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Tesla’s damage monitoring patent hints at cars driving to repair centers autonomously
Despite being cutting-edge machines that could be described as “the most fun thing” that anyone can possibly buy, Tesla’s electric cars are still subjected to a great deal of stress during operation. Electric cars have fewer moving parts than their fossil fuel-powered counterparts, but nevertheless, the components that move, such as their electric motors and suspension, are still subject to different types of stress.
One of Tesla’s recently published patent applications, titled “System and Method for Monitoring Stress Cycles,” discusses this particular issue. As noted by the electric car maker, machines may heat up or cool down, or speed up and slow down at different times during operation, resulting in thermal and mechanical stress. Over time, such stress could result in decreased performance, which is referred to as damage.
Damages are costly and hazardous. Stress-related damage results in equipment downtime, performance degradation, safety hazards, and maintenance expenses, to name a few. In the case of Tesla’s electric cars, these damages can cause breakdowns, or worse, accidents. To prevent this, strategies are usually employed to detect and address stress-related damage, such as repairing damaged parts or replacing components at set intervals. Tesla notes in its patent application that both practices are time-consuming and costly.
“Even regular inspections may not provide adequate protection against stress-related damage. For example, the inspections may not provide sufficient insight into the characteristics of the stresses imposed on a given component to accurately assess its condition. Moreover, the inspections themselves may be burdensome and costly,” the company wrote.
With this in mind, there is a need for a system that can detect and address stress-related damage in a more efficient and cost-effective manner.
Tesla’s recently published patent application outlines a system involving a processor configured to monitor stress imposed on subsystems while determining the cumulative damage to a vehicle’s systems. Tesla notes that a stress monitoring system would work optimally if the processor is configured to monitor stress cycles in real-time, allowing the system to avoid using too much memory in the process. Tesla describes the concept in the following discussion.
“To address these challenges, processor 140 may be configured to monitor stress cycles in real-time. For example, processor 140 may identify and record stress cycles concurrently while receiving the series of stress values from stress sensors 131-139. In some embodiments, for each received stress value in the series of stress values, processor 140 may perform one or more operations to determine whether a stress cycle has been completed. When processor 140 detects the end of a stress cycle, processor 140 may record the stress cycle immediately, such that the cumulative damage model can be continuously updated to reflect the latest recorded stress cycle.
“In some examples, real-time monitoring of stress cycles may be performed without storing the series of stress values in memory 150. For example, rather than storing a complete series of stress values for later data processing, a comparatively small number of stress values may be stored temporarily to track in-progress stress cycles, but other stress values may be discarded as soon as they are received. Accordingly, the amount of memory used during real-time monitoring of stress cycles may be reduced in comparison to alternative approaches.”
Adopting such a system gives notable benefits to electric car owners. By using a real-time monitoring model, for one, drivers would be notified by their vehicles once a component needs maintenance. In some instances, the car could immediately send stress and damage data to the company. Taking the concept even further, Tesla notes that a vehicle equipped with autonomous driving features would be able to drive itself to a service center when it needs repairs.
“In some embodiments, an operator of vehicle 110 may be notified when damage to subsystems 121-129 is detected. For example, the operator may be alerted when the level of damage reaches a predetermined threshold, such that the operator may take an appropriate remedial action (e.g., bringing vehicle 110 in for maintenance). In one illustrative example, when the level of damage is represented as a damage fraction, the operator may be alerted when the fractional damage to a given subsystem reaches 70%. In some examples, the alert may be communicated to the operator via a dashboard 160 (and/or another suitable control/monitoring interface) of vehicle 110.
“In some examples, processor 140 may be coupled to one or more external entities over a network 170. Accordingly, processor 140 may be configured to send stress cycle and/or damage data over network 170 to various recipients. For example, processor 140 may send stress cycle and/or damage data to a service center, such that service center may contact the operator to schedule a maintenance appointment when a damaged subsystem is identified. Additionally or alternately, when vehicle 1 10 is an autonomous vehicle, vehicle 110 may be instructed to drive autonomously to service center for repairs.”
Tesla is arguably one of the most proactive companies in the auto industry. For example, automotive teardown expert Sandy Munro has already dubbed the company’s batteries as the best in the market today, but Tesla’s Automotive President Jerome Guillen has stated that the company is still constantly making its batteries even better. In an interview with CNBC, Guillen pointed out that the design of Tesla’s battery cells is “not frozen.” With this in mind, it is not very surprising to see Tesla exploring proactive new ways to figure out more effective ways to monitor damages on its electric vehicles.
Tesla’s constant initiative to improve is teased somewhat in the patent applications from the company that has been published over the past few months. Among these include an automatic tire inflation system that teases off-road capabilities for the company’s vehicles, a system that addresses panel gaps during vehicle assembly, a way to create colored solar roof tiles, and even a system that uses electric cars as a way to improve vehicle positioning.
The full text of Tesla’s recently published patent application could be accessed here.
News
Tesla leases new 108k-sq ft R&D facility near Fremont Factory
The lease adds to Tesla’s presence near its primary California manufacturing hub as the company continues investing in autonomy and artificial intelligence.
Tesla has expanded its footprint near its Fremont Factory by leasing a 108,000-square-foot R&D facility in the East Bay.
The lease adds to Tesla’s presence near its primary California manufacturing hub as the company continues investing in autonomy and artificial intelligence.
A new Fremont lease
Tesla will occupy the entire building at 45401 Research Ave. in Fremont, as per real estate services firm Colliers. The transaction stands as the second-largest R&D lease of the fourth quarter, trailing only a roughly 115,000-square-foot transaction by Figure AI in San Jose.
