Closed-loop Power Control Research Articles

Closed-Loop Direct Power Control of Brushless DC Motor in Field Weakening Region

Closed-Loop Direct Power Control of Brushless DC Motor in Field Weakening Region

Power control in LTE based on heuristic game theory for interference management

In the conventional LTE homogeneous network, sufficient transmit power of user equipment (UE) is determined by open-loop power control (OL-PC) and closed-loop power control (CL-PC) schemes. However, in a Het-Net environment, setting the UE’s transmit power requires delicate responsiveness to handle the severe and complicated uplink interference. In this paper, an interference-aware uplink power control mechanism based on Heuristic game theory approach is proposed for devices coexisting in a heterogeneous wireless network. Various wireless constraints like channel response, path loss, fading, shadowing, interference and metrics like SNR, SINR, throughput and bit rates are considered. Uplink power is controlled by suitably selecting the penalization factor (β) based on a simple Heuristic game theory approach considering the possible wireless constraints of each user depending on its location in the cell under consideration. The algorithm is framed in such a way to reduce inter-cell interference, limit transmit power, enhance bit rates and throughput of users. A significant improvement of 5.2% in the user coverage/distribution is achieved as a result of interference management compared to conventional power control scheme and power control with convex pricing.

ControlPULP: A RISC-V On-Chip Parallel Power Controller for Many-Core HPC Processors with FPGA-Based Hardware-In-The-Loop Power and Thermal Emulation

High-performance computing (HPC) processors are nowadays integrated cyber-physical systems demanding complex and high-bandwidth closed-loop power and thermal control strategies. To efficiently satisfy real-time multi-input multi-output (MIMO) optimal power requirements, high-end processors integrate an on-die power controller system (PCS). While traditional PCSs are based on a simple microcontroller (MCU)-class core, more scalable and flexible PCS architectures are required to support advanced MIMO control algorithms for managing the ever-increasing number of cores, power states, and process, voltage, and temperature variability. This paper presents ControlPULP, an open-source, HW/SW RISC-V parallel PCS platform consisting of a single-core MCU with fast interrupt handling coupled with a scalable multi-core programmable cluster accelerator and a specialized DMA engine for the parallel acceleration of real-time power management policies. ControlPULP relies on FreeRTOS to schedule a reactive power control firmware (PCF) application layer. We demonstrate ControlPULP in a power management use-case targeting a next-generation 72-core HPC processor. We first show that the multi-core cluster accelerates the PCF, achieving 4.9x speedup compared to single-core execution, enabling more advanced power management algorithms within the control hyper-period at a shallow area overhead, about 0.1% the area of a modern HPC CPU die. We then assess the PCS and PCF by designing an FPGA-based, closed-loop emulation framework that leverages the heterogeneous SoCs paradigm, achieving DVFS tracking with a mean deviation within 3% the plant’s thermal design power (TDP) against a software-equivalent model-in-the-loop approach. Finally, we show that the proposed PCF compares favorably with an industry-grade control algorithm under computational-intensive workloads.

Multi-resonator Wireless Inductive Power Link for Wearables on the 2D Surface and Implants in 3D Space of the Human Body.

This paper presents a novel resonance-based, adaptable, and flexible inductive wireless power transmission (WPT) link for powering implantable and wearable devices throughout the human body. The proposed design provides a comprehensive solution for wirelessly delivering power, sub-micro to hundreds of milliwatts, to deep-tissue implantable devices (3D space of human body) and surface-level wearable devices (2D surface of human skin) safely and seamlessly. The link comprises a belt-fitted transmitter (Belt-Tx) coil equipped with a power amplifier (PA) and a data demodulator unit, two resonator clusters (to cover upper-body and lower-body), and a receiver (Rx) unit that consists of Rx load and resonator coils, rectifier, microcontroller, and data modulator units for implementing a closed-loop power control (CLPC) mechanism. All coils are tuned at 13.56 MHz, Federal Communications Commission (FCC)-approved industrial, scientific, and medical (ISM) band. Novel customizable configurations of resonators in the clusters, parallel for implantable devices and cross-parallel for wearable devices and vertically oriented implants, ensure uniform power delivered to the load, PDL, enabling natural Tx power localization toward the Rx unit. The proposed design is modeled, simulated, and optimized using ANSYS HFSS software. The Specific Absorption Rate (SAR) is calculated under 1.5 W/kg, indicating the design's safety for the human body. The proposed link is implemented, and its performance is characterized. For both the parallel cluster (implant) and cross-parallel cluster (wearable) scenarios, the measured results indicate: 1) an upper-body PDL exceeding 350 mW with a Power Transfer Efficiency (PTE) reaching 25%, and 2) a lower-body PDL surpassing 360 mW with a PTE of up to 20%, while covering up to 92% of the human body.

