The future of vehicle diagnostics: Powering the EV transition



The global automotive industry is entering one of the most transformative periods in its history. Electrification is accelerating, emissions regulations are tightening across major markets, and vehicles are rapidly evolving into software-defined platforms.

Yet beneath the headlines about electric vehicles (EVs), another transformation is quietly reshaping the automotive ecosystem: the evolution of vehicle diagnostics.

Rather than witnessing a simple transition from internal combustion engines (ICE) to electric propulsion, the industry is entering a dual-technology era in which advanced ICE vehicles and rapidly evolving EV architectures coexist. This reality is redefining the demands placed on technicians, workshops, and the diagnostic tools they rely on.

In this environment, diagnostics is no longer just a troubleshooting function. It is becoming a core infrastructure layer of modern automotive maintenance, enabling technicians to interpret the enormous volumes of data generated by today’s vehicles.

ICE Vehicles: Increasingly Digital Machines

Despite the rapid growth of electrification, ICE vehicles will remain a dominant part of the global fleet for years to come. According to the International Energy Agency, the global vehicle parc now exceeds 1.4 billion vehicles, and ICE and hybrid vehicles are expected to account for more than half of the global fleet well into the 2030s (IEA, 2024).

At the same time, combustion vehicles have evolved far beyond their mechanical origins.

In the early 1990s, a typical vehicle contained fewer than 10 electronic control units (ECUs). Today, modern passenger vehicles commonly include 70–150 ECUs, while high-end vehicles can exceed 200 control modules managing powertrain functions, safety systems, infotainment, and connectivity (McKinsey & Company, 2023).

These systems communicate through increasingly sophisticated in-vehicle networks such as CAN, LIN, FlexRay, and Automotive Ethernet, forming complex electronic architectures that must function seamlessly for the vehicle to operate safely.

Several forces are driving this surge in electronic complexity:

  • stricter global emissions regulations, including Euro 6 and the upcoming Euro 7 standards
  • widespread adoption of Advanced Driver Assistance Systems (ADAS)
  • increasingly sophisticated engine and transmission management strategies
  • connected infotainment, telematics, and over-the-air software platforms

ADAS technologies in particular have transformed service procedures. Radar sensors, cameras, and ultrasonic systems require precise calibration to operate correctly. Even routine repairs – such as replacing a windshield or repairing a bumper – can require advanced calibration procedures supported by professional diagnostic equipment.

At the same time, vehicles are generating unprecedented amounts of operational data. Connected cars can produce up to 25 gigabytes of data per hour from sensors and control systems. For technicians, this means traditional troubleshooting methods are no longer sufficient. Basic code readers cannot interpret encrypted gateways, cross-module interactions, or advanced communication protocols.

Professional diagnostic platforms must now support:

  • deep multi-system scanning across dozens of ECUs
  • real-time sensor and parameter analysis
  • module coding and software updates
  • secure access to manufacturer-protected systems

In short, modern ICE vehicles have become digital ecosystems on wheels, and maintaining them requires diagnostic tools capable of navigating increasingly complex electronic architectures.

EVs Introduce a New Diagnostic Paradigm

While ICE vehicles are becoming more electronically sophisticated, EVs introduce an entirely new diagnostic framework centered on high-voltage energy systems and battery management. EV adoption has accelerated rapidly. According to the International Energy Agency, global EV sales exceeded 14 million units in 2023, bringing the worldwide EV fleet to more than 40 million vehicles (IEA, 2024).

Unlike combustion vehicles, EV diagnostics focuses on monitoring electrical and electrochemical systems rather than combustion processes or emissions control.

Key EV subsystems requiring diagnostic oversight include:

  • high-voltage lithium-ion battery packs
  • Battery Management Systems (BMS)
  • electric motor controllers and inverters
  • onboard chargers and DC-DC converters
  • battery thermal management systems

Most EV platforms operate on 400-volt architectures, while next-generation systems are increasingly adopting 800-volt platforms to enable faster charging and higher efficiency (Deloitte, 2023). Battery packs themselves are highly complex. A single EV battery can contain thousands of lithium-ion cells arranged in modules, each continuously monitored by the BMS to ensure safe operation and balanced performance.

EV diagnostics therefore, centers on indicators such as:

  • State of Charge (SOC) – real-time energy availability
  • State of Health (SOH) – long-term battery degradation
  • cell voltage balancing
  • thermal management performance

In addition, EV powertrains are heavily software-controlled. Many service issues arise not from hardware failure but from software calibration conflicts, firmware errors, or communication faults between control modules.

