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lorenfb said:
Oils4AsphaultOnly said:
lpickup said:
Actually, it's more like "hockey stick" growth, but exponential will be a suitable proxy.

My crystal ball? Battery costs. Battery costs have been falling at a very consistent 19% per year, and is forecast to continue this trend. Maybe you have a reason to believe this will not be the case, but with all the research going on in the battery world, I don't really see an end to this trend in the next 5 years.

Now so far, the cost savings on the battery side have not transitioned directly to cost savings on the vehicle. This is because automakers have focused on adding larger format batteries to address a perceived range limitation. But there have been significant increases in range over the past 8 years, while keeping the price constant. I believe that once we hit an affordable 300 mile (maybe 350) EV, that there will be little reason to keep adding more battery, and instead we will see a shift towards making vehicles more affordable. And eventually there will be a crossover point where the unsubsidized cost of an EV will be less than an equivalent ICE.

And at that point, to the buying public, it simply won't matter whether it's an EV or an ICE. That's the problem I have with people that are saying this or that about "EV demand". Most people are sticker-price focused. They don't necessarily care what's under the hood. They only care about what the sticker says. And the day the sticker on an EV is less than the sticker on an ICE, they are going to get the EV. At this point it stops being a ramp and turns a sharp corner.

Yes, EVs have to become available in the form factors they want. And yes, there will need to be education of the masses about how and where to charge their cars. But the growing number of EV owners are going to be the teachers. And the more EVs that people see on the road, the more people are going to be willing to ask their friends, neighbors and co-workers about them.

If you think any part of this "crystal ball" is wrong, let me know, but you'll be disagreeing with the technology adoption curve that has been repeated throughout history, so it's a tough argument to make. About the only legitimate difference of opinion we can have is the timescale. Yes, with falling battery prices, the percentage of the cost of the battery to the vehicle becomes smaller, so the gains in vehicle price become less significant. But I don't think this is going to take more than another 4-5 years. We now have 3 mass produces vehicles with ranges over 300 miles, with several more knocking on the door at 250 (unfortunately in somewhat limited quantities). 2020 should be a big year in terms of new EV releases. Once we get those vehicles with 300 miles on the market, we can start the process of driving the costs down.

Since lorenfb's looking for a crystal ball, how about hard data? https://www.cncda.org/wp-content/uploads/Cal-Covering-1Q-19.pdf

It kinda mimics Norway's EV adoption doesn't it?

Edit: The relevant graph is on page 2.

The overall numbers are shewed because of the M3. We'll have to wait for the Q2 M3 data. Until Tesla can repeat 2018 Q4 thru 2019,
most OEMs would rather error on conservative BEV build forecasts for 2020, e.g. marginal 2019 Bolt & Leaf numbers.

ha! So, because it's tesla, the datum doesn't count?!

Alright, then I'll share with everyone my favorite statistician (jhm), and his plug-in EV predictive envelope model (based on historical data): https://teslamotorsclub.com/tmc/posts/3683239/

If you believe nothing else of his, pay attention to how his model was more accurate than BNEF's (Bloomberg NEF), which many in the oil industry rely on to make their production plans on:
" In April, 2018, BNEF forecast 2018 to come in at 1.56M or about 1.67% share. The actual was 2.018M or 2.12% share. Let's what my method would have predicted using just 2012 thru 2015 data (a sample size of just 3). My 2015 forecast of 2018 would have centered on 2.2% with a 90% predictive interval from 1.3% to 3.5%. Yeah, a lot of uncertainty, but nailed it. My 2016 forecast of 2018 centered on 1.8% ranging from 1.3% to 2.5%. This was a little more pessimistic, but less uncertain. Then the 2017 forecast of 2018 centered around 2.0% ranging from 1.7% to 2.4%. So the predictive envelope nicely closed in on the actual. Meanwhile, BNEF low forecast was ruled out of the predictive interval by the time it was made using 2017 as the last historical datum. Presumably, BNEF's forecast had that benefit of highly granular data, their proprietary data, and a multi-industry team of analysts. Surely with all that going for them, they should have been able to produce a forecast with much less uncertainty, but in fact a sample size of 5 historical observations could have alerted them to the possibility that their prediction was high improbably. "

RTFA, he writes well and should open many people's eyes on their short-sightedness.
 
Oils4AsphaultOnly said:
lorenfb said:
Oils4AsphaultOnly said:
Since lorenfb's looking for a crystal ball, how about hard data? https://www.cncda.org/wp-content/uploads/Cal-Covering-1Q-19.pdf

It kinda mimics Norway's EV adoption doesn't it?

Edit: The relevant graph is on page 2.

The overall numbers are shewed because of the M3. We'll have to wait for the Q2 M3 data. Until Tesla can repeat 2018 Q4 thru 2019,
most OEMs would rather error on conservative BEV build forecasts for 2020, e.g. marginal 2019 Bolt & Leaf numbers.

ha! So, because it's tesla, the datum doesn't count?!

