Final Project

Hristo Marokov

GIS Final

Project presentation link:


Electric vehicles are currently associated with the following public goods: pollution reduction and less costly transportation. The public sector is in position to affect their market. I want to examine what policy options cities have to increase the electric vehicle adoption rate. At first, it would be necessary to assess the capacity of the current infrastructure. Therefore, I am mapping it using an index of electric miles traveled. Second, I am concerned with optimizing the selection process of locating new charging stations. Thus, I am considering public owned facilities and electric vehicle owners’ residences with respect to existing coverage as projected by the index.

As part of my applied policy project, I came across various electric vehicle reports. The most comprehensive literature was found at the alternative fuel data center of the U.S. Department of Energy.

My first layout describes the capacity of each charging station in terms of electric miles per hour of charging. Also, it helps picturing the exact location current electrical capacity. The second map shows the number of electric miles per hour of charging available for each city. Then, to help public authorities examine the need of charging stations I have included time series maps of the existence of electric vehicles owners over a period of two years (01/2010 – 10/2011) . Further, I analyze the respective charging capacity for each station and its relative coverage by mapping the electric miles amount of per hour charging. In the fifth layout, I look into the coverage combined with the electric vehicle owners’ density. The sixth layout indicates gaps in the coverage and identifies the public parking stations to further inform the selection process of new charging sites. Similarly, the seventh layout is intended to offer a glance of the current coverage and facilitate the selection process for additional infrastructure by locating additional public facilities, such as libraries and museums. Finally, I offer a map of the important areas that will likely require additional electric capacity in order to be accounted for in the future selection process.

My research is based on two models. The first is creating an index to project the electric capacity of the current and the future infrastructure. The second model incorporates different steps of the location selection process used by the public officials. Both models and the relevant calculations could be found at the end of this narrative.

The geographic data I use is available on the LA County GIS portal. This includes the majority of the layers with exception to the original data layout. In addition, I have incorporated some shape files from our class data folders. I have created most of the attribute data using online information and fusion tables. However, the attribute data regarding electric vehicle owners has been provided by the City of Los Angeles.

The index and aggregated fields calculation is included at the end.

My findings could help cities to evaluate their assets and project their needs with regards to managing electric vehicle charging equipment. With the electric vehicle miles index available they simply need the hours in use of a charging station or a projection of them to know how many EMT this station brings to their city. Furthermore, factoring in the average price of the different type of charging station will allow quantifying the value of each electric mile supplied by it.
In addition, while comparing the gasoline and the electric fueled transportation modes, an exact number of reduction in pollutants could be derived for each electric mile. Such calculation will allow projecting the price paid for each electric mile in terms of the actual benefit derived in the form of air quality improvement.

Finally, my findings are simply a small step in quantifying the processes related to electric vehicle transportation. In this particular case, the GIS tools will enable cities to shift pollution reduction parameters from one neighborhood to another while accounting for the resources needed.


Models and Calculations:

Based on the City of Denver, Colorado output, we developed a check list for efficient installation and siting of publicly accessible charging stations.
Selection process for EVSE sitting:
1) Initially, a city could consider only parking structures that are publicly owned:
a) Considering the list of public parking structures.
b) Identifying major venues with a lot of parking spaces where people park for long periods such as cultural and art complexes, the zoo, downtown public parking, etc.
c) Coordinating with the Library, Parks, and Recreation Department to further narrow the best potential locations.
2) Make a selection based on:
a) Parking space availability
b) Completeness of the geographical coverage.
c) Opportunity for multi use of the charger (during the day – the general public, during the night – the city or employees vehicles)
d) Proximity with other private attractions, for example: libraries that are situated in popular shopping/dinning districts.
e) Ruling out areas with vandalism issues and sites with typical customers that would be more-likely early-adopters.
f) The power capacity of the existing electrical panels in the facilities of interest.
g) The electricity price schedule for each facility in order to be mindful of not placing a facility into the next rate structure.
The strategy for managing cost would vary depending on the type of charger installed and the model of service provided to users.

Electric Mile Index:

The calculation is simple and not 100% accurate due to the various assumptions made.
All of the projections, such as battery capacity, range, and charging time are made based on Nissan Leaf’s characteristics. However, the main component, 24kw/h battery, is almost identical in Ford Focus and Volvo C30.
The metrics used are:
The battery capacity to which we associate the projected range of the vehicle.
The different time periods needed for full charge: Level 1 (110-120V) – 21 hours, Level 2 (220-240V) – 7 hours, DC (480V) – 30 minutes for 80% of the battery (These time estimates can vary due to different amperage level).
The actual numbers:
Assuming a 24kw/h battery capacity (currently installed in Nissan Leaf, the most popular EV on the US market).
The projected range is 100 miles on a full charge. The European estimate gives a range of 109 whether, the DOE project a range of 99 miles. While consulting other literature, we defined a range of 68 – 132 miles based on the different driving patterns, weather and road conditions. Here, we use a range of 100 miles.
Furthermore, the battery amortization rate that directly affects the range should be accounted for. It is around 30% over 10 years. This translates into 2.5 % per year for the 8 year lifespan of the battery (the warranty period). These are the adjustment numbers per year: 1st year – 100, 2nd year – 97.5, 3rd year – 95.17, 4rd year – 92.795, 5th year -90.4825, 6th year – 88,2325, 7 year – 86.05, 8th year – 83.925.
Thus, a Leaf in its 4th and 5th year of use will average approximately 91, 64 miles per full charge. This calculation assumes that there is an equal number of cars above and below the 4th and the 5th year (rather conservative estimate, since the Leaf is a model of 2012).
The charging times for each different type of stations come straight from the Leaf owners manual. Meanwhile, they are on average the ones projected by most of the charging infrastructure manufacturers.
Level 1 – 21 hours, Level 2 – 7 hours, DC – 30 min for 80% of the battery (most vehicles are programmed to stop charging from a DC charger at around 80% of their capacity in order to extent the life cycle of the battery). Currently, incorporating the DC charging in this calculation is challenging since it is only recommended once or twice per week and many owners may not do it on a regular basis. However, once more EVs are on the street the electric miles traveled (EMT) estimate should not differ from the one associated with Level 1 and Level 2 chargers.
Finally, we divided the range (91.64 miles) by the relative charging times, to come with the following numbers:
Approximately 13.1 EMT per hour of Level 2 charging
Approximately 4.36 EMT per hour of Level 1 charging
Approximately 146.6 EMT per hour of DC charging (80% battery capacity/ range utilized).
All of these results are within the following ranges projected by the DOE: Level 1 charging adds between 2 and 5 miles per hour, Level 2 adds between 10 and 20 miles per hour, and DC charging contributes for 120 to 160 EMT per hour of charging.