The BQ79826Z-Q1 battery monitor enhances safety and extends battery life by detecting potential failures from within battery cells. The single chip tracks up to 44% more channels than previous generations. With this increase, the device significantly decreases the number of components required in a battery pack, reducing system complexity and cost without compromising reliability

“The electrification of transportation and the rapid expansion of energy storage are redefining what battery performance must deliver, and as a leader in battery management technology, TI is uniquely positioned to meet that challenge,” said Wenjia Liu, vice president and general manager, battery management systems (BMS) at TI.

“Our high-cell-count battery monitor with a built-in EIS engine helps ‘shine a light’ inside battery cells, delivering rich chemical-state data that enables systems’ software to make informed, real-time decisions on safety and performance of the battery pack, allowing engineers to address the most critical challenges in battery management.”

Delivering safety and performance with EIS technology 

EIS monitors a battery and delivers continuous, real-time insight that reveals the battery’s health and warns of issues before they become critical. Integrated EIS technology enables the BQ78926Z-Q1 to detect fault conditions earlier – from inside the cells – helping maintain safety and notifying passengers of potential vehicle hazards such as thermal runaway.

Maximizing efficiency with industry-leading cell count

According to the company, the BQ79826Z-Q1 supports up to 26 cells per device – eight more than competing solutions. By reducing the number of monitoring devices required, it lowers bill-of-materials costs, simplifies system architecture and minimizes board space requirements, delivering significant cost savings per channel without compromising quality or reliability.

When paired with the BQ79881-Q1 pack monitor and optional TI communications bridge, these devices create a powerful chipset that works across different module sizes, battery chemistries and mechanical designs, giving engineers the flexibility to design once and deploy everywhere.

Calculating charge readings with the best-in-class accuracy

With a voltage accuracy of <2mV across a full temperature range of –40°C to +125°C, higher resolution analog-to-digital converters and ultra-low noise, the BQ78926Z-Q1 enables more accurate state-of-charge calculations, directly addressing one of the biggest concerns for EV drivers: range anxiety.

Using EIS technology, this device enables more accurate temperature and state-of-charge estimation, helping designers achieve longer battery life and faster charging without compromising battery health.

With an EIS measurement time that is five times faster than previous solutions, this device delivers the highest functional safety voltage reading per cell. Compliance with Automotive Safety Integrity Level D and International Organization for Standardization 26262 gives designers a smarter, more efficient path to safer, longer-lasting batteries.

Related news, rFpro launches AV Elevate In Cabin driver and occupant monitoring simulation tool

To address this, rFpro has launched the AV Elevate In Cabin add-on package that enables automotive OEMs, Tier 1s and sensor developers to tune, train and test driver and occupant monitoring systems in simulation to improve the speed and consistency of in-cabin testing.

“Euro NCAP’s 2026 scoring changes make in-cabin monitoring one of the most consequential areas of vehicle safety development,” said Matt Daley, technical director at rFpro. “When you combine that with ADDW becoming mandatory, it is clear that the demand to develop and validate these systems faster and earlier in the program will only grow. We have taken our proven exterior simulation solution and applied the same techniques to the interior. AV Elevate In Cabin is a physically accurate, engineering-grade  simulation environment enabling thousands of tests to be conducted before anything physical has even been built.”

AV Elevate In Cabin addresses three core areas of in-cabin simulation: the fidelity of the virtual cabin environment, the control of occupant behavior within it and the physical accuracy of sensor perception.

Interior fidelity

rFpro has improved the fidelity of its vehicle interior models by adding sub-structures that are invisible to the human eye and to cameras but are detected by radar. The metal framework within seats, for example, is now modeled to ensure radar-based sensing systems encounter realistic returns.

The object library has been expanded to include items commonly found inside vehicles, including rucksacks, laptops, child seats, pets and other personal belongings. Skin simulation has also been improved, with higher-detail facial models to support systems that assess driver state from facial features.

