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Why Tesla’s lead acid 12V battery needs to be lithium-ion based
It’s a prominent issue surrounding the electric vehicle market that the old-school lead acid battery just isn’t appropriate for new technology vehicles. Many users of electric vehicles, especially Tesla owners, have cited concerns with the poor performance of their 12V or low-voltage battery, oftentimes requiring annual replacement.
In contrast, a lead acid battery in a traditional internal combustion engine (ICE) vehicle generally has a 4 year life-cycle, but why?
RELATED: Tesla Model S 12V Lithium-Ion battery replacement (up to 70% lighter, 4x life)
First off, some of the most important factors to consider in longevity of a battery are “cycle-life”, environmental conditions, discharge/charge rates and calendar-life; cycle-life is how many times the battery can be drained and recharged in its life. Environmental conditions include temperature and humidity. Discharge/charge rates are the amperages going out of and into the battery respectively.
There are two major differences between the way an ICE vehicle uses its 12V battery and the way an EV uses its 12V battery:
“OFF” state discharge and cycling frequency
ICE Vehicle: generally has a very low 12V load while the vehicle is in the “off” state, often this load doesn’t exceed a few watts and doesn’t present a major challenge for the 12V battery to maintain.
Electric Vehicle: The 12V load while in the off-state is often much higher due to advanced computer systems that are running to maintain the high-voltage battery, keep vehicle “connected” (all EV have some remote access features), maintain charging and BMS (Battery Management System) communications, etc. In fact a Tesla Model S/X puts about 50 Watts of load on the 12V system when the vehicle is in the “off” state. 50 Watts equals about 4.5 Amps of discharge on the 12V battery, this drains the battery down relatively rapidly and requires the 12V battery be “recharged” by the high-voltage battery regularly, this usage pattern results in many cycles being placed on the battery.
“ON” state utilization and purpose
ICE Vehicle: The 12V battery is used to initiate the ICE (start the car) and is designed for putting out large amounts of current to accommodate this process. Once an ICE vehicle is in the “on” state, it relies on an alternator to power all of the 12V sub-systems and also maintain the voltage of the 12V battery.
Electric Vehicle: The 12V is subjected to (practically) no additional load while the vehicle is being turned “on”, and although most vehicles are designed with DC/DC converters (which act as alternators) it is often an engineering design choice to reduce load on the DC/DC converter by minimizing the frequency with which it is utilized. This also extends the driving range of the vehicle because none of the precious high-voltage battery capacity is being shunted to non-driving tasks. Due to this usage profile the 12V battery is subjected to relatively low discharge and recharge currents.
When you combine the high number of cycles and the low current requirements of the electric vehicle 12V battery system you arrive at a completely different battery need than that of an ICE vehicle. Lead Acid batteries are very good at high discharge and low cycle count life-styles, this is their bread and butter and this is where they last a long time and provide the most bang for the buck (cheap cost and decent product life-cycle), but they aren’t lasting in electric vehicles.
The electric vehicle 12V battery system is one that is best suited by a battery capable of tremendous cycle-life as the main design goal. The battery chemistry that suits this usage scenario best? Lithium! Lithium battery technology is specifically very good at being cycled many times and continuing to provide minimal capacity loss and degradation. This, along with reduced weight, is why these batteries are used for the high-voltage battery packs, cell-phones, laptops, medical equipment and cars where batteries are being cycled frequently and longevity is important.
Editor’s note: This post was submitted into our network by Tesla Model S owner Sean Scherer. Having suffered an unfortunate incident in his Model S that left him stranded because of a faulty 12V battery, Sherer began on a mission to create a lithium-ion based 12V battery solution that was not only more reliable than the traditional lead acid battery, but better suited for the demands of a Tesla Model S, Model X, and electric vehicles in general. He began BattMobile Batteries, who have made it their mission to improve adoption of electric vehicles by solving some of the small details that has been missed by EV manufacturers.
We’ve also included a video tutorial on how to replace the Model S 12V battery.
Tesla’s Head of AI, Ashok Elluswamy, says that something that was expected with version 14.3 of the company’s Full Self-Driving platform has already partially shipped with the current build of version 14.2.
Tesla and CEO Elon Musk have teased on several occasions that reasoning will be a big piece of future Full Self-Driving builds, helping bring forth the “sentient” narrative that the company has pushed for these more advanced FSD versions.
Back in October on the Q3 Earnings Call, Musk said:
“With reasoning, it’s literally going to think about which parking spot to pick. It’ll drop you off at the entrance of the store, then go find a parking spot. It’s going to spot empty spots much better than a human. It’s going to use reasoning to solve things.”
Musk said in the same month:
“By v14.3, your car will feel like it is sentient.”
