Tesla offers Long Range model owners the ability to increase their vehicle's performance
The Kilowatts/Twitter
If you haven't driven a Tesla, you might not be familiar with the rollercoaster-like feeling of going from 0 to 60 mph. The Long Range Model 3, for example, can accomplish this in 4.2 seconds as-is. All Teslas pull you off the line almost instantly and are already quicker than most internal combustion engine vehicles.
What if, though, you could increase the speed of your Tesla even more? We break down what Tesla's Acceleration Boost is, and whether it's worth the price tag.
What Does Tesla's Acceleration Boost Do?
If you drive a Long Range Model 3 or Model Y, you may be able to purchase the 'Acceleration Boost' upgrade that increases your vehicle's acceleration and lowers your 0-60 time.
The Tesla Model 3 Long Range already has an acceleration from 0 to 60 mph time of about 4.2 seconds. With Acceleration Boost, Tesla claims that time is reduced to 3.7 seconds.
The Tesla Model Y Acceleration Boost shaves off half a second on the vehicle’s 0 to 60 mph time, dropping its run from 4.8 seconds down to 4.3 seconds.
It’s worth highlighting that these are the only two vehicles that are eligible to purchase this upgrade. When Tesla first started delivering the new Model Ys with the 4680 cells, owners of the Standard version were able to upgrade, but the company has since removed this option.
Acceleration Boost vs Performance Times
While Acceleration Boost will give you a very noticeable boost in all performance aspects, it will not turn your vehicle into a Performance model.
Here are the 0 to 60 mph time comparisons between the Long Range model, Long Range with Acceleration Boost and Performance models.
Model
Long Range
Acceleration Boost
Performance
Model 3
4.2 seconds
3.7 seconds
3.1 seconds
Model Y
4.8 seconds
4.3 seconds
3.5 seconds
As you can see from the table above, a Long Range model with the Acceleration Boost upgrade falls roughly between a Performance model and the Long Range model in terms of acceleration.
An owner independently tests out Tesla's Acceleration Boost
MagnusMako/Tesla Motors Club
The graph above was created by an independent owner and displays the vehicle's performance from 0 to 10, 0 to 20, 0 to 30 and 0 to 60 mph after purchasing Tesla's Acceleration Boost. From the graph we can see how the vehicle's acceleration rate remains fairly constant from 0 all the way to 60 mph.
Does Acceleration Boost Add Track Mode?
Track Mode is a feature that is exclusive to Performance models. It allows you to adjust how your vehicle handles and performs. For example, it allows you to adjust features that may be useful on a track, such as adjusting the motor bias from front to rear, reducing traction control or adjusting vehicle cooling.
Although vehicles with Acceleration Boost have better performance than their Long Range counterparts, they do not include Tesla's Track Mode feature.
Is Acceleration Boost Worth It?
While the Acceleration Boost update can be a costly one at $2,000, it unquestionably gives drivers acceleration capabilities that are comparable to those of the Performance model.
According to Tesla drivers who have purchased the upgrade, the actual acceleration boost is quite notable and affects all speeds, not just 0-60 mph.
On the other hand, your Model 3 or Model Y's quick acceleration will result in quicker tire wear. Additionally, it can result in decreased efficiency, which results in higher ownership costs. However, this does depend on the individual and how often they take advantage of the speed boost.
Performance models are usually quite a bit more expensive than the Long Range models, so in terms of value, the Acceleration Boost upgrade is a good deal that will increase the vehicle's value. If you own your vehicle, you'll also likely recoup some of the upgrade's cost if/when you decide to sell the car or trade it in at some point in the future.
Cost and How to Purchase
The price for Acceleration Boost hovers around USD 2,000, depending on your region and local tax rate. Owners can conveniently purchase the upgrade directly from their Tesla app, or through Tesla's website.
To purchase or see if the upgrade is available for your vehicle, open the Tesla app and navigate to the Upgrades section.
Then tap on Software Upgrades and if the feature is available for your Tesla you will see Acceleration Boost listed.
If you'd like to purchase the upgrade, make sure your vehicle is in Park and connected to Wi-Fi or has a strong cellular connection so that the vehicle can download an updated configuration.
You can add the Acceleration Boost upgrade to your cart and follow the payment instructions.
The upgrade is a one-time payment that can be made with a credit card, debit card, or Apple Pay. However, it is not possible to add the cost of the upgrade to your lease or vehicle loan payments.
Once the payment has been processed, the update should only take a few minutes to show up in your vehicle.
How to Check if Your Vehicle Has Acceleration Boost
Once you've made the purchase, you can confirm that you have received the upgrade by tapping on Controls (car icon) and navigating to Software. Below your vehicle's image, you'll see a list of features, including possible features like Full Self-Driving, Premium Connectivity and more.
If your car has received the upgrade, you should now see Acceleration Boost listed.
In addition to the upgrade appearing under the Software tab, you can also navigate to the Pedals & Steering section and your acceleration choices will now be 'Chill' and 'Sport,' instead of the previous options of 'Chill' and 'Standard.'
