Digital Twins for Next-Generation Electric Vehicles

June 6, 2023
Digital Twins for Next-Generation Electric Vehicles

Digital Twins concept has swiftly become a game-changer in many industries, including automotive. In simple terms, a digital twin is a virtual replica of a physical object or system

In the context of electric vehicles, this could be a digital model of the vehicle components, the battery system, or the entire vehicle itself. The idea is to digitally replicate the real-world scenario to enable real-time monitoring, simulation, and optimization.

This blog discusses how digital the applications of Digital Twins in electric vehicles (EV) and how it helps in developing the next-generation EVs.

Let’s start with the applications.

Application of Digital Twins in Electric Vehicles

Unlike traditional vehicles with ICE engines, EVs have a far more complex infrastructure. For instance, there are countless wiring interconnecting each system within the vehicle. And not to mention the new production process that needs to be adopted to build an EV.

All these mounts up the challenges manufacturers have to overcome to make EVs efficient and effective. And where complexity rules, Digital Twin conquers.

We will discuss the challenges manufacturers face in designing, production, and testing and how digital twins can help overcome them.

Designing Process

Designing is a crucial step in building an efficient EV. Manufacturers need to consider factors like aerodynamics, battery efficiency, structural integrity, and more. But the key challenge is to achieve optimal energy efficiency.

Designing Process

Source: Digital twin for battery-operated EV and data exchange

Designers must balance battery capacity, vehicle weight, and aerodynamics to maximize an EV's range. Furthermore, they need to simulate and understand the impact of each design on energy efficiency.

This is where Digital Twin comes in.

With a digital twin in the designing process, designers can create a virtual replica of the product, EV. Then, they can experiment on the model with different design elements, simulate their impact and optimize it accordingly. This way, designers can save time, resources, and money. Also, it ensures that the design is energy efficient before building a physical prototype.

Production Process

The production process of an electric vehicle also poses challenges. The assembly of EVs is different from traditional vehicles and requires new skills and technologies. Also, it is difficult to ensure quality and efficiency while maintaining production speed.

The application of Digital twins in the production process can help here.

Source: Digital Twin of the Manufacturing Process (DTMP)

A Digital Twin in production allows manufacturers to make a virtual replica of the production process. This way, they can simulate the assembly process and identify any potential bottlenecks or inefficiencies.

It can also help train their staff by providing a virtual environment that mirrors the real production line. Additionally, the digital twin can monitor real-time production, identify anomalies, and predict potential issues before they cause significant downtime. This proactive approach significantly enhances overall production efficiency.

Testing Process

Testing an EV involves verifying the functionality and safety of its various components. This includes the battery system, motor, and onboard software. Real-world testing can be time-consuming and costly, with potential risks.

By using digital twins in testing, engineers can simulate an EV's operation under various conditions. This will help uncover potential problems without the need for multiple physical prototypes. They can also simulate extreme conditions, which are expensive and hard to physically replicate.

Source: Towards the future of smart electric vehicles: Digital twin

In addition, digital twins allow engineers to integrate real-world data into simulations. Doing so offers insights into how an EV will perform under different driving conditions, helping them build more reliable vehicles.

Contributions to Performance, Safety, and Efficiency

Performance

Digital twins are a virtual doppelganger of the actual EV, capturing its every feature and behavior in real-time. And when an EV is on the road, the digital twin collects and processes data from various sensors in the car. This allows us to monitor its performance and identify areas needing improvement.

For example, with a digital twin, we can precisely observe the electric motor's energy usage or the effectiveness of regenerative braking.

Safety

Safety is paramount when it comes to vehicles. In fact, safety is the second most influencing factor that consumers consider while buying a vehicle.

Source: Chart: Most Important Factors When Buying a Car | Statista

Before an EV model hits the roads, manufacturers can simulate its Digital twin in various driving conditions and scenarios. These include extreme weather conditions, collision scenarios, or challenging terrains. This allows us to identify potential safety issues and preemptively resolve them.

Efficiency

If we go back to the graph that shows the factors that influence consumers while buying a vehicle, we will notice that above all comes efficiency. And Digital Twins can significantly improve this.

During the design phase itself, manufacturers can optimize every component of the vehicle. The components can be anything from aerodynamics to energy consumption. They can simulate countless scenarios to assess the impact of different factors on the vehicle's efficiency.

For example, digital twins can help determine the most efficient battery configuration or find out how to reduce energy loss while driving.

Also, digital twins can help reduce the total cost of ownership of electric vehicles. They can help predict when maintenance is needed, avoiding costly breakdowns and extending the life of the vehicle.

Now that we have learned about the application of digital twins in electric vehicles let’s see their role in next-generation EVs.

