Higher monetary incentives could be a clue for explaining higher rate of EV stocks on roads in Norway and Netherlands, even though they do not have competitive EV manufactures.
In summary, for selecting model countries, the rate of EV stocks, volume of CO2 emission, government budget, and number of EV developer were compared. The rate of EV stocks over ICE vehicle is the most important factor to look at and Norway and Netherlands showed higher rates. Another factor is volume of CO2 emitted from transport activities that could be a crucial incentive for governments to pursue EV policies and Germany and France have higher volumes compared to other countries. Furthermore, appropriated government budget to pursue EV policies can be considered as a factor showing governments’ determination on EV policy and Norway and Netherlands provide higher incentives per each EV purchase. Lastly, number of automobile manufacture is a factor to look at since collaboration between the government and these private manufactures could enhance EV deployment. Among the interested European countries, Germany and France have competitive EV manufactures and, currently, actively cooperating with their governments and with other countries.
Considering above mentioned factors, this research selected Germany and France that have competitive EV manufactures and Norway and Netherlands who do not have competitive EV manufactures while advancing in EV deployment.
Summaries of Policy Frameworks for Model Countries
Basically, governing structures for model countries are similar in a way that central or federal government does the role of a decision maker. For planning, they formed a designated public organization that coordinates activities among central and local governments, privates in EV related industries, other related public organizations, and research and development institutes.
In collaboration with involved organizations, implementation plans were formed for each country and local governments are taking their roles as executers for the plans.
Germany and France
As explained above, Germany and France have EV developers and they are taking their role in developing EVs and creating new EV business models.
In France, the notable organization that acts as a coordinator for pursuing EV development is Electric Vehicle Conference composed of vehicle developers, postal services, electricity providers, national railway organizations, highway management organizations, and local municipals including city of Paris.
Also, city of Paris developed “National Plan for Developing Environment Friendly Vehicles” in 2009 and aimed to stimulate automobile industry and employment that would induce economic benefits of 15 billion Euros by 2030. The plan included EV car-sharing program that EV developers were collaborating with governments to deploy EV car-sharing business. Therefore it became an iconic business model for EV deployment that most other countries are considering it as a benchmark.
For economic incentives, French government supported EV technology development for supply side and provide tax incentives for demand side. The bonus/malus is a tax incentive that providing bonus if one possesses a vehicle with lower GHG emission while penalize if he possesses a vehicle with higher GHG emission compared to a certain level. Beside tax incentives, monetary incentives are provided to increase EV purchase as well.
In Germany, the acting coordinator for EV development and deployment is National e-mobility platform and planned “National E-mobility Development Plan” in 2009. The goal of the plan is to deploy one million EVs by 2020 and replace most of currently dominant vehicles with non-fossil fuel vehicles by 2050. The plan became the basis for supporting EV technologies and each government involved in the project has clear boundaries for their roles. The platform also coordinates connections of federal and local government bodies with private organizations, research and development institutes, industry cooperation organizations, and the consumer groups.
For supply side, governments are planned to provide technology development grants from Grids to vehicles. Also, EV developers are aggressively involved in a grand pilot project for improving EV technologies by reflecting EV user’s needs through behavioral researches. For demand sides, Germany government is providing monetary incentives including tax exemption for a certain period of time and reformed vehicle tax systems favorable to vehicles with emitting less GHG.
Netherlands and Norway
Even though Netherlands and Norway do not have EV manufactures, they do outperform in deploying EVs. One of their major strategies for deploying EVs is providing higher incentives for EV purchasers including monetary subsidies and tax exemptions. For both countries, they also reformed vehicle tax systems that are favorable for those who possess EVs and low GHG emission vehicles.
Also, they provide exemptions for EV users from regulations on roads and vehicles including permission for EVs to run on Bus Exclusive Lanes in Norway, free parking while recharging batteries, exemption on toll fees, and etc.
The notable coordination actor in Netherlands is Formula E-team that monitors EV development policies by collaborating with central government to execute policy measures and by monitoring local governments for their performance in delivering EV policy measures as well.
Also, Netherlands planned “Action Program: 2009 – 2011” projecting long-term goals for reduction in GHG emission, deployment stock of EVs and charging infrastructure, development of charging technology, standardization, and developing business models.
For Norway, the notable coordinating organization is Transnova that is under the Ministry of Transport and their main activities are focused on implementing pilot projects. With the support of Transnova, Norway is executing several EV related projects including “The Project Green Car”, “Electric Mobility Norway”, ERANET, and other pilot projects. Norway is planning to deploy 200,000 EVs by 2020 through these projects.
Implications and Comparisons with Korea
The governing framework in Korea seems similar to those of model countries as central government taking the role of decision maker and local government taking the role of executer of policy measures. Furthermore, Green Growth Committee under the prime minister’s office is taking the role as the coordinator as well. However, their bonds as a collaborative partner do not seem strong enough to leverage positive effects from the collaboration.
