Statistical Analysis Approach to Understanding MPG Issue
I know this MPG topic has been beaten to death, and I apologize for bringing it up again, however I would like to propose a new approach to understanding this MPG issue. I am not an RX-8 owner (yet), but have been following this forum for quite a while. Like many others, I too am interested in trying to understand the cause of great variation in mpg among RX-8 owners as well as relatively low mpg in many cases. (I have a daily commute of 85 miles).
It is very possible that there may be a combination of several factors causing this MPG situation. There is a type of quantitative analysis called Multivariate Regression which takes multiple factors into consideration and calculates their relative importance in determining an outcome, in this case, mpg. I’d be happy to conduct the analysis as a fellow RX-8 supporter. I just need as many RX-8 owners as possible to answer the survey below. Based on my prior forum reading, I’ve come up with a several potential factors impacting the mpg. We’ll have to keep the responses very simple and straightforward. (Answers as explanations won’t work). Please participate…….. 1. RECENT Combined City/Highway Average MPG = ___________ (Calculated Correctly and One Number please, not a range) 2. % Highway Driving = ______ 3. Driving Style = A. Easy going (Don’t normally use high rpm range, only occasionally) B. Average, C. Above Avg (Use Upper RPM range quite often and accelerate hard) 4. VIN Number (last 6 digits) = ___________ (NOTE: If you already entered your VIN on the thread “Let's compare VIN numbers and fuel economy”, I can get it from that thread). 5. Model (eg. Base, GT, etc) = ___________ 6. Automatic / 6 speed = _____________ 7. Octane (Number) of Fuel Used = ____________ 8. DSC/TCS = Yes / No(Don’t Have or Fully Disabled) 9. Miles to Date = ___________ 10. Approximate % Time Driving with Windows Open = ___________ 11. Approximate % Time Driving with AC on = ___________ 12. State = ______________ (I’ll later convert to Geographic Region) Hope like hell I didn’t miss anything. I know this will be a pain – that many people have already responded to many threads regarding mpg. However it is very difficult to test one theory (eg. VIN # or Octane), when so many other contributing factors may also come into play. The analysis I am proposing takes all these factors into consideration simultaneously and identifies those which are important in determining mpg. If you are interested please respond. If you are not interested, well, please also respond………the more observations the better. I’ll post the results soon after receiving enough observations. For those that want to flame, hey, it’s my first post – have fun. IMPORTANT: When responding, please complete all entries. If one thing is missing, such as Octane, then your entire response cannot be used. Thanks in advance for participating. mod edit: results thread https://www.rx8club.com/showthread.p...4&page=1&pp=15 |
1. 16.2mpg
2. 40% 3. B 4. 106206 5. GT 6. 6 speed 7. 92 8. fully disabled 9. 834 10. 30% 11. 2% 12. NM |
1. 16.8 MPG
2. 40% 3. C 4. 101102 5. GT 6. 6 speed 7. 93 8. Yes 9. 8400 10. 0% 11. 25% 12. NH Observation: This only reflects my milage for my last fill-up. When I'm traveling my mileage increases significantly due to all of the time spent on the highway (20-24 MPG). Likewise I have seen horrible fuel economy on track days (7.5 MPG) or when I have been fooling around (13 MPG). Will this variation skew your results? |
suggestion
I'd emphasize to respondents that all their answers be specifically related to the 'recent MPG' answer to question 1.
-jd. |
1. RECENT Combined City/Highway Average MPG = 22
(Calculated Correctly and One Number please, not a range) 2. % Highway Driving = 85% 3. Driving Style = B A. Easy going (Don’t normally use high rpm range, only occasionally) B. Average, C. Above Avg (Use Upper RPM range quite often and accelerate hard) 4. VIN Number (last 6 digits) = 101212 5. Model (eg. Base, GT, etc) = GT 6. Automatic / 6 speed = 6 Sp 7. Octane (Number) of Fuel Used = 91 8. DSC/TCS = Yes 9. Miles to Date = 4800 10. Approximate % Time Driving with Windows Open = 10% 11. Approximate % Time Driving with AC on = 5% 12. State = AL (I’ll later convert to Geographic Region) |
1. 14.80
2. 15% 3. A 4. 108837 5. GT 6. 6 speed 7. 91 8. Yes 9. 2914 10. 1% 11. 5% 12. CA |
Speed Racer: Regarding your concern about skewing the results. As long as your responses to the questions regarding % Highway and Driving Style (?'s 2 and 3) are based on RECENT driving (in accordance with your RECENT avg. mpg), I believe the results should be o.k.