Controlling the virtual environment 

A high-density bone rig within rFpro’s human models enables fine control of facial and limb movements, supporting simulation of the macro and micro expressions that driver monitoring systems must detect. This includes ‘owl movement’, where the driver turns their head, and ‘lizard movement’, where only the eyes shift away from the road.

“We have even considered details like opening and closing vehicle windows,” said Daley. “That is not something you need to think about for external sensor simulation, but it fundamentally changes how light and radar energy travel through the cabin. If you are developing an in-cabin system that needs to work reliably in the real world, these are the kinds of variables you have to account for.”

Sensor modeling

Most in-cabin systems use a mixture of radar sensors, visible light cameras and IR cameras, that see using their own IR energy source. rFpro’s new IR camera sensor integration accurately models the energy emitted by the camera and how it interacts with every cabin surface.

Specific IR reflectivity and radar properties have been assigned to all interior materials, including the driver’s skin, seats and windows. These material characteristics have been correlated with laboratory measurements conducted under the Sim4CamSens research program, with the National Physical Laboratory and Compound Semiconductor Applications Catapult involved in the testing. Skin reflectivity, for example, has been characterized down to the difference between a nose, chin and cheek to improve the realism of IR camera data.

“Looking further ahead, understanding who is in the cabin and what they are doing is essential for autonomous vehicle operations, not just for safety, but for the passenger experience,” said Daley. “If you know where occupants are, you can optimize everything from airbag deployment to noise-cancelling audio. We are looking to partner with sensor developers and OEMs to help drive the direction of this capability further.”

Related news, Gazoo Racing unveils GRMN Corolla

The development of the higher-performance version of the GR Corolla drew on Gazoo Racing’s motorsport experience, specifically its participation in the Super Taikyu Series, and input from Morizo himself, as well as extensive testing at the iconic German racetrack.

The GRMN Corolla was put through its paces in Japan’s Super Taikyu Series and validated using advanced driving simulators, with the Nürburgring playing a central role in the vehicle’s development. According to the engineering team, the circuit’s unique combination of surface changes and road inputs exposed challenges not encountered on conventional test tracks. These conditions were used to refine the vehicle’s handling and responsiveness.

GR has applied the insights gained from GRMN Corolla development to the evolution of the base GR Corolla. For the 2026 GR Corolla, announced in September 2025 and launched in November of that year, the application of structural adhesive was extended by 13.9m to 32.7m to reinforce the body structure, and an added cool-air duct now reduces the rise in intake air temperature during high-load driving. Both were the result of applying lessons learned at the Nürburgring, Toyota said.

Aerodynamic performance

In Super Taikyu Series and similar races, and at the Nürburgring, cars constantly travel at high speeds and experience high g-forces. Maximizing vehicle performance under these conditions requires all four wheels to maintain firm contact with the road.

The GRMN Corolla features aerodynamic performance parts for enhanced road holding. Its hood duct, fender ducts, front side spoilers and rear wing incorporate know-how gained from racing and tested on the hydrogen engine-powered GR Corolla that competes in the Super Taikyu Series.

Fine-tuning of the aerodynamics came at the Nürburgring. This included adjusting the rear wing angle, which features a five-step adjustment mechanism, in 1° increments during driving tests with professional drivers to verify effectiveness and determine the optimal specification.

Suspension fine-tuned 

The GRMN Corolla’s suspension employs exclusive front and rear monotube shock absorbers with rebound springs for improved inner-wheel traction during cornering and for enhanced high-speed cornering performance.

The Nürburgring road surface has areas that induce significant vertical suspension travel beyond that found on typical circuits. To ensure high stability for confident driving, extensive Nürburgring tests were run to facilitate optimization of bump-stop characteristics. The exclusive shock absorbers were developed by adjusting their stroke down to a millimeter at the front and rear for optimal balance.

The control program of the GRMN Corolla’s EPS (electric power steering) was modified from that on the base vehicle to generate the required amount of assistance torque even during cornering under high g-forces. The exclusively tuned 4WD control system provides optimal rear torque distribution during straight-line driving and enhanced stability at the onset of steering input at extremely high speeds.

