Connect with us

News

SpaceX delays Starhopper’s first flight a few days despite Raptor preburner test success

According to NASASpaceflight.com, SpaceX's Starhopper successfully completed a Raptor preburner taste on July 15th. A static fire ignition test should follow on July 16th.(NASASpaceflight - bocachicagal)

Published

on

SpaceX has (partially) ignited Starhopper’s freshly-installed Raptor engine, successfully verifying that the engine is ready for its next major test: a full ignition and static firing. Although successful, SpaceX still has some work to do before the vehicle is ready for its first untethered flight(s).

July 15th’s progress is just the latest in a several day-series of preflight tests designed to reduce the likelihood that Starhopper is destroyed over the coming days and (hopefully) weeks. If all goes planned during the awkward Starship prototype’s first foray into hover tests, SpaceX CEO Elon Musk has stated that he will provide an official presentation updating the public on the status of the company’s ever-changing next-generation rocket.

The past week or so of Starhopper preflight testing began with Raptor serial number 6 (SN06) completing the last of a series of acceptance test fires in McGregor, Texas on June 10th. Even on its own, this was a major milestone for the new SpaceX engine: Raptor SN06 was the first of the new, full-scale engines to pass the acceptance test program with flying colors. According to Musk, for the engine to complete those tests so successfully, SpaceX had to solve a challenging bug in which some sort of mechanical resonance (i.e. vibration) damaged or destroyed Raptors SN01-05.

Hours later, the engine began a short ~450 mi (720 km) journey south to Starhopper, located in Boca Chica, Texas. The engine arrived on July 11th and was fully installed on Starhopper by the following evening (July 12th), at which point SpaceX put Starhopper and Raptor through some mild but valuable thrust vector controller (TVC) tests, wiggling the car-sized engine to ensure it can accurately steer the prototype rocket.

Around two days after the above ‘wiggle’ test was successfully completed, SpaceX moved into the next stage, partially fueling Starhopper with liquid methane and oxygen propellant and helium pressurant in what is known in rocketry as a wet dress rehearsal (WDR). The (implicitly) successful WDR was capped off with a duo of what can now safely be concluded were some sort of Raptor test preceding even pre-ignition operations. Whatever the tests were, they appear to have been completed successfully.

That appears to be the case because less than 24 hours after their completion, on July 15th, SpaceX once again began loading Starhopper with propellant and pressurant for a second round of wet testing. This time around, SpaceX got right into more critical Raptor tests once enough propellant was loaded, igniting the engine’s interwoven oxygen and methane preburners.

Starhopper (technically) came alive for the third time ever on July 15th, albeit only partially. SpaceX ignited the engine’s preburners as a precursor to a full static fire, now NET July 16th. (LabPadre – YouTube livestream)

Previously discussed 24 hours ago in a Teslarati article focused on Raptor wiggles and other miscellaneous tests, Raptor is an extremely advanced rocket engine based on a cycle (i.e. how propellant is turned into thrust) known as full-flow staged combustion.

In a staged-combustion engine like Raptor, getting from the supercool liquid oxygen and methane propellant to 200+ tons of thrust is quite literally staged, meaning that the ignition doesn’t happen all at once. Rather, the preburners – essentially their own, unique combustion chambers – ignite an oxygen- or methane-rich mixture, the burning of which produces the gas and pressure that powers the turbines that bring fuel into the main combustion chamber. That fuel then ignites, producing thrust as they exit the engine’s bell-shaped nozzle.

Unintuitively, conditions inside the preburner – hidden away from view – are actually far more intense than the iconic blue, purple, and pink flame that visibly exists Raptor’s nozzle. Much like hot water will cool while traveling through pipes, the superheated gaseous propellant that Raptor ignites to produce thrust will also cool (and thus lose pressure) as it travels from Raptor’s preburner to its main combustion chamber. If the pressure produced in the preburners is too low, Raptor’s thrust will be (roughly speaking) proportionally limited at best. At worst, low pressure in the preburners can trigger a “hard start” or shutdown that could destroy the engine. According to Elon Musk, Raptor’s oxygen preburner thus has the worst of it, operating at pressures as high or higher than 800 bar (11,600 psi, 80 megapascals).”