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JDL is correct:
PLEASE NOTE: As JDL stated; All responses should be specifically related to the 'recent MPG' answer to question 1. ie. % highway driving, etc. should be based on RECENT driving. |
Here's another take on the issue. What if the speedo's are.."optomistic"? say 1.5 mph off. That would reduce the MPG. I think before you can establish a baseline. You need to use another method of calculation. If the speedo's are at fault, then all the data collection in the world will not show a thing.
my .02 yen |
1. 22.9
2. 80% 3. Average 4. 105899 5. Sport 6. 6 speed 7. 93 8. Yes 9. 5000 10. 10% 11. 20% 12. Virginia |
"What if the speedo's are.."optomistic"? say 1.5 mph off. That would reduce the MPG. I think before you can establish a baseline. You need to use another method of calculation. If the speedo's are at fault, then all the data collection in the world will not show a thing."
Good point Matt. I have a couple comments in response. 1. If the speedos are optimistic 1.5 mph, I believe that would actually yield a higher mpg, thus reducing the problem people seem to be having. For example, if the speedo read 50 mph too high, then the odometer reading would show much higher mileage, thus yielding a terrific MPG. 2. One of the goals of my proposed analysis was to better understand the great variation in MPG among RX-8 owners. If everyones speedo reads 1.5 mph too high, then everyone is impacted the same. Though the MPG results for everyone would be a tad bit higher than reality, it would not cause variation in MPG among owners. 3. I'm assuming the optimistic 1.5 mph reading occurs at roughly 60 mph. That equates to a 2.5% error, or similarly, for someone getting 20 mpg equates to 1/2 mpg. This is not near enough to muddy the results of the analysis. |
1. 21.35 MPG
2. 85% 3. B 4. 101129 5. touring 6. 6 speed 7. 92 8. No 9. 7800 10. 5% 11. 2% 12. MD another part of driving style that may be important is average speed / or normal cruising speed. mine is probably average 72, usually in the 75 +/- 5 range. Sometimes 68, less some times in the 90s. I'm not sure how my throttle use is as an 'average'. in town driving it's very easy going,1200RPM starts. usually. Then there's a hopefully daily 9K redline short burst. My fuel buying was 87 for several tanks; the last 4 have been premium. The MPG figure I gave is the last tank which was on the 3rd full premium tank since switching back from 87. Our local temps have been in the 45-60 range mostly recently. Running close to 32PSI; 5w/20 oil, usually no passenger or extra luggage -all possible factors as well. |
1. RECENT Combined City/Highway Average MPG = 18.3
2. % Highway Driving = 10% 3. Driving Style = B 4. VIN Number (last 6 digits) = 106908 5. Model (eg. Base, GT, etc) = GT 6. 6 speed 7. Octane (Number) of Fuel Used = 91 8. DSC/TCS = Disabled (DSC off, but no squiggly lines) 9. Miles to Date = 1500 10. Approx % Time Driving with Windows Open = 0% 11. Approximate % Time Driving with AC on = 98% 12. State = Florida How about adding spoiler/no spoiler and front lip/no lip? But there are more variables to consider: Ambient temps, humidity, length of traffic lights (here in Tampa bay, some red lights are 3 minutes long), amount of time idling, Hills/no hills, average MPH...just to name a few |
1. 15mpg
2. 5% 3. B 4. 107764 5. GT 6. 6 speed 7. 91 8. fully disabled 9. 1500 10. 50% 11. 50% 12. California |
1. 17.5mpg
2. 20% 3. B 4. 104226 5. GT 6. 6 speed 7. 89 8. yes 9. 1950 10. 20% (sunroof open 75%) 11. 5% 12. OH |
another data question
norton, will your statistical analysis support multiple data sets per VIN?
