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Tesla patent hints at more reliable batteries through ‘dynamic’ management system
It is no exaggeration to state that Tesla’s business hinges on its battery technology. Fortunately for the company, its batteries are among the best in the industry today. This is particularly notable in the case of Tesla’s electric cars, as well as its energy storage products. In terms of vehicles, Tesla’s battery tech has reached a point where it is capable of supporting the demands of closed circuit driving, as is the case with the Model 3 Performance’s Track Mode. In terms of battery storage, the quality and performance of Tesla’s batteries have been so impressive in South Australia that it appears to have started an energy storage movement.
Considering Tesla’s reputation for never staying still, though, it is almost certain that the company’s batteries will improve over time. This was mentioned by Tesla’s President of Automotive Jerome Guillen to CNBC last November, when he noted that the company’s technology consistently evolves. In his segment, the executive noted that “the design of the (battery) cell is not frozen,” indicating upcoming improvements in the near future.
A recently published patent points to one of these battery tech improvements. Titled “Multi-Channel and Bi-Directional Battery Management System,” the patent describes a way for Tesla to push the envelope on its battery management system even further. In the patent’s description, Tesla noted that the increasing demand for battery-based power is putting an emphasis on the performance demands of management systems, which ensure proper operation within a range of products like electric vehicles and energy storage units.
While battery management systems perform vital functions, the units themselves could be subject to various external factors. In the case of electric cars, the system could be subject to mechanical vibration and shock, varying environmental temperature, multiple power domains and a large number of interference sources that could deteriorate signals between the centralized management controller and multiple battery integrated circuits. Considering that batteries are the only power source for electric vehicles, instances involving a failure of the system could render an electric vehicle inoperable. With this in mind, Tesla notes that there is a need for a battery management system that is “more robust and dynamic.”
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- A diagram of Tesla’s battery management system. (Photo: US Patent Office)
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- A diagram of Tesla’s battery management system. (Photo: US Patent Office)
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- A diagram of Tesla’s battery management system. (Photo: US Patent Office)
Diagrams of Tesla’s battery management system. (Photo: US Patent Office)
Tesla’s patent describes what could be dubbed as a redundant battery management system, comprising a first client coupled within a multi-channel, bi-directional and daisy-chained communication loop. The electric car maker also outlined a method for identifying a failure location within a battery management system. Tesla describes these as follows.
“The battery management system may include a host (such as a microcontroller that manages at a system level) and clients (such as battery management integrated circuits that manage battery cells within the system). In embodiments, the host may be implemented in various structures including the previously mentioned microcontroller and manages the system by transmitting commands and receiving responses from one or more of the clients. Each client may monitor and control corresponding battery cells to measure the electrical and physical status of the cells, such as voltage, amount of remaining electrical charge and temperature of each cell. For instance, the client 120a may monitor the cells 130a. It is noted that each client may monitor a different number of battery cells. The client 120a may perform measurements (e.g., voltage, charge, temperature, etc.) as well as perform certain functions (e.g., bleed-off charge from a battery cell, etc).”
Tesla further discussed its rationale behind its use of daisy-chain loops for its battery management system.
“The host and each client may communicate commands and responses via a daisy-chain transmission path loop, where the daisy-chain loop may include a pair of wires that transmit electrical signals therethrough. In embodiments, the daisy-chain loop may connect the interface of the host to the interfaces of the clients in series so that communication may serially occur on one or multiple channels within the loop. “
“The battery management system is able to provide redundant communication paths because of its ability to bi-directionally communicate along the daisy-chain loop and because the two channels used on the daisy-chain loop each allow access to completely separate and redundant battery management systems. Specifically, the host is able to communicate in a clockwise direction around the serially connected clients as well as communicate in a counter-clockwise direction along the loop. This bi-directionality allows the host to communicate with each client in case there is a single failure within the daisy-chain loop. This redundancy applies to both channels.”
Ultimately, Tesla notes that these systems will result in what could only be described as “dynamic redundancy” across its battery management systems. This, of course, could foster a new generation of battery packs that are more reliable than the company’s already stellar batteries.
