This paper proposes an intelligent and fast controller for the parallel DC-DC converters in the islanded DC microgrids (DCMG) in the shipboard power system applications (SPSs). The existence of constant power loads and propulsion loads in the SPS makes the voltage regulation as an important issue in the islanded DCMG. In this paper, the goal is to provide a fast response and proper voltage regulation and optimal current sharing in the stand-alone shipboard DCMG. To achieve this, a nonlinear I-V droop control is firstly designed in the primary control level to ensure the basic performance. Then, a new model-independent technique, entitled intelligent single input interval type-2 fuzzy logic controller (iSIT2-FLC) combined with sliding mode control (SMC), is suggested to further improve the voltage regulation and current sharing accuracy. In this control scheme, an extended state observer (ESO) is employed to estimate the unknown DCMG dynamics, whereas the SMC is adopted to eliminate the ESO estimation error. Moreover, the dynamic consensus algorithm (DCA) is implemented in the secondary control level to achieve coordinated control between DGs in the SPS. The effectiveness and applicability of the new suggested control approach are validated with hardware-in-theloop (HiL) experimental results.

With the increase in the number of electric vehicles (EVs) and developments in their related charging infrastructures, consumers have still some concerns about some limiting factors in the EV industry such as battery life, charging station availability, electric grid capacity, limited driving range, and slow charging of batteries. Although some solutions are proposed for these limitations, they are not sufficiently efficient and cost-effective. Moreover, charging of EVs on-the-road is still a challenging issue which requires more innovation. This paper proposes a novel battery charger, known as an Emergency EV-to-EV Portable Battery Charger (EPBC), which provides a cost-effective solution for charging EVs on-the-road in emergency mode. The suggested smart charger can charge another EV based on the state of charge (SOC), capacity, and other important technical specifications of batteries in a safe and reliable manner. The smart charger can regulate the output voltage and the injected current to the EV simultaneously. To realize these features, a model free nonlinear integral backstepping control (MF-NIBC) is adopted to regulate the output voltage of the battery charger. By utilizing the actor and critic networks, a deep deterministic policy gradient (DDPG) is adopted to adjust the MF-NIBC controller. Finally, real-time tests based on the OPAL-RT setup are conducted to confirm the applicability and feasibility of the proposed EV-to-EV portable battery charger.

Due to the increase in the number of electric vehicles (EVs) in the world, there is a need to design superior performance and lower operating costs of charging infrastructures to serve these vehicles. Merging extreme fast charging technology with the portable feature can provide a user-friendly and cost-effective structure for charging EVs. This paper proposes a Smart Extreme Fast Portable Charger (SEFPC) for Electric Vehicles which have several input ports (e.g., the power grid or Renewable Energy Sources (RESs)/Energy Storage Systems (ESSs)) and an output port with an optimal charging operation mode based on considering the condition of the available power sources and battery of EVs for saving the energy and time charging. Moreover, a model-free sliding mode controller-based machine learning algorithm is applied to find optimal charging operation mode based on the battery state and power of sources condition to increase battery life and overall system efficiency. Finally, real-time results based on the OPAL-RT are provided to validate the efficacy and feasibility of the proposed SEFPC and model-free sliding mode controller.

This study proposes a new decentralised non‐linear I–V droop control to achieve current sharing and voltage restoration for paralleled DC nanogrids (DCNGs) in a cluster. The performance of the conventional droop methods in current sharing among parallel converters degrades due to line impedances. The proposed method improves current sharing among the DCNGs with parallel‐connected converters by considering the effect of line impedance, which is an important issue in practical applications. By the proposed method, desired current sharing from the light‐load to heavy‐load condition is achieved. Since only local information (the output voltage and output current of the DCNGs) is used, the proposed method is fully decentralised, and no communication infrastructure is required, which improves the reliability and stability of the overall system. Furthermore, Lyapunov stability theory is applied to investigate the stability of the proposed method. Additionally, the plug‐and‐play feature is achieved as an important desired functionality in the DCNGs as well as the proposed method provides scalability and modularity for the DCNGs in a cluster. In the end, theoretical analysis and experimental results validate the effectiveness of the proposed control framework for different scenarios.

This paper proposes an intelligent and fast controller for the secondary voltage control in the islanded DC microgrids (DCMGs) for shipboard power system applications (SPSs). The existence of constant power loads (CPLs) and propulsion loads in the SPS makes the voltage regulation as an important issue in the islanded DCMG. In order to achieve fast response and proper voltage regulation as well as optimal current sharing in the stand-alone shipboard DCMG, this paper proposes a new nonlinear droop control in the primary control level. The proposed method eliminates the voltage oscillation in dynamic situations and improves the current sharing among paralleled sources. Furthermore, a novel high bandwidth fractional order general type-2 fuzzy logic proportional-integral-derivative (FOGT2FPID) controller is applied in the dynamic consensus algorithm (DCA)-based method in the secondary control level to ensure fast and accurate voltage regulation in the DCMG. The effectiveness and applicability of the new suggested approach are validated with hardware-in-the-loop (HiL) experimental results.

This brief proposes a dynamic consensus algorithm-based nonlinear I-V droop control for the balancing state of charge of energy storage systems (ESSs) in DC Nanogrids (DCNGs). The dynamic consensus algorithm (DCA) provides a coordinated secondary control with sharing information between Distributed Generation (DG) units to regulate the output power of each DG based on the capacity and state of charge (SoC) of the ESSs. Furthermore, a novel high bandwidth fractional order general type-2 fuzzy logic proportional-integral-derivative (FOGT2FPID) controller is applied in the secondary control level to ensure fast and accurate voltage regulation, and SoC balancing in the DCNG. In the primary control level, a nonlinear I-V droop control approach provides fast dynamic and accurate power-sharing among DGs. Moreover, the proposed control method can provide reliability, modularity, and flexibility. Compared with conventional methods, over-current failures and abruptly disconnection of DGs are prevented with the proposed controller. Experimental results are shown to verify the effectiveness of the proposed control scheme under different scenarios using facilities at the Microgrid Laboratory, Aalborg University.