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A few engineers exploring Simcenter automotive performance engineering to accelerate development.


Automotive engineering software

Push the boundaries of design, engineering and innovation. Integrate simulation and test strategies, MBSE, AI and multiphysics expertise with automotive engineering software and balance automotive performance engineering characteristics, optimizing range, efficiency and comfort.

Optimize automotive performance engineering

The autonomous and electric revolution is here to stay. Although the automotive industry embraced digital transformation, it doesn’t mean we collectively reached the summit. To engineer innovation faster and more efficiently, you also need to connect people, technologies and processes. When these work in unison, you’ll be able to close the gap between perfection in the digital twin and perfection in the product.


Time reduction in CAE analysis

By using the NX CAD and Simcenter 3D integrated process and CAE template, Denso reduced the time spent on CAE analysis by up to 80 percent. (Denso)


Faster model development

Deploying a multiphysics approach, French manufacturer PSA Peugeot Citroën, optimized the battery pack twice as fast while reducing cost. (PSA Peugeot Citroën)


Reduced time to pinpoint noise sources

It used to take Honda engineers three or four hours to identify where a noise was coming from. Now, they can do it in 15 minutes with extreme precision. (Honda)

What strategies can automotive engineers use to deploy their digital transformation journey?

Implement simulation and test strategies using automotive engineering software to tackle challenges in electrification, autonomy, lightweight design, safety, system integration, homologation and interconnectivity.

What can automotive engineering software do for you?

Automotive performance engineering uses advanced simulation and test solutions at all development stages. It helps make early design decisions, balance conflicting vehicle attributes, speed up your time-to-market and reduces cost.

Drive productivity, empower innovation with Simcenter

Simcenter offers predictive simulation and test solutions supporting engineers on their digital journey. With cutting-edge automotive engineering software and tools, industry expertise and customer support, Simcenter empowers engineering teams to harness the full potential of the digital twin.

The right side of the screen shows three smiling people working on a project pointing to PC screen. A picture  on the left side of the screen shows an automotive digital twin they are reviewing.

100% virtual engineering

  • Maximizing value by combining expertise, tools & processes
  • Find the right balance between conflicting functional requirements
  • Go from physical troubleshooting to virtual prototype prediction
  • Run rapid cost and energy-efficient computational fluid dynamics (CFD) simulation using GPU hardware
An electric car dashboard representing Siemens model-based systems engineering (MBSE) for better designs.

Software-defined vehicles

  • Adopt model-based systems engineering (MBSE) for better designs
  • Deploy generative engineering strategies for systems architectural innovation
  • Use AI and ML to improve product engineering
  • Scenario-based validation and verification of automated driving systems
A model of a car showing how to maximize range using a multiphysics approach to battery development.


  • Maximize range using a multiphysics approach to battery development
  • Design and engineer the electric drive in an integrated engineering workflow
  • Balance passenger comfort, efficiency, performance and in-vehicle experience
  • Improve drag and vehicle aerodynamics development
A visual illustration of cars on a highway with green and blue overlays representing multi-sensor driver assistance. Simcenter SCAPTOR accelerates the development of multi-sensor autonomous driving and Advanced Driver Assistance Systems (ADAS).

ADAS and autonomous technology

  • Meet all the requirements, safety standards and performance targets
  • Identify scenarios and extract parameters for performance analysis
  • Reduce unsafe-unknown scenarios with a patented framework
  • Accelerate algorithm development with a physics-based digital twin

Simcenter automotive mechanical simulation trial

Try Simcenter mechanical simulation today and accelerate your mechanical design. Discover how to validate product changes by adding simulation to your CAD design, generate flexible body motion in the context of automotive motion simulation, collaboratively work on large simulation assemblies and correlate testing results to verify and validate simulation results.

A rendering of a two-seat racecar.

Read what real engineers are saying about Simcenter

User perception is critical; it’s a reflection of how well Simcenter is doing, and whether our continuous software release cycles are resonating with you.

Simcenter G2 leader badges.
Making a vehicle smart by digitally connecting development and operation will be the next technological revolution. By pre-defining major calibration values using HiL simulation, we were able to reduce the number of actual vehicle tests by 40 percent.
Bang Jae-Sung, Ph.D, Senior Engineer R&D Center, Hyundai Motor Company

Embark on your engineering journey effortlessly

Leverage our experts

Engage with engineering consulting services to help you build your engineering digital twin.

Access training

Discover how Siemens Xcelerator Academy can help you master Simcenter and increase productivity quickly.

Join the community

Join our community of Simcenter experts and expand your knowledge!

Frequently asked questions

What do you mean by automotive performance engineering?

