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For the past 175 years, the bulk of tyre innovation has focused on improving the structure and composition of the tyre itself (as discussed in our recent blog). However, manufacturers are always looking for new ways to optimise tyre design and performance, hence the growing focus on tyre sensing and the emergence of so-called smart tyres.

A racing start

Like many burgeoning automotive technologies, the first tyre sensors were established in Formula 1. Under the strain of race conditions, the main obstacle facing the first sensors was their tough operating environment.

Sensitive electronics are not ordinarily suited to temperatures over 100 ºC, nor to absorbing significant impacts and withstanding the huge centripetal forces acting on the tyre. In fact, the centripetal force resulting from the wheel’s rotation is such that a 10 g sensor has an effective weight over 30 kg when travelling at 200 mph.

The design of the pressure sensor itself is therefore of paramount importance. The pressure sensors work by measuring the amount of deflection in a carefully calibrated diaphragm - the more deflection the more pressure. For tyre applications, the shape of the diaphragm is specially designed to deflect only with changes in tyre pressure, and not with tyre rotation or tyre impacts. 

The amount of deflection can then be quantified by a change in the diaphragm’s properties, for example by measuring the resistance, resonant frequency, or capacitance of the diaphragm material. For today’s systems, capacitance is favoured as it is the least power hungry.

Physical challenges aside, the formative tyre pressure monitoring systems (TPMS) were developed solely with speed in mind. Race teams could leverage the tyre pressure data they captured to better understand the demands on a tyre through corners, on different surfaces, and to see how the tyre wore between pit-stops. This relatively primitive data was used by teams to get the most out of the tyres on the track, and by manufacturers to develop the best tyres for the track.

Although track racing and road driving may seem poles apart, many of the objectives of tyre advancement are applicable to both. Reducing braking distance, improving grip, and increasing tyre longevity are as useful in improving road safety as they are in shaving milliseconds off lap times. Indeed, even improved fuel economy has its place in racing, as reduced weight and fewer pit-stops can give teams a competitive edge.

It is no surprise then that tyre sensing technology speedily transitioned from top level racing to more sedate road use.

On the road

For road travel, the safety benefits of TPMS are deemed so significant that the technology has been compulsory on all new EU vehicles since 2012. As a result, there is a huge amount of tyre pressure data available, with new data being generated continuously.

Improved sensors with better accuracy and higher sample rates are accelerating the growth and increasing the quality of this data mountain. In particular, taking measurements more frequently facilitates the study of how pressure changes over time, and even throughout a wheel’s rotation. Combined with information about vehicle type, weight, speed and acceleration (to name a few), and multiplied across millions of cars globally, this offers a rich data pool which is ripe for analysis.

Nonetheless, this valuable resource has historically been left untapped - as the vast majority of the data is not recorded or, at best, is only recorded locally.

As a result, tyre brands are partnering with Big Tech to ‘export’ and ‘exploit’ the data from vehicles. Bridgestone, one of the world’s largest tyre manufacturers, has recently partnered with Microsoft to expand the ‘Microsoft Connected Vehicle Platform’ to start bulk collection of tyre data (see the press release).

One of the key drivers for this technology has been the rise in autonomous vehicles. While a driver can quickly recognise and respond to a flat tyre or blow out, based on feel, an autonomous vehicle needs some kind of sensor output to recognise if there has been a malfunction, and to respond accordingly.

Elucidating this information from tyre pressure data in real time has been made possible by analysis with artificial intelligence (AI) and machine learning algorithms. Combining the data from vehicles around the world enables software to draw-out patterns indicative of a range of tyre conditions and malfunctions.

Bridgestone claim that their tyre damage monitoring system can detect internal and external tyre damage, and immediately alert the driver (or indeed the autonomous vehicle itself) of the problem. Such damage could otherwise only be detected by close, manual inspection, which is obviously not practical while driving.

Looking forward, Bridgestone and Microsoft aim to capture when and where tyre damage occurs. This information could then be used to inform authorities of accident hot spots and road defects such as pot-holes. These data points could even be redistributed to other vehicles to assist in avoiding pot-holes and the resulting damage. 

Reinventing the wheel 

Aside from using tyre data for immediate feedback, this data can also be leveraged in the development of the next generation of tyres, for the next generation of vehicles.

As electrical vehicles (EVs) grow in prevalence, the market for EV specific tyres is also growing. Most current EVs use the same tyres as their internal combustion driven predecessors, but as our understanding of EV usage and performance evolves it is becoming clear that this is suboptimal. 

EVs are generally heavier than petrol vehicles, due to their large battery packs. This higher weight affords more traction at low speed which, combined with the instant torque available from electric motors, can put enormous strain on a traditional tyre’s side wall. Increasing tyre rigidity to withstand the weight and acceleration is an important development area. 

There is also more emphasis on reducing high speed rolling resistance, as the range between recharges is more crucial than for re-fillable petrol cars. Noise is also a key consideration, as the lack of exploding petrol means the tyre noise is more noticeable to occupants (but perhaps quite useful for pedestrians). 

Taking all these factors into account, tyre data collected from existing EVs can be used to inform advances towards specialist EV tyres.

In the driving seat

Another key factor to learn from is how people drive, and how this can be used to improve their driving experience and overall vehicle efficiency.

The “Pirelli Cyber Car” system (see the press release) uses tyre mounted sensors to determine how you drive and to interpret road conditions. This information is then returned to the car’s own braking, traction control and engine management systems, to ensure the car performs optimally for you and for the road.

This data can also be collated to offer personalised car and tyre maintenance plans. Clearly a ‘boy racer’ will need more frequent tyre changes than a more cautious driver. Likewise, tyres used exclusively in a city will wear less quickly than tyres used primarily for motorway miles. Continental have brought this automated functionality to commercial vehicle fleets with ContiConnect - enabling monitoring of tyre pressure and wear remotely, so that vehicle maintenance can be consistently and centrally controlled.

Rolling up

Advances are always needed to keep ahead of the rapidly evolving automotive market, be it electrification or automation, and to offer exciting personalised services to companies and consumers alike. Liberating and leveraging existing tyre data from the world’s smart tyres is invaluable in making the next generation of tyres even smarter.

Niles is a trainee patent attorney working in the chemistry field. Niles has an MChem degree in chemistry from the University of Oxford. His undergraduate research project was on the synthesis of novel perylene diimide containing macrocycles for anion recognition and sensing applications.
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