Alright, then I'll share with everyone my favorite statistician (jhm), and his plug-in EV predictive envelope model (based on historical data): https://teslamotorsclub.com/tmc/posts/3683239/

If you believe nothing else of his, pay attention to how his model was more accurate than BNEF's (Bloomberg NEF), which many in the oil industry rely on to make their production plans on:
" In April, 2018, BNEF forecast 2018 to come in at 1.56M or about 1.67% share. The actual was 2.018M or 2.12% share. Let's what my method would have predicted using just 2012 thru 2015 data (a sample size of just 3). My 2015 forecast of 2018 would have centered on 2.2% with a 90% predictive interval from 1.3% to 3.5%. Yeah, a lot of uncertainty, but nailed it. My 2016 forecast of 2018 centered on 1.8% ranging from 1.3% to 2.5%. This was a little more pessimistic, but less uncertain. Then the 2017 forecast of 2018 centered around 2.0% ranging from 1.7% to 2.4%. So the predictive envelope nicely closed in on the actual. Meanwhile, BNEF low forecast was ruled out of the predictive interval by the time it was made using 2017 as the last historical datum. Presumably, BNEF's forecast had that benefit of highly granular data, their proprietary data, and a multi-industry team of analysts. Surely with all that going for them, they should have been able to produce a forecast with much less uncertainty, but in fact a sample size of 5 historical observations could have alerted them to the possibility that their prediction was high improbably. "

RTFA, he writes well and should open many people's eyes on their short-sightedness.

Just another forecast based on historical data, e.g. predicting the future S&P price for 2020 without regard to market forces such as
the outcome of the trade war with China. There's no discussion of key factors that will motivate/influence the consumer's preference
for EVs over ICEVs in the next 10 years. Again, the key point:

There was a need in the early 2000s in search of a product, i.e. a mobile device that could not only provide cell communications, but also
internet access, a camera, and music storage. The product that fulfilled that need was the iPhone. Presently, the EV is a product in search
of a need
. The majority of consumers presently don't perceive any great need that an EV can provide versus an ICEV. Given that, the sales
growth of EVs will not significantly displace sales of ICEVs in the near term.

Here in CA we wasted tax money developing a product in search of a need, a partial rail system from SoCal to NorCal.
 
lorenfb said:
Oils4AsphaultOnly said:
lorenfb said:
The overall numbers are shewed because of the M3. We'll have to wait for the Q2 M3 data. Until Tesla can repeat 2018 Q4 thru 2019,
most OEMs would rather error on conservative BEV build forecasts for 2020, e.g. marginal 2019 Bolt & Leaf numbers.

ha! So, because it's tesla, the datum doesn't count?!

Alright, then I'll share with everyone my favorite statistician (jhm), and his plug-in EV predictive envelope model (based on historical data): https://teslamotorsclub.com/tmc/posts/3683239/

If you believe nothing else of his, pay attention to how his model was more accurate than BNEF's (Bloomberg NEF), which many in the oil industry rely on to make their production plans on:
" In April, 2018, BNEF forecast 2018 to come in at 1.56M or about 1.67% share. The actual was 2.018M or 2.12% share. Let's what my method would have predicted using just 2012 thru 2015 data (a sample size of just 3). My 2015 forecast of 2018 would have centered on 2.2% with a 90% predictive interval from 1.3% to 3.5%. Yeah, a lot of uncertainty, but nailed it. My 2016 forecast of 2018 centered on 1.8% ranging from 1.3% to 2.5%. This was a little more pessimistic, but less uncertain. Then the 2017 forecast of 2018 centered around 2.0% ranging from 1.7% to 2.4%. So the predictive envelope nicely closed in on the actual. Meanwhile, BNEF low forecast was ruled out of the predictive interval by the time it was made using 2017 as the last historical datum. Presumably, BNEF's forecast had that benefit of highly granular data, their proprietary data, and a multi-industry team of analysts. Surely with all that going for them, they should have been able to produce a forecast with much less uncertainty, but in fact a sample size of 5 historical observations could have alerted them to the possibility that their prediction was high improbably. "

RTFA, he writes well and should open many people's eyes on their short-sightedness.

Just another forecast based on historical data, e.g. predicting the future S&P price for 2020 without regard to market forces such as
the outcome of the trade war with China. There's no discussion of key factors that will motivate/influence the consumer's preference
for EVs over ICEVs in the next 10 years. Again, the key point:

There was a need in the early 2000s in search of a product, i.e. a mobile device that could not only provide cell communications, but also
internet access, a camera, and music storage. The product that fulfilled that need was the iPhone. Presently, the EV is a product in search
of a need
. The majority of consumers presently don't perceive any great need that an EV can provide versus an ICEV. Given that, the sales
growth of EVs will not significantly displace sales of ICEVs in the near term.