Vehicle performance relates to the overall capabilities, efficiency and functionality of a vehicle, encompassing aspects such as acceleration, battery range, safety, aerodynamics and water management, advanced driver-assistance systems (ADAS), energy and thermal management, noise, vibration and harshness (NVH) and acoustics, strength and durability, vehicle controls and vehicle handling.

Automotive performance engineering is driven by business requirements and delivers end-to-end system optimization through a continuous virtual testing and monitoring loop. Using a shift-left strategy, car makers and suppliers aim to provide better business value by discovering potential issues early in the development cycle. By using simulation early in the design process and virtually testing if products meet the requirements, they can detect problems early and rectify them in a comprehensible digital twin. Additionally, they can explore design alternatives earlier in the design phase when changing designs is easier and less disruptive.

What is meant by an all-in-one multiphysics approach?

A multiphysics simulation refers to the analysis of multiple, simultaneous physical phenomena of a system or systems and the interactions among them. Driven by consumer demands and business requirements, multiphysics automotive engineering software aims to design safe, high-performing products faster. It enables one to model the complexity, explore the possibilities of products operating under real-world conditions and discover potential issues early in the development cycle.

Take for example vehicle battery development, design and engineering teams need to integrate electrochemical, electrical, thermal and structural engineering. Running isolated campaigns targeted at these separate attributes will generate redundant and sometimes conflicting models and data sets. Instead, using an all-in-one multiphysics approach allows you to understand exactly how components will perform when integrated with others and ensures that even the first prototype works as planned.

What is the role of testing in the global rush for digitalization?

The time that automotive (system) testing was performed on prototypes is long gone. Today, the development doesn’t stop at the end of the V-cycle. Instead, it continues in an infinity loop by using historical data, test data and data from vehicles in use to create test-based models that define the relationship between vehicle characteristics and its performance.  

A good example is model-based system testing (MBST). MBST is an engineering framework employing three key solutions: virtual models, virtual-physical systems and physical prototypes. It utilizes test data to build, validate and improve simulation models, identifies interactions through XiL in various scenarios and enhances test data with simulation models for physical prototypes. Manufacturers using MBST are more efficient, faster and avoid errors in data transfer or post-processing. 

Another outstanding example is virtual prototyping. Virtual prototyping is an efficient testing method that allows the exploration of vehicle assembly alternatives before physical prototypes are built. It specifically addresses NVH performance and uses component-based transfer path analysis (TPA) to swiftly evaluate various designs, saving costs by detecting and controlling issues early.

How to take advantage of artificial intelligence and machine learning?

Traditional design and engineering methods struggle with today's complex workflows. Leveraging artificial intelligence (AI) and machine learning (ML) accelerates decision-making, enhancing engineering teams' productivity and developing innovative products in shorter time frames. Fitting any stage in the development cycle, Simcenter offers a framework for applying artificial intelligence to leverage historical data, avoid mistakes, speed up the analysis and optimize designs with confidence.

For instance, in autonomous vehicle systems, AI and ML are used to embed human behavior into machine perception. While current autonomous vehicle perception systems nearly match human sensory abilities, especially in standard conditions, they fall short in extreme weather and complex scenarios. Simcenter's scenario-creation process helps generate critical scenarios for OEMs and AV suppliers, ensuring compliance with safety standards like the safety of the intended functionality (SOTIF).

How to manage vehicle systems integration from a technical, process and organizational point of view?

The only sustainable way to integrate vehicle systems is to approach the design and engineering as a complete ecosystem. This enables manufacturers to rapidly redesign and re-use the workflow as requirements change and trade off attributes between multiple domains. On a process level, it is key to meet requirements while staying connected with the product lifecycle management (PLM) system to ensure that changes made in one domain are reflected across the entire system. A model-based systems engineering (MBSE) approach in vehicle development connects systems engineering with the rest of the development organization, improving collaboration and decision-making.

Take the example of electric drive engineering. An e-drive consists of an electric motor, a gearbox and power electronics. Multiple experts from different domains need to work together to achieve an efficient, integrated electric drive. It is hence essential to leave the traditional development silos in the past and allow cross-functional and cross-domain systems engineering. Only a connected engineering approach, with integrated, reusable workflows through the application of MBSE and a digital twin, provides manufacturers with the automotive engineering software toolchain to manage the spiraling complexity of electric vehicle engineering – not only of the product but also of the development process.

Learn more


Presentation | Take a virtual tour of our vehicle energy management facility

Case study | Using improved digital twin accuracy to develop sustainable mobility solutions


Podcast | The power of simulation to AV design and development

Podcast | Digitalization and the future of vehicle performance engineering


White paper | Adopt model-based systems engineering in vehicle development

White paper | Make an engineering impact on vehicle electrification with the digital twin

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