Kingske

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This afternoon, I had to get my COVID vaccine at the improbable location of Atlantic City, NJ, which is a 203 miles roundtrip from where I live and therefore an ideal opportunity to test the real-world range of my Taycan 4S with the bigger battery and 19" wheels. I charged up to 98% SoC right before I left. In the 12.5C/55F garage this resulted in a guess-o-meter projected range of 275 miles or the equivalent of 281 miles at 100% SoC. The trip was almost entirely on highways and I kept an average cruising speed of 75 mph in Range mode while the A/C was in Eco mode at 20C/68F. My wife also used her seat warming on the way back. Due to the recent charging, the battery temperature was 19C/66F at start and increased further to 25C/77F during the trip.

The outside temperature during the trip to Atlantic City was about 2C/36F and during the trip back about 0C/32F. Over the entire 203 miles trip, the SoC dropped from 98% SoC to 18% SoC with the guess-o-meter projecting another 42 miles of range left upon arrival. The real-world range with a 100% charged battery in these conditions can therefore be estimated to be 203/0.80 = 254 miles (409 km). This is markedly less than the 281 miles initially projected by the guess-o-meter, but that is due to the difference between the temperature in the garage and outside, I guess?

Using the official useable battery capacity of 83.7 kWh as 100%, this translates into a consumption of 33.0 kWh/100 miles (20.5 kWh/100 km) during this trip. However, the Trip readout on the Taycan's PCM showed a consumption of 35.5 kWh/100 miles which would suggest a useable battery capacity of closer to 90 kWh, or that the Trip readout does not take regeneration gain into account, or both.

Finally, it struck me that I consumed 35% of the battery on the way to Atlantic City and 45% on the way back, despite that there is no major elevation difference and that there was little wind. This leads me to believe that one or both of the following may be true:
1) the relatively small temperature difference between both legs of the trip does make a big difference,
2) the SoC% readout is not linear with the above-50% part effectively covering a bigger share of the battery capacity than the below-50%.





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faroutinNM

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Thank you for the excellent data, hypotheses and analysis.

May your post-vaccination experience be comfortable (I'm still wait-listed for my first).

Please pardon my curiosity, but I've got to ask: did you happen to catch a glimpse of the rubble pile that was once known as the Trump Plaza?
 
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Thank you for the excellent data, hypotheses and analysis.

May your post-vaccination experience be comfortable (I'm still wait-listed for my first).

Please pardon my curiosity, but I've got to ask: did you happen to catch a glimpse of the rubble pile that was once known as the Trump Plaza?
Actually, I did. Since I was more than half an hour early in Atlantic City, I decided to do a little sight-seeing by driving around and ended up in a dead-end street next to a spectacularly high mountain of building debris. It is amazing how they could blast such a tall building away cleanly in the middle of a built-up area... Good luck with your vaccination; I hope it will be your turn soon.
 

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@Kingske thank you thank you thank you - I'm loving the data and actual real world example - it also speaks well for potential range in spring/summer/fall when temperature is higher and milder.

I will also suggest the increased consumption on the return trip could be attributed to wind - at higher speeds (75 mph) even a small increase in speed will result is statistically significant consumption change - so even a 2 or 4 mph head wind effectively increases your sped to 79 mph - causing a consequential change in consumption...

drag has a velocity^2 (squared) component - so it's not linear increase in cost - comsumption changes from 75 to 80 mph are far more costly than from 70 to 75 - even though both changes are only 5 mph - same change in speed - more costly given a higher base speed…

it's just food for thought - but I've seen the cost with my Tesla P85D on an I-5 trip in California at 75 mph for a 4 mph head wind - a trip I had dialed in and knew the consumption numbers - and one time I had a mild head wind (less than 5 mph but constant) but it dramatically screwed with my consumption…

also was it colder on the trip back? colder air = denser air = more drag for same speed…

but your analysis and thoughts are greatly appreciated the Taycan's a great car and range is not an issue when driven correctly.
 
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@Kingske thank you thank you thank you - I'm loving the data and actual real world example - it also speaks well for potential range in spring/summer/fall when temperature is higher and milder.

I will also suggest the increased consumption on the return trip could be attributed to wind - at higher speeds (75 mph) even a small increase in speed will result is statistically significant consumption change - so even a 2 or 4 mph head wind effectively increases your sped to 79 mph - causing a consequential change in consumption...

drag has a velocity^2 (squared) component - so it's not linear increase in cost - comsumption changes from 75 to 80 mph are far more costly than from 70 to 75 - even though both changes are only 5 mph - same change in speed - more costly given a higher base speed…

it's just food for thought - but I've seen the cost with my Tesla P85D on an I-5 trip in California at 75 mph for a 4 mph head wind - a trip I had dialed in and knew the consumption numbers - and one time I had a mild head wind (less than 5 mph but constant) but it dramatically screwed with my consumption…

also was it colder on the trip back? colder air = denser air = more drag for same speed…

but your analysis and thoughts are greatly appreciated the Taycan's a great car and range is not an issue when driven correctly.
Thanks for your comments @daveo4EV Your point about the amplified impact of wind at higher speeds is very convincing. Also, it was indeed 4F colder on the way back.
 

