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Graphite, a key anode material in lithium-ion batteries, primarily relies on the Acheson graphitization furnace (AGF) for production. This research focuses on the power supply module of the AGF, particularly the electrodes and their power transmission clamps. A three-dimensional transient electric-thermal-fluid coupling model was developed to numerically analyze the temperature and electric field distributions during operation. The study revealed that heat conduction through furnace electrodes dominates temperature rise. Notably, clamping plates within transmission clamps exhibit high temperatures and gradients, posing a thermal failure risk. Efficient cooling plate design with liquid-cooled channels is crucial for temperature control. Additionally, maintaining high electrode temperatures reduces resistivity, lowering power consumption in the power supply module. This study provides insights into optimizing AGF power supply module design, emphasizing the importance of effective cooling strategies for clamping plates and the benefits of maintaining elevated electrode temperatures for energy efficiency.

In this study, a robust predictive power control (R-PPC) method for an N*3-phase permanent magnet synchronous motor (PMSM) is developed in the field of flywheel energy storage systems application, which can effectively improve robustness against inductance parameter mismatch and compensate for the one-beat delay. Firstly, the mathematical model of the N*3-phase PMSM is illustrated, and the topological structure of the N*3-phase PMSM is established. The R-PPC method of the N*3-phase PMSM is then proposed by using the d–q axis current robust predictive control theory. Robustness factors are adopted to modify the current response values in the proposed robust predictive power controller, which can obtain excellent current control performance under the inductance parameter mismatch. Moreover, the next current predicted value is used to replace the current sampled value in the proposed R-PPC method to eliminate the one-beat delay. Finally, comparative simulation and experimental results verify that the proposed R-PPC method can achieve excellent current track performance and smaller torque ripple under both the charge state and discharge state.

The ESS is considered as an effective tool for enhancing the flexibility and controllability of a wind farm, and the optimal control scheme of a wind farm with distributed ESSs is vital to the stable operation of wind power generation. In this paper, a coordinated active and reactive power control strategy based on model predictive control (MPC) is proposed for doubly fed induction generator (DFIG)-based wind farm (WF) with distributed energy storage systems (ESSs). The proposed control scheme coordinates the active and reactive power output among DFIG wind turbines (WTs), grid-side converters (GSCs), and distributed ESSs inside the WF, and the aim is to decrease fatigue loads of WTs, make the WT terminal voltage inside the extent practicable, and take the WF economic operation into consideration. Moreover, the best reactive power references of DFIG stator and GSC are produced independently based on their dynamics. At last, the control scheme generates optimal power references for all ESS to make the SOC of each ESS converge to their average state. With the distributed ESSs, the WF controller regulates the WTs inside WF more flexibly. A WF composed of 10 DFIG WTs was utilized to verify the control performance of the proposed coordinated active and reactive power control strategy.

High power density energy storage permanent magnet (PM) motor is an important energy storage module in flywheel energy storage system for urban rail transit. To expand the application of the PM motor in the field of urban rail transit, a predictive power control (PPC) strategy for the N*3-phase PM energy storage motor is proposed in this paper. Firstly, the output characteristics of the N*3-phase PM energy storage motor are analyzed by using the finite element method, and the mathematical model of the N*3-phase PM energy storage motor is established. Then, the topological structure and operation principle of N*3-phase PM energy storage motor system is illustrated. Furthermore, the N*3-phase PM energy storage motor system driven by six parallel voltage source inverters (VSIs) is proposed to generate the required power. Finally, a novel predictive direct power control method is developed for the N*3-phase PM energy storage motor. The feasibility and effectively of the proposed PPC method are verified by experiment and simulation. Comprehensive simulation and experimental results both show that the proposed PPC method can obtain the lower torque/stator flux ripple, smaller values of THD of stator winding currents, and zero error tracking of stator winding flux.

Accurate detection of ripple components of the direct-current (DC) signals is essential for evaluating DC power quality. In this study, the combination algorithm based on variational mode decomposition (VMD) and Hilbert transform (HT) is applied to detect and analyze the characteristics of the ripple components of the DC disturbance signals. Firstly, the optimal modal number of VMD algorithms is comprehensively determined by observing the center frequencies of the mode components and the Index of Orthogonality (IO) of mode components. Through utilizing the VMD algorithm, the DC disturbance signal is accurately decomposed into a series of amplitude modulation-frequency modulation (AM-FM) functions. Then, the HT algorithm is applied to each AM-FM function to obtain the corresponding instantaneous amplitude and frequency, and the characteristics of DC disturbance signal are determined. Some case studies are implemented to analyze the ripple components of the DC disturbance signal with the VMD-HT and empirical mode decomposition (EMD) algorithm. Finally, the experiment results of Gree Photovoltaic Cabin have verified the feasibility and effectiveness of the proposed combination VMD-HT algorithm by comparison with EMD and the window interpolation fast Fourier transform (WIFFT) algorithms.

In recent years, modular multilevel converters (MMCs) have developed rapidly, and are widely used in medium and high voltage applications. Model predictive control (MPC) has attracted wide attention recently, and its advantages include straightforward implementation, fast dynamic response, simple system design, and easy handling of multiple objectives. The main technical challenge of the conventional MPC for MMC is the reduction of computational complexity of the cost function without the reduction of control performance of the system. Some modified MPC scan decrease the computational complexity by evaluating the number of on-state sub-modules (SMs) rather than the number of switching states. However, the computational complexity is still too high for an MMC with a huge number of SMs. A reverse MPC (R-MPC) strategy for MMC was proposed in this paper to further reduce the computational burden by calculating the number of inserted SMs directly, based on the reverse prediction of arm voltages. Thus, the computational burden was independent of the number of SMs in the arm. The control performance of the proposed R-MPC strategy was validated by Matlab/Simulink software and a down-scaled experimental prototype.

