The University as EV Ecosystem Hub

Education and Outreach to Accelerate EV Adoption

Dunbar P. Birnie III

Department of Materials Science and Engineering, Rutgers University, New Brunswick, New Jersey, U.S.A.

Keywords: Energy Systems Education, EV Ecosystem, Workplace Charging Infrastructure, EV Adoption Acceleration,

Commuter Transportation Electrification.

Abstract: The author’s university location is being developed as an alternative-fuelled-vehicle “ecosystem” that is

serving both educational and research missions. In addition, it is assisting with gradual transition from

gasoline-powered private vehicles to PHEV and EV thereby providing real positive regional environmental

impacts. By highlighting the early phases of this transformation locally and including students in the

discussion we hope to assist in accelerating this transformation for the future. This paper surveys our present

status and provides data on the usage patterns as well as on the costs and practical difficulties encountered

when considering hardware installation and making site selection.

1 INTRODUCTION

EV’s fit into a future where we envision pervasively

installed renewable electricity generation (wind and

solar) allowing for substantial reduction of fossil

fuel usage for transportation. We already see a steep

increase in the number of plug-in vehicles on the

road, as shown graphically in Figure 1, showing

cumulative vehicle sales in the US, with around

10,000 new vehicles being added per month. Still,

this has to be considered the “early adopter” phase

of this technology transformation. Many of the

available vehicles are aimed at higher price points

and are commensurate with the early-stage battery

costs, though these costs are expected to come down

substantially as manufacturing scale is increased.

Another key aspect in this transformation is the

infrastructure changes that will also be required to

facilitate the practical use of this rapidly growing

population of vehicles. This is much more

problematic since we are talking about electrical

installations at high voltage with many safety and

usage considerations.

This technology transformation has begun and

should be showcased to students who will be the

future technology innovators and civic leaders who

will participate in the continuing transformation into

the foreseeable future. To provide this educational

angle our university has chosen to make our campus

location into a visible ecosystem of activity,

involving both educational and research initiatives,

and therefore is actively participating in the

furtherance of this transformation. The next section

surveys the many reasons why EV’s must naturally

be central to the world’s energy usage for the future.

Further sections examine how our university’s

activities can connect into educational, research,

infrastructure, and policy themes – all related to the

future transportation/energy transformation.

Included in this discussion are data measured during

the last two years of on-campus EV charging, which

provide a baseline for future growth of our

ecosystem.

Figure 1: Cumulative US PEV Sales by month showing

steady growth beginning in 2012 (EPIC 2014).

P. Birnie III D..

The University as EV Ecosystem Hub - Education and Outreach to Accelerate EV Adoption.

DOI: 10.5220/0005488000900097

In Proceedings of the 1st International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS-2015), pages 90-97

ISBN: 978-989-758-109-0

 2015 SCITEPRESS (Science and Technology Publications, Lda.)

2 BACKGROUND

The future transportation transformation requires

new electric and hybrid vehicles as well as critical

modifications to the electrical distribution network

to allow convenient charging. These changes are not

easy and many pro and con claims are made about

air quality impacts, energy cost aspects, and usage

parameters. To assess these objectively we have

been studying EV usage on campus and advocating

for expansion of the EVSE infrastructure. In this

section the “carbon-footprint” impacts of EV use are

surveyed, followed by a discussion of possible

battery-storage value propositions enabled by broad

EV adoption.

Many discussions about the possible pros and

cons of electric transportation fall back on gut

instincts and worries about the carbon footprint of

the electric generation side of the picture. The

electricity needed must certainly be generated

somewhere and with some kind of fuel, often fossil

fuel. Using US Department of Energy data on the

energy usage we can learn that coal, natural gas, and

nuclear are the most significant contributing sources

of energy for electricity generation, but each has

significantly different carbon-footprint

contributions. Further, it comes as no surprise that

there is significant regional variation in the fuel-mix

used for electricity generation – and that would then

influence the net carbon-footprint for electric

transportation on a regional comparison basis. The

Union of Concerned Scientists have done a close

analysis of the regional variations in electricity

generation mix and applied that to electric vehicle

transit efficiency (Anair and Mahmassani 2012).

