Model-based systems engineering for electric vehicles

Model-based systems engineering: Navigating complexity in the development of software-mechanical systems

By Alexander Belin, Engineering Analyst, Grid Dynamics

Grid Dynamics
10 min readJan 9, 2024


In the dynamic landscape of modern engineering, the convergence of electrical, mechanical, and software systems in the development of complex products presents a formidable challenge. The automotive industry, exemplifying this complexity, is undergoing a profound transformation driven by technological innovations, environmental considerations, and changing consumer expectations. As vehicles evolve from mere modes of transportation to tech-savvy companions, the intricacies of integrating diverse components escalate, posing challenges ranging from compatibility issues to security vulnerabilities. This blog explores the paradigm shift towards model-based systems engineering (MBSE) as a strategic approach to navigating the complexities inherent in the development of software-mechanical systems, with a special focus on electric vehicles.

What is MBSE?

MBSE is a holistic and multidisciplinary approach to system development that has gained prominence in addressing the growing complexity of modern engineering challenges. At its core, MBSE represents a departure from traditional document-centric methods, emphasizing the creation and utilization of a comprehensive digital model that encapsulates all facets of a system’s architecture.

Unlike conventional document-based approaches, where information is dispersed across various documents, MBSE consolidates and interconnects this information within a unified model. This model serves as a dynamic representation of the entire system, capturing not only its structure but also its behavior, requirements, and interactions.

Model-based systems engineering concept diagram
MBSE concept

MBSE provides a visual, model-centric approach that not only simplifies the complexities of system engineering but also enhances collaboration, quality, and efficiency throughout the entire development life cycle. As industries grapple with the challenges of developing intricate software-mechanical systems, MBSE stands out as a strategic enabler for navigating this complexity and unleashing the full potential of innovation.

Software-mechanical complexity in the automotive industry

In every industry, from energy to automotive, medical, and beyond, combinations of electrical, mechanical, and software systems add complexity to products. There are hundreds of thousands of electronic control units (ECUs) and millions of lines of code with associated costs, power, and safety requirements. The complexity of the components increases the number of intersections between components.

We can take the automotive industry as an example since it is one of the largest and most influential markets on the planet. Even though the automotive industry has remained relatively stable over the past decade, the situation is changing dramatically. Rapid technological and environmental innovation has forced players to adapt to challenges.

A car is more than just a vehicle now

Nowadays, it is not enough for a car to be a vehicle for moving a person from point A to point B. They’re like tech-savvy companions. With cool features like smart connectivity, safety tech, and eco-friendly designs, they’re all about providing a personalized, enjoyable experience. Plus, they’re not just standalone machines; they’re joining the smart city scene, offering subscriptions, and fitting into a bigger transportation picture.

Complexity drivers

Among the major growth drivers of the auto industry, the most important is the shift to electric vehicles (EVs). Many automakers are investing heavily in developing electric vehicles. Governments around the world are also implementing policies to encourage the use of electric vehicles and reduce emissions. Also, the increasing safety and efficiency of transportation carried out by autonomous or driverless vehicles is sparking interest and causing more companies to invest in it. Internet of Things (IoT) connectivity and integration in vehicles is becoming more common. Connected cars offer advanced infotainment systems, real-time navigation, and smart features. Rapid technological innovation in automotive technology, including new materials, energy storage, and software, is fueling the industry’s rapid growth.

However, the combination of electrical, mechanical, and software systems in the design of automobiles significantly complicates the products produced by modern automobile enterprises. Modern cars consist of hundreds of thousands of ECUs and millions of lines of code with associated cost, power, and safety requirements. The number and variety of components increase the number of dependencies between components.

The diversity and complexity of systems cause the following problems:

  • Compatibility issues between different ECUs
  • Increased complexity of debugging and testing
  • Potential security vulnerabilities
  • The need for standardized communication protocols to ensure seamless integration of various vehicle systems.

Additionally, complexity increases as vehicles incorporate advanced features like autonomous driving and connected systems, as mentioned above. Integrating sensors, actuators, and complex software poses challenges in responding quickly to rapidly changing traffic conditions in real time.

The situation is further complicated by the fact that automakers often outsource the development of software components for their cars.

Moreover, in the production of one machine model, software modules developed by different software development companies can be used simultaneously.

