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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.
A close-up image of a Cybercab engineering vehicle in Peabody, Massachusetts, reveals a compact triangular side repeater camera housing equipped with an integrated washer mechanism.
This seemingly small hardware addition could prove to be one of the most critical components for achieving reliable, unsupervised Full Self-Driving (FSD) — not just for the dedicated Robotaxi but potentially for existing AI4-equipped vehicles as well.
The washer system’s importance cannot be overstated in Tesla’s vision-only autonomy approach. Cameras are the sole sensory input for the neural networks powering FSD, constantly interpreting the environment for safe navigation. In real-world conditions, however, lenses quickly accumulate rain, snow, mud, dust, or road spray.
Many of us Tesla owners, especially those who deal with any sort of winter weather at all, know the all-too-common alert that pops up when cameras are obstructed:
Even brief obstructions can drop perception confidence, trigger safety disengagements, or force the vehicle to pull over, although these are relatively rare. Instead, most of the time, the camera will need a wipe from the owner next time they stop the car.
But unlike human drivers who can manually clear their view, a Robotaxi operating 24/7 without a steering wheel or mirrors must maintain pristine vision autonomously. The Cybercab’s side repeater washer delivers targeted cleaning bursts precisely where needed for merging, lane changes, and blind-spot monitoring — functions that demand uninterrupted visibility from the external cameras:
And this is how the side camera and washer look like on a Cybercab. This is from an Engineering vehicle in Peabody MA. pic.twitter.com/Re8VknpmLM
— Tobias Goebel (Unsupervised) (@tpgoebel) June 17, 2026
This hardware directly tackles a known pain point in current FSD deployments. Owners frequently report camera-related alerts during inclement weather, which is understandable, but needs to be solved for a true autonomous experience.
For a production Robotaxi fleet aiming for high utilization and minimal downtime, robust washer systems represent a foundational reliability upgrade; essentially, they’re a must-have. Early sightings suggest the design may extend to rear cameras as well, creating a comprehensive cleaning architecture that keeps the entire vision suite operational in harsh environments.
Without it, even the most advanced neural nets struggle when their “eyes” are compromised.
What Does This Mean for AI4 Cars?
This Cybercab detail raises timely questions for AI4 cars already on the road. While Hardware 4 delivers superior compute and camera resolution compared to earlier versions, production models typically lack dedicated side and rear washers. Tesla has included them on Model Y robotaxis that it is using in the fleet:
Tesla Robotaxi has a highly-requested hardware feature not available on typical Model Ys
As Tesla refines unsupervised FSD for broader release, the gap in environmental resilience becomes evident. Software improvements can help mitigate issues, but they cannot fully replace physical cleaning in heavy rain or muddy conditions. Analysts and owners increasingly speculate that AI4 vehicles may eventually require similar washer retrofits — or a future AI4.5 variant — to match the Cybercab’s all-weather readiness and support the same level of autonomy.
As testing progresses, the Cybercab’s washer mechanism highlights Tesla’s pragmatic focus on real-world robustness. It may well become the hardware piece that determines how quickly and reliably FSD scales from prototypes to everyday vehicles.
Elon Musk
Elon Musk just upped his Tesla stake further fueling SpaceX merger conversation
Elon Musk just collected a $116 billion Tesla payday and the timing is eye-opening
Elon Musk quietly collected one of the largest single-transaction paydays in corporate history on Monday. A Form 4 filed with the SEC on June 17, 2026 disclosed that Musk exercised 303,960,630 Tesla stock options from his 2018 compensation package, with the transaction dated June 16. No shares were sold on the open market.
The numbers are straightforward but striking. Musk exercised the options at a split-adjusted strike price of $23.34, with Tesla closing at $404.66 that day, putting the spread at $381.32 per share and generating roughly $115.9 billion in paper gains in a single transaction. To cover the exercise cost, Tesla withheld 17,531,857 shares through a net share settlement, meaning Musk paid nothing out of pocket.