This shift reflects a broader transformation across the automotive industry. As McKinsey & Company notes: “The vehicle is rapidly becoming a software-defined platform, where functionality is increasingly determined by software rather than hardware.”

For workshops and technicians, this means diagnostics must increasingly integrate electrical system monitoring, battery analytics, and software management.

A Dual-Technology Aftermarket

The coexistence of increasingly sophisticated ICE vehicles and expanding EV fleets is reshaping the automotive aftermarket.

Rather than reducing demand for diagnostics, this technological diversity is accelerating it. According to MarketsandMarkets, the global automotive diagnostic scan tools market is projected to grow from roughly $37 billion in 2023 to more than $60 billion by 2030 (MarketsandMarkets, 2023).

This growth is driven by two simultaneous forces.

First, ICE vehicles continue to gain electronic complexity as manufacturers optimize performance, efficiency, and safety. Second, EV adoption is creating entirely new diagnostic requirements centered around battery health, high-voltage systems, and software control.

As a result, many industry observers now describe the aftermarket as entering a “Golden Age of Complexity.” For workshops, this means supporting a diverse fleet of vehicles built on fundamentally different propulsion technologies.

Supporting the Modern Workshop

For technicians and service centers, the challenge is not only technical but strategic.

As vehicle fleets diversify, workshops must decide whether to specialize in a particular technology or invest in tools capable of servicing a wide range of platforms. Diagnostic systems that support both ICE and EV architectures provide important operational flexibility, allowing service providers to adapt as the vehicle parc evolves.

In this environment, the most valuable diagnostic solutions will emphasize:

  • broad coverage across global vehicle brands
  • continuous software updates
  • compatibility with emerging EV platforms
  • advanced system-level data interpretation

As vehicles become more digital and electrified, diagnostics is evolving into the critical interface between technicians and increasingly complex automotive systems.

Diagnostics in the Era of Software-Defined Vehicles

The future of automotive diagnostics will not be defined by a single propulsion technology. Instead, it will be defined by data – and the ability to interpret that data accurately, efficiently, and safely.

Whether diagnosing a turbocharged combustion engine or assessing the electrochemical health of a lithium-ion battery pack, technicians rely on intelligent diagnostic systems to translate complex vehicle data into actionable insights.

As the automotive aftermarket enters this new era of technological convergence, companies like TOPDON that understand both dimensions of the industry – ICE refinement and EV expansion – will play a central role in enabling workshops to navigate the transition.

The road ahead may be electric, mechanical, or both. But diagnostics will remain the essential link connecting every vehicle to performance, safety, and long-term reliability.



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Recent Reviews


As I’m writing this, NVIDIA is the largest company in the world, with a market cap exceeding $4 trillion. Team Green is now the leader among the Magnificent Seven of the tech world, having surpassed them all in just a few short years.

The company has managed to reach these incredible heights with smart planning and by making the right moves for decades, the latest being the decision to sell shovels during the AI gold rush. Considering the current hardware landscape, there’s simply no reason for NVIDIA to rush a new gaming GPU generation for at least a few years. Here’s why.

Scarcity has become the new normal

Not even Nvidia is powerful enough to overcome market constraints

Global memory shortages have been a reality since late 2025, and they aren’t just affecting RAM and storage manufacturers. Rather, this impacts every company making any product that contains memory or storage—including graphics cards.

Since NVIDIA sells GPU and memory bundles to its partners, which they then solder onto PCBs and add cooling to create full-blown graphics cards, this means that NVIDIA doesn’t just have to battle other tech giants to secure a chunk of TSMC’s limited production capacity to produce its GPU chips. It also has to procure massive amounts of GPU memory, which has never been harder or more expensive to obtain.

While a company as large as NVIDIA certainly has long-term contracts that guarantee stable memory prices, those contracts aren’t going to last forever. The company has likely had to sign new ones, considering the GPU price surge that began at the beginning of 2026, with gaming graphics cards still being overpriced.

With GPU memory costing more than ever, NVIDIA has little reason to rush a new gaming GPU generation, because its gaming earnings are just a drop in the bucket compared to its total earnings.

NVIDIA is an AI company now

Gaming GPUs are taking a back seat

A graph showing NVIDIA revenue breakdown in the last few years. Credit: appeconomyinsights.com

NVIDIA’s gaming division had been its golden goose for decades, but come 2022, the company’s data center and AI division’s revenue started to balloon dramatically. By the beginning of fiscal year 2023, data center and AI revenue had surpassed that of the gaming division.