Here in CA we wasted tax money developing a product in search of a need, a partial rail system from SoCal to NorCal.

As I said, you need to RTFA. He addressed your "issue".
 
I think the argument is a bit backward.

There IS A NEED for an automobile that does not destroy the planet. The Chevy Bolt was not that automobile because it was a dumb idea. I always thought it was strange to tout long range on a car with no cargo space. What's the point of travelling far if you can't take anything with you? The Nissan Leaf also has range and battery issues that will be difficult for the carmaker to shake. Not to mention the fact that dealer sales people are absolute morons when it comes to EVs, and they tend to steer people away from them.
 
Oils4AsphaultOnly said:
lorenfb said:
Oils4AsphaultOnly said:
ha! So, because it's tesla, the datum doesn't count?!

Alright, then I'll share with everyone my favorite statistician (jhm), and his plug-in EV predictive envelope model (based on historical data): https://teslamotorsclub.com/tmc/posts/3683239/

If you believe nothing else of his, pay attention to how his model was more accurate than BNEF's (Bloomberg NEF), which many in the oil industry rely on to make their production plans on:
" In April, 2018, BNEF forecast 2018 to come in at 1.56M or about 1.67% share. The actual was 2.018M or 2.12% share. Let's what my method would have predicted using just 2012 thru 2015 data (a sample size of just 3). My 2015 forecast of 2018 would have centered on 2.2% with a 90% predictive interval from 1.3% to 3.5%. Yeah, a lot of uncertainty, but nailed it. My 2016 forecast of 2018 centered on 1.8% ranging from 1.3% to 2.5%. This was a little more pessimistic, but less uncertain. Then the 2017 forecast of 2018 centered around 2.0% ranging from 1.7% to 2.4%. So the predictive envelope nicely closed in on the actual. Meanwhile, BNEF low forecast was ruled out of the predictive interval by the time it was made using 2017 as the last historical datum. Presumably, BNEF's forecast had that benefit of highly granular data, their proprietary data, and a multi-industry team of analysts. Surely with all that going for them, they should have been able to produce a forecast with much less uncertainty, but in fact a sample size of 5 historical observations could have alerted them to the possibility that their prediction was high improbably. "

RTFA, he writes well and should open many people's eyes on their short-sightedness.

Just another forecast based on historical data, e.g. predicting the future S&P price for 2020 without regard to market forces such as
the outcome of the trade war with China. There's no discussion of key factors that will motivate/influence the consumer's preference
for EVs over ICEVs in the next 10 years. Again, the key point:

There was a need in the early 2000s in search of a product, i.e. a mobile device that could not only provide cell communications, but also
internet access, a camera, and music storage. The product that fulfilled that need was the iPhone. Presently, the EV is a product in search
of a need
. The majority of consumers presently don't perceive any great need that an EV can provide versus an ICEV. Given that, the sales
growth of EVs will not significantly displace sales of ICEVs in the near term.

Here in CA we wasted tax money developing a product in search of a need, a partial rail system from SoCal to NorCal.

As I said, you need to RTFA. He addressed your "issue".


In an effort to make a simple, but compelling forecast of plug-in EV market share, I have boiled things down to a random walk on a logit scale. May sound complex, but it actually makes very few assumptions. I examine market share from 2012 to 2018, computing the annual increase in logit market share (log(S/(1-S)). So I've got now 6 data points. I compute the mean and sample standard deviations. I make the assumption that future logit differences have the same distribution as was operative in the past. Thus, the future is modeled as a random walk with a certain mean and standard deviation. I can than predict the mean and variance (inclusive of parametric uncertainty) of the logit random walk. From this I can convert back into the market share scale, tracing out the mean path and a 90% predictive envelope.

It's total hyperbole to the max. Anyone who has studied finance theory and Fourier Analysis as applied to a random walk time series data
has learned that the predictive ability using that data is basically zero, i.e. it's a random noise signal with a variance of zero. Technical Analysis
theory of the stock market has attempted to forecast the overall stock market and individual stock prices for decades and has failed.

Total naivete and laughable!
 
lorenfb said:
Oils4AsphaultOnly said:
lorenfb said:
Just another forecast based on historical data, e.g. predicting the future S&P price for 2020 without regard to market forces such as
the outcome of the trade war with China. There's no discussion of key factors that will motivate/influence the consumer's preference
for EVs over ICEVs in the next 10 years. Again, the key point:



Here in CA we wasted tax money developing a product in search of a need, a partial rail system from SoCal to NorCal.

As I said, you need to RTFA. He addressed your "issue".