Figure 2 shows their quantification, where darker

Figure 2: Equivalent gasoline mileage (miles per gallon)

required to match typical EV travel environmental impact

on a per-mile carbon footprint basis (Anair and

Mahmassani 2012).

regions have higher carbon-footprint electricity

generation and lighter regions have more renewable

generation. The MPG labels in each region are the

carbon-footprint “break-even point” values for

gasoline vehicles that would yield the same carbon

footprint as typical EV’s. Even in the highest

footprint regions (dark blue) the EVs are better than

a substantial majority of gasoline powered vehicles

currently on the road. In the light blue regions EVs

are substantially better than their conventional

cousins. For New Jersey specifically, a gasoline

vehicle would have to get 64 MPG to be equivalent

to typical EV travel. So, in round numbers for our

region, EV transportation provides perhaps a ~50%

reduction in carbon-footprint, depending on which

gasoline vehicles are replaced (and for many cases

provide a much better reduction than that).

A related question focuses on the full life-cycle

cost of new EVs that by necessity require larger and

larger batteries as we push for longer all-electric

range. This has an added factor that battery

manufacture also has energy and carbon-footprint

impacts. This also means that EVs are typically

more expensive at their initial purchase though

having substantially lower per-mile operating costs.

The life-cycle costs for different range EVs was

assessed by (Samaras and Meisterling 2008) who

found that over all the plug-in life-cycle impacts

were significantly lower than conventional vehicles

and that the relative battery size was a rather smaller

impact on the net system carbon footprint (see

Figure 3). This second finding is not too surprising

given that many vehicle-miles are covered in

relatively short trips, so the larger battery mainly has

impact for the subset of longer distance excursions.

Figure 3: Full life-cycle costs comparing different vehicle

types as noted: Conventional vehicle (CV), hybrid (non-

plug-in, e.g. Toyota’s Prius), and three variants of PHEV

with gradually larger all-electric range (Samaras and

Meisterling 2008). Blue line added to illustrate

approximate effect for NJ-region electricity footprint.

TheUniversityasEVEcosystemHub-EducationandOutreachtoAccelerateEVAdoption

The long-term environmental impacts of

electrification are bound to improve with time

because many regions have regulated utilities where

renewable energy generation is mandated (so-called

Renewable Portfolio Standards) and so the carbon-

footprint per mile will gradually get smaller with the

life of the car simply because the grid electricity will

be getting cleaner (Anair and Mahmassani 2012) as

opposed to gasoline vehicles, which tend to become

more polluting with age.

The economics and environmental aspects of

plug-in vehicle usage are important topics and cover

many situations and issues. Whenever a plug-in

vehicle is charging then it is adding to the

instantaneous electrical generation requirement from

the utility. And, since this is not typically a planned

or gradual electrical usage then it must be budgeted

against the more rapidly rampable generation

sources rather than the base load foundational

generation (which are usually not the zero-carbon-

footprint renewables like solar and wind). So the

time-of-day when vehicles are plugged in has

consequences for the cost of electricity generally,

and for the ability of the grid to provide the overall

need.

In addition to the simple charging aspects of

plug-in vehicles, it has been proposed that EV’s be

used for grid storage – essentially allowing

bidirectional charge/discharge usage, a system

which is called “Vehicle-to-Grid”, or V2G

(Kempton and Letendre 1997; Kempton and Tomic

2005; Tomic and Kempton 2007; Lund and

Kempton 2008). Implicit within the V2G concept is

the need for fleets of vehicles to be plugged into the

charging network for times when not in use for

regular driving. This then makes it possible for

smart systems to allocate the service instantaneously

with optimization aimed at maximizing economic

value while preserving comfortable driving range;

operation to minimize carbon footprint is also

imagined (though no battery system has yet been

devised with full 100% round-trip energy retention).

The V2G valuation is increased when the battery

size in the vehicle is increased because it becomes

possible to buy (at night) and sell (during the day)

larger quantities of electricity; and, it is possible

with a larger battery to provide a larger power

input/output to the grid for frequency regulation.

