Nadia Mei Lin Tan

Design and Performance of a Bidirectional Isolated DC–DC Converter for a Battery Energy Storage System

This paper describes the design and performance of a 6-kW, full-bridge, bidirectional isolated dc-dc converter using a 20-kHz transformer for a 53.2-V, 2-kWh lithium-ion (Li-ion) battery energy storage system. The dc voltage at the high-voltage side is controlled from 305 to 355 V, as the battery voltage at the low-voltage side (LVS) varies from 50 to 59 V. The maximal efficiency of the dc-dc converter is measured to be 96.0% during battery charging, and 96.9% during battery discharging. Moreover, this paper analyzes the effect of unavoidable dc-bias currents on the magnetic-flux saturation of the transformer. Finally, it provides the dc-dc converter loss breakdown with more focus on the LVS converter.

Topology and application of bidirectional isolated dc-dc converters

A bidirectional isolated dc-dc converter manages the power flow between an energy storage device and a dc bus with functions of galvanic isolation and voltage matching. Research and development of these converters focus on improving efficiency and power density. This paper presents and compares various configurations of bidirectional isolated dc-dc converters. It also illustrates the performance of a 6-kW, full-bridge, bidirectional isolated dc-dc converter operating at 4 kHz, which is suitable for output power leveling of photovoltaic generation systems connected to homes and office buildings. The maximum efficiency of the dc-dc converter is measured at 98.1% during battery charging and at 98.2% during battery discharging. The converter maintains a high efficiency of more than 97% for a wide range of power transfer.

Modified Model Predictive Control of a Bidirectional AC–DC Converter Based on Lyapunov Function for Energy Storage Systems

Energy storage systems have been widely applied in power distribution sectors as well as in renewable energy sources to ensure uninterruptible power supply. This paper proposes a modified model predictive control (MMPC) method based on the Lyapunov function to improve the performance of a bidirectional ac-dc converter, which is used in an energy storage system for bidirectional power transfer between the three-phase ac voltage supply and energy storage devices. The proposed control technique utilizes the discrete behavior of the converter, considering the unavoidable quantization errors between the controller and the control actions selected from the finite control set of the bidirectional ac-dc converter. The proposed control method reduces the execution time delay by 18% compared with the conventional model predictive control. Moreover, the nonlinear system stability of the proposed MMPC technique is ensured by the direct Lyapunov method and a nonlinear experimental system model. Detailed experimental results with a 2.5-kW downscaled hardware prototype are provided to show the efficacy of the proposed control system.

Power-Loss Breakdown of a 750-V 100-kW 20-kHz Bidirectional Isolated DC–DC Converter Using SiC-MOSFET/SBD Dual Modules

This paper describes the design, construction, and testing of a 750-V 100-kW 20-kHz bidirectional isolated dual-active-bridge dc-dc converter using four 1.2-kV 400-A SiC-MOSFET/SBD dual modules. The maximum conversion efficiency from the dc-input to the dc-output terminals is accurately measured to be as high as 98.7% at 42-kW operation. The overall power loss at the rated-power (100 kW) operation, excluding the gate-drive and control circuit losses, is divided into the conduction and switching losses produced by the SiC modules, the iron and copper losses due to magnetic devices, and the other unknown loss. The power-loss breakdown concludes that the sum of the conduction and switching losses is about 60% of the overall power loss and that the conduction loss is nearly equal to the switching loss at the 100-kW and 20-kHz operation.

Model Predictive Control of Bidirectional AC-DC Converter for Energy Storage System

Energy storage system has been widely applied in power distribution sectors as well as in renewable energy sources to ensure uninterruptible power supply. This paper presents a model predictive algorithm to control a bidirectional AC-DC converter, which is used in an energy storage system for power transferring between the three-phase AC voltage supply and energy storage devices. This model predictive control (MPC) algorithm utilizes the discrete behavior of the converter and predicts the future variables of the system by defining cost functions for all possible switching states. Subsequently, the switching state that corresponds to the minimum cost function is selected for the next sampling period for firing the switches of the AC-DC converter. The proposed model predictive control scheme of the AC-DC converter allows bidirectional power flow with instantaneous mode change capability and fast dynamic response. The performance of the MPC controlled bidirectional AC-DC converter is simulated with MATLAB/Simulink® and further verified with 3.0kW experimental prototypes. Both the simulation and experimental results show that, the AC-DC converter is operated with unity power factor, acceptable THD (3.3% during rectifier mode and 3.5% during inverter mode) level of AC current and very low DC voltage ripple. Moreover, an efficiency comparison is performed between the proposed MPC and conventional VOC-based PWM controller of the bidirectional AC-DC converter which ensures the effectiveness of MPC controller.