In an effort to make a simple, but compelling forecast of plug-in EV market share, I have boiled things down to a random walk on a logit scale. May sound complex, but it actually makes very few assumptions. I examine market share from 2012 to 2018, computing the annual increase in logit market share (log(S/(1-S)). So I've got now 6 data points. I compute the mean and sample standard deviations. I make the assumption that future logit differences have the same distribution as was operative in the past. Thus, the future is modeled as a random walk with a certain mean and standard deviation. I can than predict the mean and variance (inclusive of parametric uncertainty) of the logit random walk. From this I can convert back into the market share scale, tracing out the mean path and a 90% predictive envelope.

It's total hyperbole to the max. Anyone who has studied finance theory and Fourier Analysis as applied to a random walk time series data
has learned that the predictive ability using that data is basically zero, i.e. it's a random noise signal with a variance of zero. Technical Analysis
theory of the stock market has attempted to forecast the overall stock market and individual stock prices for decades and has failed.

Total naivete and laughable!

He's a seasoned statistician, whose analysis (the ones that I haven't linked to) have been far more accurate than anything published out there. Anyway, I've provided the reference. You just chose to mock it.
 
Oils4AsphaultOnly said:
He's a seasoned statistician, whose analysis (the ones that I haven't linked to) have been far more accurate than anything published out there. Anyway, I've provided the reference. You just chose to mock it.

Do some reading yourself about random walk theory, and not focus on "He's a seasoned statistician".

https://corporatefinanceinstitute.com/resources/knowledge/trading-investing/what-is-the-random-walk-theory/
 
lorenfb said:
Oils4AsphaultOnly said:
He's a seasoned statistician, whose analysis (the ones that I haven't linked to) have been far more accurate than anything published out there. Anyway, I've provided the reference. You just chose to mock it.

Do some reading yourself about random walk theory, and not focus on "He's a seasoned statistician".

https://corporatefinanceinstitute.com/resources/knowledge/trading-investing/what-is-the-random-walk-theory/

You truly are in your own little world! Here's a better reference and far more relevant to my post about PEV adoption: https://en.wikipedia.org/wiki/Random_walk

What the freak does the stock market have to do with exponential growth of BEV's, which is what you asked the data for?!
 
webb14leafs said:
GRA said:
lpickup said:
Actually, it's more like "hockey stick" growth, but exponential will be a suitable proxy.

My crystal ball? Battery costs. Battery costs have been falling at a very consistent 19% per year, and is forecast to continue this trend. Maybe you have a reason to believe this will not be the case, but with all the research going on in the battery world, I don't really see an end to this trend in the next 5 years.

Now so far, the cost savings on the battery side have not transitioned directly to cost savings on the vehicle. This is because automakers have focused on adding larger format batteries to address a perceived range limitation. But there have been significant increases in range over the past 8 years, while keeping the price constant. I believe that once we hit an affordable 300 mile (maybe 350) EV, that there will be little reason to keep adding more battery, and instead we will see a shift towards making vehicles more affordable. And eventually there will be a crossover point where the unsubsidized cost of an EV will be less than an equivalent ICE.

And at that point, to the buying public, it simply won't matter whether it's an EV or an ICE. That's the problem I have with people that are saying this or that about "EV demand". Most people are sticker-price focused. They don't necessarily care what's under the hood. They only care about what the sticker says. And the day the sticker on an EV is less than the sticker on an ICE, they are going to get the EV. At this point it stops being a ramp and turns a sharp corner.

Yes, EVs have to become available in the form factors they want. And yes, there will need to be education of the masses about how and where to charge their cars. But the growing number of EV owners are going to be the teachers. And the more EVs that people see on the road, the more people are going to be willing to ask their friends, neighbors and co-workers about them.

If you think any part of this "crystal ball" is wrong, let me know, but you'll be disagreeing with the technology adoption curve that has been repeated throughout history, so it's a tough argument to make. About the only legitimate difference of opinion we can have is the timescale. Yes, with falling battery prices, the percentage of the cost of the battery to the vehicle becomes smaller, so the gains in vehicle price become less significant. But I don't think this is going to take more than another 4-5 years. We now have 3 mass produces vehicles with ranges over 300 miles, with several more knocking on the door at 250 (unfortunately in somewhat limited quantities). 2020 should be a big year in terms of new EV releases. Once we get those vehicles with 300 miles on the market, we can start the process of driving the costs down.
I agree with almost all of this, except the bolded section. When people say they want/need a 300+ mile car, what they mean by that isn't a 300 or 350 mile BEV, before all the subtractions you need to know about and allow for as regards speed, climate, and degradation, but a 300 or 350 mile range like an ICE. Now, if you were to say 300 or 350 miles including all of the above at the end of the car's life, I'd agree with you, but we all know that requires a range at least 1/3rd and maybe 1/2 or more greater than the nominal range when new. The average age of the fleet is I believe now up to 11.8 years, so EoL battery range should be for at least 12 and probably 15 or 20 years.

