A digital twin is a virtual model of a real-world object, process, or location that possesses all the design, performance, and operational characteristics of the real asset. The model is updated with real-time data and information from sensors, software, and connected systems to reflect its current state. This enables monitoring, analysis, and simulation of the functionalities, working condition, and health of the real asset. Additionally, the digital twin can capture and store historical data and information about the physical asset to evaluate past performance and identify patterns.
The concept of digital twins is used throughout the lifecycle of a vehicle. Digital twins can be employed during the design and development phases to simulate and optimise various aspects of the vehicle, such as performance, efficiency, and safety.
A digital twin may serve as a vehicle’s virtual prototype. Building a digital model enables engineers to simulate and analyse complex, costly, or dangerous processes with the aid of machine learning (ML) and artificial intelligence (AI).
Car manufacturers can take the data from the previous car model and reuse successful elements and reengineer parts that have performed suboptimally. Doing so can lead to a more streamlined engineering process and higher-quality vehicles.
During the development of Connected and Autonomous Vehicles (CAVs), digital twins are used to simulate real-life traffic scenarios. These simulations help road-test and evaluate the vehicle’s capabilities, responsiveness, and safety in different conditions. Once an ML/AI algorithm has been tested and proven successful in a simulated environment, it can be implemented in a physical prototype for further testing and validation.
In the product design and testing phases, anything from mechanical design to wind resistance, vibration tolerance, and noise generation to crash tests can be simulated on a digital twin.
Digital twins help to identify and address potential issues, optimise performance, and reduce costs and risks associated with physical testing and development processes.
A digital twin can also represent a digital replica of a vehicle after it has been manufactured and left the factory. Real-time data and interactions from the actual vehicle can be captured and transferred to the digital twin, allowing for monitoring, analysis, and simulation of its performance and behaviour. A car manufacturer Tesla, for example, creates a digital twin for each vehicle they sell.
A Complex Process
Building a digital twin is a complex process that requires capturing and incorporating various physical details and software components that make up the real vehicle. Details such as the vehicle’s design, specifications, components, systems, and operational characteristics are vital for the process. What’s more, data from sensors, connected systems, and real-time monitoring has to be integrated into the digital twin to accurately reflect the performance of the physical vehicle.
The benefits of creating a digital twin are significant, as it serves as a bridge between the physical and digital realms. Once created, a digital twin offers a range of possibilities for improving operations, maintenance, and future decision-making.
Until recently, pre-owned car buyers could only guess about the car’s condition. A used car with a digital identity helps with the tracking of its maintenance history thanks to a digital twin that has all the necessary information.
The use of digital twins enables car manufacturers to identify potential issues, test different scenarios, develop more efficient solutions, and drive innovation forward.
- Virtual twin
- Digital replica
- Virtual model