Internal combustion engine evolution via the hydrogen engine-powered Corolla 

Through its participation in the Super Taikyu Series with a hydrogen-powered GR Corolla, GR has used endurance racing to support the development of hydrogen combustion technology. The high-load racing environment has also provided insights into the performance and durability of core internal combustion engine components.

Drawing on lessons from the Super Taikyu Series, Toyota increased the GRMN Corolla’s maximum engine torque to 415Nm, up 15Nm from the base model. Development focused on improving torque delivery in the 3,600rpm-4,800rpm range commonly used during circuit driving. To help maintain consistent performance during sustained high-load operation, the GRMN Corolla was been equipped with an intercooler spray system in addition to the cool-air duct introduced on the 2026 GR Corolla.

A cockpit designed to unlock an even higher level of performance

To further enhance performance, the GRMN Corolla features a two-seat configuration, with the rear seats removed as part of a weight-reduction program. Toyota says this contributes to a 30kg reduction compared with the base vehicle.

The GRMN Corolla features a redesigned cockpit focused on driver engagement, including a bespoke full-bucket driver’s seat developed using experience from the Super Taikyu Series. Based on race-car driving positions, the seat was been designed to provide increased lateral support while maintaining everyday usability. Its glass fiber-reinforced polymer (GFRP) construction helps reduce weight, and its dimensions were refined to support pedal operation.

The GRMN Corolla will be available in limited quantities, primarily in Japan, North America and Australia.

Related news, Rigorous RAM-D program at military facility validates Torsus Terrastorm 4×4 HD

“From technological innovation to the localization of manufacturing and R&D across Europe, supported by a truly global product line-up, MG continues to push the boundaries of what is possible – making advanced technology and sustainable mobility accessible to more people than ever before,” said William Wang, managing director, MG UK and Europe.

The site will integrate vehicle research and development, advanced manufacturing, core component supply and intelligent logistics operations, forming a fully connected, end-to-end industrial ecosystem. This platform will significantly expand localized production and sourcing, strengthening the resilience, responsiveness and agility of MG’s European supply chain.

MG will deepen collaboration with leading European technology partners, research institutions and local suppliers to accelerate innovation across key future-facing domains, including next-generation battery technology, intelligent mobility systems and clean energy solutions.

This announcement comes at a pivotal moment for the European automotive industry, as the EU’s 2035 zero-emission targets continue to accelerate the shift toward electrified mobility.

Wang said, “Through our ‘In Europe, For Europe’ strategy, we are not simply responding to the future of mobility – we are helping define it. By investing in local capabilities, strengthening our European footprint and fostering a more competitive automotive ecosystem, we are accelerating Europe’s journey toward a cleaner, smarter and more sustainable mobility future.”

Related news, Liquid hydrogen prototype marks next milestone in Toyota’s hydrogen development journey

The TR LH2 Racing Prototype is based on the same chassis as the TR010 Hybrid Hypercar, which will compete in the Le Mans 24 Hours on June 13 and 14. The prototype is designed to support the development of hydrogen technology in motorsport, contribute to Toyota’s ongoing hydrogen research and infrastructure efforts and help foster partnerships aimed at expanding hydrogen applications through motorsport.

Toyota has taken on the challenge of hydrogen engine development in motorsports, initially through Rookie Racing’s participation in the Japanese Super Taikyu series with the ORC Rookie GR Corolla H2 Concept. From 2021, this vehicle used gaseous hydrogen before the introduction of a liquid hydrogen-powered car in 2023.

The potential of hydrogen engines in rallying was initially showcased in 2022 when the GR Yaris H2 completed demonstration runs at Ypres Rally, a round of the FIA World Rally Championship. Further development was highlighted when the GR Yaris Rally2 H2 Concept conducted demonstrations at the 2025 Rally Finland and this year’s Monte Carlo Rally.

