How Digital Twin Technology is Disrupting the Automotive Industry

Marcin Kłoda, CTO, intive

Marcin Kłoda, CTO, intive

Digital twin technology is creating nothing short of a revolution in the automotive industry, advancing unprecedented levels of efficiency and accuracy in both design and development. While this technology has been present in the manufacturing sector for a while, the advent of innovations such as the Internet of Things (IoT) and the growing trend of connected cars mean the time is right for digital twins to fully establish itself in the automotive production process. And rest assured, it’s a trend that’s certainly growing: The market is set to grow from $3.8 billion in 2019 to $35.8 billion by 2025, at a CAGR of 37.8%, according to the Markets and Markets research report.

Before we dive into the benefits of this technology in automotive, let us first define exactly what it means to create and use the digital twin of a product.

What is digital twin technology?

Digital twin is not a single technology, rather a concept that combines multiple technologies such as IoT, 4G/5G, blockchain, big data, edge computing, cloud computing, artificial intelligence (AI), and 3D simulation. The core principle is to create an exact virtual replica of a physical product that allows manufacturers to test and monitor certain updates and developments in real-time, without needing to perform these on the real thing.

Manufacturers can gain insights into the disparate data sources that digital twin technology connects, resulting in greater operational efficiency and improved productivity in areas such as supply chains and deliveries. The technology makes it possible for manufacturers to see clearer the state of their operations, machines, and separate parts of products ranging from cars to airplanes, and use this to flag maintenance issues or to avoid downtime.

So, how is digital twin technology causing a stir in the automotive industry?

Digital twin tech in automotive

With the advent of IoT and the cloud, cars are now a source of real-time data. By having access to all this data, carmakers can understand how their products are operating and make improvements in design, efficiency, and manufacture faster than ever before. In the design and production process, manufacturers can test, monitor and refine aspects of the vehicle design such as its material, functions, configuration, parameters, and appearance. They can also make sure that the product prototype is aligned with the manufacturer’s desired performance through simulation tests.

"Manufacturers can gain insights into the disparate data sources that digital twin technology connects, resulting in greater operational efficiency and improved productivity in areas such as supply chains and deliveries"

The capabilities of digital twins continue throughout the whole lifecycle of the car. The historical and real-time data that is constantly fed to the digital twin allows for predictive analytics capabilities that help manufacturers to make future predictions on performance and problems such as breakdowns. This also means they can proactively contact end users to make plans for repairs or maintenance. Ultimately, this does not only extend the life cycle of the car, but it also helps it run more accurately, reducing accidents and saving lives.

Tesla is leading the way

The current industry leader in digital twin technology within the automotive sector is undoubtedly the electric vehicle manufacturer, Tesla.

Every car that Tesla produces has a digital representation in the cloud that is connected to the physical car and its multiple sensors. The digital twin uses the data it receives in real-time from the individual car to update software accordingly. For example, a rattle in the door of a certain car can be rectified by a software update that adjusts the hydraulics of that particular door.

Tesla uses digital twin technology throughout the entire design process, enabling designers to understand how the car will work before the physical model is created. Assemblers are able to visualize how the car is assembled, for example, helping to mitigate problems during the production process.

After purchase, Tesla adapts cars by sending relevant updates through the vehicle’s digital twin. By using car data to drive the software development process, Tesla is able to better allocate resources and significantly improve the user experience for the vehicle owner. For example, the cars are made to adapt to the conditions in which they are running, so cars sold in warmer climates will run differently than those sold in a colder geographical area.

A great demonstration of this was when Tesla released more battery power to users that were in the path of Hurricane Florence. The carmaker sent this notification to drivers that were in danger of being hit by the hurricane:

“We are temporarily enabling your car to access additional battery capacity, as well as free Supercharging, in preparation for Hurricane Florence. We hope this gives you the peace of mind to get to a safe location, and will notify you before returning your car to its original configuration in mid-October. Badging on your display may adjust during this period. Safe travels.”

Others will follow suit

Other industry giants such as Volkswagen are starting to leverage the technology, with the German carmaker recently combining digital twin technology with virtual reality (VR) functionality to create virtual versions of their cars to enable better technical development.

While we can’t yet see widespread adoption of the technology, which has arguably barely tapped into its full potential, there is no doubt that the rest of the automotive industry will follow suit and incorporate digital twins into their manufacturing processes. The benefits of such a technology to carmakers make it difficult to envisage a situation in which they would not jump at digital twin adoption at the first chance.