In full-flow staged combustion (FFSC), even more complexity is added as all propellant that touches the engine must necessarily end up traveling through the main combustion chamber to eke every last ounce of thrust out of the finite propellant a rocket lifts off with. As such, FFSC engines can be about as efficient as the laws of physics allow any given chemical rocket engine to be, at the cost of exceptional complexity and brutally difficult development.

Additionally, FFSC physically requires two separate preburners and then makes things even harder by making each separate preburner (methane and oxygen) depend on each other’s operation for the engine to fully ignite. This means that no individual preburner can be used to kickstart Raptor – instead, SpaceX must somehow spin the turbopumps that feed propellant into each preburner with some separate system. This is all just to emphasize the fact that Raptor’s ignition sequence is a spectacularly complex orchestra of valves, spark plugs, sensors, and magic. This is why it’s valuable for Raptor to test its preburner system independently of an actual ignition test, at least as long as the engine is still in the development stages.

Advertisement
-->
A Raptor engine is pictured here during a static fire test in McGregor, Texas. (SpaceX)

According to NASASpaceflight.com managing editor Chris Bergin, what this practically translates to is a minor Starhopper hover test delay of 1-2 days, while the static fire has also been pushed roughly 24 hours from July 15th to July 16th. If that full static fire produces lots of happy data, Starhopper could be cleared for a hover test debut attempt as early as Wednesday or Thursday (July 17/18).

Check out Teslarati’s Marketplace! We offer Tesla accessories, including for the Tesla Cybertruck and Tesla Model 3.

Eric Ralph is Teslarati's senior spaceflight reporter and has been covering the industry in some capacity for almost half a decade, largely spurred in 2016 by a trip to Mexico to watch Elon Musk reveal SpaceX's plans for Mars in person. Aside from spreading interest and excitement about spaceflight far and wide, his primary goal is to cover humanity's ongoing efforts to expand beyond Earth to the Moon, Mars, and elsewhere.

Advertisement
Comments

Elon Musk

Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD

As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.” 

Published

on

Credit: @BLKMDL3/X

Tesla CEO Elon Musk has provided an updated estimate for the training data needed to achieve truly safe unsupervised Full Self-Driving (FSD). 

As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.” 

10 billion miles of training data

Musk comment came as a reply to Apple and Rivian alum Paul Beisel, who posted an analysis on X about the gap between tech demonstrations and real-world products. In his post, Beisel highlighted Tesla’s data-driven lead in autonomy, and he also argued that it would not be easy for rivals to become a legitimate competitor to FSD quickly. 

“The notion that someone can ‘catch up’ to this problem primarily through simulation and limited on-road exposure strikes me as deeply naive. This is not a demo problem. It is a scale, data, and iteration problem— and Tesla is already far, far down that road while others are just getting started,” Beisel wrote. 

Musk responded to Beisel’s post, stating that “Roughly 10 billion miles of training data is needed to achieve safe unsupervised self-driving. Reality has a super long tail of complexity.” This is quite interesting considering that in his Master Plan Part Deux, Elon Musk estimated that worldwide regulatory approval for autonomous driving would require around 6 billion miles. 

Advertisement
-->

FSD’s total training miles

As 2025 came to a close, Tesla community members observed that FSD was already nearing 7 billion miles driven, with over 2.5 billion miles being from inner city roads. The 7-billion-mile mark was passed just a few days later. This suggests that Tesla is likely the company today with the most training data for its autonomous driving program. 

The difficulties of achieving autonomy were referenced by Elon Musk recently, when he commented on Nvidia’s Alpamayo program. As per Musk, “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.” These sentiments were echoed by Tesla VP for AI software Ashok Elluswamy, who also noted on X that “the long tail is sooo long, that most people can’t grasp it.”