A deep reinforcement learning-based power control scheme for the 5G wireless systems

In the fifth generation (5G) wireless system, a closed-loop power control (CLPC) scheme based on deep Q learning network (DQN) is introduced to intelligently adjust the transmit power of the base station (BS), which can improve the user equipment (UE) received signal to interference plus noise ratio (SINR) to a target threshold range. However, the selected power control (PC) action in DQN is not accurately matched the fluctuations of the wireless environment. Since the experience replay characteristic of the conventional DQN scheme leads to a possibility of insufficient training in the target deep neural network (DNN). As a result, the Q-value of the sub-optimal PC action exceed the optimal one. To solve this problem, we propose the improved DQN scheme. In the proposed scheme, we add an additional DNN to the conventional DQN, and set a shorter training interval to speed up the training of the DNN in order to fully train it. Finally, the proposed scheme can ensure that the Q value of the optimal action remains maximum. After multiple episodes of training, the proposed scheme can generate more accurate PC actions to match the fluctuations of the wireless environment. As a result, the UE received SINR can achieve the target threshold range faster and keep more stable. The simulation results prove that the proposed scheme outperforms the conventional schemes.

A simple closed-loop interphase power controller for cascaded H-bridge converter-based DG units in islanded microgrids with imbalanced loads

A simple closed-loop interphase power controller for cascaded H-bridge converter-based DG units in islanded microgrids with imbalanced loads

Reactive Power Minimization for Modular Multi-Active-Bridge Converter With Whole Operating Range

Multi-port power electronic transformers (PET) are widely used in modern power systems to facilitate flexible interconnection between various AC or DC buses, power sources, and loads. However, due to the wide range of “source-load-storage” operating points, achieving efficient operation of the isolated DC-DC converter in the PET can be challenging. This paper focuses on the modular multi-active bridge (MMAB) converter in the PET, and proposes an optimization modulation scheme based on reactive power minimization (RPM) to improve efficiency. The RPM scheme utilizes a simple reactive power open-loop and active power closed-loop control structure that can be modulated online without the use of look-up tables. Importantly, this generalized method not only significantly improves efficiency, but can also be extended to any number of ports. Finally, experimental results are presented to validate the theoretical analysis and effectiveness of the RPM scheme.

Zero-Vector-Regulation-Based Closed-Loop Power Distribution Strategy for Dual-DC-Port DC–AC Converter-Connected PV–Battery Hybrid Systems

The dual-dc-port dc-ac converter-connected photovoltaic (PV)-battery hybrid systems present high-efficiency and low-cost features with single-stage power conversion as PV and battery are connected to the grid directly. However, it is challenging to achieve flexible power distribution in this configuration due to its coupled features in grid-side current tracking and power distribution. To deal with this issue, this paper proposes a zero vector regulation-based closed-loop power distribution strategy for the dual-dc-port dc-ac converter-connected PV-battery hybrid systems. By modeling the dual-dc-port dc-ac converter as an equivalent two-level one, an extra control freedom for power regulation is accessible and a closed-loop power control is adopted for flexible power distribution by zero vector regulation. With the proposed power distribution strategy, the desirable quality of the grid-side current is achieved without complicated voltage vector synthesis, along with good adaptivity to different modes/voltages and flexible power control. Besides, detailed power distribution discussion and analysis with different proportions of zero vector are carried out. Finally, the islanded microgrid experimental tests are conducted to verify its effectiveness and feasibility.

Ensuring energy balance for sudden demand changes in smart grids

With the increasing diversity in the use of electrical energy and the inclusion of renewable electricity power plants in the system, more efficient and more controllable electrical power systems are provided by smart grid technologies. Load balance based on pricing in electrical power systems; It is a strategy that takes into account customer demands, enables customers to use electrical energy at the most attractive price, and provides suppliers with the desired profit, that is, in summary, it coordinates the efficient operation of energy systems. In this study; While load balance is created with smart grid technology, demand-supply-price balance is achieved by using an optimum Fuzzy Logic PI controller within a closed-loop electric power control system model. Within the scope of the study, the simulation results obtained by applying 6 different demand scenarios to the power system model consisting of different types of generation resources were given graphically and analyzed. The different demand scenarios applied include difficult demand conditions such as possible sudden increase or decreases in demand in the electrical power system.