I've done this calc for my own requirements. I need a car for roadtrips, and keep them until they no longer function (current car is 16 y.o. and still going strong). I've decided that for a BEV to be reasonably useful and cost-effective for me, at a minimum I want to be able to drive from home to Lee Vininga typical weekend trip, without recharging, a distance of 207 miles on freeway and highway, and which requires climbing from about 100 ft. sea level over 9,941 ft. Tioga Pass 193 miles out before descending 14 miles and 3,160 feet to Lee Vining at 6,780 ft., any time of the year and in any conditions when the road's open (which can range from late April to late Nov., but is usually less). I want to be able to do it for at least 12 years and prefer longer, jut as I prefer longer range and faster recharging. I want to be able to do it driving just as I do in my ICE,at the same speeds while freely using heat/AC as desired, and with at least a 30 mile reserve under the same conditions. Having played around with EV tripplanner, there's not a single BEV (including the longest-ranged Teslas) now available that can meet those requirements for that length of time, although some of them can do the trip for part of the time and/or under more restrictive conditions. I've been fairly interested in the)a Kia Niro, but its ability to make the trip is questionable even when new, and would be impossible with degradation. That QCs will eventually be built along the way is true, but irrelevant to my needs, which include time limitations as well as flexibility.

By comparison, my 16 y.o. ICE can still do the trip to Lee Vining and return un-refueled basically free of care, as it has essentially the same range as when it was new, and should I need to refuel it due to unusual circumstances I can do so lots of places in no more time than it takes to use the bathroom. I paid something over $24k cash for it out the door, including TTL, so BEVs have a long way to go before they can meet the same value/capability, even if QCing gets cheaper than gas, and even with the current high gas prices in California that's at best a marginal cost advantage over my 28-30 mpg real world hwy ICE, and still at a disadvantage compared to a moderately-high mpg HEV.

And that's just for my basic weekend trip, not the extended road trips that I want to be able to take again in a ZEV, which require even more range and even faster charging

So, while I agree with you that prices will only start to drop when the range is adequate, how much range will be adequate depends heavily on extending the guaranteed, no worries EoL range of BEVs, and that currently requires such large, heavy and expensive battery packs that I don't see the cross-over point happening until sometime beyond the 4-5 years you suggest.

I would expect anyone interested in an EV would be willing to slightly inconvenience themselves out of interest in the technology and/or reducing environmental impact.

Any Tesla, the Chevy Bolt and Nissan+ could easily fit your need with a 20 minute charging stop on the uphill portion of your drive. It's likely no charging would be needed on the return drive.
There's nothing 'slight' about the level of inconvenience. Unfortunately, the available charging stops are too far away, and the charge rates too low to make that work, even if I were willing to accept a further inconvenience beyond the 50% range reduction I already am. And that ignores the fact that Just getting to Lee Vining is often just the first stop if I'm going south to Mammoth (28 miles), Bishop (64 miles), or Lone Pine (125 miles beyond L.V.), and getting to the the trailheads that are typically 10-15 miles and several thousand feet above those towns, and return to the nearest QC. The number of required QC stops each way grows beyond one, which is about the limit of additional inconvenience I or most people will accept for a weekend trip, as you can combine that stop with a meal.

To use the Niro as an example, you suggest a 20 min. QC would be adequate on the way up. Not a chance. Kia says it will take 42 minutes to charge from 20 to 80%, and 54 minutes to charge from an unstated but presumably low single digits % to 80%, in both cases from a QC rated for 100kW or more. I haven't seen the Niro's EPA Hwy range stated anywhere, but its combined range is 239 vs. the Bolt's 238, and the latter has a HWY range of 217 miles. The Niro's probably a bit more aerodynamic, so let's assume 220 miles Hwy @ 100%. 80% is 176 miles, then we need to subtract 30 miles as a reserve (nowhere near enough given the current spacing of QCs, but hopefully at some future point their density will increase to approach that of gas stations), plus allowances for HVAC use, wind, temps, elevation gain, etc. Figure no more than 130 miles Hwy, and possibly 120 or less is the real 'guaranteed' range after a QC to 80%, which will take a significant portion of an hour. and all that is only possible with a new rather than a degraded battery. At the moment the best capacity warranty I'm aware of is 70% after 8 years, so instead of starting from 220 miles we're now down to 156 miles Hwy before all the other necessary subtractions.

Oh, and I picked Lee Vining because it's the major crossroads and shortest route for trans-Yosemite traffic to 395, and I hoped that EA would build a QC there; instead, they chose to start building one 25 miles north in Bridgeport, which helps me not at all unless I take a different, longer route across the Sierra, so I'd actually need to be able to reach Bishop (once it's built), another 64 miles south of Lee Vining. Presumably someday Lee Vining will get some QCs, but as I've already been waiting over 8 years for (non-Tesla) QCs enroute to and across Yosemite and then down 395, I'm not going to hold my breath expecting its early arrival. It's only sometime later this year that such a trip will even be possible in a non-Tesla BEV.