As noted in a Silicon Valley Business Journal report, Tesla’s new Fremont lease was completed with landlord Lincoln Property Co., which owns the facility. Colliers stated that Tesla’s Fremont expansion reflects continued demand from established technology companies that are seeking space for engineering, testing, and specialized manufacturing.
Tesla has not disclosed which of its business units will be occupying the building, though Colliers has described the property as suitable for office and R&D functions. Tesla has not issued a comment about its new Fremont lease as of writing.
AI investments
Silicon Valley remains a key region for automakers as vehicles increasingly rely on software, artificial intelligence, and advanced electronics. Erin Keating, senior director of economics and industry insights at Cox Automotive, has stated that Tesla is among the most aggressive auto companies when it comes to software-driven vehicle development.
Other automakers have also expanded their presence in the area. Rivian operates an autonomy and core technology hub in Palo Alto, while GM maintains an AI center of excellence in Mountain View. Toyota is also relocating its software and autonomy unit to a newly upgraded property in Santa Clara.
Despite these expansions, Colliers has noted that Silicon Valley posted nearly 444,000 square feet of net occupancy losses in Q4 2025, pushing overall vacancy to 11.2%.
In Pennsylvania, we got between 10 and 12 inches of snow over the weekend as a nasty Winter storm ripped through a large portion of the country, bringing snow to some areas and nasty ice storms to others.
I have had a Model Y Performance for the week courtesy of Tesla, which got the car to me last Monday. Today was my last full day with it before I take it back to my local showroom, and with all the accumulation on it, I decided to run a cool little experiment: How long would it take for Tesla’s Defrost feature to melt 8 inches of snow?
Tesla’s Defrost feature is one of the best and most underrated that the car has in its arsenal. While every car out there has a defrost setting, Tesla’s can be activated through the Smartphone App and is one of the better-performing systems in my opinion.
It has come in handy a lot through the Fall and Winter, helping clear up my windshield more efficiently while also clearing up more of the front glass than other cars I’ve owned.
The test was simple: don’t touch any of the ice or snow with my ice scraper, and let the car do all the work, no matter how long it took. Of course, it would be quicker to just clear the ice off manually, but I really wanted to see how long it would take.
Tesla Model Y heat pump takes on Model S resistive heating in defrosting showdown
Observations
I started this test at around 10:30 a.m. It was still pretty cloudy and cold out, and I knew the latter portion of the test would get some help from the Sun as it was expected to come out around noon, maybe a little bit after.
I cranked it up and set my iPhone up on a tripod, and activated the Time Lapse feature in the Camera settings.
The rest of the test was sitting and waiting.
It didn’t take long to see some difference. In fact, by the 20-minute mark, there was some notable melting of snow and ice along the sides of the windshield near the A Pillar.
However, this test was not one that was “efficient” in any manner; it took about three hours and 40 minutes to get the snow to a point where I would feel comfortable driving out in public. In no way would I do this normally; I simply wanted to see how it would do with a massive accumulation of snow.
It did well, but in the future, I’ll stick to clearing it off manually and using the Defrost setting for clearing up some ice before the gym in the morning.
Check out the video of the test below:
❄️ How long will it take for the Tesla Model Y Performance to defrost and melt ONE FOOT of snow after a blizzard?
Let’s find out: pic.twitter.com/Zmfeveap1x
— TESLARATI (@Teslarati) January 26, 2026
Tesla Robotaxi ride-hailing without a Safety Monitor is proving to be a difficult task, according to some riders who made the journey to Austin to attempt to ride in one of its vehicles that has zero supervision.
Last week, Tesla officially removed Safety Monitors from some — not all — of its Robotaxi vehicles in Austin, Texas, answering skeptics who said the vehicles still needed supervision to operate safely and efficiently.
BREAKING: Tesla launches public Robotaxi rides in Austin with no Safety Monitor
Tesla aimed to remove Safety Monitors before the end of 2025, and it did, but only to company employees. It made the move last week to open the rides to the public, just a couple of weeks late to its original goal, but the accomplishment was impressive, nonetheless.
However, the small number of Robotaxis that are operating without Safety Monitors has proven difficult to hail for a ride. David Moss, who has gained notoriety recently as the person who has traveled over 10,000 miles in his Tesla on Full Self-Driving v14 without any interventions, made it to Austin last week.
He has tried to get a ride in a Safety Monitor-less Robotaxi for the better part of four days, and after 38 attempts, he still has yet to grab one:
Wow just wow!
It’s 8:30PM, 29° out ice storm hailing & Tesla Robotaxi service has turned back on!
Waymo is offline & vast majority of humans are home in the storm
Ride 38 was still supervised but by far most impressive yet pic.twitter.com/1aUnJkcYm8
— David Moss (@DavidMoss) January 25, 2026
Tesla said last week that it was rolling out a controlled test of the Safety Monitor-less Robotaxis. Ashok Elluswamy, who heads the AI program at Tesla, confirmed that the company was “starting with a few unsupervised vehicles mixed in with the broader Robotaxi fleet with Safety Monitors,” and that “the ratio will increase over time.”
This is a good strategy that prioritizes safety and keeps the company’s controlled rollout at the forefront of the Robotaxi rollout.
However, it will be interesting to see how quickly the company can scale these completely monitor-less rides. It has proven to be extremely difficult to get one, but that is understandable considering only a handful of the cars in the entire Austin fleet are operating with no supervision within the vehicle.
Tesla leases new 108k-sq ft R&D facility near Fremont Factory
Tesla winter weather test: How long does it take to melt 8 inches of snow?
