notall(evs(are(equal:( · 2017. 1. 5. · not all evs are equal: heterogeneity in behavior and...
TRANSCRIPT
ZEV Ac'onable Science Webinar Series Presenta-on 1
February 6, 2015
Not all EVs are equal: Heterogeneity in behavior and energy consump-on in the plug-‐in vehicle fleet. Stephen Zoepf
Not all EVs are equal: Heterogeneity in behavior and energy consumption in the plug-in vehicle fleet.
Stephen Zoepf MIT Sloan Automotive Lab February 6, 2015
Agenda
o Energy Consumption in PEVs n BMW ActiveE n Toyota Prius PHEV
o Charging Behavior
o Plug-ins in the rental context
3
How is this possible?
4
Accessories drive EV energy consumption at low speeds
5
0"
100"
200"
300"
400"
500"
10" 35" 60" 85" 110" 135" 160"
Energy"Use"(W
h/km
)"
Constant"Speed"(km/hr)"
Drive"Energy"
Total"(1"kW"Aux)"
Total"(2"kW"Aux)"
Total"(5"kW"Aux)"
Figure: Rodgers, 2014
Climate control cuts range by more than 50% at low temps
6
Figure: Ford Motor Company
Rodgers, Zoepf & Prenninger
BMW ActiveE Field Trial Insights
8
Accessories averaged ~25% of total energy consumed
9
Prob
ability Den
sity
0 25 50 75 1000
0.02
0.04
0.06
0.08
Comfort Energy (%)
Prob
abilit
y D
ensi
ty
Aux./Total Energy (%)
Subsequent trips show large heterogeneity in consumption
10
−90 −60 −30 0 30 60 900
0.01
0.02
0.03
0.04
Change in Total Energy (%)
Prob
abilit
y D
ensi
ty
Total
Change in Energy ConsumpAon (%) Between Subsequent Drive-‐Charge Events
Prob
ability Den
sity
Heterogeneity is higher in accessory loads
11
−90 −60 −30 0 30 60 900
0.01
0.02
0.03
0.04
Change in Energy (%)
Prob
abilit
y D
ensi
ty
Aux.
Drive
Prob
ability Den
sity
Change in Energy ConsumpAon (%) Between Subsequent Drive-‐Charge Events
High trip-to-trip heterogeneity complicates range prediction
12
Survey of EV users: A more accurate Distance to Empty estimate may be more valuable than increasing the size of the battery pack Franke, et al, August 2011
PHEVs only complicate matters! o Driver aggressiveness o Traffic / Ambient Conditions o Accessory Usage
o PHEVs now add dual-fuel options: n Gasoline vs. electric consumption n When will driver recharge the vehicle?
13
The Prius Plug-In Hybrid
o 2010 Prius-based prototype o 5.4 kWh (3kWh working capacity) o 13mi/21km Charge-depleting range o EV, “Blended” & CS operation modes
14
Photo: Toyota ESQ
Electricity consumption varies widely
15 Electricity Consumption per Electric km, Wh/km
Density
0 100 200 300 400 500
0.000
0.002
0.004
0.006
0.008
0.010
0.012
Mean: 218 Wh/km
Gasoline Consumption
16
0 1 2 3 4 5 6 7
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Gasoline Consumption, l/100km
Density
Charge-SustainingCharge-Depleting
What % miles using electricity?
17
0.0 0.2 0.4 0.6 0.8 1.0
01
23
4
Fraction of Total Distance
Density
Utility FactorPetroleum Displacement Factor
Mean: UF = 0.28 PDF = 0.14
What-If Analysis (OFAT)
o Simulated all 60k trips with new: n charging schedules (1x/day, opportunistic) n new battery sizes (up to 30kWh) n new charging rates (up to 8x)
o Recalculated Electricity, Gasoline, Utility Factor and Petroleum Displacement
18
What-If Takeaways
o Opportunistic 110V charging at all stops would double electric miles to 28%
o 15kWh battery (5x usable capacity) needed to achieve the same result
o For small battery capacity, fast charging does little
19
Agenda
o Energy Consumption in PEVs n BMW ActiveE n Toyota Prius PHEV
o Charging Behavior
o Plug-ins: Preferences in short rentals
o Conclusions & Questions
20
Charging Model o Limited literature available on observed
charging behavior o Used a mixed logit model to assess
probability of finding and using a charger
o Effects modeled: n Location n Battery State n Day, Time of Day n Time until next trip
21
Factors Increasing Charging Probability
o Longer time until next trip (up to 3 hrs) o Last trip of the day o Ending at home* location o Lower state of charge o Earlier in the day
o Significant Heterogeneity!