“One skilled in the art will recognize the use of a multi-channel signaling system as well as a bi-directional signaling architecture within the battery management system results in dynamic redundancy across the system itself. For example, if a primary or secondary circuit should fail on a client, the host may communicate a redundant command to the client using a different and fully operational channel. The multiple channel architecture ensures that even egregious malfunction of a sub-system, such as the transmission of spurious data, will not be able to interfere with normal operation of a complementary subsystem operating on a different channel. In addition, the bi-directionality of the system allows for compensation to occur in the event of a complete path failure somewhere within the loop.”
The past months have seen an influx of published patents for Tesla. Among these include an automatic tire inflation system patent that can pave the way for off-road capabilities for the company’s vehicles, a clever patent that would allow Tesla to address panel gaps during vehicle assembly, a patent that describes colored solar roof tiles, and even a system that uses electric cars as a way to improve vehicle positioning.
Tesla’s recently published patent on its Multi-Channel and Bi-Directional Battery Management System could be accessed in full here.
Tesla has reached a notable benchmark in its autonomous driving program after its Robotaxi fleet surpassed one million miles of unsupervised operation. The company made the announcement during its Cybercab event in Austin on September 3.
Tesla Vice President of AI Ashok Elluswamy told attendees he was happy to report the fleet had achieved one million miles of unsupervised Robotaxi operation as a testament to safety.
The new total marked a sharp increase from the 380,000 unsupervised miles Tesla disclosed during its second-quarter 2026 earnings update in late July.
In roughly six weeks, the company added about 620,000 miles. That acceleration followed Tesla’s decision to remove in-vehicle safety monitors from most of its operations outside the San Francisco Bay Area.
Credit: Tesla
Tesla first launched Robotaxi service in Austin in June 2025 with safety drivers present. It later began fully unsupervised rides and expanded into Dallas, Houston, Miami, Orlando, and Tampa. The San Francisco Bay Area remains the exception, where a safety monitor still rides in the vehicle under California permitting rules.
The company has not released a city-by-city breakdown of the one million unsupervised miles.
The milestone arrived as Tesla began offering public Cybercab rides in Austin. The purpose-built vehicle has no steering wheel or pedals and is designed only for autonomous ride-hailing. Production versions joined the existing fleet of modified Tesla vehicles already operating in the service.
Tesla’s unsupervised mileage is growing at a double-digit weekly rate according to earlier company comments, yet its fleet size remains modest compared with established competitors. Waymo has accumulated more than 200 million fully autonomous rider-only miles. Tesla has described its own unsupervised operations as having recorded zero notable incidents in the period leading up to the July update.
The one-million-mile figure reflects Tesla’s shift from supervised testing to broader driverless service in multiple states. It also highlights the company’s strategy of using both existing Model Y vehicles and the new Cybercab to scale its network.
Credit: Tesla
Whether the rapid recent growth continues will depend on further city expansions, regulatory approvals, and the performance of the purpose-built Cybercab in everyday paid rides. Tesla has not specified how many of the latest miles involved the new vehicle versus the rest of the fleet.
The announcement underscores Tesla’s progress toward a larger robotaxi network while illustrating the remaining gap in total autonomous experience relative to longer-operating rivals.
Tesla AI lead Ashok Elluswamy said this week that 24-hour Robotaxi service is close. Replying on X to a rider who wanted Cybercab trips all night, he wrote that the capability would arrive “next month or so” once “the next tech to merge on the v15 plan” is ready.
The comment landed on September 4, one day after Tesla opened public Cybercab rides in Austin. It is the clearest near-term timeline yet for overnight unsupervised operation. Tesla’s paid Robotaxi network currently runs from 6 a.m. to 10 p.m. seven days a week across Austin, Dallas, Houston, Miami, Orlando, and Tampa.
next month or so. the next tech to merge on the v15 plan will enable it.
— Ashok Elluswamy (@aelluswamy) September 4, 2026
That 16-hour window is shorter than the 6 a.m. to 2 a.m. schedule the company used for much of the prior year.
