Hannover, Copenhagen 10. December 2020. Continental has successfully demonstrated real time tire tread depth monitoring in a pilot that entailed electric vehicles of carsharing provider SHARE NOW Denmark. In cooperation with its project partner and telemetry specialist Traffilog, the premium tire manufacturer connected information of tire sensors and telemetry data of the fleet’s cars with a proprietary algorithm in the cloud. As a result, Continental can predict tire tread depth in real time with an accuracy of below one millimeter. In future, smart digital tire solutions like this will be a key driver to enable need-based servicing of tires, instead of regular, scheduled servicing. ”With this pilot we are first in the market to offer significantly accurate tread depth monitoring via an algorithm. With an accuracy of below one millimeter our pilot has in fact set an industry benchmark in smart digital tire solutions”, said Tansu Isik, Head of Business Development and Global Marketing at the Continental Tires business area. He added: “We have worked very closely with our Continental Automotive Technologies colleagues as well as with our partner Traffilog to achieve this success.”
For fleet providers it is beneficial to have as accurate information as possible about the condition of their tires at any time. Tire wear and damage is an important cost driver for them. Moreover, intact and maintained tires have notable positive influence on other major cost positions such as fuel efficiency and wear of parts. “Real time, telematic based tire monitoring is a huge benefit for us. We can monitor and service our tires at any time and take actions proactively”, said Steen Herløv Andersen, Head of Operations at SHARE NOW Denmark. Benefits are more efficient fleet operations, minimized downtime due to repair, greater safety and reduced overall cost due to higher energy efficiency.
“With this pilot we offer another glimpse on the future of Continentals smart digital tire solutions. Connecting tires directly to the cloud allows Continental to create exciting new business models. Our digital ecosystem for tires, in which we work together with our broad network of partners, is all about assisting our customers with tires and service at the right time and in the right place”, said Isik. He added: “At Continental we are leveraging on both, our tire expertise and our in-house know-how about sensor- and vehicle architecture, which is provided by Continentals Automotive Technologies group sector.”
Continental has a strong track record in supporting both commercial and passenger car fleet operators to run their fleets more efficiently. At the same time, the technology company is one of the biggest automotive suppliers worldwide. This unique setup of Continental had a decisive impact on the success of this pilot: The expertise of Continentals Automotive Technologies group sector in vehicle architectures and telemetry was the basis to develop, train and validate the algorithm inhouse. The same holds true for the tire sensors used, which also were designed and produced inhouse at Continental, specifically to meet project requirements. “Because of our set-up, we have all the specialists we need in-house. This means short distances to get things up and running. That is a true competitive advantage. This pilot is one sample for Continentals intensive efforts to develop customer centric tire solutions, based on their specific needs to increase efficiency, reduce costs and increase safety.” explained Isik.
The real time tread depth measurement pilot is part of a bigger project in which Continental together with its partner Traffilog also delivers real time remote tire pressure and temperature monitoring of the entire fleet of SHARE NOW in Denmark, with approximately 600 cars currently in operation. Continental was able to integrate its real time tire monitoring solution into an already existing telematic setup. To enable both capture and transfer of data, Traffilog modified its telematic unit to fit Continental’s requirements to harness the relevant data to feed its proprietary algorithm.