A technology-open drive system concept is a key feature of the new BMW 3 Series. Alongside the fully electric BMW i3, which celebrated its design premiere in March 2026, there will be a line-up of new BMW 3 Series models with four- and six-cylinder engines. The power units are “extremely efficient”, the auto maker said, and have 48V mild hybrid technology.

The new BMW 3 Series is undergoing a final round of driving dynamics testing at the BMW Group’s test centre near Miramas in southern France. The facility offers a range of track types, from a high-speed oval to handling courses, as well as different road surfaces, enabling engineers to assess and optimize the vehicle’s driving behavior. Before arriving in Miramas, the new 3 Series had already completed an extensive testing program, including trials at the BMW Group’s winter testing center in Arjeplog, Sweden, and on the Nürburgring in Germany.

“The BMW 3 Series has set standards for driving dynamics for several decades now, and thus serves as a symbol of ‘sheer driving pleasure’,” explained Dr Mihiar Ayoubi, senior vice president – driving experience development, BMW.

“With the new generation, we are building on this strength once again through the perfect interplay of chassis hardware and a continuously optimized and intelligent BMW Driving Stack. In this way, we are elevating the driving experience in the new BMW 3 Series to a new level – precise, assured und unmistakably BMW.”

Six-cylinder engine 

The BMW M350 xDrive is the performance variant of the new BMW 3 Series range, and has an internal combustion engine – a 3.0-liter BMW TwinPower Turbo six-cylinder in-line developing 326kW/443hp.

It is the only 3 Series variant offered with a six-cylinder engine and features specific chassis tuning, increased torsional and vertical stiffness, an 8-speed Steptronic transmission and BMW xDrive all-wheel drive. Like the four-cylinder models, it uses 48V mild-hybrid technology. Adaptive M suspension, an M Sport differential and variable sport steering are fitted as standard. The M350 xDrive accelerates from 0-100 km/h (62mph) in 4.1 seconds.

The BMW M350 xDrive will introduce a Drift Moment function during 2027, enabling drive from the engine to be directed entirely to the rear wheels when activated via the central display. Combined with M-specific control of the multidisc clutch and DSC switched off, the function enables rear-wheel-drive drift behavior.

Chassis development

The new BMW 3 Series combines near-even weight distribution between the axles with a longer wheelbase and wider front and rear tracks. Digital driving dynamics systems are integrated across the vehicle, with updates including an upgraded integrated braking system and revised steering ratio aimed at improving handling precision.

It has a double-joint spring strut front axle and a five-link rear axle, while anti-roll bar mounts with high preload on both axles improve roll control and stabilization.

The intelligent BMW driving stack

The new BMW 3 Series features model-specific chassis and control systems adapted to each drive system, alongside a newly developed electronics and software architecture. At its core is the BMW Driving Stack, an integrated hardware and software system that coordinates driving-related functions across the vehicle.

In the fully electric BMW i3, the Heart of Joy central computer works with the BMW Dynamic Performance Control Driving Stack to manage the vehicle’s driving dynamics. Developed for BMW’s sixth-generation electric drive architecture, the system coordinates driving-related functions across the vehicle. The ICE models use an optimized BMW Driving Stack tailored to their drive system, with transverse dynamics management integrating agility-related functions including the all-wheel-drive system. Stabilization and engine management remain distributed across specialized control units, building on BMW’s existing control architecture.

Both Driving Stacks are tailored to their respective drive systems, with future BMW 3 Series variants set to use driving dynamics management systems configured for their specific powertrain.

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Assessing increasingly sophisticated advanced driver assistance systems and autonomous driving technologies requires manufacturers and testing organizations to analyze large volumes of camera, sensor and vehicle data. During on-road testing, engineers have traditionally reviewed footage, identified road signs and conditions, compared them with dashboard data and assessed the vehicle’s response. This manual process is difficult to scale without increasing engineering resources.

IVEX was developed to address this challenge using computer vision, AI and cloud-based data processing to automate aspects of on-road vehicle safety testing. The platform can interpret the vehicle’s surroundings, including speed limits and road signs, read information displayed to the driver and compare these data sources. The analysis can then assess whether the vehicle recognized relevant road information and responded according to the applicable safety protocol.

The company uses a human-in-the-loop model, enabling engineers to review its output and retain control over the final assessment. The technology can reduce engineering time spent analyzing data by more than 95%; in one example, it processed 400 hours of multi-sensor driving data using eight hours of engineering time.

“Vehicle safety testing generates enormous amounts of data, but much of its analysis still depends on repetitive manual work,” said Mario Torres, co-founder and CEO of IVEX. “AI and rigorous mathematical algorithms allows us to make the testing process significantly faster and more scalable while keeping engineers in control and ensuring that every result remains traceable to the original data. With this funding, we can deepen the capabilities of our platform and bring IVEX technology to North America and Asia.”

