. Improvements in tread performance, rolling resistance reduction, handling, and durability have been well documented. As vehicles have evolved over the past 20 years, tyres have had to adjust along with them. Larger vehicles, higher performing vehicles, and light-weighting, along with the introduction of electric vehicle technology, are all trends that have steered development over the years.

Through all of it, several key areas in tyre testing have remained steady. Tyres need to meet minimum safety and performance standards as dictated by governments and vehicle OEMs.

•          Tyre durability testing depends on a variety of industry test standards such as endurance testing on a drum.

•          Wet stopping distance, tread wear, and winter traction testing have very specific on-vehicle testing requirements.

•          Rolling resistance testing utilises a couple standardised test methods to measure the amount of hysteretic energy loss from a rolling tyre on a drum and specified surface.

•          Force and moment testing on a moving belt has been used to characterise tyre performance for vehicle design as it relates to cornering and other use conditions.

As time has passed, tyres have been asked to do more and more on vehicles. While the testing methodology has remained similar, conditions have been altered to accommodate these vehicle performance expectations. And while reducing testing time has always been a goal, many of these standard tests still require the same amount of time to conduct.

Because much of tyre testing has been standardised over the years, many facets of the industry can use tyre testing data as a unifying benchmark for evaluating specific performance criteria. For OEMs, the data is valuable to the vehicle development process. For tyre companies, the data is used in a marketing context to compare and contrast features for consumers. Trucking fleets use the data to optimise their operations and reduce costs and fuel consumption. Consistency in testing methodology provides the industry with a unifying foundation of benchmarking data.

That being said, older methods are always being reviewed for obsolescence. For example, NHTSA in the United States is currently considering the removal of test standards for bead unseat and plunger energy testing that were originally developed for bias ply tyre designs.

There are always efforts to look at novel ways of improving the tyre testing process and increasing speed to market. For example, experimenting with different surfaces for drum and belt testing of tyres continues to take place in an attempt to more closely replicate an infinite number of real-life surface conditions. Man-made snow has been developed to extend testing seasons and try to mirror natural snow in an indoor environment. As the industry learns more about how pressure loss impacts rolling resistance and fuel efficiency, more methods have been developed to measure how well different inner liner materials maintain steady tyre pressure. Tyre companies can more readily choose the right materials of construction to suit performance requirements by using material property data from finite element analysis.

Many of these testing methodologies are trending towards virtual testing and modelling of tyre performance. And while tyre modelling has been around since the 1980s, the amount of data and range of data measurement required has increased exponentially.

The key automotive trends driving tyre development going forward continue to be electrification and autonomy. These trends will bring their own challenges to testing and validation. Electrification will present some traditional challenges with new applications, such as managing heavier loads, more aggressive torque / tread wear, reducing noise, and lowering rolling resistance. New materials and constructions are being developed to accommodate these unique challenges for electric vehicles. Tyre tuning will become exceptionally important as second-life tyres are brought into the mix, as consumers will want consistent performance.

From the perspective of autonomous vehicles, sensors and tyre intelligence are being added to provide new data sources for autonomous systems. Tyres equipped with these sensors will have to undergo the same endurance, durability, and performance tests to ensure the sensor can function as designed when faced with the same rigors as the tyre. Depending on where the sensors are mounted in the tyre/wheel assembly, normal tyre dynamics could adversely affect the accuracy of measurements or transmission of data to the vehicle. As aftermarket tires and sensors are developed, testing and validation should follow the same standards to simplify service and compatibility for consumers. Ease of replacement will be critical, as this directly affects the consumer and dealers.

There will continue to be developments and ongoing efforts to improve the fidelity and range of tyre testing data. These improvements will strive to speed up development cycles and improve virtual models going forward. However, the established standards and protocols continue to provide a steadfast and reliable set of tools that development teams, independent evaluators, and testing organisations can use to address new challenges and ensure that the ultimate goal of safety is met for regulatory bodies and consumers.

Dr. James A. Popio is Vice President of Operations - North America of the Smithers Materials Science and Engineering division. Prior to his current role, he was Vice President and General Manager of Smithers in the United Kingdom. Before that, he was General Manager and Director of Engineering at Smithers' Tire and Wheel Testing Laboratory in Ravenna, Ohio.

Jim has worked with the tyre and rubber industry for 20 years and has spent his professional career working for and/or with tyre companies, tyre dealers, automotive OEMs, industry suppliers, manufacturers, standards organisations and government agencies. 

