What is digital twin technology

As the name suggests, it refers to constructing an identical virtual thing in the digital world through digital means for things in the real physical world. This virtual thing is like a twin brother of the real thing, with the same "shape" and "state".

The main function of presenting real things in virtual space in a digital way is: you can manipulate virtual models in virtual space, observe and study changes in virtual models, and thereby simulate and predict the behavior of real things in real environments. Change patterns.

The core of digital twin technology

Digital twin technology is developed from simulation technology. Simulation technology has been used on a large scale in the last century, but the concept of digital twin technology was not proposed until 2002 by Professor Grieves from the United States. Among the top ten strategic technology development trends released by Gartner every year, digital twin technology has been on the list for many years in a row as one of the key technologies for intelligent manufacturing.

The core element of digital twin technology is the establishment of digital models. Modeling methods can generally be divided into two categories: first principles or physics-based methods, and data-driven methods; practical applications are often a combination of various modeling behaviors and modeling methods. A good model can not only describe the external shape of real things realistically, but also accurately reflect the internal changes of real things.

Closely related to digital models are data and algorithms. Data is the input of the model. They may come from real-time collection of various sensors, or they may come from the past historical accumulation of the system. The algorithm is usually based on deep learning. Through the analysis and processing of a large amount of historical data, the internal processing logic of the model is continuously established and improved. After the real-time data is input into the model, the algorithm analyzes and processes the data, and then performs operations based on the established internal processing logic. Make judgments and then control the model to make corresponding changes.

Digital twins help the automotive industry

Digital twin technology can be applied in all walks of life. Specifically in the automotive industry, it can be used in all aspects of the industry chain such as R&D, manufacturing, sales, and after-sales. , for example:

R&D stage

In today’s increasingly competitive automotive market, bringing better products to the market at less cost and faster is all The ideal state that all OEMs aspire to achieve. With the help of digital twin technology, designers can test, verify, and optimize their product designs in virtual space, and implement product iterations quickly and at low cost. Dassault, a French software company, uses its CAD and CAE platform 3D Experience to accurately analyze and simulate aerodynamics, fluid acoustics and other aspects, optimizing product designs for BMW, Tesla, Toyota and other automobile companies, significantly improving their product design. The product is streamlined and reduces air resistance.

Manufacturing Phase

Production process simulation. Before product production, virtual production can be used to simulate the production process of different products, different parameters, and different external conditions, so as to predict production capacity, efficiency, and possible production bottlenecks in advance, and accelerate the introduction of new products. process.

Digital production line. Integrate various elements of the production stage, such as raw materials, equipment, process recipes and process requirements, into a closely coordinated production process through digital means, and automatically complete operations under different combinations of conditions according to established rules. Realize an automated production process; at the same time, record various data during the production process to provide a basis for subsequent analysis and optimization.

Key indicator monitoring and process capability assessment. By collecting real-time operating data of various production equipment on the production line, we can realize visual monitoring of the entire production process, and establish monitoring strategies for key equipment parameters and inspection indicators through experience or machine learning, and promptly handle and handle abnormal situations that violate the strategy. adjustments to achieve a stable and continuously optimized production process.

Sales stage

In the car sales process, with the help of digital twin technology, combined with VR/AR, it can provide users with an immersive experience, allowing users to control and drive the car in the virtual space. Comprehensively experience the performance and charm of cars in various environments and scenarios, and stimulate users' desire to buy cars.

After-sales stage

Tesla creates a digital twin model for every electric vehicle it produces and sells, and the corresponding model data is stored in the company's database. Each electric vehicle reports on its daily experience every day, and this data is used through the digital twin’s simulation program to detect possible anomalies and provide corrective measures. Through digital twin simulation, Tesla can obtain the equivalent of 1.6 million miles of driving experience every day and provide feedback to each vehicle in the continuous learning process.

Problems in practical applications

Digital twin technology paints a beautiful vision for us, just like what is shown in science fiction movies: a bunch of digital models are placed before us In front of us, we drag and drop, and then magical things can happen. However, in reality, digital twin technology is in an embarrassing situation: it is afraid to use it in key and core places, but cannot afford to use it in less critical and core places.

The reason is that it is difficult for us to establish a numerical correspondence for real things that can fully reflect all its characteristics and laws.

Things in reality run in a complex environment, and an overlooked detail may lead to serious consequences. Just imagine, in that life-threatening scenario, who dares to leave their fate to a bunch of digital models to decide? We may never even be able to simulate the real thing 100%, only a high degree of approximation. In order to pursue the last few percent of perfection, people often have to pay a huge price.

In the future, with the advancement of technology, the fidelity of simulation will become higher and higher, and the cost will become lower and lower. At that time, digital twin technology will truly exert its power. But at present, we need to see the prospects of this technology, and we must start planning and invest human and financial resources in research and practice.

In China, some companies are already researching and applying digital twin technology. However, similar to the situation in other technical fields, we favor and are good at the integration and application of technology. However, few people are willing to invest in research and development of the underlying platforms and tools that the technology itself relies on. Basically, they are directly used directly from foreign countries. "Don't reinvent the wheel" is a popular saying in the IT industry. But in today's international situation, you have to be able to make the key wheels yourself. Otherwise, if others don't sell you the wheels, you will have problems. We should support and guide R&D investment in underlying basic platforms and tools, rather than being only interested in the integration of technology applications that can be quickly monetized.

This article comes from the author of Autohome Chejiahao and does not represent the views and positions of Autohome.