Key Takeaways
- CPU-only tools often force larger step sizes or added delays that erode fidelity at the exact moments that matter.
- Specialized real-time solvers preserve accuracy in familiar models while keeping strict fixed steps for fast events.
- FPGA solvers capture sub-microsecond dynamics so controllers experience realistic switching behavior and protection timing.
- A hybrid CPU plus FPGA split lets you scale grids and converters without rewriting models or sacrificing detail.
- Consistent build and test pipelines shorten iterations, reduce risk, and raise trust in final design choices.
Conventional simulation tools become a bottleneck when faced with the speed and complexity of modern electrical systems. Engineers worry that their models might not capture every fast transient or instability, making critical design validation riskier. In fact, the rise of high-frequency power converters in renewable energy grids has revealed new reliability issues – converter failures are now identified as major contributors to power outages. This high-stakes reality means simulations must run at true real-time speeds without sacrificing fidelity. At OPAL-RT, we believe engineers should never be held back by their tools, and decades of pushing real-time simulation boundaries have shown that integrating advanced algorithms with specialized hardware can eliminate these bottlenecks. The result is an ability to test bold, complex systems quickly and with total confidence in the results.
Standard simulation tools struggle to meet real-time performance requirements
Traditional CPU-based simulators often falter when attempting to keep up with fast, complex systems. Engineers frequently encounter numerical instability or have to simplify models just to make them run. Below are some common pain points that highlight why standard tools struggle to keep up:
- Limited time-step resolution: General-purpose electromagnetic transient (EMT) simulators typically operate with fixed steps on the order of 5–100 microseconds. However, capturing fast switching events or fault transients may require time steps near the 100-nanosecond range, orders of magnitude beyond what conventional CPU solvers can reliably achieve.
- Accuracy trade-offs from model delays: To cope with CPU limitations, engineers often introduce tiny delays or increased step sizes in their models. These artificial tweaks keep simulations running but at a cost: even minor time delays inserted for stability can noticeably reduce accuracy, undermining the fidelity that real-time simulation is supposed to provide.
- Parallel processing limits: Multi-core processors and software tricks can improve throughput, but certain high-speed control loops and power electronic interactions remain inherently difficult to parallelize. Some computations must occur sequentially, meaning a fast-switching converter or a stiff network subsystem can still bottleneck the entire simulation. In practice, this means critical transients might be missed or overly smoothed out because the simulator cannot solve all equations within the strict real-time deadlines.
- Scale versus speed dilemma: As models grow to include larger sections of a power grid or more detailed converter circuitry, the computational load per time step increases. Teams often end up compromising on detail (for example, grouping devices into a single averaged unit) to avoid overruns in step time. This trade-off between system scale and simulation speed leaves gaps in insight, since a simplified model might ignore localized phenomena that turn out to be crucial during actual operations.
These challenges illustrate why relying on out-of-the-box simulation tools can hold back innovation. When your simulator introduces doubt, via numerical errors, missed events, or forced simplifications, it becomes harder to trust the results. Engineers need solutions that eliminate these barriers. A simulator should behave just like the real system, no matter how complex or fast it gets.
Integrating standard models with specialized solvers preserves accuracy at real-time speeds
Advanced simulation specialists tackle these limitations by enhancing familiar modeling tools with high-performance solver technology. Rather than forcing engineers to dramatically simplify models, the approach is to improve how the simulation itself is computed. One proven method is integrating domain-specific real-time solvers directly into platforms like Simscape Electrical™. This allows teams to keep using their standard MATLAB/Simulink® models while gaining the stability and speed of a custom solver under the hood.
For example, the ARTEMiS solver is designed to work alongside Simscape Electrical models to ensure numerical stability at fixed time steps. It uses an advanced decoupling technique that avoids introducing artificial delays between subsystems, thereby preserving model fidelity even in large-scale grid simulations. In practical terms, this means an engineer can take a detailed Simulink model of a complex power network and run it in real time without the usual hacks or loss of detail. The solver partitions the network into smaller solvable blocks and handles them with optimized algorithms that remain stable at the required speed. Crucially, this decoupling is delay-free – the simulator does not rely on slowing down or damping the interactions between components to maintain stability. As a result, the outcomes closely mirror a high-fidelity offline simulation, but they are generated instantly, step-by-step, in lockstep with the clock.
“Conventional simulation tools become a bottleneck when faced with the speed and complexity of modern electrical systems.”
Collaboration between standard tools and specialized solvers also streamlines workflows. Engineers can develop models in the tools they know (like Simulink) and simply toggle on a real-time mode when ready to execute on a target machine. Under the surface, solvers automatically handle stiff equations and rapid switching events so that even notoriously tough components compute without instability. Industry experience shows this approach can reliably simulate sizeable systems that would normally be on the edge of instability. By preserving detail and accuracy at real-time speeds, specialized solvers give engineers a powerful alternative to “dumbing down” their models.
FPGA-based solvers are essential for modern high-fidelity electrical simulation
While advanced CPU solvers dramatically improve real-time performance, some scenarios simply require more speed than any general-purpose processor can handle. Field-Programmable Gate Arrays (FPGAs) have emerged as the indispensable tool for ultra-high-fidelity real-time simulation. These reconfigurable chips run computations in true parallel and at clock speeds that allow time steps in the sub-microsecond range. In effect, an FPGA-based solver can represent the physics of fast switching devices and electromagnetic transients with hardware-like granularity.
