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Discussion Starter · #1 ·
I did a little data analysis and thought it might be interesting to some here. I pulled the daily temperature data (average, high and low) at the Philadelphia International Airport weather station (which is sort of the mid-point of my husband's daily commute). I graphed that against the amount of energy required to restore our XC40 Recharge to its charging set point after each there-and-back 52 mile total commute.
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footnotes:
1. Charging data taken from statistics reported by Wallbox Charging Station. Temperature data taken from NOAA.
2. I only included charging data points for dates when I am reasonable sure the only travel done was the 52 mile commute. Since the Volvo App for the AAOS system lacks the trip journal feature, I had to use my judgement about which dates to include and discard (I did compare against my calendar of events, and discarded any date when were likely to have used the XC40 Recharge to take an extra trip).
3. Dates where no charging took place obviously have no data point. Extended gaps in data represent periods in which we were not using the XC40 Recharge (days off work, extended period of travel, etc.).
2. I have decided not to include precipitation and windspeed data, which made the plot overly complex and difficult to interpret.
 

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Discussion Starter · #2 · (Edited)
energy consumed (over 52 mile commute) v. average temperature

linear line of fit (with 95% confidence band)
Y = -0.1523*X + 28.55
R^2 = 0.7324
I attribute the large scatter to secondary factors — wind, precipitation, snow and ice on roadways at lower temperatures, traffic variability, etc.
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Fantastic data! Thanks for sharing!
 

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Nice. Thanks for sharing. My observations of our xc90t8 shows the best range/efficiency when temperature is up in the 70s and 80s. I laughed a little bit when the data only went down to 20F. EVs really do like the warmer weather.
 

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2022 XC40 Recharge Twin Fusion Red
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MMMM. We engineers love data! Thanks for posting! :)
 

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energy consumed (over 52 mile commute) v. average temperature

linear line of fit (with 95% confidence band)
Y = -0.1523*X + 28.55
R^2 = 0.7324
I attribute the large scatter to secondary factors — wind, precipitation, snow and ice on roadways at lower temperatures, traffic variability, etc.
View attachment 4329
Great info. What speeds were you travelling speeds? Highway speeds or surbaban speeds. I calculated range from your data to be between 283km to 395km at 86F
 

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2022 XC40 Recharge Twin Fusion Red
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OK, we've been keeping track of every charge/trip, and disappointingly I found no decent correlation between efficiency and temperature, or efficiency and speed. Couple plots below. We've driven just over 10,000 km since we bought the car (2022 XC40 Recharge Twin "ultimate" with 20-inch wheels) in late September 2021 in Australia. We had a mild summer and we live at an elevation of about 650 m in a cool climate region to the northwest of Melbourne. The plots below represent about 130 individual data points/charges. The average temperature was just below 15 C. Our overall average efficiency is 22.2 kWh/100 km (35.7 kWh/100 miles). We typically set the cruise control at the speed limit and drive conservatively. We always have OPD switched on. Most of our driving is rural 80-100 kph roads, with some 100-110 kph freeway driving. We recently did a 1400 km road trip on mostly 110 kph freeway (averaged about 24.7 kWh/100 km on the trip, so a bit worse than our long-term average). As you can see below the E-squared value on each of the trend lines is low, indicating a poor correlation. May be of interest! 2 engineer household so we love data, even if it doesn't really prove a point! ;)
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How does one keep track of this data? Are you pulling it from the car? Or is this just something you need to manually catalogue and then put into a spreadsheet or something to get the graph?
 

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How does one keep track of this data? Are you pulling it from the car? Or is this just something you need to manually catalogue and then put into a spreadsheet or something to get the graph?
It's a bit tedious, but before each charging session, we take a photo of the instrument cluster trip statistics, and we reset that after each charge, and take a pic of the charge % when the charge finishes so we know what the starting charge is for the next trip. We also record the amount of kWh going into the car at each charge - either from the charge station or at home we use an energy meter. Very manual system and we enter it all into a spreadsheet. Examples of pics below to record the data.
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Discussion Starter · #14 · (Edited)
I have converted my data to normalized consumption per distance v. temp (to align with @Greg S and because it's better reporting)

(in Americatown units)
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(in sensible units for the rest of the world)
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Discussion Starter · #15 ·
@Astus This particular commute is approximately 9% city, 91% highway (sometimes with congestion and stop-and-go traffic)

@Greg S Our car has a heat pump. What about yours?

@DreamensioN I pull the consumption data from the app for our wall charging station. It doesn't have an export option so it is a bit of tedium, but it's nice to have the numbers.
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@Astus This particular commute is approximately 9% city, 91% highway (sometimes with congestion and stop-and-go traffic)

@Greg S Our car has a heat pump. What about yours?

@DreamensioN I pull the consumption data from the app for our wall charging station. It doesn't have an export option so it is a bit of tedium, but it's nice to have the numbers.
View attachment 4366
Yes we have a heat pump. It looks like you converted the wrong way when converting to kWh/100 km...should be divide by 1.6...looks like you multiplied by 1.6? But yeah, you have much better correlation. Not sure why our correlation is so poor...it may have to do with the type of driving we do is so varied and the temperature has been predominantly around 10C...with very few high-temp days as we had a cool summer.
 

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Discussion Starter · #17 ·
Yes we have a heat pump. It looks like you converted the wrong way when converting to kWh/100 km...should be divide by 1.6...looks like you multiplied by 1.6?
Oops quite right. Had a multiply instead of a divide that carried into both. Fixed that! I haven't had my brekky yet 😃
 

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Oops quite right. Had a multiply instead of a divide that carried into both. Fixed that! I haven't had my brekky yet 😃
Hmm, something still not quite right. The upper graph (kWh/100 mi) was correct originally, now the values for kWh/100 km seem way off (ranging from .0035-.006? Should't it range from about 35-60 kWh/100 mi). Then the corresponding lower graph of kWh/100 km should be roughly a range of 20-37.5 kWh/100 km. Just having breakfast here so maybe my brain is still a bit fuzzy too.
 

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Discussion Starter · #19 ·
Hmm, something still not quite right. The upper graph (kWh/100 mi) was correct originally, now the values for kWh/100 km seem way off (ranging from .0035-.006? Should't it range from about 35-60 kWh/100 mi). Then the corresponding lower graph of kWh/100 km should be roughly a range of 20-37.5 kWh/100 km. Just having breakfast here so maybe my brain is still a bit fuzzy too.
Jesus, it's a good thing I'm not turning this in for a grade or anything 😂
I think I made it all right now
 

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Jesus, it's a good thing I'm not turning this in for a grade or anything 😂
I think I made it all right now
Getting there! Top one (kWh/100 mi) seems right. Bottom one (kWh/100 km) the values should be only 0.62x the kWh/100 mi numbers...since a km is less than a mile, the usage to go 100 km will be less than the usage to go 100 mi...need to divide kWh/100 mi by 1.6 to get kWh/100 km. I'll give you a C for effort! ;)
 
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