However, it has also been pointed out that these

larger batteries also necessitate the use of heavier

cars than we might otherwise need – and that

driving these heavier cars requires more energy as

well – essentially taxing the energy storage buy/sell

profits that might be possible when using a

stationary battery (Shiau, Samaras et al. 2009;

Viezbicke and Birnie 2011). The optimization of

V2G ultimately requires a large population of

vehicles plugged-in, infrastructure that is able to

monitor and control bidirectional power connection

to the grid, and smart algorithms that can reduce

overall cost and lower carbon-footprint system

wide. This is a classic “chicken-vs-egg” problem

balancing vehicle purchase and infrastructure

availability. As adoption accelerates we will reach a

tipping point where there are enough vehicles

connected that this economic model can move

forward. Thus, in the near-term we must be

examining policies and research efforts that can

accelerate the adoption and bring this new

transportation reality to fruition.

Our initial step in this direction was aimed at

making the connection between workplace solar

power generation and daytime-workplace plug-in

availability (Birnie 2009). Our “Solar-2-Vehicle”

concept thus highlighted that using combined

workplace and home charging that battery range

limitations are diminished substantially and a

greater fraction of travel can be electrically powered

(with a lower carbon-footprint per mile travelled).

This concept has been substantiated by testing

energy usage when trying to maximize the

utilization of workplace solar power (Birnie 2014).

With this background, the main campus of

Rutgers, The State University of New Jersey, has

selected this topic as a strategic initiative – where

research, education, and outreach can be combined

and will highlight this important technology

transformation as it moves forward. As a calibration

of our location, Figure 4 shows the one-way driving

distance between home and school for a

Figure 4: Cumulative probability of travel distance from

home to Rutgers campus using over 900 randomly-chosen

permit holders. About half of the Rutgers parking

population lives within 10 miles of their campus

destination.

VEHITS2015-InternationalConferenceonVehicleTechnologyandIntelligentTransportSystems

representative population of parking-permit holders

on campus; a one-way travel distance of 10 or 15

miles is easily handled by many current plug-in

vehicles in all-electric mode showing that work-

place plug-in is a useful stepping stone toward future

transportation electrification. The next section

presents a closer look at recent usage patterns for the

EV infrastructure now available on our campus.

3 ON-CAMPUS USAGE DATA

As noted above, the Solar-2-Vehicle project was

initiated with the intention of testing a specific

commuter operating mode for the plug-in vehicles in

connection with work-place solar power generation.

In addition, it was expected that this would highlight

the importance of solar power installations as

parking lot canopies and that other incidental data

would be gleaned from the usage patterns and

observations. This section provides a partial analysis

of the usage and different energy evaluations that

were achieved, to date.

The majority of detailed testing has been

conducted using a standard production 2012-Model

year Chevy Volt, which was kindly provided for

testing by the Rutgers EcoComplex, with further

support from the Rutgers Energy Institute (REI).

The Chevy Volt has a powertrain that is entirely

electric and a battery capacity of 16 KWH

(nominal). In addition, its standard configuration has

a gasoline powered electric generator, so even when

the battery has been drained the vehicle still has

sizeable range, though traveling on gasoline.

Generally, the vehicle power system uses electricity

first, though in cold weather it cycles back and forth

between gas and electric to protect the battery from

abuse (This operation is beyond the control of the

driver). Detailed commuter operation and data

logging commenced on December 13

, 2012 and all

travel information was logged during regular

commuting and other business travel during the

complete following year. Data logged included time

of day, external temperature, dashboard console

information on mileage, energy, and gasoline usage .

In addition, data were maintained on location of

plug-in power used as well as to log the various

other users of the plug-in spots on campus. Further,

the system data from the charging stations (through

ChargePoint and Blink) were gathered at intervals to

understand usage patterns and amounts of energy

provided by the Rutgers grid. These data were

digested to provide the various conclusions here and

in the following sections.