IVEX’s long-term goal is to develop an AI-powered platform for automotive safety testing, with different safety protocols, testing requirements and vehicle functions operating as applications. The company says its underlying models will improve as the platform processes data from additional vehicles and driving environments, supporting the development of further safety-testing applications.

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The LMDh prototype first carried out an initial low-speed run at the Paul Ricard Circuit’s Driving Center, before continuing its test program at Le Castellet Airport and then at the Paul Ricard Circuit, right next to ORECA’s Technocentre where the car was designed and developed.

Dan Sayers, WEC Hypercar program manager at Ford Racing said, “Reaching Paul Ricard and getting the car through its shakedown and three full days of running is exactly the milestone we set out to hit. Everything we did in the buildup – the dyno work in Dearborn, the fire-up in France, the countless hours in the sim – was about making sure that when we rolled out onto track, we were ready to be plug and play. There’s a long list of milestones still ahead of us before Q1 2027, but these past couple of weeks has given the team a lot of confidence and strong foundations to build on.”

From design to track

The prototype – the result of close collaboration between Ford Racing and ORECA –  was jointly developed by teams who have been working for several months at ORECA’s Technocentre to prepare for its return to competition in 2027.

Hugues de Chaunac, president of the ORECA Group, commented, “Seeing this Hypercar take to the track for the first time is a powerful moment for all the teams involved in this project. After several months of close collaboration with Ford Racing, these first real-world outings mark an important step in the car’s development. At ORECA, we are proud to contribute to the return of a brand as iconic as Ford to the highest level of Endurance racing, and we are eager to continue this journey with them through to their competitive debut in 2027.”

All six Ford Racing Hypercar drivers attended the test during the week. Logan Sargeant, Matt Campbell, Tom Blomqvist and Mike Rockenfeller took turns behind the wheel, while British drivers Sebastian Priaulx and Nick Yelloly were also on site to gather feedback and prepare for the next phase of testing.

Mark Rushbrook, global director of Ford Racing, said, “This is only the first step of a long and demanding development road, but the fact that all six of our drivers were on hand, working together and pushing this program forward, tells you everything about the spirit we’re building at Ford Racing.”

This first phase of testing marks an essential step in the development of the Ford Hypercar before starting a more intensive test program, in preparation for its homologation under LMDh technical regulations.

Ford Racing Hypercar driver Matt Campbell said, “I’ve been here for the whole test and from my side, it’s gone smoothly. I’ve seen fans online raving about how awesome the sound is, but from inside the cockpit, it’s on another level – it’s absolutely deafening! I’m genuinely excited for what’s ahead with this car. We know there’s a long road in front of us, but this has been a really positive start.”

The Ford Hypercar will continue its development program through several test sessions at European circuits through the end of 2026, before heading to the USA to continue its preparation. Ford Racing will make its return to the highest level of Endurance racing in 2027 with a two-car entry in the top category of the FIA World Endurance Championship (WEC).

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“The Nuvolari project is a striking example of how quickly we at Audi can bring an idea to life – that is ‘vorsprung durch technik,’” said Audi CEO Gernot Döllner. As the OEM states, the new model is much more than a supercar – it guides the way for future Audi developments and provides important impetus for the brand’s technology portfolio.

“The Audi Nuvolari is the fastest and most powerful road car we’ve ever produced,” noted Rouven Mohr, member of the board of management for technical development.

At the same time, the project represents a new kind of collaboration at Audi: from the very beginning, experts in design, vehicle technology, aerodynamics and powertrain worked closely together in an autonomous, focused project team. Short lines of communication, quick decisions and the close integration of all disciplines enabled the development project to move forward at a rapid pace.

“The Audi Nuvolari shows that, when you have the right mindset and close teamwork, you can succeed in delivering rapidly without making any compromises,” added chief creative officer Massimo Frascella.

A development journey across Europe

From the initial designs in Ingolstadt to cold-weather testing with technology demonstrators in Lapland, lightweight construction in Neckarsulm, tests in the Ingolstadt wind tunnel, suspension tuning in southern Spain and high-speed tests in Nardò, Italy, Audi’s engineers worked hand in hand to develop the Nuvolari in record time.

“When the Nuvolari took to the road for the first time, the best part was seeing the expressions on the faces of the people who had developed it,” recalled Döllner. “Seeing something that had existed only as a sketch come to life for the first time was indescribable.”

Final touches with Formula 1 expertise

Four hundred and five days after the initial idea, the project team presented the first driveable prototype. The Audi Revolut F1 drivers then took over testing duties. Gabriel Bortoleto drove the Nuvolari on the high-speed track at the Nardò Technical Center. Before the drive, he stated, “I’m definitely going to push it,” and waxed lyrical about its performance afterward.

