Appendix B: EVSE/PEV Adjustment Factors to Account for Local Conditions
The nominal set of EVSE/PEV ratios is adjusted to account for the unique characteristics of all geographies based on population density, PEV concentration, and ambient temperature.
As population density increases in a region, the average VMT per vehicle decreases, and thus less EVSE capacity is required. Daily VMT data from the 2009 NHTS are used to quantify this relationship and develop a population density adjustment factor. Figure B-1 shows the daily VMT cumulative distribution functions by population density. Median VMT ranges from 14 miles per day in the most densely populated areas to 31 miles per day in the most sparsely populated areas. The INRIX travel data are resampled to mimic the NHTS daily VMT distributions (Figure B-2). For example, for each U.S. urban area with 2,000–3,999 people per square mile, the INRIX data are sampled so that vehicles modeled have the same VMT distribution as NHTS vehicles from the 2,000–3,999 density bin (see Figure B-1), and so forth. EVI-Pro computed the EVSE/PEV ratio for each population density distribution from the resampled INRIX data to generate the adjustment factor shown in Figure B-3.
Figure B-1. Daily VMT cumulative distribution functions by population density, from the 2009 NHTS.
Figure B-2. Mimicking NHTS daily VMT cumulative distribution functions by population density by resampling INRIX travel data.
Figure B-3. Adjustment factor: non-residential EVSE/PEV ratio as a function of population density.
Similarly, an adjustment factor based on PEV concentration is generated by running EVI-Pro simulations at various PEV concentrations. Plug requirements are lower at higher PEV concentrations (Figure B-4) due to the greater opportunity for efficient infrastructure sharing.
Figure B-4. Adjustment factor: non-residential EVSE/PEV ratio as a function of PEV concentration.
Ambient temperature affects battery charge and discharge rates, and the temperature adjustments applied account for both impacts. Using EVI-Pro, non-uniform discharge rates are applied to driving events depending on trip average speed and ambient temperature, based on the measured effects of temperature on Nissan Leafs (Yuksel and Michalek 2014) over simulated drive cycles (Neubauer and Wood 2013). Table B-1 shows the modeled relative battery discharge rates as a function of ambient temperature and trip average speed: very hot and very cold temperatures drain the battery more quickly at any speed. EVI-Pro also adjusts DCFC charge rates for battery temperature and charge duration, based on INL’s testing of a Nissan Leaf (Figure B-5) (INL 2016). Again, temperature has a major impact, for example, reducing the 20-minute effective DCFC charge rate from over 80% of rated power at a battery temperature of 25°C to 50% of rated power at 0°C. These temperature relationships are applied across EVI-Pro simulations at multiple ambient temperatures to derive the temperature adjustment factor shown in Figure B-6.
Table B-1. EVI-Pro Driving Discharge Model: Relative Battery Discharge Rates as a Function of Ambient Temperature and Average Trip Speed 
Figure B-5. EVI-Pro DCFC effective charge rate model: percentage of EVSE rated power delivered as a function of charge duration and battery temperature.
Figure B-6. Adjustment factor: non-residential EVSE/PEV ratio as a function of ambient temperature.