Your vehicle should now be noticeably faster.
An owner independently tests out Tesla's Acceleration Boost
Smvarg/Medium
Is there an Acceleration Boost Trial?
Although not formally promoted as a trial period, Tesla does provide you the chance to get a refund for your original purchase within 48 hours of purchase, if you change your mind or the upgrade didn't meet your expectations.
It is not possible, however, to receive another refund if you re-purchase the Acceleration Boost upgrade at a later time. Any future purchases for Acceleration Boost will be final.
The Acceleration Boost upgrade might be worthwhile for you if you frequently travel on long, open highways or appreciate experiencing the acceleration surge when you depress the pedal. But if you use your Tesla for routine activities like grocery shopping or being stuck in traffic on the way to and from work, it might not be the best bang for your buck.
However, if you initially had your eye on the Performance model and ultimately decided on the Long Range version, Acceleration Boost is a great way to get closer to the performance of the higher-end trim.
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As December approaches, Tesla’s highly anticipated Holiday update draws closer. Each year, this eagerly awaited software release transforms Tesla vehicles with new features and festive flair. If you’re not familiar with Tesla’s holiday updates, take a look at what Tesla has launched in the Holiday update the past few years.
For this chapter in our series, we’re dreaming up ways Tesla could improve the charging experience and even add some additional safety features. So let’s take a look.
Destination State of Charge
Today, navigating to a destination is pretty straightforward on your Tesla. Your vehicle will automatically let you know when and where to charge, as well as for how long. However, you’ll likely arrive at your destination at a low state of charge.
Being able to set your destination state of charge would be an absolute game-changer for ease of road-tripping. After all, the best EV to road trip in is a Tesla due to the Supercharger network. It looks like Tesla may be listening. Last week, Tesla updated their app and hinted at such a feature coming to the Tesla app. A Christmas present, maybe?
Battery Precondition Options
While Tesla automatically preconditions your battery when needed for fast charging, there are various situations where manually preconditioning the battery would be beneficial.
Currently, there is no way to precondition for third-party chargers unless you “navigate” to a nearby Supercharger. If you need to navigate to a Supercharger that’s close by, the short distance between your location and the Supercharger will also not allow enough time to warm up the battery, causing slower charging times.
While we already mentioned Live Activities in the Tesla app wishlist, they’d be especially useful while Supercharging. Live Activities are useful for short-term information you want to monitor, especially if it changes often — which makes them perfect for Supercharging, especially if you want to avoid idle fees.
Vehicle-to-Load / Vehicle-to-Home Functionality
The Cybertruck introduced Tesla Power Share, Tesla’s name for Vehicle-to-Home functionality (V2H). V2H allows an EV to supply power directly to a home. By leveraging the vehicle’s battery, V2H can provide backup power during outages and reduce energy costs by using stored energy during peak rates.
Tesla Power Share integrates seamlessly with Tesla Energy products and the Tesla app. We’d love to see this functionality across the entire Tesla lineup. Recently a third party demonstrated that bidirectional charging does work on current Tesla vehicles – namely on a 2022 Model Y.
Adaptive Headlights for North America
While Europe and China have had access to the Adaptive Headlights since earlier this year, North America is still waiting. The good news is that Lars Moravy, VP of Vehicle Engineering, said that these are on their way soon.
Blind Spot Indication with Ambient Lighting
Both the 2024 Highland Model 3 Refresh and the Cybertruck already have ambient lighting features, but they don’t currently offer a practical purpose besides some eye candy. So why not integrate that ambient lighting into the Blindspot Warning system so that the left or right side of the vehicle lights up when there’s a vehicle in your blind spot? Currently, only a simple red dot lights up in the front speaker grill, and the on-screen camera will also appear with a red border when signaling.
Having the ambient lighting change colors when a vehicle is in your blind spot would be a cool use of the technology, especially since the Model Y Juniper Refresh and Models S and X are supposed to get ambient lighting as well.
Tesla’s Holiday update is expected to arrive with update 2024.44.25 in just a few short weeks. We’ll have extensive coverage of its features when it finally arrives, but in the meantime, be sure to check out our other wishlist articles:
It’s time for another dive into how Tesla intends to implement FSD. Once again, a shout out to SETI Park over on X for their excellent coverage of Tesla’s patents.
This time, it's about how Tesla is building a “universal translator” for AI, allowing its FSD or other neural networks to adapt seamlessly to different hardware platforms.
That translating layer can allow a complex neural net—like FSD—to run on pretty much any platform that meets its minimum requirements. This will drastically help reduce training time, adapt to platform-specific constraints, decide faster, and learn faster.
We’ll break down the key points of the patents and make them as understandable as possible. This new patent is likely how Tesla will implement FSD on non-Tesla vehicles, Optimus, and other devices.
Decision Making
Imagine a neural network as a decision-making machine. But building one also requires making a series of decisions about its structure and data processing methods. Think of it like choosing the right ingredients and cooking techniques for a complex recipe. These choices, called "decision points," play a crucial role in how well the neural network performs on a given hardware platform.
