Electric Vehicle Owners Drive Less Than We Thought
Analysis of home electricity usage reveals how much people charge – and therefore drive – their EVs.
Today’s post is co-authored with Fiona Burlig, James Bushnell & David Rapson.
It’s hard to overstate how different the vehicle market will be in 2035 if automakers like General Motors and Volvo stick to their plans to produce mostly electric vehicles (EVs) and stop selling gasoline-powered cars. EVs have been anointed as the replacement technology, but have a long way to go, comprising less than 1% of the vehicle fleet today.
Meeting these lofty goals without imposing serious costs on consumers will require EVs to serve as close substitutes for gasoline cars. But is this the case so far? That’s an important question to answer as California leads the way on this transition and the Biden administration signals its intention to make the shift to EVs nationally. Yet the truth is we are far from understanding how much it will cost to fully transition to EVs.
One way to start to answer this question is to look at how much people are driving their EVs. If households are putting as many miles on their EVs as on their gas-guzzling counterparts, this is a good sign for the EV revolution. On the other hand, if households only drive their EVs sparingly, it might be an indication that current EV technology simply isn’t as good. That could signal more innovation will be needed before consumers will make that switch en masse, or else the switch away from gasoline could be more costly than we hope.
Despite the importance of this question, it turns out to be surprisingly hard to gather comprehensive data on how much EVs are driven (something we have lamented before!). Some researchers have used survey evidence, but these results come from people who are particularly excited to talk about their new EVs and may not represent average drivers. Even California policymakers are choosing to rely on just a few hundred households that have installed a dedicated electricity meter for their EVs to guess the behavior of hundreds of thousands of EV drivers. These meters are costly to install, so the households that install them probably don’t represent average drivers. The financial stakes for the economy are real: these estimates of EV electricity consumption feed into infrastructure planning and determine how Low Carbon Fuel Standard credits are allocated.
Measuring electric vehicle miles traveled
In a new working paper (which we will be presenting at next month’s Energy Institute POWER Conference), we provide the first at-scale estimates of “electric vehicle miles traveled” (eVMT) that represent the overall EV population in California. We combine nearly 12 billion hours of electricity meter measurements—a representative sample of roughly 10% of residential electricity meters in California’s largest utility, Pacific Gas & Electric—with household-level EV registration records from 2014 to 2017 to estimate how much EV charging is occurring at home. We then adjust this result to account for away-from-home charging to retrieve a measure of average eVMT.
We find that when a household gets a new EV, electricity demand increases sharply, and then stays at this higher level. However, the increase we see is less than half the amount state regulators have assumed based on households with dedicated meters: only 2.9 kilowatt-hours (kWh) per day. That translates into about 5,300 miles of driving per year—roughly half as far as regulators’ estimates, and only half as far as people on average drive their gas-powered cars. Lucas found something similar using data from a nationally representative survey, although he’s looking at total miles driven, not eVMT, a distinction that matters for plug-in hybrid electric vehicles.
All told, this suggests that households may not yet view EVs as a good substitute for their gasoline-powered cars and that, unless there are major improvements in EV technology, regulators and policy-makers have more work to do to convince drivers to abandon their gasoline-powered cars for EVs.
Can this be right?
Our estimate has been reported on recently (see, e.g., here, here and here) and a number of people have raised questions about the results. We were surprised by our findings as well, and have taken a number of steps to stress-test them. Here are some of the details behind our estimates:
- But, EV owners also charge away from home. This is important, and we account for it in our estimates. We start by estimating the change in residential electricity use when households install EVs. We convert these estimates into eVMT in two steps: (i) we apply a fuel efficiency conversion (to go from home kWh to home-charged eVMT), which accounts for the fact that 1 kWh translates to different amounts of eVMT across models; and (ii) we use aggregate data on non-residential charging from the California Air Resource Board’s (CARB’s) Low Carbon Fuel Standard (LCFS) program to estimate out-of-home charging. CARB’s data include all nonresidential metered charging that earns an LCFS credit. Charging providers have a strong incentive to report to CARB: these LCFS credits are worth approximately $0.20 – $0.25 per kWh. Thus, we expect these data to cover the bulk of non-residential charging (including, for example, Tesla’s Supercharger network). Non-metered charging is necessarily excluded from these data. Even if non-metered charging were to make up 10% of all non-residential charging, however, our overall annual eVMT estimate would remain under 5,500. Using the CARB data, we calculate that EVs drive around 5,300 eVMT per year. We estimate that 75% of this, or approximately 3,975 eVMT come from at-home charging, and 25% or 1,325 eVMT come from out-of-home charging.