Bivariate active power control of energy storage hydraulic wind turbine

With the increasing proportion of wind turbines in power system, high-precision control of power generation directly affects the proportion of wind turbines connected to the grid. This paper takes the energy storage hydraulic wind turbines (ESHWTs) as the research object, the mathematical model of the hydraulic main transmission system and the hydraulic energy storage subsystem are established, and the energy transmission and control mechanism is obtained. The corresponding relationship between the output power of the hydraulic main drive system and the hydraulic energy storage subsystem and the variable motor speed is analyzed, based on the small signal linearization method, and the power transmission state is obtained with the variable motor speed fluctuation, and a double closed-loop power control strategy is proposed under the motor speed fluctuation, with the power control requirements after grid connection, Based on MATLAB software and 24 kW semi-physical simulation test platform of energy storage hydraulic wind turbine, the output power is accurately controlled and the power output problem is solved under the fluctuation of motor speed with the proposed control strategy.

Applying edge artificial intelligence to closed-loop real time control and monitoring of laser based battery pack welding

The manufacturing of battery packs plays an essential role in e-mobility. In this context, laser welding of batteries has taken a considerable momentum in recent years as it can quickly adapt to different form factors and battery arrangements which is crucial for short runs and on-demand manufacturing. In this paper, we present an assisted battery pack welding system applying a novel sensor fusion strategy. The presented work introduces a multi-camera solution combining a camera in the visual range and an infrared camera in a compact scanner head that applies graphics processing unit acceleration for image processing and real-time field programmable gate array processing for process control. In order to acquire accurate temperature measurements, the infrared camera has been characterized and calibrated for the temperature ranges of the welding process. In addition, we propose a method for image space coordinate transformation based on affine transformations used to transform the coordinates of the detected battery joints into different image spaces to adapt to the welding process in real time. A single shot multibox detector Mobilenet-v2 neural network has been retrained with custom images to detect and classify a set of battery pack types allowing the extraction of the battery cell joint coordinates using image processing, which enables the application of real-time corrections to the laser aiming system and a closed-loop laser power control. Finally, we present some battery welding results using different welding strategies on the described system.

Suppression of laser power error in a miniaturized atomic co-magnetometer based on split ratio optimization

A miniaturized atomic spin-exchange relaxation-free (SERF) co-magnetometer measures angular velocity using a balanced polarimetry technique which is easily affected by the laser power. A laser power closed-loop control system is usually used to suppress the fluctuation of the laser power. Although this method can greatly eliminate the fluctuation of the in-loop laser power (the feedback laser), it cannot fully eliminate the fluctuation of the out-of-loop laser power (the signal measurement laser). This leads to SERF gyroscope laser power error, which reduces the inertial measurement accuracy. In this paper, the influence mechanism of the split ratio (the ratio of the in-loop laser power to the out-of-loop laser power) on the out-of-loop laser power control accuracy is analyzed by establishing a laser power transmission model inside and outside the loop. Moreover, a method is developed to improve the out-of-loop laser power stability by optimizing the split ratio. Comparative experiments showed that the relative Allan standard deviation of the out-of-loop laser power decreased from 5.48 × 10−6 to 2.62 × 10−6 at 100 s, and decreased by an order of magnitude from 1.76 × 10−5 to 3.30 × 10−6 at 1000 s. Correspondingly, the rate ramp coefficient in the Allan standard deviation curve of the SERF gyroscope test data decreased from 1.312 [(°/h)/h] to 0.246 [(°/h)/h]. And the bias stability increased from 0.032 °/h to 0.019 °/h. Therefore, the proposed method can improve the long-term stability of the probe laser power and effectively suppress the laser power error of the SERF gyroscope.