To make these decisions automatically, Tesla has developed a system that acts like a "run-while-training" neural net. This ingenious system analyzes the hardware's capabilities and adapts the neural network on the fly, ensuring optimal performance regardless of the platform.
Constraints
Every hardware platform has its limitations – processing power, memory capacity, supported instructions, and so on. These limitations act as "constraints" that dictate how the neural network can be configured. Think of it like trying to bake a cake in a kitchen with a small oven and limited counter space. You need to adjust your recipe and techniques to fit the constraints of your kitchen or tools.
Tesla's system automatically identifies these constraints, ensuring the neural network can operate within the boundaries of the hardware. This means FSD could potentially be transferred from one vehicle to another and adapt quickly to the new environment.
Let’s break down some of the key decision points and constraints involved:
Data Layout: Neural networks process vast amounts of data. How this data is organized in memory (the "data layout") significantly impacts performance. Different hardware platforms may favor different layouts. For example, some might be more efficient with data organized in the NCHW format (batch, channels, height, width), while others might prefer NHWC (batch, height, width, channels). Tesla's system automatically selects the optimal layout for the target hardware.
Algorithm Selection: Many algorithms can be used for operations within a neural network, such as convolution, which is essential for image processing. Some algorithms, like the Winograd convolution, are faster but may require specific hardware support. Others, like Fast Fourier Transform (FFT) convolution, are more versatile but might be slower. Tesla's system intelligently chooses the best algorithm based on the hardware's capabilities.
Hardware Acceleration: Modern hardware often includes specialized processors designed to accelerate neural network operations. These include Graphics Processing Units (GPUs) and Tensor Processing Units (TPUs). Tesla's system identifies and utilizes these accelerators, maximizing performance on the given platform.
Satisfiability
To find the best configuration for a given platform, Tesla employs a "satisfiability solver." This powerful tool, specifically a Satisfiability Modulo Theories (SMT) solver, acts like a sophisticated puzzle-solving engine. It takes the neural network's requirements and the hardware's limitations, expressed as logical formulas, and searches for a solution that satisfies all constraints. Try thinking of it as putting the puzzle pieces together after the borders (constraints) have been established.
Here's how it works, step-by-step:
Define the Problem: The system translates the neural network's needs and the hardware's constraints into a set of logical statements. For example, "the data layout must be NHWC" or "the convolution algorithm must be supported by the GPU."
Search for Solutions: The SMT solver explores the vast space of possible configurations, using logical deduction to eliminate invalid options. It systematically tries different combinations of settings, like adjusting the data layout, selecting algorithms, and enabling hardware acceleration.
Find Valid Configurations: The solver identifies configurations that satisfy all the constraints. These are potential solutions to the "puzzle" of running the neural network efficiently on the given hardware.
Optimization
Finding a working configuration is one thing, but finding the best configuration is the real challenge. This involves optimizing for various performance metrics, such as:
Inference Speed: How quickly the network processes data and makes decisions. This is crucial for real-time applications like FSD.
Power Consumption: The amount of energy used by the network. Optimizing power consumption is essential for extending battery life in electric vehicles and robots.
Memory Usage: The amount of memory required to store the network and its data. Minimizing memory usage is especially important for resource-constrained devices.
Accuracy: Ensuring the network maintains or improves its accuracy on the new platform is paramount for safety and reliability.
Tesla's system evaluates candidate configurations based on these metrics, selecting the one that delivers the best overall performance.
Translation Layer vs Satisfiability Solver
It's important to distinguish between the "translation layer" and the satisfiability solver. The translation layer is the overarching system that manages the entire adaptation process. It includes components that analyze the hardware, define the constraints, and invoke the SMT solver. The solver is a specific tool used by the translation layer to find valid configurations. Think of the translation layer as the conductor of an orchestra and the SMT solver as one of the instruments playing a crucial role in the symphony of AI adaptation.
Simple Terms
Imagine you have a complex recipe (the neural network) and want to cook it in different kitchens (hardware platforms). Some kitchens have a gas stove, others electric; some have a large oven, others a small one. Tesla's system acts like a master chef, adjusting the recipe and techniques to work best in each kitchen, ensuring a delicious meal (efficient AI) no matter the cooking environment.
What Does This Mean?
Now, let’s wrap this all up and put it into context—what does it mean for Tesla? There’s quite a lot, in fact. It means that Tesla is building a translation layer that will be able to adapt FSD for any platform, as long as it meets the minimum constraints.
That means Tesla will be able to rapidly accelerate the deployment of FSD on new platforms while also finding the ideal configurations to maximize both decision-making speed and power efficiency across that range of platforms.
Putting it all together, Tesla is preparing to license FSD, Which is an exciting future. And not just on vehicles - remember that Tesla’s humanoid robot - Optimus - also runs on FSD. FSD itself may be an extremely adaptable vision-based AI.
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