scholarly journals Real-Time Controller Design Test Bench for High-Voltage Direct Current Modular Multilevel Converters

2020 ◽  
Vol 10 (17) ◽  
pp. 6004 ◽  
Author(s):  
Saddaqat Ali ◽  
Jahangir Badar ◽  
Faheem Akhter ◽  
Syed Sabir Hussain Bukhari ◽  
Jong-Suk Ro

Modular multilevel converters (MMCs), with their inherent features and advantages over other conventional converters, have gained popularity and remain an ongoing topic of research. Many scholars have solved issues related to the operation, control, protection, and reliability of MMCs using simulation software and small hardware prototypes. We propose a novel approach for an MMC controller design with real-time systems. By utilizing a key benefit of LabVIEW Multisim co-simulation, an MMC control algorithm that can be deployed on a field-programmable gate array (FPGA) was developed in LabVIEW. The complete circuit was designed in Multisim, and a co-simulation was performed to drive an MMC model. The benefit of this topology is that control algorithms can be designed in a LabVIEW FPGA and tested with the Multisim co-simulation circuit to obtain simulation results. Once the controller works and provides satisfactory results, the same algorithm can be deployed in any NI (National Instruments) FPGA-based controller, like a compact remote input/output (RIO), to control real-time MMCs designed in an NI PCI eXtensions for Instrumentation (PXI) system. This method saves time and provides flexibility for effectively designing control algorithms and implementing them in an FPGA for real-time model implementation.

Author(s):  
Matthew Viele ◽  
Isaac Liu ◽  
Guoqiang Wang ◽  
Hugo Andrade ◽  
Bryan Willson

Many modern engine systems are designed using one-dimensional computational fluid dynamics (1D CFD). This same technique can be used to model these systems in real time. This real-time model can be used to create virtual sensors in places where due to environmental or cost reasons physical sensors would not be practical. Achieving real-time performance of the CFD model requires more throughput than is available on single processor systems, so an Field Programmable Gate Array (FPGA) is employed. By employing an FPGA, we can synthesize and reconfigure our system to ensure determinism and lower resource usage. We instantiate several dedicated processing cores for parallel processing of sub-volumes. The number of cores can be configured to support up to 500 fluid volumes, more than enough for common 1D CFD models used in engines. This paper evaluates the feasibility of such a system and evaluates the complexity of such models against the GT-SUITE simulation software.


2014 ◽  
Vol 53 (38) ◽  
pp. 14755-14764 ◽  
Author(s):  
Valiollah Ghaffari ◽  
Paknosh Karimaghaee ◽  
Alireza Khayatian

Author(s):  
Mario L. Ferrari ◽  
Iacopo Rossi ◽  
Alessandro Sorce ◽  
Aristide F. Massardo

Abstract This paper presents a Model Predictive Controller (MPC) operating an SOFC Gas Turbine hybrid plant at end-of-life performance condition. Its performance was assessed with experimental tests showing a comparison with a Proportional Integral Derivative (PID) control system. The hybrid system operates in grid-connected mode, i.e. at variable speed condition of the turbine. The control system faces a multivariable constrained problem, as it must operate the plant into safety conditions while pursuing its objectives. The goal is to test whether a linearized controller design for normal operating condition is able to govern a system which is affected by strong performance degradation. The control performance was demonstrated in a cyber-physical emulator test rig designed for experimental analyses on such hybrid systems. This laboratory facility is based on the coupling of a 100 kW recuperated microturbine with a fuel cell emulation system based on vessels for both anodic and cathodic sides. The components not physically present in the rig were studied with a real-time model running in parallel with the plant. Model output values were used as set-point data for obtaining in the rig (in real-time mode) the effect of the fuel cell system. The result comparison of the MPC tool against a PID control system was carried out considering several plant properties and the related constraints. Both systems succeeded in managing the plant, still the MPC performed better in terms of smoothing temperature gradient and peaks.


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