Power Control Strategy for Grid-Connected Inverters in Stationary Reference Frame

The control of grid-connected converters in stationary reference frame has been investigated in several works of literature. One of the challenges of this method is in the computation of the current computing current references as a function of power references. In some works, this issue has been solved based on instantaneous power theory equations described in the stationary reference frame. However, this approach can lead to steady-state errors in the injected power if there is an error in the current control loop, which is the focus of this investigation. Firstly, analytical expressions are derived to investigate the effect of current loop steady-state error in the active and reactive power injected into the grid. Then, this paper proposes a closed-loop power control for grid-connected inverters controlled in the stationary reference frame. This strategy is experimentally investigated in two power conversion system configurations for battery energy storage systems. The results indicate that the proposed scheme guarantees zero steady-state error in the injected power even when the current loop presents an amplitude and phase steady-state error.

Backstepping sliding mode fault-tolerant control for the wind turbine system with disturbance observer

To guarantee the safe and stable operation of wind farms, this article establishes a backstepping sliding mode fault-tolerant controller for the wind turbine system to surmount uncertain problems, including actuator gain–bias faults, system modeling errors, and external stochastic disturbances. The nonlinear disturbance observer is employed for the stochastic disturbances, which can online estimate and compensate the external disturbance term. In addition, the backstepping control strategy is introduced to reduce the complexity of fault-tolerant controller design. Subsequently, combining the backstepping control algorithm and nonlinear disturbance observer, a disturbance observer-based backstepping sliding mode fault-tolerant control approach is applied for the wind turbine system. Thereinto, the terminal attractor is employed, which is mainly utilized to improve the convergence rate of the sliding surface and reduce the chattering phenomenon. The stability of the wind power closed-loop control system is rigorously verified via Lyapunov stability theory, which can obtain satisfactory control performance. Finally, numerical simulation results demonstrate that the proposed control approach can guarantee that the system state quickly reaches stability within 6–8 s, and the steady-state adjustment time is greatly reduced to 50%–62% when compared with the proportional–integral–derivative control and sliding mode control.

A 5G FR2 Power-Amplifier With an Integrated Power-Detector for Closed-Loop EIRP Control

A fifth-generation (5G) frequency range 2 (FR2) transmitter front end with a fully integrated power detector for enabling closed-loop power control is presented. The power detection path includes a miniature broad-side directional coupler, a sense pair, and a current-mode successive approximation analog-to-digital converter. The stacked power amplifier (PA) implemented in a 28-nm CMOS silicon on insulator (SOI) process delivers 12.5-dBm output power with a power-added efficiency of 10% and an error vector magnitude (EVM) lower than −25 dB with a CP-OFDM/64-QAM/400-MHz bandwidth signal. The PA supports 5G frequency bands n257/n258/n261 covering a frequency range from 24.25 to 29.5 GHz. With a matched output load, the power detector has less than ±0.15-dB error over a 15-dB power dynamic range and 85° temperature range.

Transmit Power Pool Design for Grant-Free NOMA-IoT Networks via Deep Reinforcement Learning

Grant-free non-orthogonal multiple access (GF-NOMA) is a potential multiple access framework for short-packet internet-of-things (IoT) networks to enhance connectivity. However, the resource allocation problem in GF-NOMA is challenging due to the absence of closed-loop power control. We design a prototype of transmit power pool (PP) to provide open-loop power control. IoT users acquire their transmit power in advance from this prototype PP solely according to their communication distances. Firstly, a multi-agent deep Q-network (DQN) aided GF-NOMA algorithm is proposed to determine the optimal transmit power levels for the prototype PP. More specifically, each IoT user acts as an agent and learns a policy by interacting with the wireless environment that guides them to select optimal actions. Secondly, to prevent the Q-learning model overestimation problem, double DQN (DDQN) based GF-NOMA algorithm is proposed. Numerical results confirm that the DDQN based algorithm finds out the optimal transmit power levels that form the PP. Comparing with the conventional online learning approach, the proposed algorithm with the prototype PP converges faster under changing environments due to limiting the action space based on previous learning. The considered GF-NOMA system outperforms the networks with fixed transmission power, namely all the users have the same transmit power and the traditional GF with orthogonal multiple access techniques, in terms of throughput.