Jim has extensive experience in tyre performance, characterisation, and methods development. His specialty areas of expertise are force and moment, endurance, aging, compliance, indoor wear, rolling resistance, and characterisation for modelling. Jim is a regular contributor to industry journals as well as a chair and speaker at major tyre and rubber conferences. Jim has a PhD in engineering and MS, and BS in mechanical engineering from the University of Akron

Comments (0)

ADD COMMENT

Link Copied!

As commercial vehicle operators face mounting pressure from regulations, rising costs and the shift to electric power, Webfleet, a subsidiary of Bridgestone, is focusing on turning ever-growing volumes of vehicle data into practical recommendations that improve performance and ease the daily burden on fleet managers.

Founded in Leipzig in 1999 as one of the world’s first web-based fleet management platforms, Webfleet has grown from a pioneering software-as-a-service (SaaS) start-up to Europe’s leading solution and a core part of Bridgestone’s global offering. Today it serves drivers across more than 180 countries with AI-powered insights, electric-vehicle tools and sustainability data that turn complex operations into clearer, more efficient decisions.

In an exclusive interaction with Tyre Trends, Marc Notenboom, Director of Product Management at Webfleet, shares how the company has watched the fleet-management sector evolve over more than a quarter of a century. Interestingly, it was just last year the company marked its 25th anniversary.

From its inception, Webfleet has seen the volume of available data explode, yet the real challenge remains converting that information into meaningful guidance.

“Fleets give you more data but not more insights, which continues to be a challenge. Because of new regulations, new sensors, increasing competition and customer demands, we end up generating more data. We also have access to more data, which is growing exponentially. And then comes the real question, how do you make sense of that data?” Notenboom observed.

Marc Notenboom, Director of Product Management, Webfleet

Webfleet obtains its information through black-box devices installed in vehicles, sensors or direct connections to original-equipment manufacturers. This includes telematics, GPS, video, driver behaviour and vehicle diagnostics, among others. The company then processes that stream to deliver fleet-management services.

The next step, he explained, is moving beyond retrospective analysis. “Insights tell you what happened and why it happened, perhaps, but not what you need to do to improve your performance. That is what we are doing now with the help of artificial intelligence (AI). For example, we analyse data, see if patterns are different or you have anomalies in your data to predict what is happening or what is going wrong. And then we also use AI to analyse our data to see how you are performing, for instance, against competition. And then give customers suggestions on how to improve on certain topics like fuel consumption or driver safety,” he said.

The industry, in Webfleet’s view, is therefore evolving from raw data collection towards insights, recommendations and concrete actions.

SHARED PRESSURES ACROSS DIVERSE FLEETS

Webfleet serves a wide spectrum of customers, from large transport and logistics operators to small fleets of one or two vehicles, service-and-maintenance businesses and last-mile delivery companies.

Each customer faces distinct operational issues, yet common themes emerge. “What they all have in common is that the amount of data and the pressure to enhance their performance is increasing a lot. And then there is the regulatory compliance pressures as well,” said Notenboom.

Performance, in this context, covers delivery times, cost per kilometre, driver wages, safety and fuel consumption – metrics that matter differently according to the sector, but all that demand continuous improvement.

One of Europe’s most persistent difficulties is the shortage of skilled drivers, which has led to greater reliance on migrant workers whose experience of road conditions may vary widely between countries.

Webfleet addresses part of this challenge through tools such as OptiDrive, which shows fleet managers how individual drivers perform on fuel use and safety. Language barriers are tackled with automatic translation features built into the driver’s work app or tablet.

“They can interact with their fleet manager in their own language, and the fleet manager can also interact back in their own language,” explained Notenboom. The same interface delivers active coaching: if a driver exceeds the speed limit, for example, an immediate warning appears. These software-based interventions help maintain standards without requiring constant direct supervision.

MEASURABLE GAINS AND EV TRANSITION

Notenboom agrees that customers understandably scrutinise the return on any additional technology cost. He reported that Webfleet users typically achieve efficiency improvements of up to 15 percent, though results depend heavily on the starting point. This ranges from fuel savings, faster turnaround, downtime reduction or improved driver behaviour, among others.

“If a company is already really good at saving fuel, then adding tools and driver coaching and technology might not change a lot. At the same time, even if it’s a small improvement, especially with the high fuel prices today, it could already translate to a lot of savings,” averred Notenboom.

