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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.
Tesla is starting to prepare for the launch of the Optimus robot in its smartphone app, new coding strings show. Elon Musk has referred to Optimus as what will be the greatest-selling product of any kind of all time, and now, Tesla is getting ready for its launch.
Tesla’s smartphone app had several first-time mentions of the Optimus program, according to Tesla App Updates, who intially reported on the appearance. Here’s what they found:
A Dedicated “Robot” Phone Key Authentication
Tesla is working on a Bluetooth Low Energy, or BLE, authentication that is specifically for robots. This does not only apply to Optimus, though, as Robotaxi, which is Tesla’s autonomous ride-hailing platform, might also identify vehicles within the fleet as robots as well.
Tesla shows rapid teardown of Model S and X lines, paving the way for Optimus at Fremont
Essentially, pairing your phone as a key to anything Tesla identifies as a robot to a “whitelist” of authorized devices. Optimus, Robotaxi, or other products that fall into this category will only respond if the device trying to communicate with it is authorized.
This is a great security feature that will eliminate at least face-value and low-level threats.
Home Data Collection and System Alerts
This appears to be somewhat of a neural network for Optimus within your house. There will be a dedicated screen that asks for consent to collect both video and spatial data while Optimus performs in-home tasks. Everything from vacuuming, washing dishes, dusting, and other activities will be tracked.
There will also be a comprehensive alert system that will track everything from low battery to mechanical issues.
Other Changes
Most of the changes tracked in this particular app update are related to Tesla’s 2026 Summer Update, and include things such as image assets for new features, a preview of the new custom wraps feature, and other unique features.
You can check out our coverage on what is included with the 2026 Summer Update here:
Tesla reveals 2026 Summer Update with crazy fixes to Nav and more
Tesla (NASDAQ: TSLA) will report its earnings for the second quarter of 2026 this evening after market close, and investors and analysts are waiting anxiously to see what the company will report for the second three-month span of the year.
Analysts have already put out their expectations from a financial standpoint for the company’s second quarter, but what’s unknown is what Tesla plans to discuss during the call.
Financial Expectations
Wall Street consensus expectations put Tesla’s Earnings Per Share (EPS) at $0.53, while revenues are expected to come in around $26.4 billion.
This would compare to an EPS of $0.39 and $22.19 billion compared to Tesla’s Q2 2025. Last quarter, EPS came in at $0.41 on $22.387 billion of revenue. Additionally in Q1, Tesla beat analyst expectations, but shares dropped over 3 percent the following trading day.
What We Expect
In terms of discussions, Tesla earnings are pretty sporadic and depend on a handful of things, including current events, investor questions, and more.
Tesla uses a platform called Say to field questions from investors and analysts. These questions are what will be used during the call. Here are the top 5 from the Retail side and top 3 from the Institutional side:
Retail:
“Tesla has missed short-term guidance on robotaxi 3 earnings reports in a row, from 50% coverage of USA by end of 2025 to most recently 7 new cities in 1H26. What is keeping Tesla back from accomplishing these short term goals that they’ve set for themselves?”
“What are the main constraints to expanding robotaxi operations faster, and how do you see that lining up with Cybercab production?”
“What’s the current status of Optimus Gen 3 production ramp, initial deployment in factories, and external sales timeline/volume for 2027? What tasks can we expect the Optimus to perform by end of 2027?”
“To reward long-term Tesla retail shareholders for their loyalty, can you commit to achieving at least half of the goals outlined in your 2025 compensation plan before considering any offers to acquire or merge Tesla?”
“Why has growth of robotaxi vehicles stalled? When will we see cybercab start customer rides?”
Institutional
“Previously, you’ve said Tesla would lead the R&D while SpaceX would lead production for Terafab. Can you provide an update on how that division of responsibilities is evolving, and any additional clarity on the expected capital contributions from Tesla and SpaceX?”
“For autonomous driving, Tesla’s fleet created a huge data advantage by collecting billions of real-world miles. That advantage doesn’t yet exist for Optimus. How should we think about data availability and its impact on Optimus development?”
“Why is it necessary to limit robotaxi operations within specific zones within cities to start? Will every city have to be rolled out this way?”
Tesla will report earnings for Q2 this evening with the Shareholder Deck at 4 p.m. ET, with the call starting around 5:30 p.m. ET.
Elon Musk
Elon Musk handed Grok something no other AI company can get their hands on
Elon Musk says SpaceX will feed engineering data into Grok’s next model, avoiding restricted material.
Elon Musk said Tuesday that SpaceX will feed its internal engineering data into the next major training run for Grok, the AI model now folded into SpaceX following February’s merger. In a post on X, Musk wrote that SpaceX’s “massive corpus of world-class engineering data,” excluding anything restricted under U.S. arms export law, will be added during supplemental training of what he called the “2T run,” a reference to a roughly two trillion parameter model that would nearly double the parameters behind the latest Grok 4.5 that’s rolling out.
SpaceX’s massive corpus of world-class engineering data (excluding material blocked by ITAR) will be added during supplemental training of the 2T run.
This will dramatically improve Grok’s engineering capabilities. https://t.co/BbQEViFByn
— Elon Musk (@elonmusk) July 21, 2026
The excluded material that Musk is referring to would fall under the International Traffic in Arms Regulations (ITAR), which restricts export of technical data tied to defense and space hardware. That likely rules out propulsion specifics for Merlin and Raptor engines along with guidance and control details for SpaceX’s launch vehicles, but leaves manufacturing knowledge, materials science, and Starlink hardware design on the table.
The announcement extends a pattern that has been building since SpaceX’s Nasdaq debut in June, when the company went public with Grok and xAI’s Colossus supercomputer folded into the pitch to investors.
Days after that listing, SpaceX closed its $60 billion all stock acquisition of coding startup Cursor, giving xAI both enterprise software distribution and a stream of real world developer data to train on. Grok 4.5 launched July 8 running partly on that Cursor training data, with Musk describing it as roughly comparable to Anthropic’s Opus 4.7 but faster and cheaper to run.
Feeding SpaceX’s own engineering data into the next AI model follows the same logic Musk has applied across xAI’s sister companies. Tesla supplies real world driving data and manufacturing expertise, X supplies conversational data, and now SpaceX supplies aerospace engineering data built up since 2002.
Musk did not give a release date for the upcoming AI model, referred to elsewhere as Grok 4.6. He has said the two trillion parameter run is in its final training phase and expected to wrap this week.
Tesla starts preparing for Optimus in its smartphone app
Tesla Q2 Earnings: Here’s what to expect