In 2023, the ORC Rookie GR Corolla H2 Concept completed a demonstration lap of the Circuit de la Sarthe, and a hydrogen engine concept car, the GR H2 Racing Concept, was presented to preview a potential future hydrogen category at Le Mans. Since then, development of the technology has intensified, reaching a further milestone with the unveiling of the liquid-hydrogen-powered GR LH2 Racing Concept last year at Le Mans. A year later, the next step in the company’s hydrogen journey is the first public demonstration of the TR LH2 Racing Prototype.

The TR LH2 Racing Prototype will be displayed in the Hydrogen Village before its demonstration laps.

In related news, Project Cavendish: Mahle hydrogen-fueled 13-liter engine matches diesel performance

As cellular networks transition away from legacy 2G and 3G infrastructure, auto makers face mounting pressure to deliver compliant Next-Generation eCall (NG-eCall) implementations that utilize packet-switched 4G and 5G networks. Because regional network modernization moves at varying speeds, vehicles must operate reliably across mixed-network environments. According to Keysight, its certified Hybrid eCall solution addresses this challenge directly, enabling in-vehicle systems (IVS) to dynamically switch between legacy and NG-eCall systems based on real-world network availability.

Building on Keysight’s previously achieved EN 17240 validation, this new certification ensures continuous alignment with evolving international standards.

Lourdes Sánchez, connectivity director at DEKRA, said, “At DEKRA, we are committed to supporting the automotive industry in the transition toward next-generation emergency communications through testing and certification services aligned with the latest European standards. Our collaboration with Keysight in validating its Hybrid eCall capabilities according to EN 18052:2025 has enabled the verification of critical aspects related to interoperability, reliability and regulatory readiness, helping accelerate the adoption of safer and more connected vehicle solutions for the future.”

The certification covers a range of critical real-world testing scenarios, including emergency call setup to validate rapid and stable connections across evolving network infrastructures, minimum set of data (MSD) transmission to ensure accurate delivery of vehicle location and telemetry data to emergency responders, voice communication to verify clear and uninterrupted call quality under realistic network conditions, and network fallback to confirm reliable operation when transitioning between NG-eCall and legacy network environments.

Thomas Goetzl, vice president and general manager of Keysight’s Automotive & Energy Solutions, added, “The automotive industry is at a critical juncture as cellular infrastructure evolves. Auto makers need proven, reliable testing methodologies to avoid compliance bottlenecks and deployment delays. Achieving this DEKRA certification underscores our commitment to delivering real-world-ready solutions, giving manufacturers the confidence to scale their connected vehicle platforms globally while meeting the highest safety standards.”

Keysight will demonstrate its Hybrid eCall and NG‑eCall testing at the ETSI NG‑eCall Plugtests 2026.

In related news, Hyundai Mobis joins S-Core project to advance SDV software platform development

To this end, the company has joined the Software Defined Vehicle (SDV) Working Group under the Eclipse Foundation and will participate in the S-Core project to develop an SDV software platform in earnest.

The S-Core project is a global initiative launched primarily by European companies in late 2024 to standardize foundational technologies such as software platforms and middleware. It is the first open-source-based software platform development project to meet ASIL-B, the automotive industry’s functional safety standard.

Currently, a total of 13 companies are participating in the project and prioritizing the implementation of core technologies required for SDVs, as standardized foundational technologies are essential for accelerating the development of applications such as autonomous driving. Under the common objective, participating companies are also working to prevent redundant investments while improving system stability.

The most distinctive feature of the S-Core project is that it applies an open-source development approach, previously used primarily in the IT industry, to the mobility sector. Participating companies disclose some of their software technologies, enabling developers around the world to freely use and improve them.

Another reason companies disclose coding technologies that constitute intellectual property is the potential to create both tangible and intangible added value. By encouraging more developers to use their software, companies can increase the likelihood of their technologies becoming global standards.

The technology Hyundai Mobis plans to disclose is a so-called ‘container solution’ that minimizes interference between software within the Linux operating system. The technology effectively creates partitions between a wide range of software in SDVs, packaging them individually so they can operate quickly without affecting one another.

