From Concept to Reality: The Development of an AI-Designed Car
Artificial Intelligence (AI) offers new possibilities to the automotive industry, from faster and more efficient manufacturing processes to groundbreaking new car designs. AI is truly digitalizing the automotive industry.
Could AI even design a full car on its own? With AI's ability to analyze and process vast amounts of stored information, designers could be assisted by AI to make informed decisions on the car's design. For example, improving aerodynamics and energy efficiency which would have been challenging to analyze previously.
We will examine a few examples of car components and processes that can benefit from AI. We'll also explore a real-world example of the world's first car created with AI and assembled with additive manufacturing techniques. Also, we'll discuss the use of feedstock and materials in car manufacturing and the role of AI in product design with leading-edge Deep Learning and generative design technology.
Get ready to see how AI can revolutionize the automotive industry!
Two Innovation Examples with Artificial Intelligence
The application of Artificial Intelligence (AI) is transforming the automotive industry in various ways.
AI revolutionises car manufacturing by automating quality control and assembly tasks through computer vision and machine learning algorithms. As a result, the industry is becoming more efficient and productive.
An area where AI has a significant impact is in the production of e-fuels. Using AI algorithms, e-fuel production is becoming more cost-effective and sustainable by optimizing manufacturing.
For instance in the design of front wheels, AI can impact early design stages where algorithms optimize aerodynamics and reduce wheel weight to improve performance and energy efficiency.
Overall, AI is increasingly playing a vital role in the automotive industry, with applications ranging from optimizing the design process to automating tasks in manufacturing.
Car Design: from Tradition to Innovation
Car design has traditionally been labour-intensive and time-consuming. AI algorithms open a new window by exploring multiple design options and evaluating the potential impact of different car design choices on the overall performance and efficiency of the vehicles.
Pushing the Boundaries of Car Design
AI is helping to develop and push the boundaries of car design. While humans remain at the center, AI enables manufacturers to create and develop cars with unique and innovative shapes and features. AI-designed cars can also be optimized for specific characteristics like fuel efficiency, top speed or aerodynamics.
Implications for Manufacturing
The rise of AI in the auto industry has implications for manufacturing. AI-conceived cars can be built using advanced manufacturing technologies such as 3D printing, creating complex and intricate parts that would be difficult or plainly impossible to create with traditional manufacturing techniques. Thus, no more overperforming engineering concepts will be apriori discarded only because they were not "industrially feasible".
A Case Study: Czinger
The Czinger 21C shows how generative design and additive manufacturing technology are revolutionizing the car industry. This supercar, developed by the California-based company of the same name, features a unique style, a hybrid powertrain and a body conceived using generative design software. This hypercar has an output of 1250 HP and a 0-60mph acceleration of under 1.9 seconds, making it a high-performing vehicle and all 3D printed! The top speed of the 21C in its road-spec version is 268 mph, and at 155 mph, it generates 551 pounds of downforce.
In the case of the 21C car, the generative design software was used to create a lightweight, aerodynamic body that maximized downforce while minimizing drag, not mentioning the style.
The body of the vehicle, the 21C, is made using additive manufacturing, specifically laser sintering; it reduces the parts required to assemble the car, making each component more efficiently manufactured. The car's hybrid powertrain features a mid-mounted, 2.88-liter V8 engine with one electric motor on each front wheel. The car can also operate in all-electric mode for short distances.
The 21C car is just one case of how generative design and additive manufacturing change how cars are conceived and built. This leads to quote another case.
Aston Martin Case
Aston Martin, the renowned British luxury sports car maker, has unveiled a new roadster model with an innovative 3D-printed rear assembly produced by Divergent Technologies. The rear of the DBR22 two-seater vehicle features a support structure of various lightweight aluminum parts that have been 3D printed and bonded together. The subframe has been manufactured by Divergent Technologies, which had previously produced the 3D-printed above-mentioned 21C hypercar and supplied leading OEMs.
3D Printing Technology: Feedstock
We have mentioned aluminum parts. So, what is the role of feedstock in 3D printing?
Feedstock is the raw material used as powder, liquid, or filaments to build up the 3D object layer by layer. The most common feedstocks are plastics, and metals, such as steel, Aluminum (Al) or Titanium (Ti).
The Role of Aluminum (Al)
Aluminum is commonly used in additive manufacturing for cars. It is lightweight, strong, and has excellent thermal properties, with relatively easy processing with additive manufacturing techniques. This makes it a cost-effective option. Being lighter than other materials, aluminum can also help improve the vehicle's overall fuel efficiency.
The Role of Titanium (Ti)
Ti is a commonly used material in additive manufacturing: with excellent mechanical properties for high loads and temperatures, such as engine components and suspension parts.
This is ideal for automotive applications where weight and durability are important. Additionally, it has a high melting point, allowing faster printing speeds and improved surface finish.
Case Study: CarbonCure Technologies
It's possible to conceive using carbon-recycled methanol as a feedstock for 3D printing. Carbon dioxide is captured from industrial processes to create a liquid feedstock that can be used in 3D printing to create high-performing polymer parts.
Designing and Building High Output Electric Motors for Automotive Applications
Designing and building high-output electric motors for automotive applications can be complex and challenging. Generative design and additive manufacturing are facilitating more powerful and lightweight motors.
Engineers can design motors with a high power-to-weight ratio generatively. Additive manufacturing is particularly useful for electric motors, as it allows for the creation of stators and rotors with intricate geometries that optimize the flow of the magnetic fields.
This process results in more power-efficient motors with higher power output.
Conclusions: The Role of AI in Car Design
AI can truly revolutionize how components, engines, wheels, chassis and engines can be simulated in 3D almost in real-time.
The first revolution in design was the adoption of automotive CAE (engineering simulation). AI-driven simulation is the next step.
For instance, NCS (Neural Concept Shape) can connect the computer shape (CAD) datasets created by design departments with the CAE (engineering results) datasets from a center for advanced engineering.
In conclusion, AI is transforming how car design is approached; providing new and exciting possibilities for innovative design.
AI's speed and processing power enable car manufacturers to explore unique shapes and features, creating truly innovative cars. This new approach to design is becoming increasingly essential in the automotive industry as it facilitates the exploration of previously unconsidered design options.
As AI continues to evolve, car manufacturers will be able to extract data and push the boundaries of design even further, leading to more exciting and innovative cars.