The arrival of electric trucks introduces a fresh set of complexities. Research indicates that driver behaviour exerts an even greater influence on energy consumption in electric vehicles than in conventional combustion models. Smooth operation becomes critical to range, while decisions about when and where to charge add further layers of planning. Webfleet supports the transition by helping managers determine the right vehicle for each duty cycle.

“If you do long-distance transport, electric trucks are perhaps not the best option. But if you do inner-city deliveries, then electric trucks become an interesting option. And trying to find out where the optimum is, when to use Internal Combustion Engine-vehicles, where to use electric vehicles, that is also a part where we can help the fleet manager to make that decision,” he said.

On the technology package itself, every Webfleet customer receives the software platform. Hardware can be selected according to need, or in some cases, dispensed with entirely through the OEM.connect service (access vehicle data directly from OEMs via APIs), without installing extra hardware that draws data directly from the vehicle manufacturer.

“A number of customers are preferring to use OEM.connect. So that is a solution where we don’t install hardware but take the data directly from the OEM offerings,” he explained. On the other hand, where original-equipment data fall short, Webfleet’s own devices remain available.

PRIVACY, BENCHMARKING AND THE ROAD AHEAD

Growing data volumes inevitably raise questions of privacy and regulatory compliance. Webfleet adheres strictly to General Data Protection Regulation (GDPR) – a strict European Union (EU) law that protects information privacy and data rights for individuals in the EU and the European Economic Area (EEA) – requirements.

Certain categories of information can be processed only with explicit customer permission, and for benchmarking purposes, the company anonymises data so that individual vehicles or fleets cannot be identified.

A recent example is Webfleet’s Commercial Trip Monitor, which aggregates anonymised information across the entire customer base to generate comparative insights.

Looking three to five years ahead, Notenboom identified three principal challenges for the commercial-vehicle industry: the practical difficulties of electrification, the continuing shortage of drivers (with autonomous vehicles potentially addressing certain use cases over a longer horizon) and relentless competitive pressure to deliver higher quality service at lower cost.

He regards these same pressures as sources of opportunity for those able to convert them into advantage.

Interestingly, he shared that Webfleet itself continues to evaluate new markets beyond its established presence in Europe, South Africa, South America and Australia. Bridgestone’s ownership of the US-focused Azuga platform complements the portfolio, while Asia-Pacific, including India, remains under active review even if no immediate plans have been confirmed.

As Notenboom puts it, the goal is not to simply collect more information but to translate that information into clearer decisions that keep vehicles productive, drivers safer and costs under control – regardless of whether the powertrain is diesel or electric.

Comments (0)

ADD COMMENT

Link Copied!

Vaculug has released VMS Pro Max, the next generation of its fleet management application. The product, developed over a three-year period, pairs a redesigned interface with AI-enhanced software intended to make commercial fleet management faster and more intelligent. The app is now available for download through the Apple App Store and Google Play Store.

The upgraded platform offers clear, real-time access to tyre and vehicle data, accelerates background report uploads to reduce driver time and allows measuring tools to be connected for automatic tread depth capture. It also incorporates an embedded VAN Driver Guide and can instantly flag vehicles left uninspected across 30, 60 or 90 days. Existing users must sync all pending inspections and confirm cloud upload before updating to prevent data loss.

Comments (0)

ADD COMMENT

Link Copied!

The Yokohama Rubber Co., Ltd. and dotData, Inc. have announced joint development an AI agent to help engineers form hypotheses, interpret findings and make decisions in manufacturing R&D. Before full deployment, the initiative will validate the agent's required capabilities and technical feasibility.

The solution combines technical documents such as design specifications and experimental reports with engineers' accumulated expertise and features extracted from measurement data via dotData's Signal Intelligence technology. It will provide insights tailored to each project's objectives, circumstances and constraints.

The agent is not meant to produce a single correct answer. Operating in a human-in-the-loop framework where engineers retain decision-making authority, it will present multiple possibilities, perspectives and risks to broaden thinking and support professional development.

Manufacturing R&D generates diverse data through experiments, simulations, production and evaluation. Developing hypotheses requires specialised knowledge and context. Since new technology R&D rarely has one predetermined answer, abductive reasoning plays a key role. AI can add value by using data and organisational knowledge to widen engineers' perspectives rather than replace judgment.