Continue Reading

News

Tesla earns top honors at MotorTrend’s SDV Innovator Awards

MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.

Published

on

Credit: Tesla China

Tesla emerged as one of the most recognized automakers at MotorTrend’s 2026 Software-Defined Vehicle (SDV) Innovator Awards.

As could be seen in a press release from the publication, two key Tesla employees were honored for their work on AI, autonomy, and vehicle software. MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.

Tesla leaders and engineers recognized

The fourth annual SDV Innovator Awards celebrate pioneers and experts who are pushing the automotive industry deeper into software-driven development. Among the most notable honorees for this year was Ashok Elluswamy, Tesla’s Vice President of AI Software, who received a Pioneer Award for his role in advancing artificial intelligence and autonomy across the company’s vehicle lineup.

Tesla also secured recognition in the Expert category, with Lawson Fulton, a staff Autopilot machine learning engineer, honored for his contributions to Tesla’s driver-assistance and autonomous systems.

Tesla’s software-first strategy

While automakers like General Motors, Ford, and Rivian also received recognition, Tesla’s multiple awards stood out given the company’s outsized role in popularizing software-defined vehicles over the past decade. From frequent OTA updates to its data-driven approach to autonomy, Tesla has consistently treated vehicles as evolving software platforms rather than static products.

Advertisement
-->

This has made Tesla’s vehicles very unique in their respective sectors, as they are arguably the only cars that objectively get better over time. This is especially true for vehicles that are loaded with the company’s Full Self-Driving system, which are getting progressively more intelligent and autonomous over time. The majority of Tesla’s updates to its vehicles are free as well, which is very much appreciated by customers worldwide.

Continue Reading

Elon Musk

Judge clears path for Elon Musk’s OpenAI lawsuit to go before a jury

The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder.

Published

on

Gage Skidmore, CC BY-SA 4.0 , via Wikimedia Commons

A U.S. judge has ruled that Elon Musk’s lawsuit accusing OpenAI of abandoning its founding nonprofit mission can proceed to a jury trial. 

The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder. These claims are directly opposed by OpenAI.

Judge says disputed facts warrant a trial

At a hearing in Oakland, U.S. District Judge Yvonne Gonzalez Rogers stated that there was “plenty of evidence” suggesting that OpenAI leaders had promised that the organization’s original nonprofit structure would be maintained. She ruled that those disputed facts should be evaluated by a jury at a trial in March rather than decided by the court at this stage, as noted in a Reuters report.

Musk helped co-found OpenAI in 2015 but left the organization in 2018. In his lawsuit, he argued that he contributed roughly $38 million, or about 60% of OpenAI’s early funding, based on assurances that the company would remain a nonprofit dedicated to the public benefit. He is seeking unspecified monetary damages tied to what he describes as “ill-gotten gains.”

OpenAI, however, has repeatedly rejected Musk’s allegations. The company has stated that Musk’s claims were baseless and part of a pattern of harassment.

Advertisement
-->

Rivalries and Microsoft ties

The case unfolds against the backdrop of intensifying competition in generative artificial intelligence. Musk now runs xAI, whose Grok chatbot competes directly with OpenAI’s flagship ChatGPT. OpenAI has argued that Musk is a frustrated commercial rival who is simply attempting to slow down a market leader.

The lawsuit also names Microsoft as a defendant, citing its multibillion-dollar partnerships with OpenAI. Microsoft has urged the court to dismiss the claims against it, arguing there is no evidence it aided or abetted any alleged misconduct. Lawyers for OpenAI have also pushed for the case to be thrown out, claiming that Musk failed to show sufficient factual basis for claims such as fraud and breach of contract.

Judge Gonzalez Rogers, however, declined to end the case at this stage, noting that a jury would also need to consider whether Musk filed the lawsuit within the applicable statute of limitations. Still, the dispute between Elon Musk and OpenAI is now headed for a high-profile jury trial in the coming months.

Continue Reading