Household Level Analysis of PEVs 68
A crucial aspect, which is often overlooked in majority of PEV usage studies in literature as well as in the
policy realm, is the household (HH) context. While evaluating travel behavior and emissions implications
of PEV adoption, household context is pivotal because day-to-day activities are allocated between PEVs
and the other vehicles in the household on a per-trip basis at disaggregated temporal levels.
Furthermore, in a survey of 15,000 PEV owners in California, roughly 45% of BEVs and 42% of PHEVs
belong to two-car households(Turrentine and Tal 2015, Nicholas, Tal et al. 2017). PEVs have unique
features that will alter how they are driven and charged compared to ICEs. Depending on travel needs,
individual driver preferences, fuel, and electricity costs, charging access and opportunities, VMT by the
PEV has cascading effects on VMT of other household vehicles. Apart from the quantity of miles, it is
also important to account for the derived impact of miles (GHG/mile) PEVs substituted at the household
level. Therefore, studying PEV usage in isolation may lead to inaccurate estimates of their net
environmental impacts, since it is based on partial information.
To ensure parity when comparing different PEV households, we excluded households that have more
than 1 PEV of the same type, irrespective of the number of ICEs in the household (for example a 3-car
household with 2-Leaf and one ICE or a 2-car household with 2 Volts were dropped). Furthermore, to
understand substitution and emission profile at the household, the sample size of the household was
limited to single PEV(BEV or PHEV), single ICE-PEV(ICE-BEV or ICE-PHEV), double ICE and single PEV (ICE-
ICE-BEV or ICE-ICE-PHEV), and household with both BEV and PHEV (BEV-PHEV or ICE-BEV-PHEV). The
above selection criteria was deemed fit because 65% of California households have 2 or less vehicles ;
16% of California households have 3 vehicles(McGuckin and Fucci 2017). Since only 9% of California
households have 4 or more vehicles (McGuckin and Fucci 2017), we excluded households and the
respective vehicles with 4 or more vehicles from our analysis. In addition, as outlined in Section 3, the
BMW i3 REX and its households were excluded because the logger could not acquire any data from
them. Out of the 364 Households that were logged, 61 households were dropped which accounted for
all the BMW i3, Soul EV, and Audi Etron households as well as any households with over three vehicles
or an extremely low share of PEV/ICE driving days.
The sample size of PEVs used in the household level analysis differs from the sample size referred in
Table 3-Table 6 simply because of excluding the households and their vehicle holdings due to household
car ownership patterns exceeding the 3 and/or the type of vehicles belonging to the household (double
BEV or PHEV of the same type). In our household (HH) level analysis, there are 117 BEVs (21 Leaf-24, 25
Leaf-30, 27 Bolt-60, 19 Tesla Model S-60_80, 22 Tesla Model S-80_100, and 3 RAV4 EV-42) and 197
PHEVs (20 Prius Plug-in-4.4, 50 C-max/Fusion-7.6, 26 Prius Prime-8.8, 26 Pacifica-16, 41 Volt-16, and 34
Volt-18). The total household level sample size is 303.
Table 15 summarizes the multi-PEV HHs with and without an ICEV. Approximately 60% of the HHs in our
study had two-vehicles, 30% had one vehicle, and 10% had three vehicles. Out of the 85 single-vehicle
HHs, 63 had a PHEV and 22 had a BEV. Referencing Figure 55-Figure 56, Of the 190 two-vehicle HHs, 111
have an ICEV and a PHEV, 72 have an ICEV and a BEV, and 7 had a BEV and PHEV. Among the 28 HHs
with three-vehicles, 12 had two ICEVs and a PHEV, 12 had two ICEVs and a BEV, and 4 had an ICE, a BEV,
and a PHEV. Overall, 96% (292 out of 303) of the HHs had only one PEV (BEV or PHEV). There were 85
single-vehicle HHs with only a BEV or a PHEV, 183 two-vehicle HHs with an ICEV and a PHEV or BEV, 24
three-vehicle HHs with a PEV and two ICEVs, and 11 multi-PEV HHs (with and without an ICEV).
Summary statistics and results presented in Table 15 – Table 24 and depicted in Figure 55 – Figure 72
are based on the logger data.
Compared to the vehicle level analysis, where we focused on the days when the PEV was driven or
charged, in the HH context, it was important to have parity in terms of the number of days each vehicle
was logged within each HH as well as across different HHs. When comparing two HHs with the same