- But, a lot of EV owners have rooftop solar. It is important to
account for solar PV, as approximately 20% of the EV owners in our sample also have solar panels. We observe whether each household in our sample has a solar interconnection and when this interconnection occurred. We find that installing solar PV reduces a household’s (net) kWh consumed by 0.8 kWh per hour on average. We see that this reduction occurs during daytime hours only, giving us confidence that this control is working properly and that we’re accounting for rooftop solar in our estimates. - But, all EVs are not created equally. We recognize this and estimate home charging for three distinct groups of EVs: Teslas, non-Tesla battery-electric vehicles (like the Nissan Leaf and Chevy Bolts), and plug-in hybrid electric vehicles (like the Ford C-Max). Teslas increase household load by 0.24 kWh per hour on average. The non-Tesla battery electric vehicles like Leafs increase load by 0.10 kWh per hour, and the plug-in hybrids like the C-Max increase load by 0.09 kWh per hour. This reflects both the fact that Teslas consume more electricity per eVMT than the other battery electric vehicles and that Teslas in our sample are driven further than other vehicles off of home charging. We account for these differences – and the composition of vehicle types in our sample – when we calculate the average eVMT in the sample.
- But, things have changed since 2017. This is certainly true, and there are reasons to believe that people who bought EVs over the last 3 years may drive them more than people who bought EVs from 2014-2017 (e.g., the newer vehicles have longer ranges, and people who drive a lot and were worried about range waited to buy their EVs). But, we do not see any detectable changes in our results from 2014 to 2017, and some of the same factors were at play over this time period. This makes us think that newer data might not be dramatically different, but we don’t know.
What does this mean for policy?
Whatever the explanation for the lower EV miles driven, there are clear lessons for policymakers. First, EV manufacturers should be required to make eVMT data available to regulators and researchers, so that our results can be replicated in other settings. We spent years gaining access to the data for this study – but this process could be easier. EV manufacturers digitally record data from the cars that they sell – but they haven’t been required to share the information and they have little to no incentive to share it voluntarily. 
Even utilities don’t know how much power is used by the cars in their service territories. Meanwhile, they are spending hundreds of millions of dollars upgrading electricity charging and distribution infrastructure and the companies making these investments, and the regulators approving them, have limited information about where the cars are, let alone how much electricity they are using. For example, in California, revisions to the Low Carbon Fuel Standard allow vehicle manufacturers to claim “incremental” credits for the electricity their cars use, but these regulations are set up in ways that continue to keep key decision makers out of the loop. We would support rules that require the car manufacturers to report usage data to all of the relevant government agencies. This could be made a condition for qualifying for publicly supported incentives. We also believe that agencies should be able to share such data with researchers (under confidentiality arrangements) who will perform analyses that are critical to improve EV policy.
Second, much more policy innovation is needed to move 100% of road travel to electric. Rather than relying on bans and mandates to sell EVs, we could try giving drivers the right incentives. Pricing vehicle emissions would be a good start. At the moment, incentives are backwards. Electricity prices in the United States are low where the grid is dirtiest and high where the grid is cleanest. Some EV owners in California pay several times more to charge than their neighbors due to the vagaries of utility service territory boundaries. This is both inefficient and unfair.
Collectively, we are only beginning to learn some of the most basic facts about the costs and benefits of transportation electrification. To inform efficient policy decisions going forward, we must democratize access to key data sources (like eVMT and charging behavior), acknowledge the fact that there is much we do not yet know, and create conditions that allow us to course-correct as new information becomes available.
Keep up with Energy Institute blogs, research, and events on Twitter @energyathaas.
