Why Modular Simulation Architecture Is Becoming A Standard In Engineering Workflows

Engineering teams now confront unprecedented system complexity, and they are making modular simulation architecture the new standard because nothing less can keep up. A modern vehicle, for instance, can contain over 150 microprocessor-based controllers running more than 150 million lines of code. Integrating and validating such intricate systems has become a massive effort, as analysis suggests that 40% or more of a new car’s development budget can go into system integration, testing, and validation. Faced with these challenges, teams can no longer rely on rigid, one-off simulation models or siloed tools that make every project feel like reinventing the wheel. Modular, open simulation platforms have moved from optional to essential for managing complex embedded systems with agility and real-time accuracy. When every project’s success hinges on rapidly iterating designs across mechanical, electrical, and software domains, the ability to plug and play simulation components is transforming engineering workflows for the better.

Complex projects expose the limits of monolithic simulation

Siloed tools and isolated domains

Engineering projects often span multiple disciplines—electronics, software, mechanical systems—but traditional workflows keep these domains in separate silos. Each team uses its own specialized modeling tools, and bringing their work together at the end becomes a major headache. Valuable work gets duplicated or lost in translation because a monolithic simulation environment typically supports only certain domains well. In a worst-case scenario, teams even abandon their familiar tools to fit into one rigid framework, sacrificing existing model investments; by contrast, a co-simulation approach lets each partner continue using their proven tools and preserve those investments.

Rigid models that resist change

Monolithic simulation models are by nature inflexible. When requirements change or a new component needs to be evaluated, engineers must often overhaul a single gigantic model. This is not only labor-intensive but also error-prone. In tightly coupled simulations, a tweak in one subsystem can have unexpected ripple effects on others. Scaling such models is equally problematic; trying to extend a monolithic simulator to cover additional systems or higher fidelity can push computing limits or require painful simplifications. These one-size-fits-all models struggle to adapt to the iterative nature of real engineering design, and they cannot be easily repurposed for new projects.

Late integration means higher risk

The biggest drawback of siloed, monolithic simulation is that system integration happens late in the development cycle. Software and hardware come together only after separate testing, which is when hidden incompatibilities or performance problems finally emerge. Discovering a control-loop instability or an interface mismatch just before a deadline can be costly. Late fixes might require hardware changes or rushed code patches because the simulation couldn’t expose the issue earlier. The lack of an integrated, modular testing environment throughout development often leads to unpleasant “surprises” in prototypes, undermining confidence in the design and slowing the whole project down.

“Engineering teams now confront unprecedented system complexity, and they are making modular simulation architecture the new standard because nothing less can keep up.”

Modular simulation architecture accelerates development and testing

Shifting to a modular simulation architecture directly addresses the bottlenecks of monolithic workflows. By building complex models as a collection of interchangeable components, teams can move faster and test more thoroughly with less rework. For example, a modular approach speeds up development and validation in several ways.

• Faster design iterations enable engineers to swap in updated subsystems or new design ideas without rebuilding the entire model. This flexibility allows quick turnarounds for design changes and rapid “what-if” experiments.
• Reuse of validated components means that once a module (for example, an engine model or a battery system) is proven, it can be dropped into future projects with minimal modification. Reusing proven models not only saves time but also improves reliability since known-good components carry forward into new designs.
• Parallel development becomes possible as different specialists work on sub-models concurrently. A modular architecture allows electrical engineers, software developers, and mechanical designers to progress in tandem on their parts and integrate continuously, instead of waiting to merge one massive model at the end.
• Early hardware-in-the-loop testing is facilitated by modular design, making it easier to plug real hardware like controller boards or sensors into the simulation. Teams can start testing a real controller against a virtual plant long before a full prototype is built, catching integration issues sooner. This practice has been shown to prevent potential damage to real equipment, cut debugging costs, and reduce overall testing effort.
• Lower cost and risk result from virtual testing covering many scenarios (including edge cases) before physical hardware is involved. Organizations spend less on multiple prototypes and last-minute fixes, because problems uncovered in simulation are far cheaper to resolve than those found in field tests.