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Your point about the amplified impact of wind at higher speeds is very convincing. Also, it was indeed 4F colder on the way back.
a small change in wind (if it was a head wind on trip home - would've been a tail wind on the trip there improving efficiency) and colder air (more dense more drag) could easily account for 10% difference at 75 mph…

we'll never know for sure, but it's these things that make a difference…

EV's are so so so so efficient that even minute changes in circumstance are visible at the per-mile consumption statistics - something simply not true with gas vehicles when 80% of the thermals are lost to waste heat…

you also used 80% SOC on the trip - if the usable portion is 83.7 kWh - that is 66.96 kWh consumed - let's call it 67 kWh...

kWh conversions for gasoline is about 33 kWh per gallon…
so you traveled 254 miles on about the equivalent energy of 2.03 galloons of gasoline - or about .007992 gallons per-mile - I think you can see how minute changes in drag/air-reistance and wind or head wind could easily manipulate that figure on a per-mile basis…

at 125 mpg (your observed efficiency at 75 mph based on 254 miles @ 67 kWh) - it's not hard to have small changes make a visible difference cause you're running pretty close to optimal - and it's super easy to drop from optimal with small changes…

EV's are running sooooo close to the true cost to move an object down the road that ANY change in conditions is visible in relatively mundane consumption statistics…

also a tail wind is huge benefit and the combination of tail wind (lower drag) and high temp (less drag) would be magnified on the return trip with a double impact of more drag from air density and more drag from head wind…at same constant speed

a 4 mph tail wind and the same 4 mph head wind on opposite legs of the trip - is an 8 mph swing in "air speed" vs. ground speed - 8 mph velocity change where V is V^2 in an equation could easily account for this type of efficiency impact.

tire pressure also might be a factor - if the car sat outside in the cold - you may have lost tire PSI pressure and not recovered it on the way back - so the return trip would have slightly increased rolling resistance for lower tire pressure…you left the garage at say 42 psi and maintained that PSI during the trip - but car sat outside at got down to say 39 psi and didn't add much PSI on the return trip…increase rolling resistance is also a factor to be consider _IF_ there was an observed change in tire PSI due to sitting outside in the cold.

there are a number of plausible minute changes on the return trip that could easily account for 10% - that along with your theory of the scale not being linear for the % consumption could easily account for perceived and observed consumption differences - also the vehicle could've consumed some power while it was stationary outside in the cold while parked to maintain itself...

we'll never know for sure - but all these little changes can add up…

basically 10% difference is fairly easy to envision if you consider all the factors:
  • wind changes are magnified at speed - tail and head winds can really matter at 75 mph
  • air temperature when cold and @ speed has higher impact
  • tire pressure differences on legs of the trip
  • increased demand on the HVAC on return trip home for same cabin temp but colder ambient temps
  • consumption unrelated to moving - stationary consumption while vehicle was parked at destination (this consumption would probably be attributed/measured/hidden in the return trip)
  • instrumentation inaccuracies because the whole "how much SOC do I have left?" is honestly just an advanced guess by Porsche's computers and isn't 100% accurate
  • and maybe due to sight seeing the return trip was slightly longer than the trip there...
  • slightly colder temps also mean the battery is slightly less efficient at providing electricity increasing consumption
    • if battery temp is the "same" for the two legs, then we can say with some certainty the car worked slightly harder to maintain the same temp in the face of lower temps on the return leg -again increasing total consumption per mile to maintain the same battery temp in colder conditions.
small changes in all the categories above are the reason for the difference - I doubt it's any one thing…but easily envisioned if all these things are in play - knowing which ones actually mattered on this particular trip - well that's impossible - we do not have the total data set from which to make that analysis.

again thank you - I'm loving the data.

apologies for the lengthy reply - this stuff fascinates me, and I'm bored at home during a pandemic with nothing to do…and Netflix is fresh out of stuff I want to watch.

congrats on getting vaccinated - it gives me hope one day we might be out of this mess.
 
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but let's not lose sight of an outstanding result

125 mpg @ 75 mph in cold temperatures is a stunningly efficient vehicle - it's just toooo awesome. really really amazing.
 

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Those are pretty impressive numbers.



I think I may be able to shed some additional light on the subject. Below is a graph of my range test with observations taken at 2 minute intervals. It really helps to plot the results and see what patterns pop out. The temperature of the test was about 10 degrees colder than yours, the speed about 5 mph slower and the tires were the 20 inchers. Wind was not significant.



The top panel is a plot of the Air temperature and Battery temperature.



The second panel is a plot of the battery SOC vs Distance.



The third panel is the speedometer reading with the car on cruise control.



The middle panel is the interesting one.