Suggested citation: Burlig, Fiona, Bushnell, James, Rapson, David and Wolfram, Catherine. “Electric Vehicle Owners Drive Less Than We Thought” Energy Institute Blog, UC Berkeley, February 16, 2021, https://energyathaas.wordpress.com/2021/02/16/electric-vehicle-owners-drive-less-than-we-thought/
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Catherine Wolfram View All
Catherine Wolfram is the William F. Pounds Professor of Energy Economics at the MIT Sloan School of Management. She previously served as the Cora Jane Flood Professor of Business Administration at the Haas School of Business at UC Berkeley. From March 2021 to October 2022, she served as the Deputy Assistant Secretary for Climate and Energy Economics at the U.S. Treasury, while on leave from UC Berkeley. Before leaving for government service, she was the Program Director of the National Bureau of Economic Research’s Environment and Energy Economics Program, Faculty Affiliate of the Energy Institute at Haas from 2000 to 2023, as well as Faculty Director of the Energy Institute from 2009 to 2018. Before joining the faculty at UC Berkeley, she was an Assistant Professor of Economics at Harvard. Wolfram has published extensively on the economics of energy markets. Her work has analyzed rural electrification programs in the developing world, energy efficiency programs in the US, the effects of environmental regulation on energy markets and the impact of privatization and restructuring in the US and UK. She is currently working on several projects at the intersection of climate and trade. She received a PhD in Economics from MIT in 1996 and an AB from Harvard in 1989.
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Aren’t we in danger here of missing the forest for the trees? If the main driver for moving to EV’s is dramatically reducing the greenhouse gas emissions in the transportation sector in a very short period of time, then it seems to me that this is not a question of economic optimization but a question of how to get from where we are to where we think we need to be quickly, taking advantage of what technologies we have, pushing hard for research on new technologies (which I think is batteries and charging cycles in the near and intermediate term) and building infrastructure to support the new paradigm (e.g. charging stations). As far as I can tell, much of the economic churning around these questions doesn’t do much to accommodate for the importance of what is largely an external issue – moving away from fossil fuels and their global climate change impacts.
From personal experience, I offer one data point (how many personal data points does it take to make an anecdote??). We just bought a plug-in hybrid SUV – the Subaru Crosstrek, which with the PG&E rebate (which I think is now gone) and the federal tax credit, brought the price down to about what an ICE-only Crosstrek would cost… For us, it was a question of whether there is currently enough infrastructure to support camping trips to the desert Southwest driving a fully electric SUV (as one example). On the other hand, a large fraction of our current car use is short, ‘running errands’ trips – so a plug-in hybrid seemed like a good compromise (we’re both retired). We still have not purchased any gasoline after about 550 miles (I think there is a quarter of a tank left). The Crosstrek has only a small electric-only range – 17 miles, so we plug it in about every third day (5 hour charge on 110 VAC). The ‘fuel’ cost per mile is about $0.13/mile at our marginal PG&E rate of $.30/kWh – which compares to $0.12/mile for an ICE getting 30 mpg and gasoline cost of $3.50/gal.
This is an interesting result. Given the difficulty in finding appropriate data, I assume there is a large degree of uncertainty in it but the effect they report is so large it seems sure to be significant — change the “half” in “roughly half as far as regulators’ estimates, and only half as far as people on average drive their gas-powered cars” and you don’t really change the import, IF one knows what it means, or what kind of vehicles it applies to. Consider some different interpretations:
1a) “In the period of record, EVs were only driven about half as many miles per vehicle as ICE vehicles”
1b) “Because they are electric, EVs will only be driven about half as many miles per vehicle as ICE vehicles”
2a) “Electric cars are mostly used as second cars and DO not displace the majority of ICE uses”
2b) “Electric cars will always mostly be used as second cars and WILL not displace the majority of ICE uses”
3a) “Electric cars with ranges under 150 miles are only driven X% as much as ICE vehicles”
3b) “An electric car is only driven X% as frequently as an ICE car irrespective of trip lengths”
3c) “An electric car is only driven X% as frequently as an ICE car
Whether X is 50 or 75, I would accept that the paper shows (1a). It is unlikely that it shows the pretty extreme statement (1b) (the Tucker Carlson version?).