I can imagine over time folks will have additional data for recent MPG calcs, perhaps with dramatically different driving styles, all-freeway, no-freeway, etc... I have several such data sets already. Another data point you might want to include, then, is the rough #miles on the vehicle at the time of the data set. Perhaps just to differentiate the sets per VIN, or track another correlation to "new car break-in". My motivation: well, for my break-in I took a 1200 mile road trip, yielding 22.58 mpg, which stands as my car's all-time best. I know the car's capable of doing 22+ mpg, but my last many tanks have settled more in the 14 mpg range. Clearly there a large range of data for each car. Cheers, -jd. |
1. 17.5
2. 60% 3. A 4. 1011311 5. GT 6. 6 7. 93 8. Yes 9. 790 10. 2% 11. 5% 12. VA |
I don't yet have enough observations to conduct the analysis, however I did notice one interesting thing while taking a quick look at the few observations so far. Looking at MPG and % Hwy, there appears a definite pattern. This is not too surprising, however I don't know if this has been clearly shown before.
I'm trying to attach or insert a small graph (JPEG) I made of MPG vs % Hwy, however with my lack of posting knowledge, have not had success yet. Any help?? Here's another try....... |
JDL "will your statistical analysis support multiple data sets per VIN?"
Well, kind of. It would be fine and is probably a good idea to get multiple data sets over time. The only thing is that it somewhat dilutes the impact of measuring VIN as a potential MPG impacting factor. "Another data point you might want to include, then, is the rough #miles on the vehicle at the time of the data set" If I am interpreting your suggestion properly, I believe this information is captured in Question 9, (Miles to Date). Thanks for the input. It really sucks barely knowing how to use the posting capability. As you can tell, I'm a greenhorn to forumland posting. |
Originally posted by norton JDL "will your statistical analysis support multiple data sets per VIN?" [...] "Another data point you might want to include, then, is the rough #miles on the vehicle at the time of the data set" If I am interpreting your suggestion properly, I believe this information is captured in Question 9, (Miles to Date).*snip* ``Perhaps just to differentiate the sets per VIN, or track another correlation to "new car break-in".'' So I was suggesting you might use odometer readings to distiguish one data set from another for the same VIN. I believe you can still find the VIN correlation, if it exists, from multiple data sets. In fact, more so, since you may have the same VIN with significanty varied (other) conditions. Anyhoo, I'll hold off until you say when you'd like more data sets (per VIN)... -jd. |
hope this helps. i have a appointment with mazda about my fuel consumption.
1. RECENT Combined City/Highway Average MPG = 19
2. % Highway Driving = 80% 3. Driving Style = B 4. VIN Number (last 6 digits) = 102274 5. Model (eg. Base, GT, etc) = GT 6. 6 speed 7. Octane (Number) of Fuel Used = 93(shell) 8. DSC/TCS = on 9. Miles to Date = 6300 10. Approx % Time Driving with Windows Open = 95% 11. Approximate % Time Driving with AC on = 5% 12. State = Florida |
Originally posted by norton I'm trying to attach or insert a small graph (JPEG) I made of MPG vs % Hwy, however with my lack of posting knowledge, have not had success yet. Any help?? 1. Create a post. On the "Attach File:" row, click on the Browse button. 2. Select your .jpg file and click ok. 3. Submit your post. Just make sure your .jpg is below 204k. |
1. RECENT Combined City/Highway Average MPG = 21 mpg
2. % Highway Driving = 95% 3. Driving Style = A 4. VIN Number (last 6 digits) = 109161 5. Model (eg. Base, GT, etc) = GT 6. Automatic / 6 speed = 6 Sp 7. Octane (Number) of Fuel Used = 87 8. DSC/TCS = Yes 9. Miles to Date = 2500 10. Approximate % Time Driving with Windows Open = 3% 11. Approximate % Time Driving with AC on = 0% 12. State = CA |
1. RECENT Combined City/Highway Average MPG = 19
2. % Highway Driving = 30% 3. Driving Style = Average 4. VIN Number = 102058 5. Model = GT 6. 6 speed 7. Octane (Number) of Fuel Used = 87 8. DSC/TCS = Yes 9. Miles to Date = 5300 10. Approximate % Time Driving with Windows Open = 10% 11. Approximate % Time Driving with AC on = 99% 12. State = CA |
Downshift - Thanks for the posting tip. Hopefully it will work this time.
