Zhongfu Zhou

The widespread adoption of electric vehicles (EVs) is contingent on high-power fast-charging infrastructure that can also provide grid stabilization services through bidirectional power flow. While the constituent power stages of such off-board chargers are well-known, a critical research gap exists in their system-level integration, where sub-optimal dynamic interaction between independently controlled stages often leads to DC-link instability and poor transient performance. This paper presents a rigorous, system-level study to address this gap by developing and optimizing a unified control framework for a high-power bidirectional EV fast-charging system. The system integrates a three-phase active front-end rectifier with an LCL filter and a four-phase interleaved bidirectional DC/DC converter. The methodology involves a holistic dynamic modeling of the coupled system, the design of a hierarchical control strategy augmented with a battery current feedforward scheme, and the system-wide optimization of all Proportional–Integral (PI) controller gains using the Artificial Bee Colony (ABC) algorithm. Comprehensive simulation results demonstrate that the proposed optimized control framework achieves a critically damped response, significantly outperforming a conventionally tuned baseline. Specifically, it reduces the DC-link voltage settling time during charging-to-discharging transitions by 74% (from 920 ms to 238 ms) and eliminates voltage undershoot, while maintaining excellent steady-state performance with grid current total harmonic distortion below 1.2%. The study concludes that system-wide metaheuristic optimization, rather than isolated component-level design, is key to unlocking the robust, high-performance operation required for next-generation EV fast-charging infrastructure, providing a validated blueprint for future industrial development.

Silicon carbide (SiC) metal-oxide semiconductor field-effect transistors (MOSFETs), as a new material, have the advantages of low drain-source resistance, high thermal conductivity, low leakage current, and high switching frequency compared with silicon (Si)-based MOSFETs. Therefore, in many industrial applications, Si MOSFETs have been replaced by SiC MOSFETs. However, as the switching speed increases exponentially, some problems are amplified, the most serious of which is the overshoot of current and voltage. The increase in voltage and current slope caused by high switching speeds inevitably leads to overshoot, oscillations, and additional losses in the circuit. This paper focusses on the actual performance of the optimised switching strategy (OSS) in circuit testing and combines the existing simulation results to verify the practicability of OSS. In this paper, the optimised switching strategy is introduced first, and then, the LTspice model of SiC MOSFET is established in detail and verifies the feasibility of the OSS through half-bridge circuit simulation. Finally, the test platform is built using a programmable gate drive module (2ASC-12A1HP). Through a 400 V/30 A double-pulse test, the practicality of the OSS is verified. The experiments show that the OSS can greatly improve the switching performance of SiC MOSFETs.

This paper presents an emulation of PV modules based on the buck DC/DC converter as a replacement of actual solar electricity generation sources for laboratory experiments for testing the conditioners and MPPT algorithms. The buck converter was designed in constant current control mode and the output current of the buck converter is referred to lookup tables constructed based on I-V curves of product datasheets or mathematical equations. Dynamic performance of the current control loop was investigated. To validate the performance simulation and experiment as carried out and a comparison between simulated and practical results obtained from laboratory test with actual sources is performed. It is confirmed the buck converter-based PV simulator is a simple, safe, versatile, and effective way of physically representing of real solar source.

A single-phase bidirectional DC/DC battery charger with a P&O MPPT current control strategy for a standalone energy management system has been integrated with an interleaved switched capacitor DC/AC inverter with an RMS feedback phase-shifted unipolar sinusoidal PWM control strategy. In the published literature, P&O MPPT control is used to drive a boost converter connected in parallel to a battery charger; this modified strategy combines a P&O MPPT algorithm with current control to drive an interleaving buck-boost battery charger. This battery charger circuit is connected in parallel to a closed loop controlled interleaved inverter that feeds the AC home load. MATLAB/Simulink based simulation circuit was developed and used to validate the successful integration of the interleaved battery charger with the global system. To do this, the system is tested with varying input conditions of irradiance and temperature. The system’s response to these variable inputs is monitored and analysed. The simulation results show the proposed method is effective for standalone battery-based PV systems. The system provides a more efficient and faster response compared with both an interleaved and non-interleaved voltage-controlled battery charger circuit that is also integrated with the global system. This battery charger control strategy is also shown to protect the battery from over-charging as well as discharging below 25%, which can improve and protect the long-term battery performance. Compared with novel industry approaches, the proposed system is simpler by nature due to the reduced number of conversions and therefore a reduced number of components which provides economic advantages.