Stability and Performance Investigations of Model Predictive Controlled Active-Front-End (AFE) Rectifiers for Energy Storage Systems

This paper investigates the stability and performance of model predictive controlled active-front-end (AFE) rectifiers for energy storage systems, which has been increasingly applied in power distribution sectors and in renewable energy sources to ensure an uninterruptable power supply. The model predictive control (MPC) algorithm utilizes the discrete behavior of power converters to determine appropriate switching states by defining a cost function. The stability of the MPC algorithm is analyzed with the discrete z-domain response and the nonlinear simulation model. The results confirms that the control method of the active-front-end (AFE) rectifier is stable, and that is operates with an infinite gain margin and a very fast dynamic response. Moreover, the performance of the MPC controlled AFE rectifier is verified with a 3.0 kW experimental system. This shows that the MPC controlled AFE rectifier operates with a unity power factor, an acceptable THD (4.0 %) level for the input current and a very low DC voltage ripple. Finally, an efficiency comparison is performed between the MPC and the VOC-based PWM controllers for AFE rectifiers. This comparison demonstrates the effectiveness of the MPC controller.

Power-loss breakdown of a 750-V, 100-kW, 20-kHz bidirectional isolated DC-DC converter using SiC-MOSFET/SBD dual modules

This paper describes the design, construction and testing of a 750-V, 100-kW, 20-kHz bidirectional isolated dual-active-bridge dc-dc converter using four 1.2-kV 400-A SiCMOSFET/SBD dual modules. The maximum conversion efficiency from the dc-input to the dc-output terminals is accurately measured to be as high as 98.7% at 42-kW operation. The overall power loss at the rated-power (100 kW) operation, excluding the gate-drive and control circuit losses, is divided into conduction and switching losses produced by the SiC modules, iron and copper losses due to magnetic devices, and an unknown loss. The power-loss breakdown concludes that the summation of the conduction and switching losses is about 60% of the overall power loss, and that the conduction loss is nearly equal to the switching loss at the 20-kHz, 100-kW operation.

Model predictive control of a bidirectional AC-DC converter for V2G and G2V applications in electric vehicle battery charger

This paper presents a model predictive control algorithm of three-phase bidirectional AC-DC converter that can be used for V2G and G2V applications. This algorithm utilizes the discrete behaviour of the converter to determine appropriate switching states that minimize the cost function. The proposed predictive control scheme allows bidirectional power transfer with instantaneous mode changing capability and fast dynamic response. This paper also presents the results simulated with MATLAB/Simulink and further validated with a 1.5 kW experimental set-up to confirm the feasibility of the proposed control scheme. Both the simulation and experimental results prove that the converter is operated with sinusoidal grid current, acceptable THD, unity power factor and contain very low voltage ripples in the DC side.

Modified Direct Torque Control using Algorithm Control of Stator Flux Estimation and Space Vector Modulation Based on Fuzzy Logic Control for Achieving High Performance from Induction Motors

Direct torque control based on space vector modulation (SVM-DTC) protects the DTC transient merits. Furthermore, it creates better quality steady-state performance in a wide speed range. The modified method of DTC using SVM improves the electrical magnitudes of asynchronous machines, such as minimizing the stator current distortions, the stator flux with electromagnetic torque without ripple, the fast response of the rotor speed, and the constant switching frequency. In this paper, the proposed method is based on two new control strategies for direct torque control with space vector modulation. First, fuzzy logic control is used instead of the PI torque and a PI flux controller to minimizing the torque error and to achieve a constant switching frequency. The voltages in the direct and quadratic reference frame (V d ,V q ) d q are achieved by fuzzy logic control. In this scheme, the switching capability of the inverter is fully utilized, which improves the system performance. Second, the close loop of stator flux estimation based on the voltage model and a low pass filter is used to counteract the drawbacks in the open loop of the stator flux such as the problems saturation and dc drift. The response of this new control strategy is compared with DTC-SVM. The experimental and simulation results demonstrate that the proposed control topology outperforms the conventional DTC-SVM in terms of system robustness and eliminating the bad outcome of dc-offset.

An improved active-front-end rectifier using model predictive control

This paper investigates an improved active-front-end (AFE) rectifier using model predictive control. The model predictive control (MPC) algorithm utilizes the discrete behavior of the power converter to determine the appropriate switching states by defining a cost function. The performance of the AFE rectifier has been verified with 3.0 kW experimental setup which shows that the efficiency of the MPC controlled AFE-rectifier is 96.82% and is operated with acceptable THD (4.0%) of input current and very low DC voltage ripple. An efficiency comparison is performed between the MPC and VOC-based PWM controller of the AFE rectifier which ensures the effectiveness of MPC controller. Moreover, the stability of the MPC method has been analyzed with the root locus, discrete z-domain frequency response techniques (Nyquist diagram) and non-linear experimental system. The result confirms that, the control system of AFE rectifier is stable as it operates with infinite gain margin and very fast dynamic response.