Once again --- I don't yet have enough observations to conduct the complete analysis, however I did notice one interesting thing while taking a quick look at the few observations so far. Looking at MPG and % Hwy, there appears a definite trend. This is not too surprising, however I don't know if this has been clearly shown before with % Hwy vs MPG. Please take a look at the graph (if I posted it correctly this time). https://www.rx8club.com/attachment.p...tid=5883&stc=1 |
1. 20
2. 10% 3. A 4. 113952 5. GT 6. 6spd 7. 93 8. yes 9. 440 10. 40% 11. 20% 12. FL |
1. 17.68 mpg
2. 0% Highway Driving (all town) 3. A 4. 101211 5. GT 6. 6 Speed 7. 87 octane 8. DSC/TCS = Fully Disabled 9. 3737 Miles 10. 90% Windows Open 11. 10% AC on (exact info this week) 12. Florida Average speed per mile 29 mph!!!! (added this from info at end of thread) |
1. 22
2. 85% 3. A 4. 109104 5. GT 6. Automatic 7. 92 8. DSC/TCS = Yes 9. Miles to Date = 1650 10. Approximate % Time Driving with Windows Open = 0% 11. Approximate % Time Driving with AC on = 50% 12. State = WA FYI with 95% hiway driving I get 24+ mpg. |
1. 21.0
2. 90% 3. B 4. 106429 5. GT 6. 6 speed 7. 93 8. Yes 9. 2267 10. 0% 11. 50% 12. SC Kind of sounds like the Buckingham Pi theory...good luck...:) |
1. 21
2. 80 3. A 4. 112585 5. base 6. 6 speed 7. 93 8. No DSC 9. 2000 10. 95 11. 0 12. NY - feeling blue for the Yankees |
Re: Statistical Analysis Approach to Understanding MPG Issue
1. RECENT Combined City/Highway Average MPG = 20
(Calculated Correctly and One Number please, not a range) 2. % Highway Driving = 15 3. Driving Style = A A. Easy going (Don’t normally use high rpm range, only occasionally) B. Average, C. Above Avg (Use Upper RPM range quite often and accelerate hard) 4. VIN Number (last 6 digits) = 112741 (NOTE: If you already entered your VIN on the thread “Let's compare VIN numbers and fuel economy”, I can get it from that thread). 5. Model (eg. Base, GT, etc) = Base 6. Automatic / 6 speed = 6 Speed 7. Octane (Number) of Fuel Used = 93 8. DSC/TCS = No. Don't have it 9. Miles to Date = 1,571 10. Approximate % Time Driving with Windows Open = 25% 11. Approximate % Time Driving with AC on = 10% 12. State = PA (I’ll later convert to Geographic Region) |
Norton -- Yer awesome. I nominate you for immediate instatement to Sr Member for at least attempting this. I am already impressed by your graph which shows a pretty good correlation btwn hiway driving and mpg. For those data points somewhat out of the norm, I bet if you query those drivers a bit more you would find out why they're so out of whack. For instance, "Highway driving" in LA is stop and go and could equate to city driving elsewhere. Recommend you investigate more those people who don't fall near the norm in that chart.
My responses: 1. RECENT Combined City/Highway Average MPG = 16.7 2. % Highway Driving = 40 3. Driving Style = B. Average to Above Avg (I accelerate hard but almost never go above 7K rpm. Cruise below 3500 rpm.) 4. VIN Number (last 6 digits) = It's on that thread. 5. Model: GT 6. 6 speed 7. Octane (Number) of Fuel Used = 87 8. DSC/TCS = Yes (fully enabled) 9. Miles to Date = 5100 10. Approximate % Time Driving with Windows Open: 50 11. Approximate % Time Driving with AC on: 40 12. State: CA |
1. 15
2. 10% 3. C (Like someone mentioned before, I drive it like I stole it). 4. 102787 5. GT 6. 6 speed 7. 91 8. DSC/TCS = off 9. Miles to Date = ~5,500 10. 30% 11. 1% 12. State = CA |
For instance, "Highway driving" in LA is stop and go and could equate to city driving elsewhere. |
Originally posted by ptiemann I think stop-and-go is actually worse than city driving. When I put 95% highway I was thinking of the tanks where I avoided commute hours. Silicon Valley traffic is not much different from LA. Cheers ---Dave |
Originally posted by druck Stop and go is bad, not only do you need more fuel to pull off each time, but also sitting stationary uses as much fuel as traveling at around 12mph, and you obvious aren't putting any miles on the clock. |
