In this paper, an add-on type pulse charger is proposed to shorten the charging time of a lithium ion battery. To evaluate the performance of the proposed pulse charge method, an add-on type pulse charger prototype is designed and implemented. Pulse charging is applied to 18650 cylindrical lithium ion battery packs with 10 series and 2 parallel structures. The proposed pulse charger is controlled by pulse duty, frequency and magnitude. Various experimental conditions are applied to optimize the charging parameters of the pulse charging technique. Battery charging data are analyzed according to the current magnitude and duty at 500 Hz and 1000 Hz and 2000 Hz frequency conditions. The proposed system is similar to the charging speed of the constant current method under new battery conditions. However, it was confirmed that as the battery performance is degraded, the charging speed due to pulse charging increases. Thus, in applications where battery charging/discharging occurs frequently, the proposed pulse charger has the advantage of fast charging in the long run over conventional constant current (CC) chargers.

This paper presents a frequency adaptive grid voltage sensorless control scheme of a grid-connected inductive–capacitive–inductive (LCL)-filtered inverter, which is based on an adaptive current controller and a grid voltage observer. The frequency adaptive current controller is constructed by a full-state feedback regulator with the augmentation of multiple control terms to restrain not only the inherent resonance phenomenon that is caused by LCL filter, but also current harmonic distortions from an adverse grid environment. The number of required sensing devices is minimized in the proposed scheme by means of a discrete-time current-type observer, which estimates the system state variables, and gradient-method-based observers, which estimate the grid voltages and frequency simultaneously at different grid conditions. The estimated grid frequency is utilized in the current control loop to provide high-quality grid-injected currents, even under harmonic distortions and the frequency variation of grid voltages. As a result, the grid frequency adaptive control performance as well as the robustness against distorted grid voltages can be realized. Finally, an inverter synchronization task without using grid voltage sensors is accomplished by a fundamental grid voltage filter and a phase-locked loop to detect the actual grid phase angle. The stability and convergence performance of the proposed observers have been studied by means of the Lyapunov theory to ensure a high accuracy tracking performance of estimated variables. Simulation and experimental results are presented to validate the feasibility and the effectiveness of the proposed control approach.

In this paper, a seamless power management scheme is proposed for a decentralized DC microgrid (DCMG) to maintain voltage stabilization in the presence of voltage sensor faults. First, a voltage observer is constructed in each power agent to monitor the voltage sensor abnormality under various uncertain conditions. During the normal operations, the power balance as well as the voltage regulation of the DCMG is achieved by using the voltage droop control method which consists of the secondary controller and primary controller. While the secondary controller is utilized to maintain the DC-link voltage (DCV) at the nominal value, the power balance is achieved by the droop control method in the primary controller. In both controllers, the estimated DCV value is employed as the only feedback signal from the DC-link to the power agent. To maintain a seamless power management even under DCV sensor faults, a fault identification algorithm is first presented to detect voltage sensor failure. After the power agent recognizes its DCV sensor fault, its operation mode is switched from the voltage control to the current control mode, in which the operating point in the droop curves is perturbed by changing the current magnitude in the power agent with the faulty DCV sensor. The perturbation of operating point in the droop curves makes the other power agents with normal DCV sensor take a control of DCV instead of the power agent with the faulty DCV sensor to guarantee voltage stabilization and prevent the system collapse. Furthermore, the proposed scheme adjusts appropriately the droop curve of the utility grid agent in the primary controller under high electricity price condition to minimize electricity costs. Simulation and experimental results under various conditions verify the effectiveness and reliability of the proposed seamless power management strategy.

Continuous power management for a decentralized DC microgrid (DCMG) is proposed in this study to achieve power balance and voltage regulation even under system uncertainty and voltage sensor failure. The DCMG system achieves continuous power management through only the primary controller to reduce the computational burden of each power agent. To enhance the reliability and resilience of the DCMG system under DC bus voltage (DCV) sensor failure, a DCV sensor fault detection algorithm is suggested. In this algorithm, DCV sensor failure is detected by comparing the measured DCV with the estimated DCV. If power agents identify the failure of the DCV sensor, it changes the operation properly according to the proposed control mode decision algorithm to guarantee the stability of the DCMG system. When uncertain conditions like sudden grid disconnection, DCV sensor failure, electricity price change, power variation in distributed generations, and critical battery status occur, the DCMG system is changed to transitional operation modes. These transitional operation modes are employed to transmit the power agent information to other agents without digital communication links (DCLs) and to accomplish power sharing even under such uncertain conditions. In the transitional operation modes of the DCMG system, the DCV levels are temporarily shifted to an appropriate level, enabling each power agent to detect the uncertainty conditions, and subsequently to determine its operation modes based on the DCV levels. The reliability and effectiveness of the proposed control strategy are confirmed via various simulation and experimental tests under different operating conditions.

In this paper, a reliable hybrid control scheme for distributed DC microgrid is proposed to maintain both the voltage stabilization and power management in the presence of multiple cyber attacks and voltage sensor fault. A dual Kalman filter which separately estimates the secondary control output and DC-link voltage values is implemented to effectively identify the system abnormalities. As soon as the abnormalities such as cyber attacks or sensor failures are detected, the proposed hybrid control scheme instantly changes the operation of the power agents to appropriate control mode to maintain the stability of DCMG system. The proposed hybrid control scheme requires only unidirectional communication links for distributed DC microgrid, which contributes to achieve the consensus in secondary control output with optimal communicational cost. In addition, an adaptive droop curve is also considered in the primary control to minimize the electricity price. The stability of the proposed hybrid control scheme is mathematically analyzed. The reliability of the proposed strategy is verified through several simulations and experimental results.

In this study, to enhance the system reliability under false data injection (FDI) attacks and DC-link voltage (DCLV) sensor failures, a hybrid control strategy for a DC microgrid (DCMG) based on the Lagrange extrapolation and voltage observer is proposed. Under normal conditions without FDI attacks or DCLV sensor failures, the DCMG system works in a distributed control scheme. To enhance the reliability of the system under the DCLV sensor failure or FDI attack, the DCMG system utilizes a hybrid control strategy that combines distributed control with decentralized control. The hybrid control strategy is achieved by the proposed detection algorithms for FDI attacks and DCLV sensor failures. The detection of FDI attacks is accomplished by comparing the predicted secondary controller output based on the Lagrange extrapolation with the actual one. When a power agent detects an FDI attack, its control mode is switched to decentralized control by using the proposed hybrid control strategy. The DCLV sensor failure detection algorithm to enhance system reliability against DCLV sensor failures is achieved by comparing the estimated DCLV with the measured one from the voltage observer. Upon detecting a DCLV sensor failure, the operation of the power agent is switched to the current control mode to sustain the system operation even under DCLV sensor failures. The proposed detection algorithms are simple, effective, and precise, operating without mutual interference that deteriorates the detection accuracy. Simulation and experiments are carried out under various uncertain test conditions to validate the reliability and effectiveness of the proposed control strategy.