Also, Korea has own automobile companies that develop EVs. However, compared to other manufactures in other countries, their EV related activities seem relatively passive. Taking their role in research development and participating in pilot projects will be mutually beneficial for all parties in EV related industries. EV manufactures could create new business models and learn consumers’ needs for EVs and consumers will have more options to choose. Furthermore, experiences in creating new business models in Korean market would enhance their competitiveness in overseas markets as well.
Furthermore, Korea government is financially supporting EV policies and granting subsidies for EV purchases. Current stage of Korea’s EV deployment is considered the initial stage and more subsidy funds will be required to pursue EV deployment. Therefore, budget constraint to support EV policy is expected in the near future. To ease such constraints, government should relax regulations to invite private sector investors to create new EV businesses for benefiting all parties in EV market.
Behavioral Analysis on e-Mobility in Korea
Purpose of Surveys and Experiments
The purpose of this study is to observe how far drivers’ opinions on EVs and travel behaviors change as their commitment to Electric Vehicle (EV) gets stronger. Also, it tries to draw implications on driver’s perception on EVs and determine if their opinions on preferred driving range have reflected actual needs for daily travels.
To deal with these questions, three consecutive surveys were carried out along with two GPS tracking experiments for Internal Combustion Engine (ICE) vehicles and EVs.
Urban and Transport Feature of Jeju Island
Jeju is the largest island, located in Nam Hea (South sea) of Korea, with 41㎞ length from North to South and 71㎞ from East to West. With its suitable climate for wind and solar power generation, Jeju Island was selected as the test bed for Smart Grid pilot project that included smart transportation.
The Island could be divided into two parts for administrative purpose and two major cities are located along the seaside near the middle of north and south sides each. Most of economic activities are focused on the two cities and so do the traffics.
Participants and Specification of used Electric Vehicles
Participants of this study were recruited from the applicants for government EV subsides for the first half of the year 2014. The survey were conducted three times including before the decision for EV subsidy grant was made (T0), after EV was purchased but not driven (T1), and three month after driving EV (T2). The Number of participants who answered all of the three surveys was 16 and the number of households who agreed to participate in GPS tracking experiments was 33 with 44 vehicles including EVs.
Four types of electric vehicles were available for the study that includes Soul and Ray by Kia-Hyundai motors, SM3 E.Z. by Renault Samsung, and BMW i3. Average driving range per charge for these vehicles is 126㎞ (min 91㎞, max 148㎞). Each participant was granted a subsidy about 16 thousand euro for purchasing an EV.
Survey Design and GPS Data Collection Procedure
The questionnaires include motivations and concerns of purchasing and operating an EV regarding subsidy, operation costs, driving range, battery performance, charging infra, and other opinions. Respondents indicated their responses to the questions with 5 scale points. Scale of 1 was indicating the least agreement and 5 was indicating the most agreement for each question item.
One of the major interests this research drew is how the respondents’ opinion would change as their commitment on EV got stronger, especially for purchasing price of EV, operational costs, driving range, and charging options.
At T0, respondents were supposed to express their expectations and concerns for purchasing and operating an EV prior to their monetary commitments. Therefore, their expectations might vary widely. At T1, the respondents made monetary commitment for purchasing an EV that must have encouraged respondents to do enough research on EV and its operations. Therefore, it is assumed that respondents were more informed compared to the prior stage. At T2, respondents experienced EV and they were expected to form clear opinions on how satisfied with their EV experiences with respect to driving ranges, charging options, operation costs, and other question items.
Furthermore, it also employed automobile Black Box and GPS tracking technologies to collect precise driving data. Data was collected twice for ICEs and EVs from the same drivers to analyze their behavioral changes with respect to trip frequencies and average daily vehicle kilometers. Data was collected through the Black Box that provided info on date and time of starting and finishing for each trip and length of every movement the vehicles made.
Results of Surveys and Experiments
Satisfaction with Economic Benefits for Driving an EV
Economic benefits for purchasing and driving an EV were major determinant for their decision. At T0, 60% of respondents fairly agreed that their major motivation for considering EV purchase was government subsidies and tax incentives. While at T2, 75% of respondents strongly agreed that their major motivation for purchasing an EV was economic incentives. Furthermore, most of respondents strongly agreed that they had expectations for lower operation costs and most of them were satisfied with it after they experienced EVs.
Satisfaction with Recharging Options
Regarding recharging options, respondents were satisfied with access to charging stands compared to their initial expectations. At T0, 53.3% of respondents strongly agreed that they would not easily access charging stands. However, it turned out that 43.75% of respondents were satisfied with access to charging stands at T2. However, recharging time took longer than they expected. At T0, 53.3% of respondents were strongly agreed that recharging time would be longer and the figure increased to 62.5% at T2.