The question “Paul” raises is whether the population of EVs examined is different from the population of ICE cars, because they are “second cars”. The Working Paper says the authors had access to DMV data on registrations from 2008-2019 including address and “unique vehicle identifier” (VIN?). Since they were comparing addresses with utility bills they should be able to tell apart apartments with a common street address and they should be able stratify their data based on the presence of a second vehicle to answer that question.
The second question that arises is whether EV type was important. As “Paul” also notes, there are some trips on which a Leaf will not be taken because it doesn’t have the range; but a Tesla would be. You might not even take a Tesla cross-country, but you’d probably be more likely to take a Tesla than a Leaf or Bolt from Berkeley to Sacramento and back to testify at the CEC! The authors have looked at this kind of distinction — “Teslas in our sample are driven further than other vehicles off of home charging.” Do they have enough Tesla data, for example, to characterize Teslas separately? If so, it may be that the data supports something like (3a) better than (1a). If they don’t have enough Tesla data then Richard McCann is probably right that that study is not applicable to “modern” EVs.
Finally, national average VMTs are used as the standard of comparison; do California vehicles have similar annual usage? I don’t know. Yes, there are long distances in California — it’s a long way from San Diego to Susanville or even (staying in the SoCal metroplex) from Santa Monica to Riverside but that doesn’t mean people frequently take their cars on those trips. (It also doesn’t mean they don’t.)
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Thank you for the article: this is a very interesting subject! It makes me wonder if the lower EV miles driven could be partially a result of self-selection of people buying EVs. I would assume that most households buying EVs have middle or high income, and can therefore afford living closer to work (eg people living on Manhattan will drive their EVs to work less than people who live in other lower-income boroughs and drive their more affordable fuel cars to work on Manhattan). Is there data to control for how close the EV owner lives to his place of work?
Studying a sample of cars produced several years ago may not be representative of the driving behavior for cars purchased today. This article notes that the Leaf, Bolt, E-Niro of today have much more range than the early Leaf, Focus, and 500Es that made up the pre-2017 non-Tesla “compliance: fleet. Those early cars got us started, but are now available cheap from dealers like Paramount Motors. https://www.paramountmotorsnw.com/
But for many who now own the early compliance cars, that limited range may be just fine. My neighbor bought one for her six-mile commute as a teacher. A 2011 Leaf, with 32,000 miles on it, for $6,500, was a terrific buy. Reliable, quiet, cheap to drive, and an ability to be “cool” at her school (for 10% of the cost of a dual-motor Tesla with 300 miles of range) is a good choice. Her household also has a Forester for longer-range driving. The Leaf makes a terrific “second can.”
It’s probably incorrect to compare EV mileage from early cars to the national or state “average” of VMT. First, the “mean” has some long-tail effects of fleets, taxis, parts-runners, and other very high mileage cars; the median may be a more useful figure. Second, many EV drivers are wealthy retirees (all three of my friends who drive Teslas fall in this category), who probably as a group do not drive very much.
Finally, very few EV drivers have any desire to be “average” in any way.
It may be important to measure actual input electricity to an EV rather than the claimed miles/kwh. We are getting just 2.8 miles/kwh input electricity as measured with a watt meter in the charging line to our 2011 Nissan Leaf. However, the internal calculator on the Leaf insists we are getting 4.3 miles/kwh, a large discrepancy. Now with colder weather in the very mild San Francisco east bay the average has dropped to 2.6 miles/kwh as we are using the car heater. This means that it is important to measure the input electricity used to charge the EV, not just what the EV calculates it is using for power. We are driving the Leaf just 5-6,000 miles per year just for local trips mostly for shopping as its effective reliable range is only about 30 miles.
Our other car is a 2017 Toyota Prius that we were driving long trips in and averaging 22,000 miles/year prior to Covid. In order for us to replace this with an EV for long trips we would have to have a reliable range of a minimum 300 miles between charges, preferably 400 or more, with recharge times of at most a few hours. If the range is 500 miles then the charging time could be six hours or more overnight. Therefore, until this range and charging time is improved, we will not replace the Prius with an EV.