In total during the first year of testing 7809.0

miles of travel were logged. During this time 6197.5

of the miles were under battery-electric mode

(79.4%), while the remaining 1611.5 miles were

under gas-generator-powered mode (20.6%). For

this travel 1979 KWH of electricity was provided

from the Rutgers grid and 44.9 gallons of gasoline

were consumed. If we compare the travel under all-

electric mode with the electricity that has been

provided by charging then we can get a composite

number for the electric-drive efficiency at 3.13 miles

per KWH, averaging through the year. Figure 5

shows how the electric drive efficiency evolved

through the test-year with each data point derived

from each battery fill-up event. Notable reduction in

driving range is evident for winter season driving;

part of this is due to the energy required for cabin

climate control, but part is also likely due to

reduction in battery efficiency at colder

temperatures. Also, during the hotter parts of the

summer there were times of lower efficiency, which

again correlated with times where significant air

conditioning energy usage was experienced.

Figure 5: Miles travelled per KWH of energy metered at

grid source level, through the year 1 testing period.

The average electric-drive efficiency found above

was 3.13 miles per KWH based on the electricity

metered in. However, as this power was only used

after being stored in the battery we are able to assess

this “round-trip” storage efficiency. Figure 6 (next

page) shows a comparison of the energy received

from the meter (X-axis) and the energy metered out

of the battery during use and logged on the

dashboard/console (Y-axis) for each battery recharge

event through the test period. Assuming a simple

linear relationship then we measure an 83% round-

trip efficiency for the charge/discharge process,

averaging through the whole year. It is interesting to

note that this round-trip energy recovery ratio also

changed with season; the best values were typically

found during the colder seasons, suggesting that the

TheUniversityasEVEcosystemHub-EducationandOutreachtoAccelerateEVAdoption

Figure 6: Round-trip electric energy recovery after storage

in the vehicle battery.

relatively complicated battery temperature

management system may add parasitic energy losses

that don’t get logged at the dashboard level

especially during the warmer parts of the year when

active cooling may be needed.

The EV range and its practical utilization for

basic commuting was the core concept for that first

year of testing. The project was aimed specifically at

testing the circumstances where it might be possible

to be a commuter who was able to fully utilize solar-

generated workplace parking/charging locations to

feed full round-trip commuting. Similarly this could

equally well substantiate the converse model: full-

electric commuting sourced at home from grid-

available electricity (which, for most commuters

would likely be taken at night). In either case the

times, distances, and traffic conditions would be the

same. Figure 7 shows the final performance metrics

related to the core hypothesis. For this plot a 40 mile

distance was used as the cut off. Clearly a majority

of the trips have been conducted entirely on

electricity, but in the colder seasons there are many

instances of commute cycles that required some

gasoline after the EV range was exhausted.

During the year of testing complete notes were

kept on the other users and congestion of the four

parking spaces and their connection to the charging

Figure 7: Fraction of simple round-trip commute cycles

powered completely by work-place-sourced electricity.

equipment. While the actual parking spot occupancy

measurement was only possible when I was there

(arriving, leaving, or moving the vehicle), the

connection logs downloaded from the ChargePoint

system provided further information about their

usage. These data were combined to help provide a

more complete picture of the utilization of the EVSE

at Rutgers during that full year.

The occupancy data were processed to provide

an hour-by-hour overview of the usage of the four

spots. To avoid confounding affects caused by

measuring my own utilization, the data reported

below are based on observations of the remaining

parking spots subject to the understanding that I was

typically occupying one of the spots already. Figure

8 shows how the parking space utilization was as a

function of time of day, where the data were

grouped as: “Available”, “Blocked” (meaning

occupied by a non-plug-in vehicle), and “Other EV”.

This chart shows a pattern that would be typical for

a university location: basically empty in the early

Figure 8: Probability of occupancy as a function of time of

day for the EV spots located by the School of Engineering.

The time groupings are rounded down: ie, the 9 O’Clock

entry includes all data points through 9:59.

morning, then with people leaving substantially by

6PM. And, we see pretty constant occupancy

throughout the day which might be expected for a

work-place location where most drivers stay for the

majority of the day, though clearly there is some

turnover. This shows a pretty steady usage, but the

“blocked” fraction is quite significant at around 30-

40% for most of the day. On average this is at least

one full parking spot prevented from access for most

of the day. The parking lot in question was heavily

used and during this time period there was no policy

in place for preferential usage by vehicles needing to

charge and no enforcement, though the signage was

clear that they were EV charging spots.