At the test track in Neustadt an der Donau, F1 teammate Nico Hülkenberg also pushed the Nuvolari to its limits. “The acceleration and the full system output of more than 1,000ps – that’s a real statement.”

In June 2026, the Audi Nuvolari debuted.

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Drawing on the experience gained in the car’s debut in the Hypercar category, Team Peugeot TotalEnergies is working on a series of technical evolutions aimed at enhancing performance, efficiency and competitiveness and said that this latest step marks an important milestone in the ongoing development of the Peugeot 9X8.

“Since its debut, the Peugeot 9X8 has been a platform in constant evolution. Competing at the highest level of endurance racing means continuously learning, adapting and progressing,” said Emmanuel Esnault, team principal, Team Peugeot TotalEnergies.

“The intensity of competition at a world championship level reinforces our determination to keep evolving. Our objective is clear: to position the 9X8 consistently among the top contenders.

“As we look ahead to 2027, the team is taking the next step in its development, focused on a revised approach to performance, efficiency and design. This work is a key milestone in preparing the next chapter of the Peugeot 9X8 story and perpetuating the legacy of Peugeot in endurance racing.”

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This next phase of Nigel AI introduces prompt-based code generation within NI LabView and automated sequence generation in NI TestStand, enabling engineers to move from design to validation more quickly while maintaining the rigor required in mission-critical applications.

As product complexity increases and validation cycles grow more demanding across industries, engineering teams face pressure to deliver higher throughput without sacrificing quality.

Emerson’s approach embeds context-aware AI directly into the test environments engineers already use, helping streamline development while ensuring robust security, alignment with regulatory requirements such as the Cyber Resilience Act (CRA) and strong engineering oversight.

“In one year, Nigel has evolved from an AI advisor to AI author, showing the strength of the NI platform and its ability to integrate the most in-demand technologies quickly for the benefit of our customers,” said Ritu Favre, president of Emerson’s test and measurement business.

“By enabling purpose-built AI to generate code and test sequences within workflows, we’re accelerating productivity while ensuring engineers remain in control of validation and decision-making.”

With this release, Nigel AI is now available across the broader NI LabView+ Suite, bringing AI-driven workflows to NI InstrumentStudio, NI FlexLogger and NI VeriStand. The expansion brings context-aware intelligence into interactive measurements, sensor-based datalogging and hardware-in-the-loop test environments. Engineers can apply AI capabilities consistently across the full test lifecycle – from initial development through system validation and deployment.

Nigel AI is purpose-built for engineering environments and operates directly within structured test workflows. It leverages modular instrumentation, open software systems, configurable workflows, engineering code and structured data to produce outputs aligned with real-world system constraints.

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“We believe physical AI will become one of the defining technologies of this century,” said Qasar Younis, co-founder and CEO of Applied Intuition. “Our ambition is to help bring intelligence to a billion machines, and Dana is the platform we built to make that possible.”

Unlike general-purpose AI tools designed primarily for digital workflows, Dana is built for the complexities of machines operating in the physical world. Dana comes with all the platform capabilities needed to build and deploy safety-critical physical AI applications, including data, visualization and tooling, as well as the evaluation, traceability and governance these systems require. The platform was designed to work across industries and with a wide range of use cases including software-defined vehicle development and advanced driver assistance systems (ADAS), truck fleet management, robotics and intelligent in-vehicle experiences.

Dana enables customers to deploy Applied Intuition’s reference applications for areas including autonomous driving and fleet operations, or develop their own applications. The platform supports both natural language and command-line interfaces to simplify development tasks and accelerate software iteration. It can also be integrated with enterprise tools such as Slack and Jira to help connect engineering and operational workflows.

Applied Intuition has used Dana internally since last year and says the platform has reduced some stages of vehicle development from months to days through agent-driven workflows. The company has also provided early access to selected customers, including Komatsu and Isuzu Motors, with Isuzu using the platform to support development of Level 4 autonomous commercial trucks.

“We’ve been impressed by how Dana can streamline complex engineering workflows and accelerate development,” said Yasuhiro Yazawa, director, Isuzu Motors, Japan. “Dana gives our engineering teams greater confidence to develop, track and deploy safe autonomous-vehicle capabilities at a much faster pace.”

“Applied Intuition has been a valuable technology partner as we continue advancing the digital capabilities that support the next generation of mining equipment and solutions,” said Peter Salditt, CEO, Komatsu Mining. “Dana represents another step forward, bringing intelligent, agentic capabilities into our engineering workflows to help our teams innovate faster, improve efficiency and ultimately create greater value for our customers’ operations.”

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With these tools, agents can write MATLAB code, run it in a live session, examine outputs or errors and iterate toward a correct result, while engineers remain responsible for validating results and applying their expertise.