First at constant speed (load), SOC vs distance appears highly linear both visually, in absolute terms and relative terms. The Standard Error of the estimate is .0009 and R square is .9997



This means the line can be accurately described with the simple equation y = mx + b



To get the range at 100% SOC, substituting in the slope we get 0 = -.4767x + 100. And solving for x we get an estimated range of 210.1 miles.


From the plot itself, each black dot represents an observation at two-minute intervals. The last red dot is equal to the last black dot plus the range on the guessometer yielding a range of 210.1 miles, the same as the estimated range.

When I ran the test, I had some concern that the SOC might not be linear as it approaches zero as I did not directly observe it. But that appears to be not the case.

A lot can be said about the SOC, but first and foremost the SOC is accurate and the range from the guessometer starts out inaccurate and becomes accurate with time. If the SOC is linear under constant load, then you don’t have to run all these long tests. A test of 20 or 30 minutes should be sufficient.

For the car to be useful, it needs to be accurately forecasting the range and state of charge otherwise people would be randomly stopping by the roadside.

The intention is to run the test again around the freezing mark next weekend to see what happens. I need more observations to be confident in what is going on, and the whole procedure needs to be critiqued.
 

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Scandinavian

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First of all a big Thank You for sharing this data. As @daveo4EV said very interesting data and real world data.

There was one sentence in your post that also is a differentiator for the trip back!

My wife also used her seat warming on the way back.

You did not state for how long time, but this heater is a pure resistive element and could make quite a difference in the result. Colder outside temperature and perhaps against the wind will also increase cabin heating requiremet.

By the way do you have the Heat Pump in your car?

Regarding the initial decrease on the GOM, did you have the destination set in the navigation system. Would be interesting to see if prediction would change in such case, compared to just relying on previous stored data for consumption? The car is said to take into account weather, elevetaion and legal speed limits etc on the route to calculate consumption.
 

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Thanks Kingske and JimBob for the great data, and happy vaccination day Kingske.

More than 258 miles in those conditions is fantastic range - way more than I’ve managed in my Turbo in similar conditions, but I’ve never been able to get the battery that warm before setting off. It really therefore makes a HUGE difference to have the battery warm before setting off. I wonder if another reason for the greater consumption on the way back is that the battery had just been exposed to cold temps for longer so you steadily lose the benefit of the pre-heating over time - the car may have been using a little more energy to heat the battery on the way back.
 
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By the way do you have the Heat Pump in your car?

Regarding the initial decrease on the GOM, did you have the destination set in the navigation system. Would be interesting to see if prediction would change in such case, compared to just relying on previous stored data for consumption? The car is said to take into account weather, elevation and legal speed limits etc on the route to calculate consumption.
@Scandinavian , I do have the Heat Pump and you are making an interesting point about the guess-o-meter taking the changing conditions (whatever those may be) into account. Ten to fifteen miles into my first leg of the trip, the estimated SoC upon arrival was revised upwards to a number which proved to be accurate upon arrival. Same thing happened upon my return when the predicated arrival-SoC was adjusted downward accurately.
 
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small changes in all the categories above are the reason for the difference - I doubt it's any one thing…but easily envisioned if all these things are in play - knowing which ones actually mattered on this particular trip - well that's impossible - we do not have the total data set from which to make that analysis.
@daveo4EV , this outsize impact on consumption/range of already very efficient vehicles may also explain why many of us are so surprised about the relative impact on range of e.g. the difference between 19" and 21" wheels, don't you think?
 

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@Kingske yes I agree

I moved from a Model X with 21” wheels (2016) to a (2017) with 19” wheels and range was dramatically improved

EV’s are sooo close to efficiency limits you can actually “see” the efficiency impacts, something much more difficult with gas cars.
 
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I think I may be able to shed some additional light on the subject. Below is a graph of my range test with observations taken at 2 minute intervals. It really helps to plot the results and see what patterns pop out. The temperature of the test was about 10 degrees colder than yours, the speed about 5 mph slower and the tires were the 20 inchers. Wind was not significant.

The intention is to run the test again around the freezing mark next weekend to see what happens. I need more observations to be confident in what is going on, and the whole procedure needs to be critiqued.
Thanks a million @JimBob for these amazing data. To measure is to know! Your analysis convinced me that the SoC measurement is indeed linear over the entire load range of the battery. I am looking forward to the results of your next test around the freezing mark.
 

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From the plot itself, each black dot represents an observation at two-minute intervals. The last red dot is equal to the last black dot plus the range on the guessometer yielding a range of 210.1 miles, the same as the estimated range.

When I ran the test, I had some concern that the SOC might not be linear as it approaches zero as I did not directly observe it. But that appears to be not the case.
Very interesting data from real world testing!

I am most impressed by your ability to drive at so constant speed for such a long distance. That is something I have never experienced here in Europe. There are either road works or toll booths in so many places.

Looking forward to seeing any updates when testing in colder weather.
Thanks
 

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