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Tesla’s liquid-cooled charging connector patent paves way for the Semi’s Megachargers

The Tesla Semi visits Yandell Truckaway. (Photo: Arash Malek)

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A recently published patent application from Tesla suggests that the electric car maker is continuing in its efforts to improve its already-stellar Supercharger Network. The design outlined in the document, which features a liquid-cooled charging connector, can potentially pave the way for a more ambitious charging infrastructure, perhaps one that can specifically cater to the all-electric Semi’s Megacharger Network. 

During the all-electric truck’s unveiling, CEO Elon Musk mentioned that the Semi will be able to replenish as much as 400 miles of range in as little as 30 minutes thanks to a network of Megachargers. Neither Musk nor Tesla provided the specs of the Megacharger during the vehicle’s unveiling, though speculations were high that network might provide a power output that is several times more powerful than the company’s Supercharger V2 Network, which had an output of around 120 kW then (Supercharger V2 stations have since been improved to 150 kW).

Being a large vehicle, the Semi requires a lot of power for its charging needs, involving the rapid transfer of mass amounts of electricity in a very short period of time without encountering any heating issues. This is a key concept outlined by Tesla in its recently published patent, titled “Liquid-Cooled Charging Connector,” which involves the use of a liquid cooling system on a charging connector itself. Tesla describes its concept in the discussion below. 

An illustration of Tesla’s liquid-cooled Supercharger design. (Credit: US Patent Office)

To transfer energy faster and decrease charging times, the cable and charging connector must be capable of withstanding high current loads. Current charging connectors are limited in the current loads that they can support as their ability to dissipate heat is limited. Thus, there is a need for a new charging connector to solve the aforementioned problems.

“The present disclosure related to a new charging connector. The charging connector has a first electrical socket and a second electrical socket. A first sleeve is concentrically coupled to the first electrical socket and a second sleeve is concentrically coupled to the second electrical socket. A manifold assembly encloses the first and second electrical sockets and the first and second sleeves, such that the first and second sleeves and manifold assembly create a hollow interior space there between. The manifold assembly has an inlet conduit and an outlet conduit such that inlet conduit, interior space, and outlet conduit together create a fluid flow path. 

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“Cooling fluid flows through the fluid flow path and cools the charging connector. During operation, the cooling fluid bifurcates into a first fluid stream which flows around the first sleeve, and a second fluid stream which flows around the second sleeve. The first and second fluid streams combine upstream of the outlet conduit. The first sleeve encloses the first electrical socket, and the second sleeve encloses the second electrical socket. The cooling sleeves are made from a thermally conducting material such that heat generated by electrical sockets can be removed by the cooling fluid. In embodiments, this thermally conducting material is a thermally conductive plastic material.” 

Tesla notes that its liquid-cooled supercharger connector does not only allow faster charging; it also makes the routing of wires in a charging connector much more efficient. This means that Tesla’s Supercharger connectors could eventually be smaller and more compact despite being capable of greater output. An example of this appears to be hinted at by Supercharger V3’s liquid-cooled cables, which are smaller and more compact than those used in Tesla’s V2 Network. 

An illustration of Tesla’s liquid-cooled Supercharger design. (Credit: US Patent Office)

“Cooling fluid absorbs thermal energy from heat in the electrical sockets 404, 406. Sleeves 410, 412 are made of a thermally conducting, electrically insulating material. Heat from the electrical sockets 404, 406 is transferred to cooling fluid through sleeves 410, 412. After flowing around hollow interior space 416, the first fluid stream 804 and the second fluid stream 806 combine together upstream of outlet conduit 514 and flow outside of manifold assembly 414 through outlet conduit 514. Cooling fluid flowing out of manifold assembly 414 through outlet conduit 514 may be received by a reservoir (not shown) which may provide for heat exchanging arrangements. A heat exchanger may be provided to take away heat absorbed by cooling fluid. After rejecting absorbed heat, the cooling fluid may be recirculated back to inlet conduit 512 for further cooling of charging connector 210.

“FIG. 9 shows another component included by charging connector 210. A Printed Circuit Board Assembly (PCBA) 902 is thermally coupled to charging connector 210. In embodiments, PCBA 902 is a two-part structure. A first part of PCBA 904 is coupled to charging connector 210 such that the first part of PCBA 904 sits on top of electrical sockets 404, 406. A second part of PCBA 908 is connected to the first part of PCBA 904 through a rigid-flex PCB construction, or other similar interconnects. The two-part structure of PCB A 902 allows for a more efficient routing of electrical wires of charging connector 210, and overall size of charging connector 210 may be conveniently reduced.”

Tesla’s Superchargers are among the fastest and most expansive electric vehicle charging infrastructures in the auto industry. In keeping with its spirit, the company has made it a point to never stop innovating, as exhibited by the company’s debut and ongoing ramp of its Supercharger V3 Network. This could ultimately pay off for Tesla, whose lead in the electric vehicle race might potentially increase even more. 

