. 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

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DUNLOP (company name: Sumitomo Rubber Industries) has confirmed that its proprietary SENSING CORE technology has been adopted for medium-duty truck models. The system, designed to detect the conditions of tyres, vehicles and road surfaces, is fitted to Isuzu Motors' FORWARD medium-duty trucks with a gross vehicle weight exceeding 14.5 metric tonnes, which come standard with the Wheel Detachment Prediction Detection System, one of the functions offered by SENSING CORE.

SENSING CORE is a software technology built on expertise gained from the Deflation Warning System, a tyre pressure warning system. It analyses wheel speed data generated by tyre rotation together with controller area network data transmitted through the vehicle's control system, allowing it to detect various tyre and road conditions, including tyre pressure, wear, load and signs of potential wheel detachment. The Wheel Detachment Prediction Detection System in Isuzu's FORWARD models detects loosening of wheel nuts while the vehicle is in motion, alerting the driver through a warning message and buzzer if an abnormality is found.

This capability complements conventional inspections and driver experience and is expected to play a significant role in preventing wheel separation accidents. Isuzu's FORWARD is a medium-duty truck with a broad lineup designed to meet diverse logistics industry needs, and such trucks are widely used in local delivery, long-haul transport and building and construction operations, serving as a vital means of transportation.

Operated across urban areas and major highways, wheel detachment accidents involving these trucks could cause serious harm to third parties such as pedestrians and cyclists, driving growing societal demand for improved safety. Preventing such accidents requires fundamental inspection and maintenance measures, yet drivers find it difficult to detect loosening wheel nuts while driving, making early-detection technologies essential. The provision of the Wheel Detachment Prediction Detection System to medium-duty trucks enables early detection of signs of vehicle malfunctions and contributes to further improving safety and preventing wheel detachment accidents.

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SYMX.AI, a developer of artificial intelligence technology for mobile industrial equipment, has raised USD 6 million in Series A financing led by Ascent Capital Partners and agreed a global technology and commercial partnership with Yokohama Off-Highway Tires.

The Canadian company develops software and hardware for mining, construction and forestry operations. Its platform provides connectivity in areas without network coverage, integrates data from equipment made by different manufacturers and supports fleet optimisation.

Its products cover dispatch, fleet management, enterprise asset management and tyre life management, as well as equipment health, fuel consumption, haul road intelligence, inventory and operator performance. The company also holds patents covering its internet of things and AI technologies, including a patent for its “Greenhouse Gas Emissions Data Collection and Cross-Validation System”, granted in 2026.

SYMX.AI has also launched an AI-powered inspection platform and a chatbot for industrial operations.

“Physical AI has been struggling in mining for simple reasons. The machines are mobile, mixed-fleet data is vendor-locked, and most of the industry has limited to no network coverage. Intelligence needs a body and a nervous system before we deploy a model. Even today, assembling that foundation takes seven or eight vendors and up to twelve months. We deliver it in a week. We built the hardware and the connectivity first, which is why our AI layer delivers real results. I am glad that capital is finally flowing to atoms again, and mining will finally get what it has long deserved,” said Ash Agarwal, CEO of SYMX.AI.

Technology tested in mining operations

SYMX.AI said it had validated its technology through projects across the mining value chain. At Glencore's Onaping Depth project in Ontario, Canada, the company demonstrated battery monitoring, short-interval control and fleet optimisation for battery-electric vehicles.

“The problem SYMX.AI solves is foundational,” said Peter Xavier, Chief Operating Officer of Canada Metals, a Glencore company. “Connectivity and cross-OEM data integration at the point of work are infrastructure gaps the mining industry has struggled with for decades, but SYMX.AI changes the paradigm. Our proof-of-concept validation of the SYMX.AI platform on our OEM BEV equipment successfully supports underground short-interval control, battery monitoring and fleet optimization. This level of integration and insight is exactly what the industry needs to move forward.”

Global partnership with Yokohama

Under the partnership, Yokohama Off-Highway Tires will offer the integrated hardware and software platform to customers through its international commercial network. SYMX.AI will supply the internet of things hardware, connectivity, cloud platform and intelligence capabilities.

