Digital Prototyping and Simulation for Better Automotive Design

This page was originally published as a part of Hexagon's Design and Engineering blog. Hexagon Design and Engineering is now a part of Cadence.

Virtual prototyping and simulsimulation ation are revolutionising automotive design, promising enhanced efficiency and improved quality, while reducing costs and time to market. Pressures on supply chains and market competition are pushing manufacturers towards agile methodologies, such as digital prototyping, streamlining development cycles. 

The shift in automotive design and manufacturing 

Quality and efficiency are paramount in automotive manufacturing, as safety is critical and challenges such as supply chain disruptions, regulatory changes, and the need for rapid innovation are constant. 

Digital prototyping enables faster iterations and testing, ensuring quality and safety without compromising speed-to-market; also allowing for easier adaptation to changing requirements, keeping projects within budget and on schedule. 

Advancing design with digital twins and simulation technologies 

Digital twins: The foundation of virtual prototyping 

At the core of zero prototyping lies digital twins, mirroring the physical vehicle in every aspect and enabling the simulation of vehicle behaviours in varied scenarios, from extreme weather conditions to high-impact collisions. For simulation engineers, this provides a sandbox for conducting exhaustive tests under myriad scenarios, including extreme conditions that would be challenging or impossible to replicate with physical prototypes. Advanced simulation software can model the complex interactions between various vehicle systems, allowing engineers to identify potential issues and optimise designs in the virtual realm. 

Enhanced design validation with multiphysics simulations 

The ability to employ multiphysics simulations is one of the key technical advantages of zero prototyping, integrating various physical phenomena like fluid dynamics, structural mechanics, and electromagnetism into a cohesive analysis. This holistic approach enables a comprehensive understanding of complex interactions within the vehicle system, such as how aerodynamic improvements might affect thermal management or how vehicle weight reductions impact structural integrity. 

Real-world application: Enhancing EV battery performance 

In the realm of electric vehicles (EVs), zero prototyping facilitates detailed analysis of battery systems to optimise performance, safety, and longevity. Engineers can simulate thermal behaviours under different charging and operating conditions to improve battery life and safety. For instance, leveraging simulation to design battery cooling systems can significantly enhance EV efficiency and range, addressing one of the key consumer concerns about electric mobility. 

Streamlining development with AI and Machine Learning 

The integration of AI and Machine Learning into the zero prototyping process marks a significant leap forward. These technologies process the massive datasets generated by simulations, identifying patterns and predicting outcomes. For example, machine learning algorithms can optimise structural components for both weight reduction and durability, striking a balance that manual analyses might miss or take much longer to discover. 

Practical application: Predictive maintenance and material selection 

AI-driven simulations extend beyond design optimisation to predictive maintenance and material selection. By predicting wear and tear on vehicle components, engineering teams can select materials that extend the lifecycle of the vehicle while maintaining safety and performance standards. This predictive approach minimises the risk of failure and ensures that the vehicles are not only efficient but also durable. 

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