The Data Behind EV Driving

Posted on Jan 2, 2023

Presentation Video

Debunking Common Electric Vehicle Myths with a Self Collected Dataset


This past February, my wife and I purchased a fully-electric 2019 Chevy Bolt with an EPA estimated range of 238 mi. None of our friends and family had an electric vehicle, so before our purchase, we scrounged around for information about EVs, trying our best to learn the new terms and adapt to the new change in lifestyle. Despite – or maybe due to – our extensive research, we still felt confused by the competing narratives about ‘going electric.'

The vehicle we purchased was advertised as having :

  • 238 EPA-Estimated Miles of Range
  • 66 kWh Battery
  • 200 Horsepower

But we were concerned about what we’d heard about EVs because three myths have been perpetuated:

  • Myth #1: EVs can't drive very far, which means I could get stuck on the side of the road.
  • Myth#2: The cold weather will limit the battery range in the wintertime.
  • Myth #3: My electric bill will go through the roof charging an electric vehicle at home.

Despite those concerns, we bought the car. However,  I felt I needed to investigate further to ascertain if the myths were based on facts.  To that end, I purchased a device to collect data coming out of my car to analyze.

Data Collection Process

The private data available to everyday users has significantly increased over the past 10 years, especially with the proliferation of Internet of Things (IoT) data collection devices. Individual users now have the power to collect their own data, from wearable fitness devices tracking their heart rate to smart plugs monitoring electricity usage.

For my project, I used an OBDII reader to extract data from every trip made with the car and send it to an online account. This device demonstrates how someone can collect data from an everyday object, like a car, and use it to improve their performance and understanding of that object.

On February 24, 2022, I plugged the OBDII reader into my car and extracted the entire dataset on December 1, 2022. The device logged a trip each time the car was turned on and off, and it remained plugged into the car the entire time.

A small black and blue electronic device plugged into the obd2 port of a car, located near the footwell of the driver's seat in a car.
The OBDII Reader I used to collect my dataset.

I was able to collect the following data points for every trip:

  • start and end times
  • Distance driven, in miles
  • Electricity consumed, in kWh
  • Battery percentage at the start and end of the trip
  • Outside temperature

GPS location data was not included in this data collection process. My device did not have this functionality.

The Dataset


After some cleaning and formatting, here is what the first few rows of the data frame looks like:

a dataframe screenshot

Summary Stats

  • The dataset took place over the course of 280 days.
  • There were 1,092 trips.
  • The total mileage was 17,400 miles.
  • The temperature range was 23°F - 100°F.
  • A total of 4,251 kWh was consumed.
  • Average mileage per day was 67.4.
  • Daily trips averaged to 3.69 trips/day.

Now that I have collected this awesome dataset with over 1,000 observations, I can start to address the myths stated above:

Myth #1

  • Myth #1: EV's can't drive very far and I could get stuck on the side of the road.
  • Myth#2: The cold weather will limit the battery range in the wintertime.
  • Myth #3: My Electric bill will go through the roof charging an electric vehicle at home.

According to the US Federal Highway Administration the average American drives 13,476 mi/year or 36.92 mi/day. Compared to my total of 17,400 mi/year and average of 67.4 mi/day, I'm nearing twice the average American and would classify myself as a "Frequent Driver," given my above-average mileage.

Before I had an electric vehicle, I had the same worry: that I wouldn't have the vehicle range for my daily/weekly mileage needs. But the data clearly shows I have plenty of vehicle range for my "Frequent Driver" lifestyle.

On average, I started every trip with 73% battery status and end every trip with 66% battery. That equates to 216 miles of range to use at the start of every trip and 199 miles of range left after every trip. Maybe this says more about my preparedness, but I clearly had a lot of range to use on the regular. The longest stint I drove out of all the trips was 177.48 miles. The longest distance I drove in a day was 351.69 miles. Additionally, there were 25 trips that lasted 90 miles or more.

This data shows the Chevy Bolt can drive very far, and has a lot of range that can meet my needs for both daily use and long trips. However, I do have to add two caveats:

  1. I was able to achieve that consistency of "State of Charge (SOC)" because I can plug my vehicle in at home. Not everyone has that luxury.
  2. Those long trips required one stop in the middle to recharge at a fast charging station, where we would spend 30-80 min charging depending on temperature outside.

"...and I could get stuck on the side of the road"

There is a very low chance of getting stuck on the side of the road. Out of all 1,092 trips, I only ended trips with less than 5%, twice, meaning I rarely was in the situation where I could possibly get stuck on the side of the road. Anecdotally, this feels like the same chance I would have with pushing the range of a gas car. The only big difference is that, though both a  gas car and an electric car getting stuck on the side of the road would have to wait 30-120 minutes for a tow truck, the gas car could receive its gas instantly and then proceed., In contrast,the  EV would require a tow to the nearest charger (at least until tow trucks become more regularly equipped with battery charging equipment) and then take another half an hour to get recharged..

The stakes are just different, and there is a mindfulness and lifestyle shift to consider when switching over to an EV.

