{"id":182,"date":"2025-06-04T09:00:00","date_gmt":"2025-06-04T13:00:00","guid":{"rendered":"https:\/\/blogs.sw.siemens.com\/pave360\/?p=182"},"modified":"2026-03-27T10:13:10","modified_gmt":"2026-03-27T14:13:10","slug":"siemens-and-arm-work-together-to-build-digital-twin-solutions-for-ai-defined-vehicle","status":"publish","type":"post","link":"https:\/\/blogs.sw.siemens.com\/pave360\/2025\/06\/04\/siemens-and-arm-work-together-to-build-digital-twin-solutions-for-ai-defined-vehicle\/","title":{"rendered":"Siemens and Arm work together to build Digital Twin solutions for AI-Defined Vehicle"},"content":{"rendered":"\n

PAVE360 digital twin solution gives developers access to virtual models of Arm\u00ae automotive IP in the cloud, including the new Arm Zena\u2122Compute Subsystems (CSS)<\/a>, far in advance of silicon availability. Siemens has been a longstanding partner with Arm and was a lead partner in offering a virtual platform for the Arm Cortex\u00ae<\/ins>-A720AE<\/a>. We are pleased to extend this first-to-market support to Zena CSS.<\/p>\n\n\n\n

Zena CSS is designed to meet the needs of highly complex, mixed criticality and AI-defined workloads, so developers need virtual environments like PAVE360<\/a> to address the challenges that inevitably come with next generation vehicle technology platform development. Furthermore, customers currently have no way to assess system integration failures prior to integrating the actual hardware and software. PAVE360 offers them a solution for this.<\/p>\n\n\n\n

Siemens is unique as it offers integrated EDA, and PLM\/ALM solutions to build multi-domain, multi-vertical digital twin, for design, development and validation. This enables early identification of potential issues, ensuring better integration and validation of the entire system throughout the development cycle.<\/p>\n\n\n\n

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Software-Defined Vehicles\u201d (SDV) are a subset of Software-Defined Systems (SDS); a development methodology where software and hardware are flexible and refined in parallel along with connectivity to iteratively ensure the system under development meets requirements.<\/em><\/strong><\/strong><\/p>\n\n\n\n

The result is an optimal solution measured by performance, cost, manufacturability, reliability, safety and customer satisfaction. It extends the vehicle\u2019s lifespan and creates additional revenue models.<\/em><\/strong><\/p>\nDavid Fritz, Vice President, Hybrid and Virtual Systems, Siemens Digital Industries Software.<\/strong><\/cite><\/blockquote>\n\n\n\n

\u201cSoftware-Defined Systems\u201d methodology accelerates development for the SDV<\/strong><\/h3>\n\n\n\n

Software-Defined Vehicles and AI-Defined Vehicles are more than cars, they are highly complex, highly connected systems. They are extensions of the home, the office, entertainment and consumers lifestyle. Traditional development methodologies cannot hope to address these new complexities, so future success will depend on two new criteria.<\/p>\n\n\n\n

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The vehicle should be software-defined<\/strong> as customer interaction brings the opportunities for differentiation. Here early software development<\/strong> is key.<\/p>\n\n\n\n

Development must be systems-aware\u201d <\/strong>to handle the growing complexity. Many failure mechanisms will only arise during systems integration, or worse, when the vehicle is deployed in the field. Finding these issues earlier in the design cycle reduces the risk of failure and ensures better integration and validation of the entire system.<\/p>\n<\/div>

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This requires a \u201cthreaded\u201d <\/strong>approach automatically connecting validation from system level down through unit testing, requirements fulfillment, and verification through all levels of abstraction, all levels of fidelity. This avoids the inevitable systems integration storm experienced by vehicle developers today, mostly caused by manual processes to reconcile validation with requirements. This leads to multiple failed and cancelled vehicle electronics platforms \u2013 holding industry back, making customers less competitive.<\/p>\n\n\n\n

Siemens SDV framework \u2013 for scalable Software-Defined Systems development<\/strong><\/h3>\n\n\n\n

Siemens has recognized that to optimize for the future and scale for the SDV enterprise, a fast end-to-end platform is required. <\/p>\n\n\n\n