The container solution is known to be more than 10 times faster than existing technologies in automotive controller environments. The company has also secured an always-on integrity assurance function to prevent software tampering caused by external intrusions and other risks.

Related news, Next-generation Helm.ai models deliver full-HD 360° synthetic driving environments

“For the BMW Group, the use of industrial data is a key factor in translating artificial intelligence into value creation,” said Dr Franz Decker, CIO and senior vice president of the BMW Group. “By combining our engineering datasets with Mistral AI’s model training capabilities, we are building specialized AI which supports complex development tasks.”

Complexity and data volume in crash simulation

Each week, BMW runs thousands of virtual crash simulations, generating vast amounts of engineering data. Over time, this has resulted in a historical dataset of over one petabyte of crash simulation data that provides highly detailed insights into vehicle structures and material behavior, forming a unique foundation for training an industrial AI model.

“As Industrial AI becomes the new frontier for AI, we are proud to partner with the BMW Group” said Marjorie Janiewicz, chief revenue officer of Mistral AI. “This collaboration shows how industry specific AI models can help solve complex engineering challenges such as crash simulation.”

Large industry model as a technical foundation

To scale this approach, the BMW Group is focusing on large industry models. These are AI systems trained on industry-specific engineering and simulation data from vehicle development and safety testing. Unlike general‑purpose AI systems, LIMs embed domain‑specific knowledge directly into the AI model. This requires not only industrial data, but also deep domain expertise and technical environments that enable AI systems to learn directly from BMW’s development processes.

Related news, Next-generation Helm.ai models deliver full-HD 360° synthetic driving environments

The foundation models address what is often referred to as the industry’s data wall, where the cost and effort of collecting real-world edge-case data can slow development. Traditional generative world models typically produce video at sub-HD or VGA resolutions (around 0.4MP per camera). In contrast, Helm.ai generates full-HD (2MP) output that matches the resolution of modern production vehicle cameras, helping to reduce the sim-to-real gap in training for Level 2 and Level 4 autonomous driving systems.

Scene transfer versus fully synthetic generation

Helm.ai’s platform provides auto makers with a pipeline for data augmentation and creation.

GenSim-3 (high-fidelity scene transfer) enables development teams to restylize real-world video synchronously across six-camera, 360° surround-view setups. The model alters parameters such as weather, illumination and object appearance at full-HD (2MP) resolution. Additionally, the latest model introduces improvements in environmental texture, surface reflectivity and light behavior on complex materials.

VidGen-3 (fully synthetic generation) generates highly realistic driving sequences completely synthetically. By simulating complex environments, human-like agent behaviors and traffic logic from scratch, VidGen-3 bridges geographic and environmental data gaps at scale.

The 5X pixel density advantage

The technology’s key breakthrough is the fidelity of the multicamera generative simulation.

By producing full-HD (2MP) video, Helm.ai provides significantly more visual information than traditional generative datasets. Because modern production vehicles use high-resolution camera systems, training data is more effective when it matches that resolution. Lower-resolution synthetic data can create a domain gap when used to train full-HD perception systems. By generating data natively at 2MP per camera, Helm.ai aligns training inputs with real-world sensor output, supporting more consistent model performance in deployment.

To accommodate diverse sensor and training requirements, engineering teams can optimize for dynamic, high-speed validation with three-camera setups at 30fps, or maximize spatial context with a full six-camera, 12MP surround view at 5fps.

The virtual sensor twin

Unlike CGI-based video generation methods, Helm.ai’s models are designed to simulate hardware-like sensor output by incorporating certain physical characteristics of real camera systems. This includes reproducing effects such as sensor noise patterns, lens flares and exposure-related artifacts. This produces training data that more closely reflects real-world camera behavior, helping perception systems learn under conditions similar to those encountered in actual driving environments.

High fidelity on lower compute

While other generative world models rely on the massive computational scaling of thousands of GPUs to generate sub-HD video, the full-HD (2MP) resolution milestone was achieved using a highly optimized cluster of just a few hundred advanced GPUs.