In fiscal year 2026 (which began on July 1, 2025, and ends on June 30, 2026), NVIDIA’s gaming revenue has contributed less than 8% of the company’s total earnings so far. On the other hand, the data center division has made almost 90% of NVIDIA’s total revenue in fiscal year 2026. What I’m trying to say is that NVIDIA is no longer a gaming company—it’s all about AI now.

Considering that we’re in the middle of the biggest memory shortage in history, and that its AI GPUs rake in almost ten times the revenue of gaming GPUs, there’s little reason for NVIDIA to funnel exorbitantly priced memory toward gaming GPUs. It’s much more profitable to put every memory chip they can get their hands on into AI GPU racks and continue receiving mountains of cash by selling them to AI behemoths.

The RTX 50 Super GPUs might never get released

A sign of times to come

NVIDIA’s RTX 50 Super series was supposed to increase memory capacity of its most popular gaming GPUs. The 16GB RTX 5080 was to be superseded by a 24GB RTX 5080 Super; the same fate would await the 16GB RTX 5070 Ti, while the 18GB RTX 5070 Super was to replace its 12GB non-Super sibling. But according to recent reports, NVIDIA has put it on ice.

The RTX 50 Super launch had been slated for this year’s CES in January, but after missing the show, it now looks like NVIDIA has delayed the lineup indefinitely. According to a recent report, NVIDIA doesn’t plan to launch a single new gaming GPU in 2026. Worse still, the RTX 60 series, which had been expected to debut sometime in 2027, has also been delayed.

A report by The Information (via Tom’s Hardware) states that NVIDIA had finalized the design and specs of its RTX 50 Super refresh, but the RAM-pocalypse threw a wrench into the works, forcing the company to “deprioritize RTX 50 Super production.” In other words, it’s exactly what I said a few paragraphs ago: selling enterprise GPU racks to AI companies is far more lucrative than selling comparatively cheaper GPUs to gamers, especially now that memory prices have been skyrocketing.

Before putting the RTX 50 series on ice, NVIDIA had already slashed its gaming GPU supply by about a fifth and started prioritizing models with less VRAM, like the 8GB versions of the RTX 5060 and RTX 5060 Ti, so this news isn’t that surprising.

So when can we expect RTX 60 GPUs?

Late 2028-ish?

A GPU with a pile of money around it. Credit: Lucas Gouveia / How-To Geek

The good news is that the RTX 60 series is definitely in the pipeline, and we will see it sooner or later. The bad news is that its release date is up in the air, and it’s best not to even think about pricing. The word on the street around CES 2026 was that NVIDIA would release the RTX 60 series in mid-2027, give or take a few months. But as of this writing, it’s increasingly likely we won’t see RTX 60 GPUs until 2028.

If you’ve been following the discussion around memory shortages, this won’t be surprising. In late 2025, the prognosis was that we wouldn’t see the end of the RAM-pocalypse until 2027, maybe 2028. But a recent statement by SK Hynix chairman (the company is one of the world’s three largest memory manufacturers) warns that the global memory shortage may last well into 2030.

If that turns out to be true, and if the global AI data center boom doesn’t slow down in the next few years, I wouldn’t be surprised if NVIDIA delays the RTX 60 GPUs as long as possible. There’s a good chance we won’t see them until the second half of 2028, and I wouldn’t be surprised if they miss that window as well if memory supply doesn’t recover by then. Data center GPUs are simply too profitable for NVIDIA to reserve a meaningful portion of memory for gaming graphics cards as long as shortages persist.


At least current-gen gaming GPUs are still a great option for any PC gamer

If there is a silver lining here, it is that current-gen gaming GPUs (NVIDIA RTX 50 and AMD Radeon RX 90) are still more than powerful enough for any current AAA title. Considering that Sony is reportedly delaying the PlayStation 6 and that global PC shipments are projected to see a sharp, double-digit decline in 2026, game developers have little incentive to push requirements beyond what current hardware can handle.

DLSS 5, on the other hand, may be the future of gaming, but no one likes it, and it will take a few years (and likely the arrival of the RTX 60 lineup) for it to mature and become usable on anything that’s not a heckin’ RTX 5090.

If you’re open to buying used GPUs, even last-gen gaming graphics cards offer tons of performance and are able to rein in any AAA game you throw at them. While we likely won’t get a new gaming GPU from NVIDIA for at least a few years, at least the ones we’ve got are great today and will continue to chew through any game for the foreseeable future.



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