This paper proposes an optimized switching strategy (OSS) based on a silicon carbide (SiC) MOSFET gate driver with variable voltage, which allows simultaneous variations in several different parameters to optimize the switching performance of semiconductor devices. As a relatively new device, the SiC MOSFET shines in the field of high power density and high-frequency switching; it has become a popular solution for electric vehicles and renewable energy conversion systems. However, the increase in voltage and current slope caused by high switching speeds inevitably increases the overshoot and oscillation in a circuit and can even generate additional losses. The principle of this new control strategy is to change the voltage and current in the turn-on and turn-off stages by changing the gate driver’s voltage. That is, we reduced the drive’s voltage after a certain time delay and maintained it for a period of time, thus directly controlling the slopes of di/dt and dv/dt. This study focused on the optimization of the SiC MOSFET by changing the time delay preceding the decrease in the voltage of the gate driver, analyzing and calculating the optimal time delay before the decrease in the voltage of the gate driver, and verifying the findings using LTspice simulation software. The simulated results were compared and analyzed with hard-switching strategies. The results showed that the proposed OSS can improve the switching performance of SiC MOSFETs.

This paper proposes a control algorithm for single-phase battery inverters to provide voltage unbalance compensation in distribution networks with high penetration of photovoltaic panels and electric vehicles. A typical distribution system is studied to quantify the impact of single-phase loads and generating units on voltage unbalance levels, and identify the conditions that lead to the highest voltage unbalance. Voltage unbalance compensation is then performed by regulating active and reactive power exchange between three single-phase battery energy storage units and the power grid. The proposed control strategy consists of an upper level control system to coordinate the three units by sending active and reactive power reference signals, and a BESS control system to regulate active and reactive power exchange between each single-phase inverter and the grid. Simulation results show that the effectiveness of this approach depends on the location where the energy storage units are installed. The positive impact of the proposed methodology on balancing the power flow and reducing the transformer zero-sequence current is also demonstrated. Finally, Hardware-In-The-Loop (HIL) experiments are carried out to provide validation of the control algorithm in real-time.

In this paper, Cascade PI Controller-Based Robust Model Reference Adaptive Control (MRAC) of a DC-DC boost converter is presented. Non-minimum phase behaviour of the boost converter due to right half plane zero constitutes a challenge and its non-linear dynamics complicate the control process while operating in continuous conduction mode (CCM). The proposed control scheme efficiently resolved complications and challenges by using features of cascade PI control loop in combination with properties of MRAC. The accuracy of the proposed control system’s ability to track the desired signals and regulate the plant process variables in the most beneficial and optimised way without delay and overshoot is verified using MATLAB/Simulink by applying comparative analysis with single PI and cascade PI controllers. Moreover, performance of the proposed control scheme is validated experimentally with the implementation of MATLAB/Simulink/Stateflow on dSPACE Real-time-interface (RTI) 1007 processor, DS2004 High-Speed A/D and CP4002 Timing and Digital I/O boards. The experimental results and analysis reveal that the proposed control strategy enhanced the tracking speed two times with considerably improved disturbance rejection.

In this paper, Proportional Gain Resonant and Gain Scheduled Proportional (PR-P) Controller based variable perturbation size real-time adaptive perturb and observe (P&O) maximum power point tracking (MPPT) algorithm is presented. The proposed control scheme resolved the drawbacks of conventional P&O MPPT method associated with the use of constant perturbation size that leads to poor transient response and high continuous steady-state oscillations. The prime objective of using the PR-P controller is to utilize inherited properties of the signal produced by the controller’s resonant path and integrate it to update best estimated perturbation that represents the working principle of extremum seeking control (ESC) to use in P&O algorithm that characterizes the overall system learning-based real time adaptive (RTA). Additionally, utilization of internal dynamics of the PR-P controller overcome the challenges namely, complexity, computational burden, implantation cost and slow tracking performance in association with commonly used soft computing intelligent systems and adaptive control strategies. The proposed control scheme is verified using MATLAB/Simulink by applying comparative analysis with PI controlled conventional P&O MPPT algorithm. Moreover, performance of the proposed control scheme is validated experimentally with the implementation of MATLAB/Simulink/Stateflow on dSPACE Real-time-interface (RTI) 1007 processor board, DS2004 A/D and CP4002 Digital I/O boards. The experimental results and analysis reveal that the proposed control strategy enhanced the tracking speed five times with reduced steady-state oscillations around maximum power point (MPP) and more than 99% energy extracting efficiency.