For instance, "Highway driving" in LA is stop and go and could equate to city driving elsewhere. Recommend you investigate more those people who don't fall near the norm in that chart. Exactly my point. If you say your are driving 50 percent hiway but your hiway is stop and go, might as well count it like city driving. It is assumed hiway driving is more efficient (i.e, greater miles per gallon) but clearly that is not always the case. 1. Per the quotes above (great observation), not all Hwy driving is the same type of driving for everyone and its not the same for an individual every time that person hits the highway. Likewise not all city driving is the same. 2. The % Hwy is an educated guess, at best a ballpark figure. It's not really an emperically measured number like odometer reading or mpg. There is bound to be some error in these estimates. 3. People may have differing interpretations as to exactly how Highway and City are defined. Thus a somewhat apples to oranges comparison among responses. Even with these problems though, I am fairly pleased with the results so far, using % Hwy as one of the primary determining factors of MPG. ************************************************* I do have a NEW variable I thought of, which pretty much removes the shortcomings of using % Hwy described above. Unfortunately determining this factor will be a pain, time consuming, and will take a while before you could provide it. The NEW factor is............. . Average Speed per Mile . The good thing about using Avg Speed per Mile is that it is totally emperical. No subjective guessing involved, no different interpretations of Hwy vs City, and it pretty much "normalizes" all road conditions (eg A highway full of stop and go traffic is quite similar to city driving). The pain in using Average Speed per Mile is in the calculation, though I will simplify it as much as possible. Basically you would need to provide a couple things: [/B]1. # of miles traveled recently (from odometer reading). 2. The amount of time spent driving. (unfortunately this requires recording the beginning and ending time of every ride).[/B] Average Speed Per Mile = (Total Miles / Total Minutes) * 60 This calculation should be done on the same odometer mileage as is used in calculating MPG. (Yes, unfortunately that would need to be provided again). I'm NOT suggesting we do this right now (or even that we do it), however it is certainly something to think about. My guess is that there would be a very very strong relationship between Avg Speed/Mile and MPG. Please let me know what your thoughts and feelings are about later pursuing the Avg Speed/Mile information. If people think its overkill or not worth it, I can understand their viewpoint. ******************************************* For now I would like to stay focused on working with the great data I have been getting. I have begun working on the Regression Model. Due to the volatility and variation in the observations I'm receiving, the Regression results vary somewhat with each additional response. As I continue getting more observations, the results should begin to settle towards a stable conclusion. Great response data. Please keep 'em coming. Thanks. |
Too bad we don't have an hour meter for total ignition-on time. We could then just use the odometer for miles & total gas consumed (if you've been recording that, like you should if you're really recording things to compute overall mpg).
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1. 20.2
2. % Highway Driving = 90 3. Driving Style = C 4. VIN Number (last 6 digits) = 103169 5. Model (eg. Base, GT, etc) = GT 6. Automatic / 6 speed = 6sp 7. Octane (Number) of Fuel Used = 93 8. DSC/TCS = Yes 9. Miles to Date = 4700 10. Approximate % Time Driving with Windows Open =0 11. Approximate % Time Driving with AC on = 50 12. State = MO |
1. RECENT Combined City/Highway Average MPG = 15
(Calculated Correctly and One Number please, not a range) 2. % Highway Driving = 20% 3. Driving Style = C A. Easy going (Don’t normally use high rpm range, only occasionally) B. Average, C. Above Avg (Use Upper RPM range quite often and accelerate hard) 4. VIN Number (last 6 digits) = 574 (NOTE: If you already entered your VIN on the thread “Let's compare VIN numbers and fuel economy”, I can get it from that thread). 5. Model (eg. Base, GT, etc) = GT 6. Automatic / 6 speed = 6MT 7. Octane (Number) of Fuel Used = 95 8. DSC/TCS = Yes / No(Don’t Have or Fully Disabled)yes 9. Miles to Date = 800 10. Approximate % Time Driving with Windows Open = 10%___________ 11. Approximate % Time Driving with AC on = _30% 12. State = wa (I’ll later convert to Geographic Region) |
1. 16.5mpg avg last 4 fill ups (with an autox)
2. 40% 3. C ++ 4. 101182 5. Touring 6. 6 speed 7. 91 8. dsc off 50% time 9. 4400 10. 20% 11. 80% 12. NV |
Well I have 24 observations so far. That's about the minimum I need, so I will hopefully get the initial Regression Analysis done tomorrow. Here is an updated graph depicting % Hwy vs MPG. Still shows a definite pattern.