Control Hardware-in-the-Loop Simulation on Fast Frequency Response of Battery Energy Storage System Equipped With Advanced Frequency Detection Algorithm

Fast frequency response (FFR) of battery energy storage system (BESS) is an effective way to mitigate the system frequency deviation induced by the fluctuation of power generation from the increased renewable energy resources and the impact of reduced system inertia caused by decreased synchronous generators. However, existing standards referring to technical requirements for the frequency measurement do not sufficiently consider abnormal grid conditions, such as voltage unbalance, frequency sweep, and dynamic voltage step. This article shows the impact of frequency measurement logic on the FFR performance of BESS in grid disturbance conditions by control hardware-in-the-loop (CHIL) testing and proposes improved frequency measurement logic based on a phase-locked loop (PLL). A benchmarking of the proposed PLL was conducted against existing PLL and discrete Fourier transformation-based frequency measurement logics. Finally, the FFR performance of BESS with each frequency measurement logic has been tested in CHIL simulation. This CHIL comprises the actual power plant controller, the actual bidirectional inverter control board, and a real-time simulator. In the CHIL experiments, several system disturbance situations likely to happen in existing power systems were considered as test cases and showed that the frequency measurement accuracy and latency were violated in some frequency measurement logics. Furthermore, this article reveals the effects of frequency measurement accuracy and latency on the FFR performance of BESS by a closed-loop power control simulation with a CHIL environment. In conclusion, considerations for the frequency measurement method used for FFR are proposed.

Design and simulation of current-fed dual-active full-bridge DC/DC converter control system applied to proton exchange membrane fuel cell

Proton exchange membrane fuel cells (PEMFC) have been increasingly applied in clean and efficient distributed power generation systems in recent years. However, the output characteristics of PEMFC are relatively soft due to the influence of multiple polarization overvoltage. With the increasement of current density, the output voltage shows to be a nonlinear downward trend. In addition, in order to ensure the lifetime of PEMFC, the output ripple current is often concerned. Considering above characteristics, in order to achieve efficient power transmission of the PEMFC system, this paper adopts the current-fed dual-active full-bridge (DAB) DC/DC converter topology, which can achieve soft switching of most switches. Furthermore, it can restrain the characteristics of the current ripple. Hence, the power transmission efficiency and current ripple requirements of PEMFC are fulfilled. Finally the current-fed DAB is designed and simulated through PSIM. The C-block is applied to simulate the PEMFC nonlinear power supply according to the actual PEMFC parameters. In order to achieve efficient constant power transmission of the nonlinear PEMFC, a novel power closed-loop control strategy is proposed.

Unmanned Aerial Vehicle Wireless Charging System With Orthogonal Magnetic Structure and Position Correction Aid Device

Design and fabrication of a wireless charging system, which includes a wireless charging base station and an unmanned aerial vehicle (UAV) with wireless charging capability is proposed for enlarging the UAV's working range. First, an optimized magnetic coupler featuring with an orthogonal magnetic structure with a flexible soft magnetic core in receiver is proposed to ensure high efficiency and low-leakage magnetic flux interference. Second, a wireless charging circuit topology and a closed-loop power controller implemented on the primary side are designed and analyzed in detail to maintain constant current/constant voltage charging for the UAV. Then, a wireless charging station with position correction aid device is developed, which can achieve high-precision alignment. A prototype of the UAV wireless charging system with the proposed magnetic structure, primary-side control, and position correction are built and tested. Experimental results show that the fabricated wireless charging system can deliver 87.4 W at a dc-to-battery efficiency of 87.3%, and the system is adapted autonomous charging of UAV.

Wirelessly-Powered Cage Designs for Supporting Long-Term Experiments on Small Freely Behaving Animals in a Large Experimental Arena

In modern implantable medical devices (IMDs), wireless power transmission (WPT) between inside and outside of the animal body is essential to power the IMD. Unlike conventional WPT, which transmits the wireless power only between fixed Tx and Rx coils, the wirelessly-powered cage system can wirelessly power the IMD implanted in a small animal subject while the animal freely moves inside the cage during the experiment. A few wirelessly-powered cage systems have been developed to either directly power the IMD or recharge batteries during the experiment. Since these systems adapted different power carrier frequencies, coil configurations, subject tracking techniques, and wireless powered area, it is important for designers to select suitable wirelessly-powered cage designs, considering the practical limitations in wirelessly powering the IMD, such as power transfer efficiency (PTE), power delivered to load (PDL), closed-loop power control (CLPC), scalability, spatial/angular misalignment, near-field data telemetry, and safety issues against various perturbations during the longitudinal animal experiment. In this article, we review the trend of state-of-the-art wirelessly-powered cage designs and practical considerations of relevant technologies for various IMD applications.