The new capabilities are aimed at MATLAB users, AI engineers building agent-driven workflows and platform teams managing AI-assisted engineering environments. Because agents run code directly in MATLAB, their outputs are based on deterministic computation, numerical analysis and executable models rather than only language-model-generated text. Engineers can check results by reviewing outputs, comparing them against expected behavior and refining workflows through iteration – standard practices in engineering development.

“As organizations adopt agentic AI in model-based design and engineering, the focus is shifting from code generation to reliable execution within established multi-disciplinary toolchains,” said Diego Tamburini, AI practice director at CIMdata.

“Engineers remain responsible for defining problems, validating outcomes and maintaining oversight, while AI agents increasingly handle iterative and repetitive tasks – augmenting human efficiency and effectiveness. This reinforces the importance of human-in-the-loop workflows, where real execution and validation underpin trust in AI-driven engineering processes.”

MATLAB MCP Server and MATLAB Agentic Toolkit are open-source packages, enabling developers and organizations to inspect, extend and incorporate agent‑based workflows with MATLAB in their own environments using agentic tools such as Claude Code, GitHub Copilot, OpenAI Codex and Gemini CLI. This supports interoperability across diverse AI agent frameworks and positions MATLAB as foundational infrastructure for emerging agent‑based engineering ecosystems.

“AI agents are most effective in engineering when they can directly interact with the tools used for design, simulation and analysis,” said Seth DeLand, generative AI product manager at MathWorks.

“By enabling agents to execute and iterate MATLAB workflows, we’re connecting AI-driven iteration to the same computational environment engineers use to develop and validate their work. This allows teams to move from LLM generated code to executable, testable results within a consistent engineering framework.”

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The system combines an FPGA core for real-time data processing with interchangeable SerDes (serializer/deserializer) interface devices, enabling engineers to reconfigure test setups as display and camera requirements change.

The launch is the latest addition to Emerson’s NI PXI platform, an open, modular test system, and extends its capabilities for automotive testing applications. The system includes the NI PXIe-1480 FlexRIO multiprotocol vision carrier module, which supports interchangeable interface devices for testing automotive displays and cameras. The first available interface devices support FPD-Link IV, a high-speed automotive video interface used in ADAS and in-vehicle display applications.

As vehicle architectures shift toward centralized electronic control units, engineers must validate multiple high-speed interfaces on increasingly complex systems. Conventional display test methods, often relying on cameras or visual inspection, limit scalability and introduce variability. By providing a direct interface to ECU and display SerDes input/output (I/O), the modular PXI-based approach improves test coverage through automated, deterministic testing. The result is a single, flexible platform that streamlines validation and improves test repeatability.

“The increasing complexity of automotive electronics requires a more flexible and scalable approach to validation,” said Sam Burhans, chief product manager with Emerson’s test and measurement business. “This modular architecture allows engineers to adapt their test systems to evolving interface standards without redesigning their entire setup.”

The NI PXIe-1480 carrier module serves as the foundation for this architecture, supporting interchangeable interface devices tailored to specific testing requirements.. Emerson plans to extend the platform later this year with additional interface devices supporting a broader range of camera and display protocols.

The solution is designed for engineers in automotive validation and production test environments, including Tier 1 suppliers and original equipment manufacturers, supporting applications across in-vehicle infotainment, ADAS and autonomous driving systems.

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Through the program, selected companies may receive funding ranging from US$25,000 to US$250,000 to support deployments on Curiosity Lab’s autonomous mobility route in Peachtree Corners in the US state of Georgia. The program is designed for companies with technology that is ready to move beyond the lab, beyond the closed course, and into live operating conditions.

Curiosity Lab is a living laboratory for place-based deployment in metro Atlanta, built to help companies test next-generation technologies in an active city environment. The autonomous mobility route includes a nearly four-mile smart mobility loop along Technology Parkway and State Route 141, with dedicated autonomous vehicle lane segments, shared and mixed-traffic roadway, enhanced sidewalks, rights-of-way, smart city infrastructure and real destinations throughout the corridor.

The test lab recreates a real city environment with active traffic, intersections, sidewalks, business entrances, commercial activity and public infrastructure. For autonomous mobility companies, it creates an opportunity to validate technology in the kinds of conditions that matter for commercialization, customer adoption and scale.

Curiosity Lab is looking for growth-stage companies and innovation teams working on autonomous mobility technologies, including autonomous passenger shuttles, low- or high-speed autonomous vehicles, autonomous delivery vehicles, sidewalk or curbside delivery robots, autonomous logistics and last-mile mobility systems and robotic mobility systems.

Applications must be submitted by 11:59pm Eastern Time on July 24, 2026. Selected projects will take place in Peachtree Corners between October 1, 2026, and September 30, 2027.

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