The agent will explore measurement and experimental data patterns beyond factors engineers previously identified, combining quantitative insights with design documents and expert knowledge to reveal difficult-to-spot relationships. It will offer input from materials, design, analysis, production and evaluation perspectives, challenge existing hypotheses and raise questions about alternative interpretations and conditions. Engineers will then test hypotheses and feed results back into further dialogue, guiding Signal Intelligence processes so non-specialists can explore data features as needed.

Yokohama Rubber has advanced HAICoLab since 2020, using dotData as a foundational technology in tyre design and rubber mixing. This joint development expands those efforts, with engineers interpreting and evaluating the agent's suggestions using their own expertise rather than accepting them unquestioningly. The companies aim to transform R&D processes while strengthening engineers' creativity and judgment, establishing a new model for human-AI collaboration in manufacturing R&D.

Motoji Fujita, Head of Research & Advanced Development Division, The Yokohama Rubber Co., Ltd., said, “Since 2020, we have conducted research and development under the HAICoLab framework, drawing on the complementary strengths of people and AI to create a collaborative environment. We believe AI agents will give engineers access to perspectives beyond their own experience and enable them to evaluate hypotheses from multiple angles. Through this development initiative, we aim to advance our R&D capabilities while supporting the continued growth of our engineers.”

Ryohei Fujimaki, CEO, dotData, Inc., said, “Success in manufacturing R&D depends heavily on an organisation’s ability to connect its proprietary data and knowledge with AI. The quantitative context generated from data through automated Signal Intelligence provides a foundation for AI agents to engage engineers in practical, data-driven discussions. Together with Yokohama Rubber, which has many years of experience in advanced data utilisation, we intend to establish standards for using AI in highly specialised business domains.”

Comments (0)

ADD COMMENT

Link Copied!

Bridgestone Aircraft Tire (Europe), a Bridgestone Corporation subsidiary, has announced the deployment of its ‘easytrack’ tyre management system at SR Technics Spain SAU, the tyre and wheel maintenance hub of global maintenance, repair & overhaul (MRO) provider SR Technics. The scalable digital platform is accessible on desktop and mobile devices.

Designed for airlines and MROs, ‘easytrack’ manages inbound and outbound tyre and wheel flows across single- or multi-site operations. It delivers real-time identification, tracking and documentation throughout each asset’s lifecycle. The project follows the solution’s first airline implementation in 2025, becoming its second customer rollout and first MRO application.

MRO providers handle large tyre and wheel volumes for multiple airlines, complicating operations. ‘easytrack’ simplifies asset management and improves traceability, accuracy, safety and productivity. At SR Technics Spain SAU, it digitalised paper-based processes, cutting processing time by 45 percent, reducing data-entry and identification errors and improving flow management across Palma de Mallorca and Madrid.

From left: David Sautois, ‘easytrack’ Product Manager, Bridgestone Aircraft Tire (Europe) S.A.; Antonio Colella, General Manager, SR Technics Spain SAU; Jean-Philippe Minet, Managing Director, Bridgestone Aircraft Tire (Europe) S.A.; Eugenie Baradzina, Commercial Director, SR Technics Spain SAU.

The results stem from a Bridgestone and SR Technics Spain SAU co-creation initiative built on long-standing partnership. ‘easytrack’ was adapted to support tyre and wheel combinations for the hub’s wheel and brake operations. Bridgestone’s expansion of airline and MRO solutions aligns with its E8 Commitment, emphasising efficiency and ecology.

Antonio Colella, General Manager, SR Technics Spain SAU, said, "The successful implementation of easytrack is a significant achievement for SR Technics Spain SAU and our teams in Mallorca and Madrid. From the very beginning, the collaboration with Bridgestone was built on trust, openness and a shared vision for innovation. Together, we have developed a solution that not only improves efficiency and traceability but also creates lasting value for our operations. We are proud to be the first MRO in the world to adopt this technology and look forward to continuing this journey with Bridgestone Corporation.”

Jean-Philippe Minet, Managing Director, Bridgestone Aircraft Tire Europe, said, “I’d like to thank SR Technics for their trust and another fruitful collaboration with Bridgestone. What the teams have jointly achieved is remarkable: co-creating through efficient teamwork and customising the Bridgestone easytrack application to digitise SR Technics tyre and wheel tracking operations. This is a brilliant example of how Bridgestone amplifies the value created at our partners.”

Comments (0)

ADD COMMENT

Link Copied!