The Verdict


Myth #1: EV's can't drive very far and I could get stuck on the side of the road BUSTED.

My data has shown:

  • On average, I consistently have enough range to drive where I need to.
  • The car has the ability to drive on long car trips.
  • The chance of getting stuck on the side of the road is very low.

How Efficient is My Car?

Exploring the first myth got me thinking about how efficient the Bolt is. On all 1,092 trips this past year, I averaged an efficiency of 4.5 mi/kWh. I wondered if there was anything in particular that could affect that efficiency.

  • Maybe distance has an effect on efficiency. If I drive farther, will the car be more “fuel efficient?"
  • Maybe time of day has an effect on efficiency. If I drive in the morning, will the car be more “fuel efficient?"
  • Maybe temperature has an effect on efficiency. If I drive in warmer temperatures, will the car be more “fuel efficient?"

Let’s go on a brief side-quest to explore the dataset a bit deeper to address each of those ideas before proceeding to explore Myth #2.

Distance vs. Efficiency

  • Maybe distance has an effect on efficiency.

  • Maybe time of day has an effect on efficiency.

  • Maybe temperature has an effect on efficiency.

Here is a histogram showing different groupings of distances I drove over the past year. They are grouped into bins of around 10 miles.

On the left side of the graph, you can see that a vast majority of the trips took place in the 0-10 mile trip range. Let's break this data up into three areas: short, medium and long trips. That way we can get a better sense to see if there is any correlation between distance driven, and how efficient the car is.

Distance definitions:

  • Short Trip: < 3.3 mi
  • Medium Trip: <3.3 mi & < 18 mi
  • Long Trip: > 18 mi


Visually looking at this graph, there doesn't seem to be a strong correlation between improving efficiency and distance. There is no overall trend up or down. What we can conclude is that the farther you drive, the more focused the range of efficiency is. You can see visually from left to right that the dots become more focused around the 3.5-5 mi/kWh range. This means that the farther you drive, the more predictable your energy efficiency will be. 

The above graph can be improved as the x-axis scale is too condensed in the 0-25 mi trips. I have applied a log transformation to the x-axis to make all of the points equally visible and better understand the grouped trend lines.  



Time of Day vs. Efficiency

  • Maybe distance has an effect on efficiency.

  • Maybe time of day has an effect on efficiency.

  • Maybe temperature has an effect on efficiency.

Time of day definitions:

  • Wee Hours: 12am - 6am
  • Morning: 6am - 12pm
  • Afternoon: 12pm - 6pm
  • Night: 6pm - 12am

The line in the center of each of the boxes represents the median value of the grouping.

 There does not seem to be a huge effect on efficiency based on time of day. The spread of median values ranges from 3.8 to 4.1, but I'm not sure that the time of day is the primary driver of that correlation. It’s tough to say what is going on here, but I think that there is a story about efficiency ranges again. The Afternoon grouping seems to have the greatest range in efficiency.  It cannot be concluded purely from visuals, but I could hypothesize that afternoons have the greatest range in efficiencies because that group has the largest amount of data points, or maybe it's because traffic is most prevalent in the afternoons, therefore, skewing the data. I don't want to get hung up on this, but thought the exploration was notable enough to include. 

Temperature vs. Efficiency

Let’s expand the third part of this side quest as a way to transition into exploring the Myth #2.

  • Maybe distance has an effect on efficiency.

  • Maybe time of day has an effect on efficiency?

  • Maybe temperature has an effect on efficiency.

Myth #2

  • Myth #1: EV's can't drive very far and I could get stuck on the side of the road.
  • Myth #2: The cold weather will limit the battery range in the wintertime.
  • Myth #3: My electric bill will go through the roof charging an electric vehicle at home.

This was the myth I was most worried about! I heard a lot about this leading up to the purchase of my vehicle, and there wasn't a lot of data on this for the Chevy Bolt. There were a lot of people crowdsourcing data for Tesla vehicles, but there seemed to be a lack of information regarding range loss for the Bolt. 

I've created an exploratory scatter plot with a linear regression line overlaid to get a sense if there is any correlation between mi/kWh and Temperature. 

There seems to be a slight positive correlation and the concentration of points seems to tend toward a higher efficiency as it gets hotter. Now I will take it one step further and break this dataset into 3 groups: 

  • Hot: > 70°F
  • Normal:  40°F - 70°F
  • Cold: < 40°F

The above chart shows that colder temperatures negatively impact how efficient the car runs. There is a 1.07 mi/kWh difference between the average warm trip vs the average cold trip. 

How Much Efficiency is Lost in the Winter Time?

In trips taken in temperatures below 40°F, an average of 70 miles is lost due to cold temperatures. 

cold avg: 3.49 mi/kWh
cold range: 230.55 mi
norm avg: 4.23 mi/kWh
norm range: 279.12 mi
warm avg: 4.56mi/kWh
warm range: 300.99 mi

The Verdict


Myth #2: The cold weather will limit the battery range in the wintertime CONFIRMED. 

My data has shown: When temperatures are lower, the car performs less efficiently and can't drive as far compared to warmer temperatures.