The Siemens SDV framework <\/strong>utilizes the vast Siemens portfolio as well as offering a platform where ecosystem partners and customers can integrate their solutions and in house models. PAVE360 is a key element of the framework as it provides the capability to connect products from both Siemens and partners to build a digital twin that covers multiple fidelity and abstraction levels for SoC, vECU, systems and real hardware.<\/p>\n\n\n\n

Early software development using PAVE360 digital twin – Example Virtual Reference Solution for Arm Zena CSS<\/strong><\/h3>\n\n\n\n

This example reference solution leverages Innexis\u2122 Architecture Native Acceleration (ANA)<\/a><\/strong> for software development at real world chip speeds meeting the needs of software developers who don\u2019t yet have hardware. Not only is it possible to simulate the software at real world SoC speeds, but it is also possible to introduce, both synthetic and real world, system-level stimuli via tooling such as Simcenter\u2122<\/strong><\/strong> Prescan<\/a> and <\/strong>Simcenter\u2122 Amesim\u2122<\/strong><\/strong><\/a>.<\/strong> It\u2019s easy to configure and analyze data thanks to the Innexis\u2122<\/strong><\/strong> CodeBench<\/a> IDE and can be packaged with the Zena CSS reference software. Requirements and verification threading<\/strong> is present throughout, linking verification and validation with requirements set out in Siemens Teamcenter<\/a>\u2122<\/strong><\/strong> and Polarion<\/a>\u2122<\/strong><\/strong> PLM products<\/a>.<\/p>\n\n\n

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Example 1: PAVE360<\/strong> digital twin Zena CSS Virtual Reference Solution<\/strong><\/figcaption><\/figure><\/div>\n\n\n

Multiple OEMs and Tier 1s are having success today using PAVE360 solutions to test their early software, pre-hardware, increasing design confidence and avoiding the risk of investing in platforms that are later aborted.<\/p>\n\n\n\n

Explore and right size SoC Architecture using PAVE360 digital twin – Example Hybrid Reference Solution for Arm Zena CSS<\/strong><\/h3>\n\n\n\n

When greater accuracy is required, we move from virtual to hybrid simulation. Switching from Innexis ANA<\/strong> <\/a>to Innexis Developer Pro <\/a><\/strong>and RTL emulation using Veloce Strato CS<\/strong>,<\/a> customers can run mixed fidelity simulations of Zena CSS to determine latency, bandwidth, critical path timing, and power consumption for workloads they develop on Innexis ANA . A hybrid, or mixed fidelity, simulation has the benefit of running uninteresting code on a virtual model at speed until a more interesting part of the code is reached (Run Fast). Users can then switch over to running the software on the actual RTL to gather the required accurate metrics for that interesting part of the code (Run Accurate). This has the effect of speeding up simulation time, therefore debug time, shortening overall development time.<\/p>\n\n\n

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Example 2: PAVE360<\/strong> digital twin Zena CSS Hybrid Reference Solution<\/strong><\/figcaption><\/figure><\/div>\n\n\n

Developers can access performance data to show how Zena CSS works in an SoC from the perspective of Quality\u2013 of-Service, Freedom-from-Interference and other timing and power related factors. For example, to validate safety software, it\u2019s imperative to have accurate measurements to determine when particular functions complete and how they interact with other applications in the broader system. Simcenter Prescan and Simcenter Amesim can also work alongside Innexis Developer Pro within PAVE360, allowing users to migrate through fidelity levels to more accurate algorithms and physical models.<\/p>\n\n\n\n

Requirements and verification threading is even more important here because system integration failures often present themselves when running real and integrated workloads on real hardware. Running those workloads using accurate cycle timing, latency, bandwidth or CPU capacity and threading simulation results back to requirements means those integration failures can be exposed way before any real hardware is created. Threading technology in PAVE360 is the only way to ensure coverage of these types of system integration failures.<\/p>\n\n\n\n

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To find out more <\/em><\/strong>about how PAVE360 solutions can cover the full SDV development cycle visit www.siemens.com\/PAVE360<\/a><\/p>\n<\/div>\n<\/div>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

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