Don't know if this seat story with Model 3 production numbers is old news:
Tesla's seat strategy goes against the grain...for now
Tesla's seat strategy goes against the grain...for now
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yep- older news rehashed;
My conjecture:
It's one of the many pieces for the eventual Dreadnaught efforts, which includes pulling production speed bottlenecks and costs out of the whole car. Seats would be a prime target, as they are labor intensive (by the supplier) and still costly to inventory (volume)-- Not sure if this extends to M3 though currently- It may be added later for that I suspect
Here's a good summary write-up from Fred on the newly revealed EPA document:
Tesla could be underselling Model 3’s range and charging capacity, reveals EPA document
summary clippings:
"<
In the case of the Model 3, the document reveals that the vehicle achieved an EPA-cycle range of 334 miles (537 km), but Tesla asked the EPA to lower the official range to 310 miles.
Another interesting tidbit of information from the EPA document:
“The vehicle is also capable of accepting DC current up to 525A from an off‐board charger (Supercharger)”
That’s especially interesting considering Tesla’s advertised charging rate for Model 3 is actually a bit slower than Model S and Model X.
Yet, a DC charging current of “up to 525A” at 400 volts would be mean a charge rate of 210 kW, which is significantly higher than the current Model S/X’s Supercharger charge rate of 120 kW.
It would be an important jump in capacity – though nowhere near the expected 350 kW+ system enabled by the anticipated Supercharger version 3 announced by Tesla CEO Elon Musk last year.
Another interesting tidbit of information from the document is the expected self-discharge rate, also known as “vampire drain”, of Model 3’s battery pack. Tesla wrote in the document:
“The self‐discharge rate of the battery is likely to be less than 4% per month.”
If true, that’s actually really impressive and a significant improvement over Model S and Model X.
When Tesla first introduced Model S in 2012, the vampire drain was as high as 1% per day – meaning a vehicle could discharge about 30% of its capacity in a month of being parked.
Tesla has since improved on the issue for Model S and Model X, but if I had to guess, I’d say it’s still nowhere near as low as 4% per month.
The document also confirms the weight of the battery pack at 480 kg (1,058 lbs) or just over a quarter of the entire curb weight of the vehicle: 1,740 kg (3,837 lbs).
>"
Tesla could be underselling Model 3’s range and charging capacity, reveals EPA document
summary clippings:
"<
In the case of the Model 3, the document reveals that the vehicle achieved an EPA-cycle range of 334 miles (537 km), but Tesla asked the EPA to lower the official range to 310 miles.
Another interesting tidbit of information from the EPA document:
“The vehicle is also capable of accepting DC current up to 525A from an off‐board charger (Supercharger)”
That’s especially interesting considering Tesla’s advertised charging rate for Model 3 is actually a bit slower than Model S and Model X.
Yet, a DC charging current of “up to 525A” at 400 volts would be mean a charge rate of 210 kW, which is significantly higher than the current Model S/X’s Supercharger charge rate of 120 kW.
It would be an important jump in capacity – though nowhere near the expected 350 kW+ system enabled by the anticipated Supercharger version 3 announced by Tesla CEO Elon Musk last year.
Another interesting tidbit of information from the document is the expected self-discharge rate, also known as “vampire drain”, of Model 3’s battery pack. Tesla wrote in the document:
“The self‐discharge rate of the battery is likely to be less than 4% per month.”
If true, that’s actually really impressive and a significant improvement over Model S and Model X.
When Tesla first introduced Model S in 2012, the vampire drain was as high as 1% per day – meaning a vehicle could discharge about 30% of its capacity in a month of being parked.
Tesla has since improved on the issue for Model S and Model X, but if I had to guess, I’d say it’s still nowhere near as low as 4% per month.
The document also confirms the weight of the battery pack at 480 kg (1,058 lbs) or just over a quarter of the entire curb weight of the vehicle: 1,740 kg (3,837 lbs).
>"
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I'm not sure that "self discharge" and "vampire drain" are the same thing. Some kinds of batteries really do go down even when not connected to anything at all, and that's usually referred to as self-discharge. But I could be wrong here, maybe vampire drain is what they meant.
Thanks.
Particularly for showing an awareness of volume, and its consequences.
Typically there is a frame and foam. City cars (Honda and Fiat) have tried to use fabric/hammock like designs in the 70s and 80s, but it has never seemed work out. Foam on frame still rules. I don't know if the EV vibration profile makes those conclusions invalid, I don't think so as the stiffness profile drops off too fast with a hard seat or stretched fabric - for people who don't sleep on concrete.
If the volume is foam, will Tesla manufacture the foam in facility?
10000 to 30000 can’t keep a secret, that’s why.
The 9-26 picture indicates the first slip.
dc_h
Active Member
Elon saidcftom day 1 the production goal of July was a stretch goal and unlikely. His aim for the stars and hit Mars is and has been his mgmt philosophy from day one. Anyone investing in TSLA should know this. I’m optimistic about Model 3 getting on track soon, but I’m prepared for a bumpy ride the next few weeks. Numbers matter know, and like during the X rollout, new product or other good news did not matter, only getting X production going mattered. So 300 or less or 400 or more are both options depending on production of the 3 by end of year.
I think Elon is intending and I’m hoping, to have good news on production by earnings, but we’ll see.
gavine
Petrol Head turned EV Enthusiast
Great video....My favorite line from Elon at 6:00 mark. "At a certain point, people have to get tired of being wrong".