The difference FPGAs make is striking. For example, one FPGA-based simulation handled 1,200 power semiconductor switches with only a 373 ns time-step while maintaining 99.83% accuracy. These numbers are not just academic; they translate directly into the ability to model high-frequency phenomena like fast switching transitions or the propagation of transients through a large network. In contrast, a CPU-based simulator would either crash, slow down dramatically, or be forced to average out these dynamics.
FPGA-based solvers excel because they can compute many operations simultaneously. An FPGA can dedicate different logic circuits to solve parts of the model in parallel, for example, solving matrix equations while integrating device models in the same clock cycle. This massive parallelism means even large-scale systems can be simulated with uncompromising detail. Modern real-time simulation platforms often pair CPUs with FPGAs: the CPU manages the overall model and interfaces, while FPGA boards handle the sub-microsecond calculations. The result is a simulator that can run a 50 kHz switching converter in real time, capturing each pulse and transient where earlier generation tools would have had to slow things down or omit details entirely.
“Field-Programmable Gate Arrays (FPGAs) have emerged as the indispensable tool for ultra-high-fidelity real-time simulation.”
Pushing real-time simulation boundaries accelerates innovation and builds confidence in design
Seamless hardware-in-the-loop testing
Real-time simulation at high fidelity makes hardware-in-the-loop (HIL) testing seamless. Modern real-time simulators achieve such precise timing that real hardware cannot tell it isn’t connected to the actual system. Engineers can plug in physical controllers or protection devices and test them under rigorous, lifelike conditions. The simulator is capable of injecting faults, for example, a sudden voltage spike or component failure, and the controller will react exactly as it would in the field. This means teams can verify their control software and hardware across countless scenarios, including extreme corner cases that would be too risky or impractical to test on physical equipment.
Validating complex systems with confidence
Perhaps the greatest advantage of advanced real-time simulation is the confidence it brings to final design decisions. Modern designs in every sector – from electric vehicle powertrains to renewable-rich power grids to aerospace systems – involve countless interactions and edge cases that must be validated. Engineers can subject their projects to events like multi-cycle grid faults, rapid load changes, or device failures and observe how the entire system responds. High-fidelity simulators capture subtle effects that simpler models miss, ensuring that potential problems are discovered virtually instead of for the first time in the field. This proactive approach avoids costly surprises and means the final design has already been proven in a digital twin of the system.
Advanced users leverage the ARTEMiS toolbox as a plug-in solver within Simscape Power Systems (formerly SimPowerSystems) to achieve real-time accuracy. Practically, this means building the electrical model in Simscape Electrical™ as usual, and then selecting ARTEMiS as the fixed-step solver when running on real-time hardware. ARTEMiS augments the standard model by automatically partitioning the network and applying numerical stabilization techniques so the simulation remains stable at the chosen time step. The result is that engineers can simulate complex power systems – like microgrids or multi-motor drives – in real time without adding artificial delays or simplifying the model. In essence, ARTEMiS serves as a real-time execution engine that ensures the Simscape model’s fidelity is preserved at high speed.
FPGA-based solvers have become essential because modern electrical systems often involve phenomena that unfold faster than what traditional CPU solvers can handle. High-frequency power electronic devices, such as silicon carbide (SiC) or gallium nitride (GaN) converters, switch so quickly that to simulate them accurately, you need extremely small time steps. FPGAs can compute these tiny step simulations in parallel, which is something general CPUs struggle with at scale. By using FPGAs, simulators can capture every rapid transient and switching event, so they accurately model everything from high-speed motor drives to lightning-fast protection circuits. Essentially, FPGA solvers ensure that a simulation’s resolution is fine enough to mirror reality in cases where even microsecond-level steps would blur important details.
CPU-only real-time simulations are limited by the sequential nature and clock speed of general-purpose processors. As simulation models grow in complexity – with more nodes, switching elements, and control loops – a CPU has to perform more calculations in the same fixed time step. Eventually it hits a point where it cannot finish all computations before the next step is due, leading to missed deadlines or the need to increase the step size. Engineers often must simplify models under CPU-only constraints, for instance by grouping components or reducing switching speeds, which can omit critical dynamic behaviors. Moreover, some power electronics simulations involve very stiff equations that are prone to numerical instability on a CPU unless the step size is made larger. All these factors mean a CPU-only approach might not faithfully simulate extremely fast or large-scale systems, limiting the scenarios you can confidently test.
Yes, one of the big advantages of advanced real-time simulators is their ability to explore and predict rare failure conditions that might be hard to recreate otherwise. Because these simulators can run highly detailed models, engineers can insert fault conditions or extreme events into the simulation and observe the outcomes. For instance, a real-time simulator can model what happens if a circuit breaker in a power grid fails to open on time, or how a multi-inverter renewable energy system behaves during an unplanned islanding event. By accelerating or repeating scenarios in the simulator, you might discover failure modes that would normally take years of actual operation to surface. Importantly, when the simulation runs in real time, it can interact with actual protective devices or controllers, revealing how the entire system (both hardware and software) responds to those rare events. This predictive capability helps engineers design more robust systems and put safeguards in place for events that are unlikely but possible. In short, high-fidelity real-time simulation enables a proactive approach to reliability, where potential failures are understood and mitigated in advance.