“We are moving the industry from standard ‘AI video’ to authentic, hardware-accurate sensor emulation,” said Vladislav Voroninski, the CEO and founder of Helm.ai. “By leading with a full-HD (2MP) standard and a 12MP total aggregate capability per timestep, we have solved the resolution bottleneck that has historically limited the utility of generative AI in safety-critical systems. By optimizing our compute architecture, we are giving our partners a high-performance platform to validate their autonomous stacks using synthetic data that perfectly matches the fidelity of their actual production sensors.”

In recent news, Candera unveils “smarter and faster” CGI Studio 3.16 HMI development software

The release extends the capabilities of Candera CGI Studio across the entire workflow from design and validation to deployment, and enables development teams to create and scale modern user interface concepts more efficiently across industries, hardware platforms and a wide range of use cases.

“With Candera CGI Studio 3.16, HMI development gets smarter and faster, combining AI-assisted tools, flexible workflows, and broad platform support,” said Roland Winkler, senior product development manager at Candera.

Improvements and updates

The Scene Composer experience has been enhanced with a new View Editor that simplifies automotive HMI workflows by allowing developers to preview scene combinations and manage transitions within a structured framework.

An Embedded Player enables seamless switching between design and runtime simulation inside Scene Composer, while a standalone Player remains available.

Multi View in the Scene Editor adds up to four synchronized views with selectable camera angles, improving inspection of complex 3D interfaces and enabling quick switching between single and multi-view modes.

Localization and documentation workflows are improved with built-in XLIFF 2.0 support. Developers can import, merge, edit and export localized text in a standard XML-based format, making CGI Studio easier to integrate into existing localization toolchains.

The new AI Docs Agent provides in-workflow support by delivering tailored answers in any language, helping users find information more quickly and reducing day-to-day friction. Each response also includes direct links to relevant Candera CGI Studio documentation, enabling users to access source material immediately.

Solution templates and advanced 3D

Another highlight of Candera CGI Studio 3.16 is the expansion of ready-to-use automotive HMI templates. The new In-Vehicle Infotainment (IVI) template includes building blocks for navigation, weather, media, phone, HVAC and digital twin scenarios. It supports both 2D and 3D use cases, with advanced visualizations and customizable application screens.

The new Instrument Cluster Solution Template integrates advanced driver assistant system functions such as adaptive cruise control (ACC), lane departure detection (LDD) and side assist alongside essential dashboard elements like speed gauge, media, telltales, time, odometer, temperature and turn-by-turn guidance. These templates help teams accelerate prototyping and shorten time to value.

The update enhances 3D capabilities with full glTF 2.0 support and features such as clear coat rendering. It also adds HDR rendering with tone mapping and automated import of image-based lighting cube maps for global illumination. Together, these improvements enable more realistic HMI visuals across automotive, industrial and embedded applications.

Engine and platform improvements

On the platform side, Candera CGI Studio 3.16 expands deployment flexibility with native rendering support for Apple iOS, enabling developers to build applications for Apple devices using Xcode and Metal.

The release also introduces Vulkan support as a modern graphics backend for 3D GPUs, improving CPU and GPU efficiency on Linux and Android platforms.

Another key addition is Software Rendering, which enables Candera CGI Studio 3.16 to run on platforms without a GPU. This enables platform-independent rendering across a wide range of targets, including ESP32-S3, ESP32-P4, Traveo II Body MCU, Raspberry Pi Pico and Linux-based systems. The renderer supports transformations, blending and visual effects while achieving up to 60 FPS depending on the platform and configuration, with low memory requirements.

Additional engine optimizations round out the release. Candera CGI Studio 3.16 now supports the new Monotype Spark Engine, designed for low memory usage and high performance. The update also includes newer versions of FreeType and HarfBuzz, delivering significant cache improvements for more efficient text rendering.

Candera CGI Studio 3.16 also streamlines behavior configuration through automatic code-size optimization using the SC plugin and CMake integration. These improvements help developers reduce memory footprint, improve performance and simplify overall project setup and configuration.

Recent news, Michelin reveals software-based tire digital twin platform