Myth #3

  • Myth #1: EV's can't drive very far and I could get stuck on the side of the road
  • Myth #2: The cold weather will limit the battery range in the wintertime
  • Myth #3: My electric bill will go through the roof charging an electric vehicle at home

In order to address this myth, I will need to append two new data sources to my trip dataset.

  1. Gasoline price data for NY in 2022
  2. Electricity prices for my home in 2022

Gas Prices

I was able to source weekly average gas prices from the US Energy Information Administration. I then converted this weekly data into repeating daily values and merged that onto my original dataset. I filtered the data to NY, Regular gas prices in the year 2022.

Here is what 2022 gas prices looked like:

Electricity Prices

My Chevy Bolt plugged into my home charging setup.

Most EV drivers end the day by plugging their car into their home and paying whatever electric rate they are billed to recharge their car. During the past three years, electricity rates have varied a great deal, so it's understandable why this myth exists.

My utility company changes the rate it charges every month. An additional complication is that they deliver the bill in .pdf form. In order to collect the data, I had to scrape all of my ConEd pdf's for the following:

  • Date Range

  • Supply Charge Rate kWh

  • Delivery Charge Rate kWh


After scarping the data from all of the pdf's, I now have an electric rate to easily compare to any day of the year.

I appended the gas and electric data to the Trip Dataset according to the date the trip was taken. But I am missing one big piece of the puzzle; I do not have equivalent trip data recorded on a gas vehicle to compare to my Bolt EV. Moving forward, I will estimate the MPG of my other car -a 2005 Toyota Corolla, which gets an EPA estimated 29 MPG. It's a rough assumption, but I think it's fair, because if we didn't have our Chevy Bolt, we would drive the Corolla on these same exact trips.

Now I can calculate cost per trip in the Bolt versus a 29 MPG gas car.

Electricity Cost

The cost of all of my trips compared with the price of electricity:

Total Cost: $1,038.78/year

Average Cost: $0.95/trip

Gas Cost

The cost of all my trips if I was driving my Toyota Corolla at 29 MPG:

Total Cost: $2,498.94/year

Average Cost: $2.29/trip

That's more than twice the yearly cost. 

If I wanted a gas car to perform at the same cost performance as my Bolt, the gas car would have to get 70 MPG in order to match that $1,038.78 total.


The Verdict


Myth #3: My electric bill will go through the roof charging an electric vehicle at home BUSTED.

My data has shown:

  • Charging and EV at home does increase the electric bill
  • However, there is a significant cost savings overall compared to an average gas vehicle


After collecting my own data with over 1,000 observations over the course of almost a year, I was finally able to demystify those myths and better understand my Chevy Bolt, as well as the electric vehicle lifestyle. 

BUSTED - Myth #1: EV's can't drive very far and I could get stuck on the side of the road

  • On average, I had 73% battery and 219 miles of range at the start of every trip.
  • The longest single stint I drove was 177.48 miles.
  • The longest I drove in one day was 351.69 miles.

CONFIRMED - Myth #2: The cold weather will limit the battery range in the wintertime

  • In trips that took place in temperatures below 40°F, an average of 70 miles is lost due to cold temperatures. 
  • There is 1.0 mi/kWh difference between temperatures above 70°F and below 40°F.

BUSTED - Myth #3: My Electric bill will go through the roof charging an electric vehicle at home

  • It is cheaper to charge your car at home than to fill up a gas car.
  • The average trip in a gas car costs $2.29, and the average trip in an electric car costs $0.95.
  • The total cost of electricity for my Chevy Bolt was $1,038.78.
  • The total cost of gas for a 29 MPG car mapped over my EV Trip data was $2,498.94.

Future Ideas

The scope of my project could be expanded to include the following ideas in the future:

  • Merge my trip data with my Google Maps timeline to get access to geographic data. This would require some tricky approximate DateTime matching and wouldn't be one-to-one as I don't always use GPS.
  • Start the data collection again, but this time with an upgraded OBDII sensor to collect GPS data.
  • I could look at elevation changes and compare them to my trip data.
  • I could also pull the data from charging on-the-go trips, and compare those costs to my at-home costs.
  • I might also consider different living situations. My data is very skewed to the fact that I could pull into my garage every night and charge my car. This large assumption means these conclusions don't all apply to someone who lives in an apartment and needs to use public chargers all the time. I could also consider different areas of the US, different temperature ranges, climates, and elevation changes.
  • I could also replicate the study across many cars and collect a whole database of information about a fleet of different cars, akin to what Consumer Reports does.

Data Sources

My Chevy Bolt Trip Dataset - Hosted on my GitHub

US Federal Highway Administration

US Energy Information Administration

Cover Photo: Photo by Alex Ralston





About Author

Brian Ralston

Experienced Data Scientist and Database Administrator with 3 years experience in SQL, Python, and R. Strong understanding of data warehousing, modeling, mining techniques, and dedicated to staying up to date with the latest technologies and industry trends. Excited...
View all posts by Brian Ralston >

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