Modeling and Simulation of Power Electronic Components
Modeling and simulation are essential aspects of the analysis and design process in power electronics. This first article in a short series will provide an overview of what modelling and simulating electronics means in the power space.
The process of building a model is referred to as modeling. Simulation is defined as the process of using a model to study the behavior and performance of an actual or theoretical system. In a simulation, models can be used to study existing or proposed characteristics of a system. The modeling approach for simulating large interconnected systems is proven to be very effective. Read on to learn more about the basics of modeling and simulation of power electronic components, and the pros and cons of modeling and simulation endeavors.
An Overview of Modeling and Simulation
The modeling and simulation concept involves the use of models as a basis for simulations to develop data that is utilized for decision making, both in terms of technical and management aspects. Models can be of any kind like physical, mathematical, or logical representation of the system, entity, process, or the phenomenon itself. Simulation is the process of using these models which function as digital prototypes of the actual physical model and predict their real-world performance. The basic elements of modeling and simulation lifecycle are as illustrated in Figure 1.
Figure 1: Basic elements of modeling and simulation lifecycle 
Power electronic systems are used extensively to enable power processing for a wide range of applications and power levels ranging from few milliwatts to hundreds of megawatts. They typically involve switching circuits that comprise semiconductor switches and diodes along with passive components like inductors, capacitors, and resistors. They may also include integrated circuits used for control purposes. Due to the complexity and vastness of these systems, the process of design and analysis of these systems pose a significant number of challenges.
In order to cater to this situation, modeling and simulation tools come in handy. They help a design engineer in gaining a better understanding of the operation of the circuit. This prepares the designer in choosing the right topology along with appropriate circuit components based on the specifications. This also works as a tool for evaluating the circuit performance while anticipating variations in operating conditions based on modifications to the circuit component values.
Differences Between Modeling and Simulation
The key difference between the modeling and simulation is that modeling serves as a process of building an exact representation of a physical system using different methods while simulation facilitates the determination of how a system responds to different inputs under different conditions. The scenarios are simulated to discover and understand how a real-life system performs while gaining insight into modeling aspects. When mathematical techniques are used to model a real-world situation, key variables, constraints and trade-offs are accounted for so that an optimal solution can be obtained such that it is both feasible and achieves targeted objectives .
On the other hand, simulation evaluates multiple scenarios in order to reveal and analyze system responses. This process involves the study of the behavior and performance of a real-world system through the testing of theoretical, mathematical, or physical representation of the system. For example, Monte Carlo is a simulation method that utilizes randomly generated inputs based on probability to determine the outcome of various scenarios. However, not all the outcomes could be feasible nor can a single optimal solution be finalized.
The Pros and Cons
Modeling helps in viewing the system from different perspectives. This also facilitates the discovery of the causes and effects of simulated scenarios using the model traceability aspect which is safe, accurate, and cost-effective. It helps in showcasing the system visually while helping in evaluating risk along with possible alternatives earlier in the lifecycle of the system development. Simulation helps in solving real-world problems and helps in evaluating feasible solutions by providing clear insights into the analysis of complex systems. It provides the ability to evaluate a product or system before actually building it in hardware . It helps in the exploration phase and in predicting unexpected issues. The real-time simulations add to the basic capabilities by enabling the option to vary the model run based on required speed and time intervals.
The crucial disadvantage of simulation is that it is only as good as the hypothesis and rules used to implement it. At times, it is extremely hard to create a model that is accurately realistic as the data and algorithms are based on research and information collected from past scenarios. The mistakes made by the programmer might adversely affect the decisions made by relying on the simulation results. This hampers the credibility of the model and might also be a result of inadequate model fidelity. There is a significant amount of time involved in the process of creating a reliable model along with a learning curve for use or reuse of the same. All of these have to be accounted for in the development cycle.
- Dragan Maksimovic et. al., Modeling and Simulation of Power Electronic Converters, 2001.
- Deniz et. al., Applying a model driven approach to component based modeling and simulation, 2010.
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