Customers will be able to adopt the technology as a standalone tyre intelligence solution or as part of a broader fleet optimisation platform.

“The tyre technology market is crowded with TPMS providers, but most systems monitor pressure and temperature while offering little insight beyond those measurements. Operators are asking a more important question: can the same system help us increase production, protect valuable assets such as tires and reduce fuel consumption? SYMX.AI has built a complete platform that addresses this market need by connecting tire condition with equipment performance, haul road conditions and operator behavior. This helps sites reduce costs, extend tire life and improve overall fleet performance,” said Loïc Ravasio, President of Yokohama Off-Highway Tires. “By working with SYMX.AI and offering flexible business models, Yokohama OTR is becoming a true digital partner to the industry, helping customers optimize their operations.”

Expansion and investment

SYMX.AI is expanding its product range with an AI-driven dispatch and fleet management system and an enterprise asset management platform based on live machine sensor data and fault codes.

The asset management system combines equipment health monitoring, diagnostic alarm management, oil analysis and work order management. The company says the system is designed to reduce reliance on fixed maintenance schedules and manual data entry.

Its products integrate with AVEVA Connect, SAP, Oracle and existing data historians, allowing operators to add the technology without replacing their existing systems.

The company said it supported open-pit and underground operations in Kazakhstan, the US, Mexico, Europe and Asia.

“We have watched this team for three years demonstrating grit, perseverance, and commitment. They build things that work in places most software never reaches, and the customers keep renewing worldwide. That is rare in this industry. The comprehensive IoT, connectivity, and AI app layer is deployed at difficult sites, and I’m glad that the market is finally catching up,” said Jonathan Loeffler, Co-Founder and Managing Partner of Ascent Capital Partners.

The financing will support international deployment, development of the AI platform and a broader range of wireless communication products, SYMX.AI said.

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Anyline, a global leader in mobile AI and intelligent data capture technology, has rolled out version 1.9 of TireBuddy, featuring a redesigned inspection report that aims to help customers more easily understand the condition of their tyres and place greater trust in technician recommendations. The updated report is intended to make the information gathered during an inspection simpler for customers to digest.

The report presents tread depth, tyre age and estimated braking distance to convey overall tyre health, while make, model, size and seasonal markings identify exactly which tyres are mounted on the vehicle. The new version also allows technicians to attach images of sidewall and rim damage to the report, transparently documenting issues that require attention so customers can have confidence in the recommended work.

Technicians can now record rim and tyre damage, such as scratches on rims and bulges on sidewalls, during the inspection workflow and display it in the report. Photo evidence of rim and sidewall damage can be attached to technician notes and added to the report. A not-roadworthy flag can also be set for a tyre with healthy tread depth but other serious defects, showing in the report as recommended for immediate replacement. All existing and new elements continue to fit on a single page, which can be saved as an image or PDF for sharing with the customer.

The TireBuddy report addresses a critical issue for workshops by ensuring customers fully understand inspection findings. Verbally conveying such information is not always easy, and traditional inspection forms tend to be dense and text-heavy. Everything a technician finds in the bay needs to be detailed in the report the customer sees, which should serve as visual support for service recommendations. With version 1.9, evidence appears alongside the recommendation, and photos of tyre or rim damage are inserted with other tyre information so customers can recognise findings without entering the bay.

Damages are categorised alongside visual evidence, so a bulge is recorded consistently regardless of technician, location or shift, turning individual reports into a comparable record that still captures the state of every tyre on the inspection day. From version 1.9, every report can carry damage, roadworthiness and photo evidence alongside the tread reading. Smaller changes include an optional pair replacement setting that automatically marks the paired tyre on the same axle for replacement when one tyre is not OK, up to 10 custom fields per account in the vehicle identification step for work order or storage numbers and a redesigned vehicle identification screen consistent with the tyre identification screen.

Lukas Kinigadner, CRO, Anyline, “Every replacement recommendation is a request for trust. With 1.9, the technician doesn't have to ask for it. The damage is on the report, photographed, next to the tyre it belongs to.”

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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.

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