One interesting thing to note are the two outliers which show 20 mpg, yet a low % Hwy - 10% and 15% respectively. Based on % Hwy alone, someone would probably conclude those are aberations. There is a valid reason for these two outliers though. For those two observations, the Driving Style was "A" (easy going), thus yielding a higher MPG. This is exactly the kind of situation that the Regression Analysis automatically takes into account, by simultaneously assessing multiple factors. Can't wait to get the Regression results. https://www.rx8club.com/attachment.p...tid=5914&stc=1 |
Erm, hate to throw a spanner in the works at this stage, but is that % highway driving by time or by distance?
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Erm, hate to throw a spanner in the works at this stage, but is that % highway driving by time or by distance? If someone spent only 5% of their time on the highway and drove 80% of the total combined hwy/city distance on th hwy, would we say that person has 5% hwy proportion or an 80% hwy proportion? This situation would mean that the person spent a frustrating 95% of their driving time going very little distance (20% of the combined hwy/city distance). My view is that the % Hwy would be based on DISTANCE. The reason is that City Driving implicitly assumes more time spent going fewer miles than Hwy Driving. So I believe the time factor in the % split is already taken into consideration. Nonetheless, you've raise a very good point about the ambiquiety in using % Hwy. I think it's an o.k. variable to use in the analysis, however Average Speed per Mile is an infinitely better measure to assess City vs Hwy driving. (Please see my comments about 7 posts up. |
Keep rockin', Norton. You data and methodology seem very valid so far.
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Thanks 8_wannabe. I've been following this terrific forum for close to a year always find it interesting and exciting. I would really like to help towards understanding the factors heavily impacting mpg.
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Originally posted by norton Lurcher: Excellent catch. You've got a very valid point. Let's see now. If someone spent only 5% of their time on the highway and drove 80% of the total combined hwy/city distance on th hwy, would we say that person has 5% hwy proportion or an 80% hwy proportion? This situation would mean that the person spent a frustrating 95% of their driving time going very little distance (20% of the combined hwy/city distance). My view is that the % Hwy would be based on DISTANCE. The reason is that City Driving implicitly assumes more time spent going fewer miles than Hwy Driving. So I believe the time factor in the % split is already taken into consideration. Nonetheless, you've raise a very good point about the ambiquiety in using % Hwy. I think it's an o.k. variable to use in the analysis, however Average Speed per Mile is an infinitely better measure to assess City vs Hwy driving. (Please see my comments about 7 posts up. |
1. RECENT Combined City/Highway Average MPG = _15.8__________
(Calculated Correctly and One Number please, not a range) 2. % Highway Driving = __10%____ 3. Driving Style = B A. Easy going (Don’t normally use high rpm range, only occasionally) B. Average, C. Above Avg (Use Upper RPM range quite often and accelerate hard) 4. VIN Number (last 6 digits) = ___________ (NOTE: If you already entered your VIN on the thread “Let's compare VIN numbers and fuel economy”, I can get it from that thread). 5. Model (eg. Base, GT, etc) = ____GT_______ 6. Automatic / 6 speed = ____6_________ 7. Octane (Number) of Fuel Used = ___93_________ 8. DSC/TCS = Yes / No(Don’t Have or Fully Disabled) fully disabled when i remember 9. Miles to Date = ___1018________ 10. Approximate % Time Driving with Windows Open = ____50_______ 11. Approximate % Time Driving with AC on = ______5%_____ 12. State = ___NJ___________ (I’ll later convert to Geographic Region) |
1. RECENT Combined City/Highway Average MPG = 15.044
2. % Highway Driving =65% 3. Driving Style = C 4. VIN Number (last 6 digits) =101877 5. Model (eg. Base, GT, etc) = GT 6. Automatic / 6 speed = 6 speed 7. Octane (Number) of Fuel Used = 91 8. DSC/TCS = Yes 9. Miles to Date = 3,240M/5217km 10. Approximate % Time Driving with Windows Open = 2 11. Approximate % Time Driving with AC on = 0 12. State = Alberta, Canada Can I mention that it would be more useful if you dealt with kilometers, liters and other than only US geography? I also suggest to ask altitude, as it has a significant effect on fuel economy. In my case 2,700ft/855M |
Originally posted by matt Here's another take on the issue. What if the speedo's are.."optomistic"? say 1.5 mph off. That would reduce the MPG. I think before you can establish a baseline. You need to use another method of calculation. If the speedo's are at fault, then all the data collection in the world will not show a thing. my .02 yen |
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