Finite Control Set – Model Predictive Control Based On Sliding Mode For Bidirectional Power Inverter

Estrada, Leonel; Vázquez, N.; Vaquero, Joaquín; Hernandez, C.; Arau, J.; Huerta, Héctor

doi:10.1109/tec.2021.3063601

Cited by 19 publications

(7 citation statements)

References 45 publications

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“…Figure 15 shows the bidirectional inverter used as a gateway between the NG and the AC mains. The detailed model of the bidirectional inverter can be found in [16]. The difference equations associated with this converter are:…”

Section: Power Converter Modelsmentioning

confidence: 99%

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Asynchronous and Decoupled HIL Simulation of a DC Nanogrid

et al. 2022

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In this paper, an asynchronous and decoupled Hardware-In-the-Loop simulation of a DC nanogrid is presented. The DC nanogrid is a recent way to solve problems presented in traditional power generation, such as low efficiency, pollution, and cost increase. The complexity of this kind of system is high due to the interconnection of all the composing elements, making the use of HIL simulation attractive due to its advantages regarding computational power and low solution time. However, when a nanogrid is simulated in commercial and personalized platforms, all the elements presented are solved at the same integration time, even if some elements could be solved at smaller integration times, causing a slowdown of the system solution. The results of the asynchronous HIL simulation are compared with a synchronous HIL simulation with an integration time of 425 ns, and also with an offline simulation performed in PSIM software. The proposal achieves an integration time of 200 ns for the fastest element and 425 ns for the slowest, with an error of less than 0.2 A for current signals and less than 2 V for voltage signals. These results prove that the asynchronous and decoupled solution of an HIL simulation for nanogrid is possible, allowing each element to be solved as fast as possible without affecting the accuracy of the result, as well as simplifying programming.

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Section: Power Converter Modelsmentioning

confidence: 99%

“…Figure19shows the implementation of the BI model, the generation of the three-phase power supply signals, and the control used for this converter based on[16].…”

mentioning

confidence: 99%

Asynchronous and Decoupled HIL Simulation of a DC Nanogrid

et al. 2022

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“…There are two types of HIL the controller hardware in the loop (CHIL) and the power hardware in the loop (PHIL). In CHIL the objective is to test the controller, in Mitsugi et al (2020) it is used to test the control of an energy storage system, in Amiri et al (2020), it is used to test the controller of a converter used to correct the power factor, in Zucuni et al (2020), and (Estrada et al, 2021), it is used to test a new cost function for predictive controllers, in Busarello et al (2020) it is used to test digital controls for converters connected to the electrical network, the HIL simulation is helpful to reduce the time to market for new products.…”

Section: Introductionmentioning

confidence: 99%

Practical considerations for HIL simulations of power converters using different numerical methods

Estrada,

Vázquez,

Tafoya

et al. 2023

JART

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The use of Hardware-In-the-Loop systems implemented in FPGAs is constantly growing due to their performance. However, hardware implementation of numerical methods to solve differential equations presents some challenges when applied to power converters. This paper shows a comparison of several numerical methods: Euler, Heun, Midpoint and 4th order Runge-Kutta, taking into account the accuracy of the methods and how they can be applied to power converters, where the equations change depending on the status of the switches. Results show that the speed in the solution of the numerical method is the main variable that affects the accuracy of the simulation, so in order to keep a fast resolution speed numerical method with low resources should be used.

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“…Although the robustness is improved, it is essentially a multi-loop control instead of single-loop multi-variable control, which may increase the implementation complexity. In [26], [27], the reaching conditions of continuous-time SMC are included in the cost function of FS-MPC to guarantee the stability. Nevertheless, the control objective is to find the most negative value of the cost function instead of minimizing the tracking errors, which may degrade the steady-state performance.…”

Section: Introductionmentioning

confidence: 99%

Finite-Set Quasi-Sliding Mode Predictive Control of $ LC$-Filtered Voltage Source Inverters

Zheng

Gong

et al. 2022

IEEE Trans. Ind. Electron.

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Finite Control Set – Model Predictive Control Based On Sliding Mode For Bidirectional Power Inverter

Cited by 19 publications

References 45 publications

Asynchronous and Decoupled HIL Simulation of a DC Nanogrid

Asynchronous and Decoupled HIL Simulation of a DC Nanogrid

Practical considerations for HIL simulations of power converters using different numerical methods

Finite-Set Quasi-Sliding Mode Predictive Control of $ LC$-Filtered Voltage Source Inverters

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