VEHITS2015-InternationalConferenceonVehicleTechnologyandIntelligentTransportSystems

It is interesting to see how the usage changed

during the progress of the one year of study. So the

data were regrouped into 26 2-week intervals and

replotted as Figure 9. It is interesting to see that the

usage by EV’s increased significantly during this

year (which was also clear by the appearance of new

vehicles that hadn’t been system users when the

study commenced). And, the bigger change with

time is the reduction of blocking by non-EV parked

cars. While the signage is clear that preference

Figure 9: Parking spot congestion mapped through the

one-year test period. Other EV usage increased

significantly during this time.

should be given to EV’s, there is no specific penalty

and there has been no enforcement to date.

However, it seems that the population of non-EV

drivers at least has gradually recognized that there

are regular EV users and improved how they

preserve these spots for EVs.

Next we turn attention to the entire population of

EV users and their usage patterns. The ChargePoint

usage logs provide session information that includes

start and stop times, energy delivered (in KWH),

power selected (level 1 or level 2) and some other

basic stats. One key measure of the usage is the

amount of time that the plugs are “in-use” which is a

proxy measure for the length of time that the parking

space has been occupied. Figure 10 shows the

cumulative probability distribution as a function of

the length of time plugged in. Sessions which were

shorter than 2 minutes were not included as these

were often incorrectly initiated or were restarted

immediately after. The distribution shape still has a

population of around 10% of sessions that have been

between 2 and 10 minutes only (the nearly vertical

jog near the origin). After that EV users tend to stay

an hour or longer, but the very smoothly linear

region from 2 to 6 hours covers about 50% of the

sessions. There is a relatively significant grouping at

Figure 10: Duration of plug-in session plotted as a

cumulative probability distribution. Sessions shorter than

2 minutes were not included. The usage is widely and

continuously varying including shorter and longer times.

8-9 hours plug-in time (many of which were plug-in

events associated with the present study). The

gradual sloping up from 2 to 6 hours might be

consistent with events caused by a full-time

employee who needed to attend a meeting on a

different location on campus or went out for lunch

but returned for continued charging later in the day.

These would likely happen at different enough times

that it would have combined to give the shape seen.

Finally, we examined the energy delivered and

the effective duration of active charging to calculate

the power accepted by various vehicles during

charging. These data are shown in Figure 11. It is

not surprising that different vehicle types have

different battery sizes and therefore have electronics

that control the power at different levels. The Level

1 specification for our ChargePoint units is limited

to 16A but the current seems to be limited by the

vehicles at 12A operating at the standard 120V,

providing a comfortable safety margin.

Figure 11: Cumulative probability distribution of the

active power provided for each charging session. The

specific humps represent vehicle types as marked.

Thus, EV charging data collection and vehicle

performance studies can yield a wide range of

information about energy systems and the users of

these systems. This has added educational benefits

when students can participate in these studies, as

outlined in the next section.

TheUniversityasEVEcosystemHub-EducationandOutreachtoAccelerateEVAdoption

4 EDUCATIONAL IMPACTS

One key mission of universities is to educate the

future generation in their chosen career fields. An

equal and commensurate mission of universities is

the advancement of new knowledge. Faculty are

involved in research on the cutting-edge and

students are learning the ropes so they can graduate

with the most up-to-date understanding of the world.

So universities are natural places to investigate the

adoption of new technologies, and in this case, the

transformation of transportation from fossil fuels to

electricity. It is a huge effort that spans many

engineering fields, but also intersects with business

majors, supply chain, and social sciences in many

ways.

With our relatively new effort studying EV usage

patterns we have already had many chances to

intersect with students and develop further

understanding about EV usage. For example the

author teaches a solar device technology class with

thematic semester projects required of all students.

Recently one of these project assignments was

aimed at having the students design parking-lot

solar-arrays with the added feature of stationary

battery storage for storm resiliency. Also, one

engineering capstone design team is underway

examining electricity usage by EV fleet vehicles

being operated by the university – with the aim of

providing advice about recharging strategies and

understanding total cost of ownership for these new

vehicles.