For perspective, in 2018, Elon Musk’s award was originally approved by Tesla shareholders on March 21, 2018, and structured entirely around performance milestones that many analysts at the time called unreachable. Every tranche eventually vested. The original grant covered 20,264,042 shares at $350.02, which after Tesla’s 5-for-1 split in 2020 and 3-for-1 split in 2022 adjusted to 303,960,630 shares at $23.34. A Delaware court rescinded the award in January 2024, ruling the board was conflicted. As Teslarati reported, Tesla shareholders voted to ratify the package anyway in June 2024 by a wide margin. The Delaware Supreme Court reversed the decision in December 2025, finding full cancellation too extreme, and Tesla’s board signed an Implementation Agreement on April 21, 2026 to formally deliver the shares.
The Tesla and SpaceX merger everyone is talking about is quietly building
The timing and structure of the Form 4 filing carries more weight than a routine stock option exercise typically would. Musk exercised his 2018 Tesla award on June 16, a week into SpaceX completing its IPO and trading publicly, and giving SpaceX a public market valuation and share currency for the first time in the company’s history. A stock-for-stock merger between two companies requires the acquiring entity to have tradeable shares it can offer to the target’s shareholders, and SpaceX now has exactly that. At the same time, Musk just increased his direct Tesla voting power to approximately 20%, giving him greater influence over any shareholder vote that a merger would require. The restricted shares he received cannot be sold until 2033, which removes any near-term incentive to cash out and instead positions this stake as long-term structural collateral in a deal. Additionally, Musk’s two companies are already deeply intertwined through shared semiconductor fabrication at their joint TERAFAB facility in Austin, cross-company supply chain transactions, and Tesla’s $2 billion investment in xAI prior to the SpaceX-xAI merger.
Wedbush analyst Dan Ives has publicly placed the odds of a Tesla and SpaceX combination at 80% to 90% by early 2027. The Implementation Agreement that made Monday’s exercise possible was signed on April 21, 2026, roughly two months before the SpaceX IPO closed. That sequencing, building Musk’s Tesla ownership to its highest point ever immediately before SpaceX gains the public currency needed to acquire it, is either an extraordinary coincidence or a carefully staged foundation for the largest corporate merger in history.
Tesla Full Self-Driving is going to be getting a major parking upgrade. That’s according to CEO Elon Musk, who detailed a crafty new feature that will improve parking preferences, removing a layer of human input.
Musk said that upcoming releases of Full Self-Driving will “remember your parking preferences.” It will go to the location you prefer, based on where you’ve parked in the past, instead of taking the first spot available, which is where the suite is currently.
The CEO went on to explain that destination parking is “by far” the biggest reason for intervention during FSD operation. We’d have to believe this is true; many takeovers in my Model Y, which runs the latest version of FSD as it is in the Early Access Program, are due to parking because it chooses a spot I do not want to be in.
Many times, as soon as I enter a parking lot, I take over and park manually. I prefer to park away from the entrance of wherever I am, away from cars. Too many lessons learned over the years from people with free-swinging doors.
Upcoming releases of FSD will remember your parking preferences, so that the car goes to the right location at your home, office, school drop off, etc.
Destination parking is by far the biggest reason people now intervene with FSD. Critical safety interventions are extremely…
— Elon Musk (@elonmusk) June 17, 2026
We’d imagine these new updates will also solve things like parking orientation. Let’s say when you arrive at work, you always park in the third spot in the third row, and you prefer to back in. It seems as if Musk is implying that your car will now do this, learning from takeovers and aiming to eliminate the need to manually park whenever possible.
This is a major upgrade because parking is a major shortcoming of FSD currently. We’ve requested things like manual input of parking preferences, choosing to park far away, first available, or away from cars, for example.
This is a big reason Parking Preferences with Supervised FSD will be so valuable.
If possible, parking a little further away and being distant from people like this is worth it. https://t.co/1YqQLgnfTz pic.twitter.com/3Ac71KQiQ3
— TESLARATI (@Teslarati) June 7, 2026
However, some have used the option of dropping a pin at the location you’d like to park at your destination. This has worked some of the time, but FSD will still choose to park in whatever it sees first.
Musk did not give a timetable for when the improvements would be released, but it is likely to come soon. Tesla has been releasing a new FSD version every few weeks, so we may not have to wait long to test it.
Tesla Cybercab has one important piece that AI4 cars might need for FSD
Elon Musk just upped his Tesla stake further fueling SpaceX merger conversation
