The era of the traditional carmaker is over. Vehicle development has become a complex integration exercise with electrification and advancements in ADAS technologies. The various platforms, model variants, concepts, and modular sub-systems challenge engineering teams while simulation and testing are helping them accelerate decision-making and balance design choices. In this on-demand webinar, discover how vehicle engineering teams can deal with the challenges of tomorrow while keeping quality, brand values, time, and cost under control by making better use of simulation models in model-based development and effectively combining test and simulation. Register to watch now!
You will discover in this on-demand webinar:
Electrification, globalization, brand identity, connectivity, and autonomous driving have enormous pressure on vehicle engineering performance. Engineers must now solve new challenges related to new lightweight materials, hybridization, electrification, autonomous systems, and the inclusion of intelligent systems. To stay competitive, today’s vehicle performance engineering departments must support simulation and test-based verification and validation in various stages of the vehicle development, from early program to prototype and pre-production sign-off. By offering a wide range of simulation and testing solutions and engineering services, Siemens Simcenter solution enables engineers to design and engineer better products, gain earlier insights on performance, accelerate innovation, and achieve greater productivity at any organizational level.
Electrification on its own brings its specific challenges, such as range anxiety and efficiency in electric vehicles (EV). Optimal lightweight design and efficient thermal management are critical for EV safety and balancing passenger comfort. Unique EV battery platforms with multiple body vehicle variants also give specific engineering challenges. Siemens Simcenter supports Predictive Engineering Analytics — the application of multi-discipline simulation and test, combined with intelligent reporting and data analytics — to develop digital twins that can predict the performance behavior of products across multiple performance attributes throughout the product development lifecycle. This multi-attribute solution enables engineers to explore digitally and physically confirm a vehicle that balances all these performance considerations. And by combining digital twin with machine learning to optimize across multiple attributes, engineers can reuse data to frontload performance engineering and design right the first time.
It takes millions of miles to run on a test track or in real life to make sure that autonomous vehicles are safe to drive, which is impossible to do. However, a digital twin of the vehicle and the world defined from formal requirements and system architecture definitions can simulate real-world behavior to validate many scenarios and vehicle variants as fast as possible. Siemens Simcenter solution provides a verification and validation framework for a full vehicle or system-level performance verification. By having the requirements and test case definitions and the virtual right-fidelity level representation of the vehicle in its environment, simulation makes it possible to automatically generate test runs of millions of tests in a cloud or cluster set up. And if the design has not met the requirements, closed-loop simulations will continuously run to the point where the vehicle or system can be certified for release on the market.
Register to watch the on-demand webinar now and learn more about the advantages of simulation and testing in vehicle performance engineering.