But those are my particular needs, and say nothing about what limitations a member of the general public will be willing to put up with, which is likely to a lot less than I am as they have zero ideological motivation. We know what the major issues preventing them from getting a BEV are: MSRP, range and charging sites.
 
WetEV said:
GRA said:
I've done this calc for my own requirements. ...

So, while I agree with you that prices will only start to drop when the range is adequate, how much range will be adequate depends heavily on extending the guaranteed, no worries EoL range of BEVs, and that currently requires such large, heavy and expensive battery packs that I don't see the cross-over point happening until sometime beyond the 4-5 years you suggest.

GRA, you are a corner case. As are my former neighbors in Boston area who had once taken a road trip... to Springfield MA. A 60kWh Chevy Bolt, LEAF+ or similar could do this trip with ease.

Most people are between these extremes. Remember we don't need to put everyone in an electric car. Just the next 2% over the next 3 years. Then the next 4% over the 3 years after that.
I recognize that my particular usage case is skewed almost entirely towards road trips, but the average person doesn't buy a car based on their routine needs, they buy one based on what Waymo CEO John Krafcik calls "The Occasional Use Imperative," which is why most people drive around in 5-8 pax. vehicles when the avg. occupancy per trip is 1.7, and only 1.1 during commutes. The potential advantage of ride-shared AVs
is that most of the cars can be small, light 1-2 pax. BEVs with batteries sized for local use instead of what cwerdna calls BRoD-class 4WD SUVs that people may only need once a year. IOW, Smarts, not Expeditions.
 
lpickup said:
GRA said:
I've done this calc for my own requirements.

They may not meet your own requirements. But that's not what matters. What matters is when carmakers stop focusing on just adding more battery and start focusing on reducing costs.

Even Tesla has started doing this, making the statement that they can pump out more SR+ vehicles that LR vehicles (because they are battery constrained), so that is their focus right now. I personally think that 240 miles is a bit below what I think the sweet spot is (280 miles).

I don't know exactly what the motivations were, but Nissan decided to focus on the sub-$30K niche with the 40kWh LEAF.

VW appears headed in this direction as well, but I will reserve comment until they do prove that they have battery supply and are really serious about entering the market.

And like I said, it may not be 4-5 years. Maybe it's 7-8. But it's coming. Folks that say otherwise are burying their heads in the sand.
In the meantime, as battery supply is going to be an issue while manufacturing scales up (even if raw material supply doesn't further slow things down), it makes far more sense, if reducing GHGs and local air pollution are your motivations, to put several more people in much less expensive PHEVs with smaller batteries sized to handle routine needs, instead of sticking huge, expensive batteries in a much smaller number of cars, when most of that capacity will go unused most of the time. One Niro/Kona/Soul BEV = 3.5 Volt 2s or 7.3 Prius Primes.

lpickup said:
P.S. While I do agree with your factoring in battery longevity and temperature into required range calculations, my opinion is that is more of a local travel phenomenon. Cold temps on a trip should only really matter for the first leg of the trip (and maybe not even that if you pre-heat), so range loss is not going to be as extreme as when you are just driving around town.
No, it's the opposite. Around town you benefit from Regen, on a trip (uphill) you don't. On a road trip you want to stop as little as possible, so times between pre-heating are going to be long, and any energy for that while charging just makes your charge time longer.

lpickup said:
Degradation could be a factor of course, but again, I don't think you have to assume any more than 20% loss. Why? Because by then a battery replacement (if needed) should be reasonably affordable for a 10 year old car, and in a Tesla you are probably only looking at 10-15% loss in that timeframe. Factoring in 50% loss in 12-15 years is far too conservative.
I'm not going to assume anything about future battery prices or the availablility of replacements. We've got plenty of LEAF owners here who did that; enough said. As noted in another post, the best capacity warranty extant AFAIK is 70% for 8 years, and we've got plenty of examples of batteries losing more than that in less time. At the moment, the oldest Model S is not quite 7 y.o., and there are Teslas that have exceeded that 30% loss. I know of no battery chemistry currently available which can provide 12 years of service at anything like the capacity % required for other than local use. which is one reason I'm a fan of battery leasing with guaranteed capacity.

lpickup said:
I simulated my long distance trip using various vehicles as well. I found that even the Model 3 SR could handle the trip I take without any timing impact to my driving pattern (although the stops would be strictly regimented), which was a big surprise to me. That's 220 miles of range and slower charging that I can get from my LR. So even if I experience 30% degradation I am not too worried.
Unfortunately, even the Model 3 LR couldn't handle mine except when brand new, and it's far too expensive to be mass market.
 
Oils4AsphaultOnly said:
lorenfb said:
Oils4AsphaultOnly said:
He's a seasoned statistician, whose analysis (the ones that I haven't linked to) have been far more accurate than anything published out there. Anyway, I've provided the reference. You just chose to mock it.