Finally, the rapid development of technology poses the challenge of maintaining and updating complex software systems throughout the vehicle’s life cycle. This requires effective software update strategies that not only improve functionality but also address security vulnerabilities.

This increasing complexity of vehicle architecture results in a significantly increased risk of product errors. To confidently deliver complex products, companies must change their engineering processes to manage these interfaces where product failures occur.

How to solve automotive complexity issues

Developing and maintaining such complex systems is almost impossible without a single, holistic model of the complex system. The model aims to improve standardization (i.e., the creation of common interfaces and protocols that facilitate interaction between the components of a single complex system). Moreover, these components can differ significantly in their nature and purpose, and can be developed by different manufacturers.

MBSE as the solution

One of the most common approaches to solving problems associated with the growing complexity of technical systems is the use of systems engineering (SE) practices.

The International Council on Systems Engineering (INCOSE) and ISO/IEC/IEEE 15288 (2023) defines SE as follows:

“Systems engineering is a transdisciplinary and integrative approach to enable the successful realization, use, and retirement of engineered systems, using systems principles and concepts, and scientific, technological, and management methods.” [1]

But the question is, how can SE help manage the system complexity and ensure the creation of correct and working systems?

Friedenthal, Sanford; Moore, Alan; and Steiner, Rick answer this question in their bestseller “A Practical Guide to SysML: The Systems Modeling Language.” They claim the following:

“Systems engineering is a multidisciplinary and holistic approach to develop solutions for complex engineering problems. The continuing increase in system complexity demands more rigorous and formalized systems engineering practices.” [2]

Shift from a document-based approach to a model-based (MBSE)

Significant advancements in computer technology have enabled the practice of systems engineering to make a fundamental shift from a document-based approach to a model-based approach.

“In a model-based approach, the emphasis shifts from producing and controlling documentation about the system to producing and controlling a coherent model of the system. Model-based systems engineering (MBSE) can help to manage complexity, while improving design quality and cycle time, enhancing communication among a diverse development team, and facilitating knowledge capture and design evolution.”

Thus, one of the most effective ways to develop and maintain complex systems is by transitioning from developing and using architectural and requirements documents as the primary tool to adapting to systems engineering approaches to designing complex systems.

The essence of this approach is the collective development of a unified model of a complex system, reflecting its possible aspects and integrating all the heterogeneous components of the system into a single model.

This approach ensures the integration of heterogeneous elements through the detailed elaboration of interfaces and protocols and the formation of requirements based on the developed model.

This is a huge benefit that comes from the MBSE approach.

How MBSE can help to resolve the complex system development issues

The INCOSE Systems Engineering Vision 2020 (2007) defines MBSE as follows:

“The formalized application of modeling to support system requirements, design, analysis, verification, and validation activities beginning in the [concept stage] and continuing throughout development and later life cycle [stages].” [3]

How exactly can MBSE help eliminate all the problems we discussed earlier?

  1. Firstly, MBSE enables interdisciplinary collaboration. Teams from different disciplines can collaborate using a single digital model, improving communication, and reducing misunderstandings during development.
  2. Since MBSE is based on modeling, it provides not only simulation but also validation. Digital models enable extensive simulations and validations, helping identify issues early in the development cycle. This results in more robust and reliable systems.
  3. An equally important aspect of the development process for complex systems is configuration management. Managing different configurations becomes more streamlined with a digital representation, ensuring accurate documentation and reducing the risk of errors in system setups.
  4. Lastly, since the development process of complex systems is lengthy and contains several complex and interconnected stages, ensuring life cycle traceability is no less important. The digital thread provides a traceable record of decisions and changes throughout the product’s life cycle, aiding in maintenance, updates, and compliance with evolving standards.

How MBSE enhances software quality

Here are several ways in which MBSE can contribute to enhanced software quality:

1. Early and continuous requirements validation:

  • MBSE allows for the creation of precise and detailed system models that capture requirements in a visual and understandable manner.
  • Engineers can validate requirements early in the development process through simulations and analyses, ensuring potential issues are identified and addressed before software development begins.

2. Improved collaboration and communication:

  • MBSE promotes collaboration among multidisciplinary teams by providing a common visual language for system representation.
  • Enhanced communication between stakeholders, including system engineers, software developers, and end-users, reduces the risk of misunderstandings and ensures everyone understands the system.

