Journey Towards Next-Gen Vehicle Architecture
A Guide to Implementing Software-Defined Vehicle Technology
Read WhitepaperTrending
The number of functions in the average vehicle is growing, and OEMs are adopting advanced connectivity and autonomous features. Changes to the ecosystem—such as the shift to service-oriented architectures (SOA) and centralized computing—along with the increased use of logical vehicle elements like ADAS and automated driving features, have led OEMs to source software and hardware from multiple vendors.
To address these challenges, many are turning to Model-Based Systems Engineering (MBSE). MBSE helps visualize system behavior, simulate performance early, and identify integration issues before physical prototypes are built. This approach enables structured development, promotes cross-team collaboration, and reduces costly rework.
As a result, vehicle systems and architectures are becoming more complex. Automakers and suppliers are seeking advanced methods, tools, and processes to manage this complexity and shorten development cycles. This has driven a shift toward embracing the entire systems engineering lifecycle—from requirement analysis and behavior modeling to physical architecture design and validation.
By leveraging MBSE, OEMs and suppliers can ensure system correctness through early verification of behavior models, improving development efficiency and product quality. In an era of connected, software-defined, and autonomous vehicles, MBSE is a vital enabler of innovation, reliability, and faster time-to-market.
Opportunities & Challenges
Tailored MBSE Implementation
- Develop comprehensive system models using a top-down engineering approach.
- Reverse-engineer existing artifacts to identify optimization opportunities and align with organizational processes.
- Our customized approach ensures minimal disruption and maximized ROI.
Efficient Tools & Process Integration
- Identify gaps in requirements via systematic analysis and behavior visualization, ensuring cohesive system definitions.
- Deploy tool-specific solutions and plugins (e.g., CATIA Magic, Rhapsody, PREEvision) to automate engineering tasks and enhance consistency across teams.
Capability Building & Continuous Support
- Offer MBSE training, including SysML fundamentals and advanced model-based techniques.
- Provide ongoing guidance for successful adoption, ensuring organizational readiness and cross-functional collaboration.
Solution Framework
Our MBSE-based service framework visualizes every development phase—from initial requirements capture to final verification. Each step is interconnected, allowing real-time feedback loops and enhanced traceability. This holistic representation promotes collaboration across stakeholders, minimizing errors and accelerating time-to-market. By unifying processes, tools, and people, our framework ensures quality and seamless integration for sustainable, future-ready vehicle programs. It aligns with evolving standards.
Holistic Requirements Management
Stay ahead of escalating complexity through robust requirements management. Our approach integrates SysML to capture, trace, and validate requirements, ensuring alignment across OEMs, Tier 1s, and third-party vendors. By systematically linking each requirement to design elements, we reduce errors, minimize rework, and accelerate time-to-market and reliability for advanced automotive solutions.
Scalable Architecture Design
Embrace scalable architecture to accommodate connectivity, ADAS, and electrification demands. Our model-based approach seamlessly merges software and hardware components, enabling flexible deployment across diverse vehicle platforms. By unifying communication protocols and interfaces, we mitigate integration risks and ensure the agility needed to adapt quickly to evolving global automotive market requirements.
Accelerated Verification & Validation
Leverage virtual simulation and early behavior modeling to validate critical functions before physical prototypes. Our MBSE methods detect inconsistencies early, cutting down development costs and cycle times. By continuously refining designs via digital twin environments, we deliver reliable vehicles that meet stringent safety and performance benchmarks across global automotive markets.
Why Tata Elxsi?
- Decades of MBSE expertise meticulously tailored to diverse automotive, aerospace, and rail industry requirements worldwide.
- Proven frameworks that integrate seamlessly with existing processes, fostering accelerated adoption across global automotive organizations.
- Extensive tool expertise, including CATIA Magic, Rhapsody, and PREEvision, enabling automation and consistent, efficient development throughout projects.
- Flexible, scalable solutions crafted to manage complex multi-vendor environments, reducing rework and ensuring future compatibility.
- Dedicated support and training, empowering long-term stakeholders to confidently utilize MBSE for superior product outcomes.
Information Hub
-
What is Model-Based Systems Engineering, and why is it crucial for modern automotive development?
Model-Based Systems Engineering (MBSE) is a structured methodology that uses visual models to define, design, and analyze complex systems. Unlike document-centric approaches, MBSE creates a unified, digital thread linking requirements, behaviors, and components, offering greater traceability and consistency. In the automotive domain, MBSE is essential for managing the rapid growth of ADAS, connectivity, and electrification features. By simulating system interactions early, potential issues are identified sooner, reducing costly rework. Ultimately, MBSE accelerates development, enhances collaboration, and ensures the vehicle architecture meets evolving market and regulatory demands.
-
How does MBSE help reduce costs in vehicle architecture and feature development?
By introducing a unified modeling environment, MBSE eliminates redundancy and detects design flaws early in the development cycle. Because teams can visualize interactions between software and hardware components, problems are identified before physical prototypes are built, minimizing both time and resource expenditures. Additionally, MBSE’s systematic approach to requirements management prevents costly scope creep and rework. Ultimately, this model-driven method streamlines collaboration, shortens development timelines, and ensures that each subsystem integrates smoothly, leading to substantial cost savings over traditional engineering practices.
-
What are the key challenges when implementing MBSE in automotive organizations?
One primary challenge is cultural, as traditional engineering teams may resist transitioning from document-based processes. Another is the need for specialized skills—engineers must learn SysML or other modeling languages to fully leverage the approach. Additionally, selecting and integrating the right tools (e.g., Rhapsody, PREEvision) requires careful planning to ensure compatibility with existing workflows. Data security and version control can also become complex as more stakeholders collaborate on shared models. Finally, effective coordination among multi-vendor ecosystems is critical to maintain consistency and alignment throughout the entire systems engineering life cycle.
-
How does Tata Elxsi assist with MBSE adoption and training for automotive teams?
Tata Elxsi provides end-to-end support, starting with process assessments to understand your current engineering workflows. We then tailor an MBSE roadmap, incorporating best practices specific to your organizational structure. Our experts deliver hands-on training, including SysML and tool proficiency, to help teams quickly gain confidence in model-based methodologies. Additionally, we offer ongoing consulting to address emerging challenges, ensuring seamless transitions. By integrating MBSE within existing processes, Tata Elxsi helps you foster a culture of innovation and continuous improvement across automotive projects.
-
What future trends in automotive development make MBSE increasingly relevant?
As vehicles evolve to include autonomous driving, electrification, and advanced connectivity features, engineering teams face mounting complexity. Stringent safety regulations, faster product lifecycles, and shifting consumer expectations require flexible, adaptable architectures. Meanwhile, emerging technologies like software-defined vehicles and over-the-air updates demand real-time synchronization between hardware and software components. MBSE helps tackle these challenges by providing a unified framework for cross-functional collaboration, early defect detection, and holistic system optimization. As these trends accelerate, the model-driven approach becomes indispensable for organizations aiming to stay competitive and deliver cutting-edge solutions.
