# Real-Time Simulator for Dynamic Systems on FPGA
## 2 Related Work  
In the work of [12], a low-cost RTS was proposed, which could be constructed in the laboratory for use in electronic power systems. The system could be implemented on a computer possessing a multi-core processor together with data acquisition and signal conditioning systems. In another similar approach, but using a general-purpose process sor, a low-cost RTS was described that could easily be developed in the laboratory using \(\mu\)Ps and \(\mu\)Cs [1]. This proposal involved a distributed architecture composed of different hardware platforms, enabling it to be constructed with limited resources. As an example, a case study was presented where the RTSDS was composed of a personal computer (Intel DN2800 MT Mini-ITX) associated with low-cost and easily obtained hardware platforms (with embedded software), such as the Arduino and CY8 CKIT-001 kits [26; 27; 28; 29; 30]. RTS proposals using general-purpose processors have been described by [2; 3], offering distributed software solutions for RTS, in which many computers are used in an internet network in order to simulate real-time systems. The benefits of using RTS in undergraduate and postgraduate engineering courses are described in detail in [13; 14], which describes several commercial RTS tools. The signal processing techniques presented in [15] aim to reduce the sampling frequency and computational cost associated with RTS. It was demonstrated that the computational cost could be reduced up to 100-fold, without compromising the precision of the simulation. In [16], a methodology consisting of seven steps is described for the validation of real-time simulation models. Real-time simulators have been proposed for power systems that use FPGAs associated with computers, where the main advantage is parallel implementation of the simulated dynamic systems [6; 8; 9]. Hardware-in-the-loop (HIL) systems have been described by [4; 5; 10; 31]. In [4], an FPGA platform was used for digital hardware implementation of a real-time simulator for a multi-phase system. According to the author, this could be developed using an ordinary computer, but this would not allow the real-time simulations that are essential for control using HIL. The implementations employed a Xilinx SP605 kit that included a Spartan-6 FPGA to facilitate the implementation of the system inputs and outputs. The kit has a 200 MHz clock, and the PWM signals use 50 and 100 MHz clocks derived from the main clock, resulting in the model having a simulation step of 40.96 \(\mu\)s. The performance of the real-time system was evaluated using a configuration with an induction motor model (DT-PIM) in Matlab/Simulink and the system step used the fourth-order Runge-Kutta method. The experimental results and statistical comparisons showed satisfactory performance of the Matlab/System Generator environment, in the absence of bench tests. Already, in [10], a simulation framework with HIL has been described to estimate the state of Li-ion batteries in electric vehicles. In this work, the framework was implemented on FPGA and it shows that this is a fast simulation strategy. The high-performance real-time simulator on FPGA is showed in [31]. In this work, the simulator was implemented on Altera's FPGA using the DE3-150 development kit and a low fixed sample time was achieved, at about 500 ns. In [11], an implementation is presented of a dynamic system molecular model. In order to improve the execution time, this model is accelerated using the FPGA. In [5], a model is proposed for a permanent magnet synchronous motor. The system uses the HIL approach, where a Matlab/Simulink vehicle model is executed in conjunction with an embedded engine model in a Virtex-6 (XC6 VLX240T) FPGA of the ML605 development kit. This system performs its actions with a cycle of 2 \(\mu\)s, and in [7], the real-time Hardware-in-the-Loop (HIL) simulation of vehicle systems is presented.