3. Traceability and impact analysis:

  • MBSE tools provide traceability between requirements, design elements, and implementation artifacts.
  • Traceability allows for impact analysis, helping software developers understand the implications of changes and ensure modifications are made consistently across the system.

4. Consistency across the development life cycle:

  • MBSE supports consistency in the system model throughout the entire development life cycle.
  • Consistent and accurate models help maintain alignment between the system design and the software implementation, reducing the likelihood of discrepancies and errors.

5. Automated code generation:

  • Some MBSE tools support automated code generation from system models, reducing the manual effort required for translating design specifications into code.
  • Automated code generation promotes consistency between the design and the implementation, minimizing the risk of coding errors.

6. Simulation and testing:

  • MBSE allows for the creation of executable models that can be used for simulation and testing.
  • Simulation enables early validation of software behavior, uncovering issues that might not be apparent through static analysis alone.

7. Iterative development and prototyping:

  • MBSE supports an iterative development approach, allowing for the creation of prototypes and the incremental refinement of system models.
  • Iterative development enables software developers to receive early feedback, facilitating continuous improvement and reducing the likelihood of defects in the final product.

8. Change management and configuration control:

  • MBSE tools provide features for change management and configuration control, helping manage modifications to the system model.
  • Software developers can better control and understand changes, ensuring alterations are properly documented and implemented without introducing unintended consequences.

9. Enhanced understanding of system context:

  • MBSE facilitates a holistic understanding of the system and its context, helping software developers consider the broader implications of their work.
  • A comprehensive understanding of the system’s architecture and requirements improves design decisions.

10. Documentation and knowledge transfer:

  • MBSE promotes the generation of comprehensive documentation directly from the system model.
  • Rich documentation aids in knowledge transfer, making it easier for new team members to understand the system’s design and functionality.

Application of the MBSE approach in software development

Systems engineering approaches to the development of complex high-tech systems, particularly MBSE, have long been mainstream in the automotive industry and used in complex engineering fields such as aerospace and defense.

As discussed earlier, modern aircraft, spacecraft, defense systems, cars, railway systems, and other complex systems are not just a combination of devices, units, and mechanisms but also millions of program code lines.

Software development companies are deeply integrated into the development of complex and intelligent systems.

That is why it is vital for companies developing a software product to know, understand, and use MBSE approaches.

For companies engaged in automotive software product development, irrespective of prior experiences in traditional business information systems, embracing the principles and methodologies of systems engineering, particularly MBSE, marks a transformative leap. It propels them beyond the confines of traditional IT development, transforming them into active participants in the realm of complex engineering projects.

Moreover, implementing MBSE principles into the daily practice of a software development company, regardless of the type and level of complexity of projects, will optimize software development by offering a visual, model-based approach that improves requirements management, collaboration, and early error detection, which leads to more efficient processes for developing a higher-quality software product.


In the realm of complex system development, the adoption of MBSE emerges as a transformative solution. As highlighted, the challenges posed by the integration of electrical, mechanical, and software components in modern vehicles are vast and multifaceted. However, by transitioning from traditional document-based approaches to a model-based methodology, MBSE offers a holistic framework to manage complexity effectively. From interdisciplinary collaboration to early validation, enhanced communication, and automated code generation, MBSE addresses key pain points in the development lifecycle. As industries, particularly the automotive sector, navigate the evolving landscape, embracing MBSE not only streamlines processes but also paves the way for innovation, quality improvement, and sustained excellence in the creation of software-mechanical systems.

Get in touch with Grid Dynamics to learn more about MBSE.


[1] INCOSE. INCOSE Systems Engineering Handbook. 5th Edition, Wiley.

[2] Friedenthal, Sanford; Moore, Alan; Steiner, Rick. A Practical Guide to SysML: The Systems Modeling Language.

[3] INCOSE Technical Operations. 2007. Systems Engineering Vision 2020. Version 2.03. Seattle, WA: International Council on Systems Engineering, Seattle, WA, INCOSE-TP-2004–004–02.



Grid Dynamics

We accelerate digital transformation of Fortune 1000 US enterprises. We bring expertise in customer experience, data analytics, and cloud, lean software, etc.