Amazingly, Tesla Full Self-Driving v14.2.2.2, which is the most recent iteration released, is very close to this sentient feeling. However, there are more things that need to be improved, and logic appears to be in the future plans to help with decision-making in general, alongside other refinements and features.
On Thursday evening, Elluswamy revealed that some of the reasoning features have already been rolled out, confirming that it has been added to navigation route changes during construction, as well as with parking options.
He added that “more and more reasoning will ship in Q1.”
🚨 Tesla’s Ashok Elluswamy reveals Nav decisions when encountering construction and parking options contain “some elements of reasoning”
More uses of reasoning will be shipped later this quarter, a big tidbit of info as we wait v14.3 https://t.co/jty8llgsKM
— TESLARATI (@Teslarati) January 9, 2026
Interestingly, parking improvements were hinted at being added in the initial rollout of v14.2 several months ago. These had not rolled out to vehicles quite yet, as they were listed under the future improvements portion of the release notes, but it appears things have already started to make their way to cars in a limited fashion.
Tesla Full Self-Driving v14.2 – Full Review, the Good and the Bad
As reasoning is more involved in more of the Full Self-Driving suite, it is likely we will see cars make better decisions in terms of routing and navigation, which is a big complaint of many owners (including me).
Additionally, the operation as a whole should be smoother and more comfortable to owners, which is hard to believe considering how good it is already. Nevertheless, there are absolutely improvements that need to be made before Tesla can introduce completely unsupervised FSD.
Elon Musk
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
Tesla CEO Elon Musk has provided an updated estimate for the training data needed to achieve truly safe unsupervised Full Self-Driving (FSD).
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
10 billion miles of training data
Musk comment came as a reply to Apple and Rivian alum Paul Beisel, who posted an analysis on X about the gap between tech demonstrations and real-world products. In his post, Beisel highlighted Tesla’s data-driven lead in autonomy, and he also argued that it would not be easy for rivals to become a legitimate competitor to FSD quickly.
“The notion that someone can ‘catch up’ to this problem primarily through simulation and limited on-road exposure strikes me as deeply naive. This is not a demo problem. It is a scale, data, and iteration problem— and Tesla is already far, far down that road while others are just getting started,” Beisel wrote.
Musk responded to Beisel’s post, stating that “Roughly 10 billion miles of training data is needed to achieve safe unsupervised self-driving. Reality has a super long tail of complexity.” This is quite interesting considering that in his Master Plan Part Deux, Elon Musk estimated that worldwide regulatory approval for autonomous driving would require around 6 billion miles.
FSD’s total training miles
As 2025 came to a close, Tesla community members observed that FSD was already nearing 7 billion miles driven, with over 2.5 billion miles being from inner city roads. The 7-billion-mile mark was passed just a few days later. This suggests that Tesla is likely the company today with the most training data for its autonomous driving program.
The difficulties of achieving autonomy were referenced by Elon Musk recently, when he commented on Nvidia’s Alpamayo program. As per Musk, “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.” These sentiments were echoed by Tesla VP for AI software Ashok Elluswamy, who also noted on X that “the long tail is sooo long, that most people can’t grasp it.”
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Tesla earns top honors at MotorTrend’s SDV Innovator Awards
MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla emerged as one of the most recognized automakers at MotorTrend’s 2026 Software-Defined Vehicle (SDV) Innovator Awards.
As could be seen in a press release from the publication, two key Tesla employees were honored for their work on AI, autonomy, and vehicle software. MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla leaders and engineers recognized
The fourth annual SDV Innovator Awards celebrate pioneers and experts who are pushing the automotive industry deeper into software-driven development. Among the most notable honorees for this year was Ashok Elluswamy, Tesla’s Vice President of AI Software, who received a Pioneer Award for his role in advancing artificial intelligence and autonomy across the company’s vehicle lineup.
Tesla also secured recognition in the Expert category, with Lawson Fulton, a staff Autopilot machine learning engineer, honored for his contributions to Tesla’s driver-assistance and autonomous systems.
Tesla’s software-first strategy
While automakers like General Motors, Ford, and Rivian also received recognition, Tesla’s multiple awards stood out given the company’s outsized role in popularizing software-defined vehicles over the past decade. From frequent OTA updates to its data-driven approach to autonomy, Tesla has consistently treated vehicles as evolving software platforms rather than static products.
This has made Tesla’s vehicles very unique in their respective sectors, as they are arguably the only cars that objectively get better over time. This is especially true for vehicles that are loaded with the company’s Full Self-Driving system, which are getting progressively more intelligent and autonomous over time. The majority of Tesla’s updates to its vehicles are free as well, which is very much appreciated by customers worldwide.
Tesla AI Head says future FSD feature has already partially shipped
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