This paper proposes a robust nonlinear predictive current control (RNPCC) method for permanent magnet synchronous motor (PMSM) drives, which can optimize the current control loop performance of the PMSM system with model parameter perturbation. First, the disturbance caused by parameter perturbation was considered in the modeling of PMSM. Based on this model, the influence of parameter perturbation on the conventional predictive current control (PCC) was analyzed. The composite integral terminal sliding mode observer (SMO) was then designed to estimate the disturbance caused by the parameter perturbation in real time. Finally, a RNPCC method is developed without relying on the mathematical model of PMSM, which can effectively eliminate the influence of parameter perturbation by injecting the estimated disturbance value. Simulations and experiments verified that the proposed RNPCC method was able to remove the current error caused by the parameter perturbation during steady state operation.

The dc-link voltage balance and reactive power equilibrium of the cascaded H-bridge rectifier (CHBR) are the prerequisites for the safe and stable operation of the system. However, the conventional PI (Proportional-Integral) control strategy only puts emphasis on the CHBR dc-link voltage balance without taking into account its reactive power equilibrium under capacitive and inductive working conditions. For this reason, this paper has proposed a novel control strategy for the CHBR that can not only balance dc-link voltage, but also achieve reactive power equilibrium and eliminate the coupling effect between the voltage-balancing controller (VBC) and original system controller (OSC). The control strategy can achieve dc-link voltage balance and the reactive power equilibrium of the CHBR through modifying the active duty cycle by closed loop control, and adjusting the reactive duty cycle relatively according to the modifiable amount of the active duty cycle. Moreover, the strategy can eliminate the coupling effect between the VBC and OSC by the open loop control modification of the active and reactive duty cycle of any H-bridge module in CHBR. Simulations and experiments have shown that the proposed control strategy is feasible and effective in performing the CHBR dc-link voltage balance and reactive power equilibrium under all working conditions and load variations.

This paper presents a cascaded robust fault-tolerant predictive control (CRFTPC) strategy with integral terminal sliding mode observer (IT-SMO) to achieve high performance speed loop and current loop for permanent magnet synchronous motor (PMSM) drives. The modeling of PMSM considers the disturbance caused by parameter perturbation and permanent magnet demagnetization. With this model, we can derive the optimal control law of the proposed scheme, which avoids the tuning work of the weight factor effectively. This new CRFTPC strategy has a cascaded structure, external loop and internal loop, both implemented with robust fault-tolerant predictive control. In addition, a new integral terminal sliding mode observer is designed to estimate the disturbances, and thus the robustness of the proposed method can be increased significantly. Comparative simulations and experimentations verify that the proposed CRFTPC provides fast dynamic response, static-errorless speed, and current tracking, even with the system disturbance.

The permanent magnet synchronous motor (PMSM) with dual-rotating rotors is a typical nonlinear multi-variable coupled system. It is sensitive to load disturbances and the change of interior parameters. The traditional proportional-integral (PI) controller is widely used in the speed control of a motor because of its simplicity; however, it cannot meet the requirements needed for high performance. In addition, when the loads of both of the rotors change, it is difficult to ensure that the system runs stably. With an aim to mitigate these problems, a method called master-slave motor control is proposed to guarantee the stability of the motor system in all cases. And then, a speed controller is designed to eliminate the influence of uncertain terms. The proposed control strategy is implemented both in simulations and in experiments. Through the analysis and comparison of the proportional-integral (PI) controller and the sliding-mode controller, the effectiveness of the proposed control strategy is validated.

The demands of remarkable reliability and high power density of traction systems are becoming more and more rigorous. The conflicting requirements imposed on the control strategy are higher accuracy and higher efficiency over the whole speed range. However, parameter variations caused by the cross coupling and magnetic saturation effect (omitted from the cross saturation effects in the following) are usually neglected in conventional control strategies, which could reduce the control precision. In order to fully consider the influence of parameter changes on the motor control and derive an approach that could realize the maximum efficiency during the whole speed range, this paper proposes a dynamic DC-link voltage adjustment strategy considering the cross coupling and magnetic saturation effects. The strategy can be categorized into three parts. Firstly, the torque request is transformed to the optimal current reference signal. Secondly, the differences between the setpoint and the real-time feedback signals of torque and voltage can be applied in the linearized function in the did,q coordinate. The solution guides the current vector into the optimal direction under the current and voltage limits to ensure the safety and reliability of the motor. Finally, last, the bus voltage can be modified according to the asked terminal voltage. A 10 kW prototype which instrumented a bidirectional DC-DC converter to regulating the bus voltage has been studied. The simulation and experiment results verify that the proposed control strategy can reduce the inverter losses in low speed region by offering the low bus voltage and track the actual maximum torque control trace more accurately, meanwhile, the flux weakening region can be delayed in high speed region by applying a high bus voltage. It helps the motor realize the high utilization rate of the DC-link voltage and guarantees the system reliability and robustness.