Increasing Fuel Economy with Improved Tire Design

Tire Engineering Solution

Like many other people around the world, I take a lot of pride in my car. My first car, a prized possession, added a lot of value to my life. Whether it be a daily commute to the office, family vacations, or long, leisurely drives, my car keeps up with me through the ups and downs of life. But what keeps the car going? Is it the luxurious cabin? The ride and handling characteristics? All these are true, however; the tire is also a very essential component to keeping my car going through the journey of life.

Day-by-day, fuel prices are rising around the world and international regulations on CO2 emissions are becoming more stringent. In 2015, 135 grams of CO2 per kilometer was the permissible limit of the vehicle. The target value by 2020 is 95 grams per kilometer.  Therefore, automobile manufacturers need to figure out how to improve the vehicle performance but also increasing the fuel economy. And SIMULIA can help!

Aerodynamic drag is one of the biggest contributors to the fuel economy of a car.  The higher the drag, the lower the fuel economy or range in terms of electric vehicles. So what is aerodynamic drag? Why is it so important to study the drag in the early stages of design?

Aerodynamic drag is the air resistance on the moving vehicle. Drag is mainly affected by three parameters of the vehicle: shape, size and speed. Every part of the vehicle contributes to the total drag, including the wheels and tires.

So why do we neglect the tires when they play such a crucial role? Did you know that the wheels can contribute to almost 25% of the total aerodynamic drag of a vehicle? A tire with better aerodynamic properties will not only consume less fuel, but will also have better acceleration capabilities, higher maximum speed, and increased driving range. Despite all of these advantages, so far tire designers have mostly thought about structural rigidity, rolling resistance and durability and have not done due diligence when it comes to the aerodynamic aspects.

Let’s now walk through the steps of designing a tire with improved aerodynamics:

  • Start with a ribbed tire in deformed position – you will get this as output of the footprint analysis performed using our simulation tools. This gives the realistic shape of the tire under deformation due to the weight of the car.
  • Then, simulate the ribbed tire for a 100 kmph speed using the ready-to-use template and plot the surface drag on the car with respect to position. Using the template reduces the setup for simulation from hours to just a few minutes. This way, we can calculate the drag as per the requirements from the WLTP regulations for CO2 emission.
  • However, as a caution while working on the above step, one can lose the drag details because of the tread pattern, therefore, at SIMULIA we provide capability for simulating a treaded tire to capture the details of tread pattern variation.

  • From the above figure, we can see that the ribbed tire, which is qualifying for WLTP regulation, actually underestimates the drag on tire versus the actual treaded tire.
  • The tire model that we have created is a parametric model. This allows to varying the tread patterns in CATIA and simulate them as well. We changed the tread pattern by changing the tread block height and width between the treads and calculated the drag forces for various configuration of tread patterns.
  • Our observation was that by simply changing the tread height and width between the tread blocks, the drag on the tires can be reduced by 2%, which leads to an increase in the fuel economy of the car.

In addition, this simulation of realistic tread gives confidence to tire manufacturers to design robust and fuel economic tires.

From the above demonstration, SIMULIA provides an excellent way to predict the drag of a tire using computational fluid dynamics in the early design phase. One can analyze the aerodynamic drag of different tire configurations for the same vehicle.  In addition, one can improve the tire performance by changing the tread patterns of the tires. This solution can facilitate not only tire manufacturers but also the automobile manufacturers to find the best suitable and most effective tire model for the car.

So sit back and enjoy the ride!

For more information, email: Ketan.GHOTKAR@3ds.com, Jonathan.Jilesen@3ds.com


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Katie Corey

Katie manages SIMULIA's social media, blog and online communities. As a writer and technical communicator, she is interested in and passionate about creating an impactful user experience. Katie is a native Rhode Islander and loves telling others about all it has to offer. As a self-proclaimed nerd, she enjoys a variety of hobbies including history, astronomy, science/technology, science fiction, geocaching, true crime, fashion and anything associated with nature and the outdoors. She is also mom to four amazing furbabies (2 cats and 2 dogs).

Deepak Goyal

Dr. Goyal is a Senior Technical Specialist, currently playing the role of simulation consultant in SIMULIA's Aerospace & Defense Industry growth team. He received his M.S. & Ph.D. degrees in Aerospace Engineering at Texas A&M University in August 2003 & December 2007 respectively. He is a recipient of American Institute of Aeronautics and Astronautics (AIAA) open topic graduate award in the year 2006. In academia, he has conducted extensive FAA, NASA & AFOSR funded research in tape laminated composites, textile composites & materials with complex microstructures. Since January 2008, he has been working with Dassault Systèmes SIMULIA Corp. where he has provided training & consulting services to SIMULIA’ s customers in various industries. Dr. Goyal has published several journal papers in highly reputed peer-reviewed international journals and has also reviewed scholarly articles of other researchers for leading journals in the area of Composites Materials.

One Response to “Increasing Fuel Economy with Improved Tire Design”

  1. t.muthusivasankar@apollotyres.com'

    Muthu Sivasankar

    May I know the computation time of this drag simulation?
    On how many cores and finite elements?

    Reply

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