Electric vehicles (EVs) are getting more popular in the field of automobiles due to environmental factors and others. Since electric vehicles manage their power from the rechargeable battery so it’s essential to have a reliable, efficient, and economical battery charger that can provide stable required output for the specified EV’s battery. In this paper, a DC-DC converter with a modified PI controller has been presented which helps to achieve the required output voltage and high current density with negligible overshoot for the specified lithium-ion battery system to minimize the charging time. Apart from minimizing the power loss of the active switches, the proposed system minimizes the junction temperature which eventually improves the life cycle of the converter. The analysis of the proposed converter is performed both in ideal and non-ideal conditions. The power loss of the active switches and the junction temperature have also been analyzed. An economical and effective dc and ac side inductor has been designed and perform the total power loss and the temperature rise. The analysis results show that the proposed converter can maintain a power factor of more than 90% and a total harmonic distortion of less than 0.46%, which is ideal for the high-density load current. The reliability of the dc-dc converter is also evaluated. A hardware prototype has also been implemented to confirm its viability for EV battery charging applications.

Uninterrupted power supply with sustainable microgrid remains a big challenge for Kutubdia Island in Bangladesh. However, the majority of study has been focused on the techno-economic aspects of producing electricity in support of this isolated area. To bridge the gap, the present study proposes a methodology for assessing off-grid hybrid microgrid pertaining to the priorities of four key sustainability performance indicators (KSPI): economy, environment, technology, and society. The evaluation process also includes total 13 sets of sub-indicators under KSPI, such as levelized cost of energy, return on investment, CO2 emissions, renewable fraction, excess electricity, unmet load, land usage, job creation etc. The comprehensive value of KSPI regarding economic, environmental, technical, and social priorities are computed using fuzzy logic Mamdani type rules, which facilitates human judgment in linguistic terms and eliminates weightage ambiguity. Seven microgrid scenarios integrating locally accessible resources have been scored and ranked to identify suitable configuration. According to the findings, the PV/Wind/Diesel/Converter/Battery combination reveals best option considering economic priority. On the other hand, the PV/Wind/Converter/Battery alternative receives excellent performance scores and is recommended in both environmental and social categories. However, the PV/Diesel/Converter/Battery arrangement outperforms the others architectures and gets preference for technical reasons. Additionally, the electrical, financial, emission, and sensitivity analysis are carried out for a selected microgrid in Kutubdia. This assessment framework can assist academics, policymakers and investors for planning microgrid in a better way based on sustainable dimensions.

Smart electric vehicles (EVs) are attractive because of their clean, zero-emission, low impact on the environment whilst providing a safer and smoother riding experience. To provide the latter, driving control requires appropriate systems and algorithms to optimize smart vehicle performance, maximize vehicle stability and protection, minimize accident probability, heighten driving comfort, and optimize transportation costs. Despite advancements in these areas, the realization of optimal smart EVs still requires considerable effort. This paper reviews driving control systems and algorithms for smart EVs, including the advanced driving assistant system, implementation of sensors, vehicle dynamics, and control algorithms. The major contribution of this review is to identify promising work to assist researchers with the most advanced trends in this area for prospective regulations.

A Proportional-Integral-Derivative (PID)-controlled synchronous buck converter (SBC)-based battery charging system was designed to charge a lead-acid cell battery using commercially available Photovoltaic (PV) panel. The proposed system was installed aboard a fishing trawler to power its electrical system replacing the conventional system, which uses a diesel generator and a few kerosene lamps for lighting purposes. A PID algorithm instead of traditional Maximum power point tracker (MPPT) is used in the proposed system since the charging process of the battery requires a maximum current instead of maximum power. The proposed control algorithm is compared with the popular MPPT technique Perturb and Observation (P&O) to validate its dynamic performance at different solar irradiance levels using MATLAB/Simulink^®. The simulation and the experimental results have demonstrated that the dynamic response of the proposed algorithm is significantly improved by considering higher charging current, the capability to charge the battery at low irradiance, high stability, and lower cost. Finally, a successful 15-day field trial was conducted at sea using the proposed system, and a maximum charging current output of 6.5 A was achieved by the SBC during noon time; it was sufficient to charge a 12 V, 100 Ah battery, with a state of charge (SoC) of 33%, at a voltage charging rate of +0.3 V/h.

This paper presents the design and evaluates the system performance of one-kilowatt capacity asynchronous and synchronous buck converter based solar-powered charging systems for battery-driven electric vehicles. The dc motor-operated three-wheeler rickshaw was taken for testing the systems, where a battery bank containing four series-connected sub-colloid storage type batteries of each with a capacity of 12V, 120Ah has been used. PSIM simulation software has been used to evaluate the performances of these two types of battery charging systems. Hardware prototypes of these two types of charging systems have also been made and an experimental testbed comprising a 48V battery bank of 100Ah capacity with a charging current of 6A was performed. The experimental results have also been evaluated and compared.

This paper explores sustainable energy management strategies for a remote community on the Island of Bhashanchar in the Bay of Bengal, designated by the Government of Bangladesh to host Rohingya refugee camps. The island lacks utility‐scale power infrastructure, relying primarily on rooftop solar systems. Addressing the challenge of efficient energy utilization, the study analyses the Bhashanchar Community System's energy dynamics, load demand, and renewable energy integration feasibility. The primary objective is to design an optimised hybrid microgrid system to balance energy supply and demand, reducing blackout risks. A Supervisory Control and Data Acquisition based load management system is introduced for real‐time energy distribution, enhancing reliability. The proposed off‐grid hybrid microgrid system includes solar PV, wind, diesel, biomass, wind turbine, tidal turbine, and battery storage. It incorporates priority setting mechanisms to categorise energy sources by reliability, availability, and environmental impact, ensuring consistent, reliable, and sustainable energy supply. The study demonstrates that the proposed system can achieve significant energy savings, around 23%, compared to traditional models, showcasing the effectiveness of the hybrid microgrid approach in powering remote communities with limited conventional energy access.