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Such innovations appear to be required of the company, especially with the rollout of ambitious EVs such as the Semi, a vehicle with a different charging infrastructure compared to Tesla’s existing lineup of electric cars. That being said, Tesla nevertheless deserves credit for pushing the envelope and staying on top of its innovations. In the electric vehicle race, after all, a liquid-cooled charging connector could end up making the difference between the fast-charging capabilities of the Tesla Semi and rivals from Daimler and Nikola.

A link to the full text of Tesla’s liquid-cooled charger connector patent could be accessed here.

Simon is an experienced automotive reporter with a passion for electric cars and clean energy. Fascinated by the world envisioned by Elon Musk, he hopes to make it to Mars (at least as a tourist) someday. For stories or tips--or even to just say a simple hello--send a message to his email, simon@teslarati.com or his handle on X, @ResidentSponge.

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Tesla urges New Jersey owners to oppose new bill that could block Robotaxi

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Credit: Grok

Tesla has launched a direct campaign targeting its customers in New Jersey, sending emails that warn of pending legislation that could effectively block true driverless technology in the state.

The email focuses on Senate Bill S.1677 and Assembly Bill A.3968, measures intended to create a three-year autonomous vehicle pilot program but laden with requirements that Tesla argues make unsupervised Robotaxis impossible.

According to the email, the bills impose “restrictions so severe that true driverless deployment would remain illegal.” Specific hurdles include mandates for human safety drivers during operations, multimillion-dollar insurance minimums, reportedly $5 million, and thresholds like 100,000 miles of demonstrated safe autonomous driving before any driverless approval.

Tesla contends these are arbitrary barriers that ignore real-world performance data and favor entrenched competitors over innovative technologies like its Full Self-Driving (FSD) system.

The push comes as Tesla has started expanding Robotaxi operations in states like Texas, where unsupervised vehicles are already providing rides in several cities. New Jersey, by contrast, risks falling behind. The company highlights in the email communication that more than 94 percent of serious crashes result from human error, meaning impairment, distraction, or fatigue. These are all problems that Robotaxis eliminate entirely.

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In 2025, New Jersey recorded 582 traffic deaths, underscoring the human cost of delayed adoption.

Tesla’s outreach stresses the transformative potential of robotaxis. For families, they could offer safer school runs without drowsy or distracted drivers. For seniors and people with disabilities, robotaxis promise independence and reliable mobility.

In areas with limited public transit, they could deliver affordable, on-demand transportation, reducing congestion, emissions, and overall transportation costs. Economically, the company warns that restrictive rules could cost New Jersey jobs, innovation investment, and billions in potential growth as autonomous ride-hailing scales elsewhere.

Supporters of the legislation, including Sen. Andrew Zwicker, describe the pilot as a cautious framework with strong safety oversight, including incident reporting, expert task forces, and restrictions in sensitive zones like school areas. They view it as balancing innovation with public protection.

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Tesla and pro-AV advocates counter that the bill lacks technology neutrality, creates insurmountable entry barriers for commercial deployment, and prioritizes process over outcomes — effectively functioning as a de facto ban on services like Robotaxi.

This latest clash echoes Tesla’s past battles in New Jersey over direct vehicle sales. The email directs owners to Tesla’s advocacy platform, where they can send customized messages to legislators calling for amendments: outcome-based safety standards, open competition, and clear pathways for fully driverless commercial operations.

As hearings approach, Tesla’s campaign frames the issue as a choice between protecting the status quo and embracing life-saving progress. With robotaxi technology already proving itself in permissive states, New Jersey owners are being asked to ensure their state doesn’t lock out the future of transportation.

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Tesla’s Navigation Nightmare: Why the easiest part of FSD might be the hardest

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Credit: TESLARATI

Turn-by-turn navigation is not new technology.

For over two decades, drivers have relied on Garmin, TomTom, and later smartphone apps like Google Maps and Waze to receive precise, reliable directions. These systems have guided millions safely through unfamiliar cities, highways, and backroads with remarkable effectiveness. They handle real-time traffic, construction detours, and complex intersections with minimal fuss.

Yet Tesla, the company that promised revolutionary Full Self-Driving (FSD), continues to struggle with this foundational capability. As FSD (Supervised) v14.3.4 has started rolling out to cars this week, navigation remains its glaring Achilles’ heel, undermining the entire autonomous vision.

Tesla Summon got insanely good in FSD v14.3.2 — Navigation? Not so much

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Tesla’s FSD excels in many driving behaviors—smooth acceleration, confident lane changes in ideal conditions, and responsive handling of visible obstacles. However, when it comes to following a route accurately, the system falters repeatedly.

Owners report wrong turns, missed exits, inefficient routing through local roads instead of highways, phantom speed limit errors, and even directing vehicles to building rear entrances. Interventions for navigation issues often outnumber those for core driving maneuvers. Tesla has begun surveying owners specifically about these errors, acknowledging the problem after years of complaints.

