This study presents an energy management approach for a hybrid energy system comprised of a photovoltaic (PV) array and a polymer electrolyte membrane fuel cell (PEMFC). Two storage devices [a Li-ion battery module and a supercapacitor (SC) bank] are used in the proposed structure as a high-energy high-power density storage device. Multisegment converters for the PV, fuel cell (FC), battery, and SC are proposed for grid-independent applications. Nonlinear differential flatness-based fuzzy logic control for dc-bus voltage stabilization for power plant is investigated. To validate the control approach, a hardware system is realized with analog circuits for the PV, FC, battery, and SC current control loops (inner controller loops), and with numerical calculation (dSPACE) for the external energy control loop. Experimental results with small-scale devices [a PV array (800 W, 31 A), a PEMFC (1200 W, 46 A), a Li-ion battery module (11.6 Ah, 24 V), and an SC bank (100 F, 32 V)] demonstrate the excellent energy-management scheme during load cycles.

This paper presents a nonlinear control algorithm based on differential flatness approach for controlling a servo permanent magnet synchronous motor (PMSM) drive. The differential flatness approach is a model-based estimation. Subsequently, two state-observers are introduced to calculate a load torque disturbance and a stator resistance (representing losses in an inverter and motor) using its voltage drop. This can enable the improvement of the PMSM drive system and its efficiency. Using the flatness approach, we propose simple solutions to the dynamics and stabilization problems of the PMSM drive structure. In order to evaluate the proposed control algorithm, a hardware system is realized in a laboratory, and digital estimation is obtained using a dSPACE controller DS1104 platform. Simulation and experimental results with a small-scale motor of 1000 W and 3000 rpm in a laboratory corroborate the excellent control scheme during motor-drive cycles.

This paper presents an energy management approach for a hybrid energy system comprised of a photovoltaic (PV) array and a polymer electrolyte membrane fuel cell (PEMFC). A single storage device, i.e., a Li-ion battery module, is used in the proposed structure. Linear proportional-integral (PI) and nonlinear flatness-based controllers for dc bus stabilization for power plants are compared. To verify the control approaches, a hardware system is realized with analog circuits for the PV, FC, and battery current control loops (inner controller loops) and with numerical calculation (dSPACE) for the external energy control loops. Experimental results with small-scale devices [namely, a PV array (800 W, 31 A), a PEMFC (1200 W, 46 A), and a Li-ion battery module (11.6 Ah, 24 V)] illustrate the excellent energy management scheme during load cycles, and the nonlinear differential flatness-based control was determined to provide improved dc bus regulation relative to a classical linear PI control method.

DC microgrid applications include electric vehicle systems, shipboard power systems, and More Electric Aircraft (MEA), which produce power at a low voltage level. Rapid developments in hydrogen fuel cell (FC) energy have extended the applications of multi-phase parallel interleaved step-up converters in stabilizing DC bus voltage. The cascade architecture of power converters in DC microgrids may lead to large oscillation and even risks of instability given that the load converters considered as loads feature constant power load (CPL) characteristics. In this article, the output DC bus voltage stabilization and the current sharing of a multi-phase parallel interleaved FC boost converter is presented. The extended Port-Hamiltonian (pH) form has been proposed with the robust controller by adding an integrator action based on the Lyapunov−Energy function, named “Adaptive Hamiltonian PI controller”. The stability and robustness of the designed controller have been estimated by using Mathematica and Matlab/Simulink environments and successfully authenticated by performing experimental results in the laboratory. The results have been obtained using a 2.5 kW prototype FC converter (by two-phase parallel interleaved boost converters) with a dSPACE MicroLabBox platform. The FC main source system is based on a fuel reformer engine that transforms fuel methanol and water into hydrogen gas H₂ to a polymer electrolyte membrane FC stack (50 V, 2.5 kW).

This paper proposes a flatness control scheme for controlling the speed/torque of a permanent magnet synchronous motor (PMSM). As the flatness control, its performance largely depends on the accuracy of model parameters. So, to improve the performance of the flatness control, extended luenberger observer is utilized to estimate the parameter of PMSM such as a load torque disturbance and a stator resistance (represent losses in an inverter and PMSM) by means of its voltage drop, which has advantages over conventional observers such as independence from mathematical model accuracy, robustness, and good dynamic performance. Also, only observer gains need to be tuned and the tuning process is not complicated because the gains are determined by the desired observer bandwidth. To validate the proposed method, a hardware system is realized in a laboratory, and digital estimation is accomplished with a dSPACE controller DS1104 platform. Simulation and experimental results with a small-scale PMSM of 6-pole, l-kW, and 3000 rpm in a laboratory corroborate the excellent control scheme during a motor-driven cycle.

The two new state observers are proposed in this paper to improve the performance and robustness of the flatness-based control against the changeable parameter. The hardware system of the PMSM control is implemented by using a small-scale PMSM of 6-pole, 1-kW, and 3000 rpm in a laboratory, to validate the proposed methodology. Simulation and experimental validation reflect that the two new state observers are better than the linear observer such as extended Luenberger observer (ELO) method regarding convergence for nonlinear systems and convergence rapidity.