A tongue-in-cheek response that I also happen to agree with
In a serious vein, I consider at least 50% of the work involved in "doing data science" to be this problem. Namely, what is the problem / opportunity / challenge that we want/need to work on, what does success look like, and what data do we have available that addresses that problem.
I shorten all of that down to "frame business problem as analytics problem". I've worked on projects for weeks or months before we knew what the problem was that we were trying to solve. And invariably, once this becomes crisp, it also seems like it becomes vanishingly small and specific.
As difficult as model building and validation is, I consider the "frame business problem as analytics problem" to be far and away the hardest problem of all to solve consistently. Because it's not strictly math, and because it's also not strictly whatever you think/decide it might be - it's a mix of imagination that gets connected back to specific data and analysis techniques in which you can imagine a path to success (even if the eventual path to success looks completely different what was originally imagined).
Here's an example, as somebody that uses some of the techniques, but doesn't actually work in autonomous driving. Given "autonomous driving", what is the specific problem that we need our program / AI to solve for?
For me at least, the first articulation of that problem is something like "keep it in your lane, don't hit the person in front of you". This actually results in two problems that need to be solved - sense the vehicle / thing in front of your vehicle and don't hit them, while simultaneously steering right and left in such a fashion that you don't leave your lane.
Of course, this simple first pass won't get you to autonomous driving, but it DOES get us to something that is immediately useful today. Many of us use it on a regular basis in our Teslas.
So what else do we need our autonomous driving program to do?
Well, it'd be nice if it knew where we were going (navigation destination has been chosen), if it were able to signal and change lanes on the freeways into exit lanes, exit one freeway, and then merge onto the next freeway. That introduces a whole host of additional problems to solve, while still being a pretty well constrained problem to solve and still being far short of "autonomous driving". Encompassed in this will be logic / AI for changing into an adjoining lane without hitting somebody and without cutting somebody off, and then changing lanes again for merging onto a highway.
There's also a another bit of more strategic logic that is monitoring your vehicle's progress along a route specified in nav, and making decisions about the need to change lanes, exit one highway, merge onto a new highway. And at some point, signal to the driver that the portion of the route the car is ready/willing to navigate on it's own is ending and the driver needs to be ready to take over.
This functionality is something Tesla has talked about releasing, and we're STILL nowhere close to "autonomous driving".
Upshot, at least for me - "autonomous driving" isn't a single problem. It's dozens (and maybe more like hundreds) of intertwined problems that all need to be solved. And remember, as difficultl as all of these problems are indivdually and collectively to solve, they are still trivial next to "what is the problem/challenge/opportunity for us to address".
We data scientists may find ourselves automated out of a model building job in the future (plenty of technology showing up to automate / simplify the model building process). I STILL haven't seen something that will automate, or even make a guess for us, at what problems are worth solving, need solving, and can be solved given the data available or that can be acquired.
In the spirit of the village idiot like Nasrudin, all my knowledge is based on the old paper, "Dave," by NVDA and a recent series of articles in the New York Times on AI. On the latter it is mostly a survey but one idea stood out. AI researchers are concerned about the machines resistance to the off switch.
In my simpleton understanding of the "Dave" approach it appears above you are doing the work of the machine. I think the problem is easier to understand. What programmers must do, it seems to me is far simpler than you sketch out. The machine is told, here is a data set. What you are receiving are inputs from an environment. We call it a car being navigated. Learn what "the car" is doing. They are teaching the machine how to drive. They are not specifying what the machine is supposed to learn. The drivers of the car are doing in many subtle ways the thinking you want to formalize. With the variety of drivers and situations encountered the machine will learn from us how to drive. No?
To protect ourselves from malicious AI we have to show the machines good behavior and why bad behavior is to be avoided. Since in a first principle sense all intelligence is a hybrid of machine and human, what we must do is lead by good examples, and teach that morality to the machines. Bearing in mind, of course, George Bernard Shaw's observation "if you must provide yourself as an object lesson for your children, do so as a threat and not an example." That is the dilemma of the off switch.
I refrain from elaborating on the example, "you're fired," or observing we have a Potemkin White House. That would be OT for investors.
Please let me know where I am wrong. Obviously, I don't know **sugar** about programming, although I was exposed to html in preparation for a stand alone course online at just about the time html 5 was being introduced.
Does anyone have insight into how much flexibility Tesla has to switch cell and pack production between autos and TE? For example, assuming the Model 3 ramp is delayed by one month, can Tesla/Panasonic quickly shift a significant amount of the production capacity that was lined up for the Model 3 to produce Powerpacks and Powerwalls for Puerto Rico instead?
Great video!
In my life I have never seen a dumb guy getting tired of being dumb. Just watch Mark Spiegel.
FredTMC
Model S VIN #4925
A couple of points:
- It's unlikely that 525A charging would be at 400V, as that's nearing the full-charge limit of the battery... current will have tapered significantly by then. You would most likely see it at below 350V... so maybe something like 160-180KW.
- The pack on the Model 3 includes charger, HVJB, DC-DC converter, etc... so that weight includes a lot that's not in the Model S pack.
ValueAnalyst
Closed
Tesla integrates seat manufacturing and attempts to automate it for Model 3, says report
Reuters published a report based on comments made by an unnamed former Tesla executive and some auto analysts.
They described “a commitment to vertical integration not seen in the auto industry for decades” and they give the example of Tesla’s seat assembly, which they are reportedly trying to automate.
Reuters published a report based on comments made by an unnamed former Tesla executive and some auto analysts.
They described “a commitment to vertical integration not seen in the auto industry for decades” and they give the example of Tesla’s seat assembly, which they are reportedly trying to automate.
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