Navigation is perhaps my biggest complaint when it comes to FSD, because sometimes, we do know better. Some of us have been living in our areas for our entire lives, but even those who have not have years or even decades of experience driving on local roads. We might know a little better about routing.

But the navigation mistakes are more than just FSD potentially taking a slightly different route that may or may not save you a few minutes. Sometimes, they’re genuinely mind-boggling.

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This isn’t just annoying; it cascades into broader failures. A flawed route plan confuses the AI’s decision-making, leading to hesitant behavior, unnecessary disengagements, or dangerous maneuvers like attempting impossible U-turns or ignoring clear ramps. In a system meant to operate with minimal supervision, unreliable navigation erodes trust.

More often than not, false or plain incorrect navigation is what causes me to interrupt FSD operation. Unfortunately, I believe the latest FSD version is the worst example of it, and it leads me to believe that Tesla might be making some changes; they’ve just made them in the wrong direction.

It makes you wonder: Why is a company that has done so much with the progress of FSD and autonomy struggling so much with navigation, something that is not new and has been around a long time?

Multiple Data Sources

First, Tesla’s navigation relies on a fragile patchwork of multiple data sources—Google Maps, TomTom, OpenStreetMap, Valhalla, and its own fleet-derived data—stitched together rather than a single authoritative map. When these conflict on lane geometry, road status, or turn details, the system hesitates or chooses incorrectly.

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Traditional GPS providers maintain centralized, regularly validated databases with professional curation and rapid updates. Tesla’s hybrid approach, while innovative in crowdsourcing, introduces inconsistencies that a purely vision-based or end-to-end AI approach may not easily reconcile in real time.

Persistent Learning

FSD seems to struggle with persistent learning from driver interventions.

Unlike consumer apps that quickly adapt to repeated corrections or user preferences (e.g., avoiding certain routes or remembering habitual detours), Tesla’s FSD often fails to internalize fixes on the same trip or across similar scenarios. Owners note making the same manual override multiple times without the routing engine updating its behavior meaningfully.

This stems from the neural architecture prioritizing real-time perception and control over long-term route memory and personalization, making navigation feel rigid and “opinionated” compared to the adaptive logic in Waze or Google Maps.

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I noticed that when I asked Grok to try and get me home a certain way (a way that FSD routinely took in the past because it was the most efficient), it had to place a waypoint between my location at the time and my house. When I went to edit the waypoint out, as Grok had placed it for a way to get FSD to get off the highway at the right exit, it was stumped again, rerouted, and took a longer way home.

Reasoning, Scaling, and Intuition

Third, scaling navigation for unsupervised or robotaxi ambitions requires not just accuracy but adaptability and user-like reasoning. Current FSD often defaults to single routes that ignore driver preferences or real-world nuances like time-of-day traffic patterns. It fails to match the intuitive, context-aware planning that traditional systems have refined over the years.

Resolving navigation is critical for several reasons. Practically, it is the backbone of any autonomous journey: without trustworthy routing, the car cannot reliably reach destinations, rendering FSD useless for robotaxis or hands-free commutes. Safety depends on it—mismatched plans create hesitation in merges or intersections, increasing accident risk.

Economically, Tesla’s valuation and future hinge on FSD delivering unsupervised driving; persistent navigation flaws delay regulatory approval and erode consumer confidence. For owners who paid premiums for FSD, these issues represent unfulfilled promises. While it is unlikely Tesla will lose too many customers due to bad navigation, some will be frustrated with the constant need for human input.

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Tesla has achieved miracles in electric vehicles and battery tech. Mastering turn-by-turn—technology Garmin nailed in the early 2000s—should not be this hard. By investing in tighter data integration, faster learning loops from interventions, and more intuitive routing algorithms, Tesla could close this gap.

Until then, FSD’s navigation struggles highlight a humbling truth: even the most ambitious innovator must sometimes master the basics before conquering the future.

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Tesla Cybertruck driver gets pickup seized for ‘legitimate concerns’ in UK

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A Tesla Cybertruck driver in the United Kingdom had their all-electric pickup seized by local police in the Greater Manchester area after the department cited “legitimate concerns.”

Last Thursday, police saw the pickup on the roads and decided to pull the driver over. Greater Manchester Police said:

“Whilst this may seem trivial to some, legitimate concerns exist around the safety of other road users or pedestrians if they were involved in a collision with the Cybertruck.”

The Cybertruck in question was, according to the BBC, registered and insured abroad and was confiscated. The driver, who is a UK resident, was reported.

The Greater Manchester Police Department then added:

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“The Tesla Cybertruck is not road-legal in the UK and does not hold a certificate of conformity.”

The Cybertruck cannot be legally driven in the UK because it has no UK Type Approval for operation in the country. This is due to some safety concerns, which are related to its angular shape and design. The stainless steel exoskeleton has sharp edges and projections that violate UK/EU rules on pedestrian protection.

Tesla has considered creating what it referred to as an “international version” that would be approved for operation in Europe. However, there has been no real movement on that front by the company, as it has been focused on the Robotaxi rollout primarily.

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