In these ways, modular simulation accelerates the entire cycle from concept to validation. Teams can iterate rapidly, incorporate real-world constraints earlier, and collaborate without stepping on each other’s toes. The end result is a development process that delivers better-tested, more robust designs in less time. Crucially, reaping these benefits at scale also requires embracing open standards so that modules from different tools and domains fit together seamlessly.

Open standards make multi domain integration seamless

One of the key enablers of modular, multi-domain simulation is the use of open standards for model interfaces. Engineers need to integrate components developed in different tools and by different teams, and proprietary formats or closed ecosystems make that integration clumsy. Standards like the Functional Mock-up Interface (FMI) have emerged to solve this problem. The vision behind FMI is that if a real product is assembled from many parts governed by different physics and control logic, one should be able to assemble a virtual product the same way—from a set of models of each part, each encapsulating its own physics and controls. An engine model from one vendor and a controller model from another can thus coexist in a shared simulation environment as long as both adhere to the FMI standard for exchanging data. By relying on such open interfaces, organizations avoid vendor lock-in and ensure that each module can talk to others, no matter which tool was used to create it.

Open standards make it practical to perform true multi-domain co-simulation. A power systems engineer can use an electrical grid simulator while a mechanical engineer uses a finite element model; through standard interfaces, their models can run together as one. This capability means teams choose the optimal tool for each domain without worrying about compatibility. It also smooths collaboration with external partners or suppliers—everyone can contribute their piece as an encapsulated module, confident that it will plug into the overall simulation. In essence, adopting open standards ensures that all the specialized simulations interconnect seamlessly to represent the behavior of the entire complex system.

Engineering workflows shift to modular simulation

Engineering leaders now recognize that simulation is no longer an afterthought in engineering—it has become central to the workflow from day one. Across industries, organizations are infusing simulation into each stage of design and development, a change enabled by the modular, real-time approaches described above. In a recent industry survey, faster time-to-market was identified as the number one expected benefit of simulation, surpassing even product performance gains. This reflects a mindset shift. Companies now treat simulation not just as a tool for troubleshooting or final validation, but as a driver of development speed and agility.

Traditional methods once forced teams to wait for a physical prototype to see how all the pieces worked together. Now, with modular models and advanced simulation techniques (from software-in-the-loop to full hardware-in-the-loop testing), teams integrate and iterate continuously. An embedded systems simulation can run in parallel with hardware design, ensuring the control software, electronics, and mechanical components all evolve in sync. By the time physical prototypes arrive, most integration issues have already been ironed out virtually. The overall engineering workflow has transformed, emphasizing simulation-driven development as a standard practice to meet the demands of today’s complex, software-driven products.

“Once a module is proven, it can be dropped into future projects with minimal modification.”

OPAL-RT’s commitment to modular, real-time simulation

As engineering workflows embrace modular simulation, OPAL-RT is committed to providing the open, real-time simulation platforms that make this approach practical. Its real-time digital simulators and software support open standards like FMI and integrate with tools such as Simulink, allowing engineers to combine models from different sources into one unified real-time platform. This means a development team can take advantage of modular design (reusing models and performing hardware-in-the-loop tests) without being limited by proprietary toolchains. The company’s focus on ultra-low latency hardware and a scalable, modular software architecture enables users to accurately simulate complex embedded systems and seamlessly connect virtual models with physical components in the lab.

This alignment with modular simulation isn’t new; it has been the foundation of our approach from the beginning. Across industries, engineering teams around the world use our real-time simulation technology to accelerate product development and ensure confidence in their designs. They can iteratively model, tweak, and validate each subsystem, then integrate everything with real hardware controllers as needed, all on the same cohesive platform. The end result is fewer surprises and a faster path from concept to reality.