Satisfaction with Driving Range and Battery Performance
The respondents answered that performances for driving ranges and battery capacity could not meet their expectations. Especially, respondents’ answers were diverged largely from their a priori opinion. At T0, 66.67% of respondents were strongly agreed that they were expecting enough driving ranges for currently available EVs. However, their answers diverged at T2 that 50% of them dissatisfied with driving range for their EVs.
This result rose further questions on what rationale the respondents had to change their opinion. Did the respondents have biased opinions on EVs at first? Did they really experience any difficulties due to short ranges while driving or did they need such a long driving range for daily use compared to their ICE vehicles?
To answer these questions, automobile Block Box and GPS data tracking technique were employed at T1 and T2. Among the respondents, 33 agreed to provide GPS data for their ICE and EV. Driving records were tracked for about a week for each period.
Comparisons of Average Daily Driving Frequency
Trip frequencies for ICE and EV were shown with distance ranges of 5km in the figure. Average driving day for ICE was 5.8days (std = 1.46) and EV was 5.06 days (std = 1.56). 72.1% of trips for ICE and 68% for EV were made within 5km and the difference between ICE and EV were not significant. Drivers made more trips for the ranges from 3㎞ to 20㎞ with EV than ICE.
Comparisons of Average Daily Driving Distances
Average daily driving distance for ICE and EV were not significantly diverged as shown in the figure. Average daily driving distance for ICE was 33.67㎞ and for EV was 32.53㎞ and average trip frequency per day were 6.1 trips for ICE and 5.4 trips for EV. EV users were more likely to drive EV for shorter distances while ICE users were likely to drive longer distances. However, the differences were not significant.
The results of comparisons between ICE and EV regarding the trip frequencies and average daily driving distances could be interpreted that EV could be a perfect substitute for ICE to meet respondents’ daily travel needs in this study set. Though, existence of some geographical limitations should be noted .
In more detail, this study further investigated how the respondents changed their usage of EV versus ICE for daily driving needs. This study categorized five types of households for their use of ICE and EV combination as shown in the table. Prior to purchasing an EV, most of households possessed at lease one ICE. After purchasing an EV, they may dispose of their ICE or use both of them together.
Comparing average distance and the number of trips per day for type 1 households, the differences between ICE and EV were not significant. Average distance per day for ICE was 32.9㎞ and EV was 34.9㎞ and number of trips per day for ICE was 5.9 and EV was 5.3
For type 2 households, they ended up to add another vehicle for their family. Therefore, both of their trip distance and frequency made by vehicles had increased. At T1, average distance per day was 36.8㎞ and average number of trips was 8.5. At T2, EV was used more often than ICE and for longer travel. Average distance for EV was 23.9㎞ and average number of trip was 5 while for ICE was 18.6㎞ and trip number was 3.7. This result implies that, after an EV was purchased, EV was used as a primary vehicle and ICE was secondary.
A consistent implication could be drawn from type 3 households. At T1, primary and secondary vehicles were compared and average distance for the primary vehicles was 32.6㎞ while the secondary was 16.8㎞. At T2, overall travel distance and trip frequency had increased and usage of EV increased more than that of ICE. Average distance per day for EV was 37㎞ while for ICE was 20.7㎞ and average trips for EV was 7 while for ICE was 5.1.
Conclusion
This research selected model countries in Europe including Germany, France, Norway, and Netherlands for case study in governing frameworks for pursuing EV policies. The selection criteria include number of deployed EVs, volume of CO2 emission from household for transport activities, number of EV developers, and amount of monetary incentives for an EV purchase.
Governing frameworks for pursuing EV policies for each country were analyzed and implications to Korean government were drawn with comparisons of model countries. Regarding governing framework, the model countries set up an organization, committee, or conference that coordinates execution of EV policy measures in collaboration with various interest groups. Also, model countries are imposing vehicle tax schemes based on volume of GHG emission. This scheme is favorable to EVs and non-fossil fuel vehicles which provide consumers monetary incentives. It is conjectured that these two factors might influence on efficacies of EV related policy measures as a result.
Furthermore, this research tried to answer questions on how drivers’ opinion and travel behaviors change as their commitment to EV gets stronger as well as how driver’s perception on driving range of EVs shifts.
Within the scope of this study setting, several conclusions could be drawn. First, respondents were satisfied with economic benefits of EVs for saved operation costs and purchasing subsides and tax incentives. Second, while they were satisfied with the access to recharging stands, they were disappointed for recharging time. Third, respondents were not satisfied with battery performance and driving ranges.
To deal with the question regarding to the driver’s perception on driving range of EVs, this research collected GPS data for ICE and EV. The results showed that EVs were able to provide enough driving range that meet respondent’s daily driving needs compared to ICE. Furthermore, this research drew an implication that EV could be substitutable for ICE as a primary vehicle for households