22
Simulating the charging probability
Variable Value SOC (0-100) 0 Hours til next trip 12 Length of last trip (miles) 10 Last trip of day (1=yes, 0=no) 1 Ends @ "home" (1=yes, 0=no) 1 Ends on weekend (1=yes, 0=no) 0 End time 6:00 PM
Simulated Probability 0.53
23
Variable Value SOC (0-100) 50 Hours til next trip 3 Length of last trip (miles) 10 Last trip of day (1=yes, 0=no) 0 Ends @ "home" (1=yes, 0=no) 1 Ends on weekend (1=yes, 0=no) 0 End time 6:00 PM
Simulated Probability 0.33
Variable Value SOC (0-100) 50 Hours til next trip 1 Length of last trip (miles) 10 Last trip of day (1=yes, 0=no) 0 Ends @ "home" (1=yes, 0=no) 0 Ends on weekend (1=yes, 0=no) 0 End time 6:00 PM
Simulated Probability 0.04
Conclusions & Recommendations o High variability PEV energy
consumption, even trip-to-trip
o Accessories are source of large power draw and variability
o Charging 100% every night not a good assumption – more study needed.
24
Agenda
o Energy Consumption in PEVs n BMW ActiveE n Toyota Prius PHEV
o Charging Behavior
o Plug-ins: Preferences in short rentals
o Conclusions & Questions
26
Why Study Carsharing? o Opportunity to study over a million
consumers who select and use new vehicle technology for short duration
o Carsharing fleets count towards Zero Emission Vehicle law requirements (CA)
o A large portion of carsharing users may purchase a vehicle within a few years
27
What Matters when Renting?
o Price, Distance & Availability top-cited criteria
o Environmental Impact ranked 8th o 63% were interested or extremely
interested in EVs o Hybrids and electric vehicles were top
requested cars in 2012
28
Survey Summary
o 68,982 survey email invitations
o “Random” selection of member base
o ~4,000 respondents (>5% response rate (!!) )
29
Users familiar with hybrids only
30
Experience with HEVs by Respondent
Perc
ent o
f Res
pond
ents
3.3
50.5
13.8
28.3
4.1
Own orPreviously
Owned
Driven aZipcarHybrid
Driven aHybrid
Elsewhere
NeverDriven
a HybridDon'tKnow
Experience with PHEVs by Respondent
Perc
ent o
f Res
pond
ents
0.13.3 2.9
86.3
7.5
Own orPreviously
Owned
Driven aZipcarPHEV
Driven aPHEV
Elsewhere
NeverDriven
a PHEVDon'tKnow
Experience with EVs by Respondent
Perc
ent o
f Res
pond
ents
0.1 2.3 3.9
88.4
5.3
Own orPreviously
Owned
Driven aZipcar
EV
NeverDrivenan EV
Don'tKnow
Suggests ~400:1 ratio of exposure per hybrid in service
Users overstate travel distance
31
This is bad news for range-limited vehicles!
0 10 20 30 40 50
0.00
0.05
0.10
0.15
0.20
Actual and Reported Trip Times
Trip Length (hours)
Freq
uenc
y
ReportedMedian(Prior Year)
0 50 100 1500.
000
0.00
50.
010
0.01
50.
020
Actual and Reported Travel Distances
Travel Distance(miles)
Freq
uenc
y
ReportedMedian(Prior Year)
PEV Utility is Distance-Dependent
32
−1.0
−0.5
0.0
0.5
1.0
Piecewise Utility of Distance Interacted with Fuel Type
Reported Reservation Distance (miles)
Util
ity
0 20 40 60 80 100 120 140
GasolineHybridPHEV30EV100
Summary 1. Zipcar is exposing large numbers of
users to alt-fuel vehicles 2. Users are good at estimating time,
frequency but overestimate distance (bad for plug-in vehicles)
3. Plug-in vehicle desirability falls off with travel distance (never positive!)
33