Elluswamy did not name the specific feature or say whether the change would apply first to purpose-built Cybercabs, the existing Model Y fleet, or both. He also offered no city-by-city rollout list. The link to Full Self-Driving v15 is nevertheless significant.
Tesla has described v15 as a step-change architecture with seven parallel improvement tracks and roughly ten times more parameters than earlier builds. Early versions of that software already operate on the Robotaxi fleet and contain about 40 percent of the planned gains.
By July 2026, the unsupervised fleet had logged more than 380,000 miles across six cities in two states with what the company called an impeccable safety record and no notable incidents caused by the vehicles themselves. Tesla has repeatedly argued that camera-based end-to-end neural networks, rather than extra sensors, are the core of the solution.
Overnight service would test that claim in lower-light conditions and would also raise vehicle utilization, a key variable for Robotaxi unit economics. The company has already begun using public Superchargers at night and is building dedicated Robotaxi charging sites.
Riders have asked why software must change if the cars already drive in the dark. The practical answer appears to be reliability and scale: Tesla has held back mass expansion until more of the v15 stack is merged, citing the need for higher confidence before putting thousands of unoccupied vehicles on streets around the clock.
If the next module arrives on the timetable Elluswamy sketched, 24-hour service could begin in October 2026 in at least some markets.
That would mark a shift from a daytime-bounded pilot to a service that can run whenever demand exists, including the late-night hours that have so far remained out of reach.
Tesla is beginning to roll out Full Self-Driving Supervised v14.3.9 with a new active safety layer that can take control even when the driver is operating the car manually.
Tesla AI said the software can activate FSD on the driver’s behalf when an imminent collision is detected and Automatic Emergency Braking may not be enough. It may also engage if the system detects heavy distraction or an accidental FSD disengagement.
FSD Supervised v14.3.9 starting to roll out shortly
This release includes a new active safety feature set: FSD Supervised can now activate on your behalf when an imminent collision is detected and Automatic Emergency Braking (AEB) may not be enough.
It may also engage if we…
— Tesla AI (@Tesla_AI) September 4, 2026
The capability is essentially Automatic Collision Evasion. However, unlike conventional AEB, which mainly applies the brakes in a straight line, this feature can use steering, braking, and acceleration together if the car calculates that stopping alone will not prevent impact and a safer path exists. The system may change lanes or move toward a shoulder when conditions allow, then continue driving after the immediate threat is handled rather than simply coming to a stop.
The intervention is meant as a last-resort safety net, not a replacement for attentive driving.
Tesla Full Self-Driving v14.3.7 early review: FSD saved me from an accident
Tesla’s own description still frames FSD as supervised assistance. Secondary reports on internal release notes say the feature can fire while the car is being driven manually if cabin-camera monitoring suggests the driver is not sufficiently attentive, such as reaching toward the back seat, or if FSD appears to have been turned off unintentionally.
After the emergency maneuver, the car is expected to alert the driver and request a return to manual control.
The safety case is straightforward. Many collisions happen in the last second because a driver is looking away, fumbles a control, or faces an obstacle that braking cannot fully solve. A system that can both recognize that AEB is insufficient and execute a coordinated evasive path can reduce those remaining high-severity events.
Re-engaging after accidental disengagement also addresses a practical failure mode: a small steering nudge that drops FSD at the worst moment. The advantage is a background safety net that uses the same vision stack already running in v14, instead of leaving the car solely to emergency braking once the driver is no longer in command.
The feature still depends on FSD being enabled and, according to reports, an active FSD purchase or subscription. It does not make the vehicle unsupervised. Drivers remain responsible, and Tesla has not published how often the system is expected to intervene or how it will handle false positives.
If the rollout is conservative and the false-alarm rate stays low, the update is a meaningful step: FSD is no longer only a feature the driver turns on. In the rare moments when disaster is already forming, it can step in.
Tesla crosses major Unsupervised Self-Driving milestone
Tesla Robotaxi will be a 24/7 service: here’s when