Our 2011 Nissan Leaf was bought used with only 33,000 miles on it and 9 batter bars available. We use an extra 5.5 kwh/day and added extra solar panels to our house to account for this increase, so in principle our annual electricity input from the grid is zero. The battery is gradually deteriorating and over the last 4,000 miles the battery bars available have dropped to 8. Even if the car becomes unusable for short trips with a deteriorating battery, we have enough property to keep the car just as battery backup if vehicle to grid (V2G) becomes available. This would allow us to use the battery power when electricity rates are higher. Surprisingly, the cheapest storage battery is a used Nissan Leaf.
“But, we do not see any detectable changes in our results from 2014 to 2017, and some of the same factors were at play over this time period. This makes us think that newer data might not be dramatically different, but we don’t know.“
The timing of this study reminds me of trying to analyze cell phone use in the mid-2000s. Now household land lines are largely obsolete, and we use phones even more than we did then. The period used for the analysis was during a dramatically changing period more akin to solar panel evolution just before and after 2010, before panels were ubiquitous. We can see this evolution here for example: https://www.cnn.com/interactive/2019/07/business/electric-car-timeline/index.html.
The primary reason why this data set is seeing such low mileage is because is almost certain that the vast majority of the households in the survey also have a standard ICE vehicle that they use for their extended trips. There were few or no remote fast charge stations during that time and even Tesla’s had limited range in comparison. In addition, it’s almost certain that EV households were concentrated in urban households that have a comparatively low VMT. (Otherwise, why do studies show that these same neighborhoods have low GHG emissions on average?) Only about one-third of VMT is associated with commuting, another third with errands and tasks and a third with travel. There were few if any SUV EVs that would be more likely to be used for errands, and EVs have been smaller vehicles until recently.
As for solar panel installation, these earlier studies found that 40% of EV owners have solar panels, and solar rooftop penetration has grown faster than EV adoption since these were done.
Click to access California%20Plug-in%20Electric%20Vehicle%20Owner%20Survey%20Report-July%202012.pdf
Click to access producer%2F2013-UCD-ITS-RR-13-02.pdf
Click to access 2017-Delmas-Kahn-Locke-ResearchinEconomics.pdf
I’m also not sure that the paper has captured fully workplace and parking structure charging. The logistical challenges of gaining LCFS credits could be substantial enough to not bother.
A necessary refinement is to compare this data to the typical VMT for these types of households, and to compare the mileage for model types. Smaller commuter models average less annual VMT according to the CEC’s VMT data set. This analysis arrives at the same findings that EV studies in the mid 1990s found with less robust technology. That should be a flag that something is amiss in the results.
That is a better question for vehicle mileage overall. It does not seem relevnt to this study right now.
I’m surprised that this paper expresses ‘surprise’ at the EV mileage findings. First, prior papers on EV’s from the Institute have already documented that those purchasing EVs have ‘above average’ incomes, which is also consistent with federal and state tax credit incentives which favor higher incomes. It might be expected that higher income individuals would also be more than likely to live closer to their area of employment and also own multiple vehicles, where non-EV vehicles would be used for longer duration travel.
Second, it was disturbing to see in your introduction the statement that the incentives to push more EV sales goals could only be met by “imposing serious costs on consumers”. Your partial redemption came late in your presentation when you stated that “Rather than relying on bans and mandates to sell EVs, we could try giving drivers the right incentives”. Great point! Unfortunately, you then revert back to punative incentives by suggesting the need for additional emission penalties (which will punish all consumers) and strangely, better electricity pricing that seems to favor clean rather than dirty generation.
Better electricity pricing is absolutely necessary but be careful what you wish for when it comes to EV’s. The recent paper by Severin Borenstein might not prove completely supportive of EV’s especially when the cost of distribution and other grid improvements to support increased demand from EV’s is factored in.
Finally, if the economic policy focus is on carbon reduction, why the focus on EV’s and not on more reliable, cleaner long term generation options like hydro and nuclear?
How much has domestic vehicle mileage generally gone down in the US as a result of Covid-19? Indications in the UK are that the fall has been quite significant, due to lower commuting.