Role of Digital Twins in Next-Generation EVs

The landscape of personal transportation is changing dramatically, and the forefront of this is EVs. The sales share forecast in the US given below will give you a better idea of how the market is changing.

Source : EV Sales Forecasts | EVAdoption 

The 'next generation' of electric vehicles promises a shift toward cleaner and renewable energy. They will also bring a host of advances, including autonomous vehicles and smart grid integration. And they can promote even more sustainable production methods. 

Digital twins play a critical role in realizing this next generation of EVs and will shape the future of the automotive industry. Let’s look at some of the ways Digital Twin can enable next-generation EVs. 

Autonomous Driving

Digital twin in automobile sector plays an essential role in developing autonomous driving. By creating a complete digital replica of an electric vehicle, engineers can 

  • Simulate various driving conditions

  • Test the car's responses

  • And gather valuable data [Without risking real-world assets]

The digital twin can mimic the behavior of the real vehicle in countless scenarios. As a result, it can predict the vehicle's response to a wide range of situations. Thus, the necessary adjustments and improvements can be made digitally before they are done on the actual vehicle. This accelerates the development of autonomous vehicle technology while ensuring safety. 

Smart Grid Integration 

Source: Interaction between EVs and the smart grid 

The electric infrastructure is evolving, making the integration of EVs with the smart grid crucial. Digital twins in EVs can communicate with the grid's digital twin, paving the way for more efficient two-way interaction between the grid and vehicles. 

For instance, information about an EV's battery status and charging schedule could be shared with the smart grid. This enables optimal power distribution based on vehicle usage patterns and grid capacity. 

Such interaction can help balance the load on the grid and reduce energy waste. Also, it can promote the efficient use of renewable energy resources. 

Predictive Maintenance

A significant advantage of using digital twins in EVs is the ability to predict maintenance needs. The digital twin can monitor various aspects of the vehicle, such as battery health, brake wear, etc., in real-time. 

By analyzing this data, the digital twin can anticipate potential problems before they become serious. For instance, if the digital twin detects declining battery performance, it can warn the owner or maintenance service. This allows them to prevent unexpected failures and extend the overall lifespan of the EV. 

Learn more about predictive maintenance

Moreover, digital twins can support green manufacturing practices. Manufacturers can experiment with different materials and production methods with a digital twin. This allows them to test each vehicle model in a risk-free virtual environment. 

For example, an automotive company can test the performance and durability of a vehicle if it uses sustainable materials instead of conventional materials. 

The role of digital twins in the next generation of EVs is profound and multifaceted. As technology continues to evolve, the role of Digital Twins in electric vehicles will expand. In fact, it might become a key driving force in the evolution of the automotive industry.

This brings us to the future of digital twins in EVs. 

Future Outlook

According to a study by Statista, the value of digital twins in the automotive industry is growing steadily. The market value of digital twins in automobiles is set to hit 5 billion USD by 2025. So, I don't think I need to push how important the tech is.

Source: Global digital twin market by industry 2025 | Statista 

The digital twin could revolutionize the production and management of electric vehicles in particular. Below, we explore some of these potential advances that could redefine the future of EVs. 

Optimized Manufacturing

We have already discussed the application of Digital twins in EV; How it helps in the design, production, and testing process. Manufacturers can monitor, analyze and optimize each step of the process. 

For instance, a digital twin of the manufacturing process can help identify potential bottlenecks in the assembly process. Thus, it enables them to make the necessary changes and improve the process efficiency. 

Battery Life Optimization

One of the biggest challenges in the EV is finding ways to extend the lifespan of batteries. Unlike gas or fuel stations, there aren't many charging stations in need. Thus, it is essential to have longer battery life. 

Digital twins can help here. We can simulate various driving conditions and how they affect battery performance. This allows engineers to optimize battery design to improve energy use, increase range and overall battery life. 

Personalized User Experience

Digital twins in electric vehicles can also revolutionize the way drivers interact with their cars. By continuously learning from the driver's habits and preferences, the digital twin can automatically adjust various settings. These include climate control, steering height, and seat position. 

In connected cars, they can personalize the music, podcasts, or radio according to the driver's behavior. 

Conclusion

There is no doubt that the future of automobiles is green, and EVs will be leading the way. But as we discussed, there are challenges automotive companies have to overcome to make it efficient, safer, and more sustainable. And Digital Twins are the best way to achieve it. 

The use of digital twins in electric vehicles offers many opportunities for innovation. And as digital twin technology evolves, we can expect even more breakthroughs that will push the boundaries of what is possible in EVs. 

If you are an automobile manufacturer and are thinking of integrating digital twins into your production process, it’s best you partner with a digital twin development company like Toobler. Their experts will guide you in overcoming the challenges, and their expertise will ensure faster and more efficient implementation of digital twins.