Do some reading yourself about random walk theory, and not focus on "He's a seasoned statistician".

https://corporatefinanceinstitute.com/resources/knowledge/trading-investing/what-is-the-random-walk-theory/

You truly are in your own little world! Here's a better reference and far more relevant to my post about PEV adoption: https://en.wikipedia.org/wiki/Random_walk

What the freak does the stock market have to do with exponential growth of BEV's, which is what you asked the data for?!

Read his naive methodology:
In an effort to make a simple, but compelling forecast of plug-in EV market share, I have boiled things down to a random walk on a logit scale. May sound complex, but it actually makes very few assumptions. I examine market share from 2012 to 2018, computing the annual increase in logit market share (log(S/(1-S)). So I've got now 6 data points. I compute the mean and sample standard deviations. I make the assumption that future logit differences have the same distribution as was operative in the past. Thus, the future is modeled as a random walk with a certain mean and standard deviation. I can than predict the mean and variance (inclusive of parametric uncertainty) of the logit random walk. From this I can convert back into the market share scale, tracing out the mean path and a 90% predictive envelope.

Your "statistician" is attempting to forecast future product demand/sales based on a random walk process (historical data), similar to
forecasting future stock prices, which basically has been proven baseless. One can attempt to forecast future production volumes based
on historical data, because all the key model factors are known, e.g. worker productivities, supply chain lead times, etc. But to attempt
to forecast future demand for a product based on historical data only is naive - similar to forecasting future stock prices. One lacks key
market info such as, competitive future products/advertising, future technology breakthroughs, new market entries, etc., which are
critical for optimizing the forecasting model and are basically not know.
 
lorenfb said:
Oils4AsphaultOnly said:
lorenfb said:
Do some reading yourself about random walk theory, and not focus on "He's a seasoned statistician".

https://corporatefinanceinstitute.com/resources/knowledge/trading-investing/what-is-the-random-walk-theory/

You truly are in your own little world! Here's a better reference and far more relevant to my post about PEV adoption: https://en.wikipedia.org/wiki/Random_walk

What the freak does the stock market have to do with exponential growth of BEV's, which is what you asked the data for?!

Read his naive methodology:
In an effort to make a simple, but compelling forecast of plug-in EV market share, I have boiled things down to a random walk on a logit scale. May sound complex, but it actually makes very few assumptions. I examine market share from 2012 to 2018, computing the annual increase in logit market share (log(S/(1-S)). So I've got now 6 data points. I compute the mean and sample standard deviations. I make the assumption that future logit differences have the same distribution as was operative in the past. Thus, the future is modeled as a random walk with a certain mean and standard deviation. I can than predict the mean and variance (inclusive of parametric uncertainty) of the logit random walk. From this I can convert back into the market share scale, tracing out the mean path and a 90% predictive envelope.

Your "statistician" is attempting to forecast future product demand/sales based on a random walk process (historical data), similar to
forecasting future stock prices, which basically has been proven baseless. One can attempt to forecast future production volumes based
on historical data, because all the key model factors are known, e.g. worker productivities, supply chain lead times, etc. But to attempt
to forecast future demand for a product based on historical data only is naive - similar to forecasting future stock prices. One lacks key
market info such as, competitive future products/advertising, future technology breakthroughs, new market entries, etc., which are
critical for optimizing the forecasting model and are basically not know.

You criticize his methodology as "naive", yet missed the first sentence of "In an effort to make a simple, but compelling forecast". You obviously didn't bother reading the rest of his case where he retested the predictability of his "naive" model using 2012-2015 data to predict the subsequent years and demonstrated how it was more accurate than BNEF's more complicated model and predictions. His entire point was that the adoption curve is sufficiently defined within this "naive" model, and that a more complicated model isn't necessary to give a good approximation of how fast EV adoption is progressing.

Pay attention to his graph! By 2025, there's a huge 25% spread of EV adoption between the low and high ends of his predictive envelope. If you factor in market info, you might end up with a more precise prediction model, but you're still going to have exponential growth that exceeds 60% market share by 2030. You're asking for the theory of relativity, when newtonian physics is enough.
 
Oils4AsphaultOnly said:
lorenfb said:
Oils4AsphaultOnly said:
You truly are in your own little world! Here's a better reference and far more relevant to my post about PEV adoption: https://en.wikipedia.org/wiki/Random_walk

What the freak does the stock market have to do with exponential growth of BEV's, which is what you asked the data for?!

Read his naive methodology:
In an effort to make a simple, but compelling forecast of plug-in EV market share, I have boiled things down to a random walk on a logit scale. May sound complex, but it actually makes very few assumptions. I examine market share from 2012 to 2018, computing the annual increase in logit market share (log(S/(1-S)). So I've got now 6 data points. I compute the mean and sample standard deviations. I make the assumption that future logit differences have the same distribution as was operative in the past. Thus, the future is modeled as a random walk with a certain mean and standard deviation. I can than predict the mean and variance (inclusive of parametric uncertainty) of the logit random walk. From this I can convert back into the market share scale, tracing out the mean path and a 90% predictive envelope.

