The global reliance on electric vehicles (EVs) has been rapidly increasing due to the excessive use of fossil fuels and the resultant CO₂ emissions. Moreover, EVs facilitate using alternative energy sources, such as energy storage systems (ESSs) and renewable energy sources (RESs), promoting mobility while reducing dependence on fossil fuels. However, this trend is accompanied by multiple challenges related to EVs’ traction systems, storage capacity, chemistry, charging infrastructure, and techniques. Additionally, the requisite energy management technologies and the standards and regulations needed to facilitate the expansion of the EV market present further complexities. This paper provides a comprehensive and up-to-date review of the state of the art concerning EV-related components, including energy storage systems, electric motors, charging topologies, and control techniques. Furthermore, the paper explores each sector’s commonly used standards and codes. Through this extensive review, the paper aims to advance knowledge in the field and support the ongoing development and implementation of EV technologies.

Integrated On-Board Battery Chargers (IOBCs) have shown promise as an elegant charging solution for electric vehicles in recent literature. Although the three-phase charging technique of IOBCs has extensively been discussed in the literature, single-phase charging is still a challenging research topic. The Predictive Current Control (PCC) approach has shown many benefits, including a straightforward algorithm, simple implementation, comparatively quick response, and appropriate performance, when compared to conventional control techniques. This paper investigates the impact of single-phase charging of a six-phase-based IOBC system with different winding configurations using PCC, which, up to the best authors’ knowledge, has not been conceived thus far. Under single-phase charging, the zero-sequence current component is utilized to ensure zero torque production during charging mode. Since the impedance of the zero subspace is highly affected by the employed winding design, the performance of PCC with different winding layouts of either induction machine (IM) or permanent magnet synchronous machine (PMSM) is investigated and compared. The proposed method is experimentally validated using a 1.1kW six-phase IM and a 2 kW 12-slot/10-pole PMSM. Finite Element analysis is also carried out to investigate the effect of single-phase charging mode on the induced radial forces and vibration level when PM machine is employed.

The control of energy storage systems (ESSs) within autonomous microgrids (MGs) is critical for ensuring stable and efficient operation, especially when incorporating renewable energy resources (RESs) such as photovoltaic (PV) systems. This paper addresses managing a standalone DC microgrid that combines PV generation and a battery energy storage system (BESS). We propose a hybrid control strategy that combines a Recurrent Neural Network (RNN) with Proportional-Integral (PI) controllers to improve the performance of the bidirectional converter that connects the BESS to the microgrid. The RNN processes the voltage error and derivative into a reference current, which a PI controller refines to determine the best duty cycle for the converter’s switches. This hybrid control scheme provides superior adaptability and performance in various load conditions, including pulsed power load (PPL) demands. Simulation results show that the proposed control method exceeds traditional PI-PI control algorithms, particularly in improving the transient stability of the DC bus voltage and optimizing BESS performance. We conducted extensive hardware experiments to verify the robustness and effectiveness of the developed control algorithm. The experimental results confirmed the superior performance of the hybrid RNN-PI control scheme, demonstrating its ability to maintain system stability and efficiency across a wide range of real-world scenarios. This experimental validation reflects the reliability and effectiveness of the proposed control strategy in improving microgrid operations.

Cyber-physical power systems integrate sensing, communication, and control, ensuring power system resiliency and security, particularly in clustered networked microgrids. Software-Defined Networking (SDN) provides a suitable foundation by centralizing policy, enforcing traffic isolation, and adopting a deny-by-default policy in which only explicitly authorized flows are admitted. This paper proposes and experimentally validates a cyber-physical architecture that couples three DC microgrids through an SDN backbone to deliver rapid, reliable, and secure power sharing under highly dynamic conditions, including pulsed-load disturbances. The cyber layer comprises four SDN switches that establish dedicated paths for protection messages, supervisory control commands, and high-rate sensor data streams. An OpenFlow controller administers flow-rule priorities, link monitoring, and automatic failover to preserve control command paths during disturbances and communication faults. Resiliency is further assessed by subjecting the network to a deliberate denial-of-service (DoS) attack, where deny-by-default policies prevent unauthorized traffic while maintaining essential control flows. Performance is quantified through packet captures, which include end-to-end delay, jitter, and packet loss percentage, alongside synchronized electrical measurements from high-resolution instrumentation. Results show that SDN-enforced paths, combined with coordinated multi-microgrid control, maintain accurate power sharing. A validated, hardware testbed demonstration substantiates a scalable, co-designed communication-and-control framework for next-generation cyber-physical DC multi-microgrid deployments.

The Increasing Demand for Renewable energy and the need for sustainable power systems have driven the development of networked microgrids, offering a decentralized approach to energy management. This article presents an experimentally validated power-sharing framework for interconnected microgrids, emphasizing system security and sustainability. The proposed system leverages software-defined networking (SDN) to optimize energy distribution, enhance resilience, and mitigate cybersecurity threats within the networked microgrid environment, particularly denial-of-service (DoS) attacks. Microgrids integrate distributed energy resources (DERs) such as solar, wind, and battery storage, providing localized, reliable, and sustainable power solutions. When multiple microgrids interconnect to share power, balancing local loads becomes crucial for efficiency. However, these interconnections introduce vulnerabilities in the communication network, making the system susceptible to cyberattacks. SDN offers a centralized control mechanism that dynamically configures the network, manages real-time traffic, and strengthens protection against disruptions. Our results show that the system maintains stable operation and uninterrupted communication despite malicious traffic, thereby ensuring continuous power sharing among microgrids. This robustness enables the high utilization of renewable energy resources and reduces reliance on carbon-intensive backup solutions, advancing sustainability objectives for clean and reliable power distribution.