EV data and energy strategies are also useful for

outreach in a variety of ways. For example the

author has given several presentations in the

“Energy Café” series organized by the Rutgers

Energy Institute. These are open to the public,

though mostly attract interested students.

In the future we expect students to be engaged in

research projects examining many facets of the

electrification of transportation in the region. For

example: Could EV’s be charged at the university’s

solar array during storm/grid failures and then used

for emergency delivery of power to critical facilities

in the region? This would build on our recent

probability model for guiding battery size for these

resilient power islands (Birnie 2014).

Also, could electric buses be used within the

sprawling university campus? What infrastructure,

performance and environmental impacts would

result (Rutgers maintains one of the largest bus

systems in the state of New Jersey).

Further, could “vehicle-to-grid” (V2G) systems

be fielded on or near campus? New variants of V2G

could be tested and evaluated within the context of a

large commuter population, both of students and for

faculty and staff. Again there are significant

infrastructure, logistics, and social changes that will

be required to allow for smooth operation of V2G

and other complicated energy systems in the future.

Already we are increasing our data gathering

capabilities and will be connecting these data with

driving habits, seasonal temperature variations, and

commuting routes. Our overall aim is to have

students involved in the data gathering, analysis, and

interpretation so that we can increase the impact for

regional transportation modification in the future.

5 INSTALLATION ISSUES

The transformation that we envision is hampered

significantly by the infrastructure needed to provide

power to growing numbers of commuters. The EV

charging hardware is only part of the story as

electric conduit may have to be laid and new circuits

added, depending on the location and anticipated

number of vehicles to be serviced. Up to this point

these infrastructure costs are quite a bit larger than

the value of the electricity that the vehicles receive.

Also, the EV equipment that we have installed so

far has been added with relatively little consideration

of the population of likely users and their charging

habits and how this impinges on the general

limitation on availability of parking. And, the

question of different usage patterns that will match

with Level 1, Level 2 or higher power rates has not

been clarified.

The best strategy will likely be to combine new

EV charging locations with new construction

projects and building renovations so that the

rewiring and new hardware can be made as cost-

effective as possible. And, there may be new ways

of co-funding for charging units that will be used

partly by the university fleet and partly by the

student/faculty/staff private vehicles. This is a wide-

open discussion that is evolving rapidly on campus

as we move this initiative forward.

6 POLICY CONNECTIONS

Our studies of electric transportation integrate the

technological (hardware and algorithms) with the

social (attitudes and behaviour patterns). In many

cases these combined socio-technological changes

will be assisted by policy choices that we make

VEHITS2015-InternationalConferenceonVehicleTechnologyandIntelligentTransportSystems

along the way (local to campus, but also state and

federal policies, as well). For example, the IRS has

issued a ruling that electricity provided without cost

to employees in workplace charging is of “de

minimis” value and thus not a taxable benefit. And,

some regions have given EVs priority in the High

Occupancy Vehicles (HOV) lane, providing

encouragement for rush-hour commuters to change

to electric-drive vehicles.

Another gradual policy push will come from the

steadily increasing fuel efficiency standards imposed

on car manufacturers, thus giving preference to

electric vehicles that can take advantage of

regenerative braking and generally have higher

effective fuel efficiencies.

And, we have certainly seen that local policy

choices have had an influence on EV usage patterns

(for example the EV-only parking space interference

by gasoline vehicles when no enforcement policy

was in effect).

In the long run we hope to establish local

policies that encourage our community to rely on

EVs for commuting to campus and to appreciate the

environmental advantage provided by moving from

gasoline to electricity.

7 CONCLUSIONS

Large university campus locations are ideal for

installing, studying, using, and developing

technology needed for the coming transition to

pervasive electric personal transportation. The

involvement of students in these studies and in the

classroom provides an excellent chance for the

future leaders of our country (our students) to

interact with the technology in the formative stages

of their lives and then eventually participate in the

continuation of this transition when they join the

workforce.

ACKNOWLEDGEMENTS

Vehicle testing on campus has been sponsored by

the Rutgers EcoComplex and the Rutgers Energy

Institute. Additional support through the McLaren

Endowment at Rutgers is also greatly appreciated.

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Electric and Hybrid Vehicles 3: 309-317.

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