Your "statistician" is attempting to forecast future product demand/sales based on a random walk process (historical data), similar to
forecasting future stock prices, which basically has been proven baseless. One can attempt to forecast future production volumes based
on historical data, because all the key model factors are known, e.g. worker productivities, supply chain lead times, etc. But to attempt
to forecast future demand for a product based on historical data only is naive - similar to forecasting future stock prices. One lacks key
market info such as, competitive future products/advertising, future technology breakthroughs, new market entries, etc., which are
critical for optimizing the forecasting model and are basically not know.

You criticize his methodology as "naive", yet missed the first sentence of "In an effort to make a simple, but compelling forecast". You obviously didn't bother reading the rest of his case where he retested the predictability of his "naive" model using 2012-2015 data to predict the subsequent years and demonstrated how it was more accurate than BNEF's more complicated model and predictions. His entire point was that the adoption curve is sufficiently defined within this "naive" model, and that a more complicated model isn't necessary to give a good approximation of how fast EV adoption is progressing.

Pay attention to his graph! By 2025, there's a huge 25% spread of EV adoption between the low and high ends of his predictive envelope. If you factor in market info, you might end up with a more precise prediction model, but you're still going to have exponential growth that exceeds 60% market share by 2030. You're asking for the theory of relativity, when newtonian physics is enough.

And to sum it up and end the issue:

With just six data points, one is able to forecast a market 15 years out, right?

A totally laughable joke!

A common case where the wrong theory and background are used to solve a problem.
 
lorenfb said:
Oils4AsphaultOnly said:
lorenfb said:
Read his naive methodology:


Your "statistician" is attempting to forecast future product demand/sales based on a random walk process (historical data), similar to
forecasting future stock prices, which basically has been proven baseless. One can attempt to forecast future production volumes based
on historical data, because all the key model factors are known, e.g. worker productivities, supply chain lead times, etc. But to attempt
to forecast future demand for a product based on historical data only is naive - similar to forecasting future stock prices. One lacks key
market info such as, competitive future products/advertising, future technology breakthroughs, new market entries, etc., which are
critical for optimizing the forecasting model and are basically not know.

You criticize his methodology as "naive", yet missed the first sentence of "In an effort to make a simple, but compelling forecast". You obviously didn't bother reading the rest of his case where he retested the predictability of his "naive" model using 2012-2015 data to predict the subsequent years and demonstrated how it was more accurate than BNEF's more complicated model and predictions. His entire point was that the adoption curve is sufficiently defined within this "naive" model, and that a more complicated model isn't necessary to give a good approximation of how fast EV adoption is progressing.

Pay attention to his graph! By 2025, there's a huge 25% spread of EV adoption between the low and high ends of his predictive envelope. If you factor in market info, you might end up with a more precise prediction model, but you're still going to have exponential growth that exceeds 60% market share by 2030. You're asking for the theory of relativity, when newtonian physics is enough.

And to sum it up and end the issue:

With just six data points, one is able to forecast a market 15 years out, right?

A totally laughable joke!

A common case where the wrong theory and background are used to solve a problem.

Indeed! I've led, yet the parched horse doth not drink. :(
 
InsideEVs May M3 update; https://insideevs.com/news/352626/ev-sales-scorecard-may-2019/

Summary:

1. 2019 YTD (5 months) M3 U.S. - 46K
2. 2019 YTD Average per month - 9K
3. 2018 Q4 M3 U.S. - 62K, average per month - 20K
4. May 2019 M3 U.S. - 14K

Conclusion - Three months in 2018 outsold five months in 2019. M3 YTD U.S. demand compared to 2018 Q4 is weak.
 
Really amazing negative spin in your "summary". Great job completely ignoring all the international deliveries (which these numbers do not show).

Here's the insideevs numbers for U.S. deliveries of the 3 for last year and this.
Code:
Jan    Feb    Mar    Apr    May    Jun    Jul    Aug    Sep    Oct    Nov    Dec    Jan    Feb    Mar    Apr    May
1875   2485   3820   3750   6000   5902   14250  17800  22250  17750  18650  25250  6500   5750   10175  10050  13950

Looking at the whole table on insideevs, I see that LEAF U.S. sales continue to be less than 1/10 of the 3 sales. If the 3 demand is "weak", what do you call the LEAF demand?
 
jlv said:
Looking at the whole table on insideevs, I see that LEAF U.S. sales continue to be less than 1/10 of the 3 sales. If the 3 demand is "weak", what do you call the LEAF demand?

So what, Nissan doesn't rely on Leaf sales for its viability does it? Please avoid non sequiturs.
 
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