The modern era of green transportation based on Industry 4.0 is leading the automotive industry to focus on the electrification of all vehicles. This trend is affected by the massive advantages offered by electric vehicles (EV), such as pollution-free, economical and low-maintenance cost operation. The heart of this system is the electric motor powered by lithium-ion batteries; however, due to their many limitations, a hybrid energy storage system (HESS) consisting of batteries and ultracapacitors is currently gaining increased attention. This paper aims to review the distinct motor technologies such as brushless motors, synchronous reluctance and induction motors currently used in EVs. Additionally, through eleven selected criteria, such as regenerative braking efficiency and power density at different load ranges, the motors are classified in terms of their combined ability to operate with a HESS in order to maximize efficiency and sizing. The results show that permanent magnet and induction motors are the best options when all criteria are considered, while synchronous reluctance motor outperforms the induction motor regarding only the main factors affecting the performance of the hybrid storage system.

The transportation sector has a significant impact on climate change, as it is responsible for 20% of the global greenhouse gas (GHG) emissions. This paper evaluates the role of electric vehicles (EVs) in achieving Europe’s ambitious target of carbon neutrality by 2050. The limitations of internal combustion engines (ICEs) along with the recent advancements, such as Euro 6 standards, are examined with a pseudo–lifecycle analysis (pseudo-LCA). While ICEs remain cost-effective initially, their higher long-term cost and environmental impact make them unsustainable. The benefits of EVs, including high energy efficiency, minimal maintenance, and reduced GHG emissions, are stated. However, challenges such as range limitations, charging infrastructure, and the environmental cost of battery production persist. Hybrid electric vehicles (HEVs) are highlighted as transitional technologies, offering improved thermal efficiency and reduced emissions, enhancing air quality in both urban and rural areas. The analysis extends to the use of alternative fuels, such as bioethanol, biodiesel, and hydrogen. These provide interim solutions but face scalability and sustainability issues. Policy interventions, including subsidies, tax incentives, and investments in renewable energy, are crucial factors for EV adoption. As EVs are pivotal to decarbonization, integrating renewable energy and addressing systemic challenges are essential for a sustainable transition.

Energy consumption demands are rapidly increasing every year, with an 8% annual growth rate projected for the next five years. As buildings represent over 35% of this demand, a metering system is required for monitoring to accurately calculate costs. This paper explores the evolution and impact of energy management through smart meters, emphasizing their superiority over traditional electromechanical devices, in applications such as minimizing power losses and enhancing grid reliability. This study compares the performance of five distinct metering systems, including electromechanical and advanced smart meters. Real-time testing across various scenarios is incorporated, examining parameters such as real and reactive power measurement, accuracy and adaptability to smart grids. Key findings revealed that smart meters, notably the EDMI Mk10A, outperform legacy systems in precision, data transmission and energy optimization. In addition, the potential of smart meters to enable dynamic cost calculation and prevent electricity theft is evident. Despite their advantages, challenges such as data privacy, installation costs and electromagnetic radiation concerns, persist. Future investigations to address the identified limitations are required.

Following the European Climate Law of 2021 and the climate neutrality goal for zero-emission transportation by 2050, electric vehicles continue to gain market share, reaching 2.5 million vehicles in Q1 of 2023. Electric vehicles utilize an electric motor for propulsion powered by lithium batteries, which suffer from high temperatures caused by peak operation conditions and rapid charging, so hybridization with supercapacitors is implemented. In this paper, a fuzzy logic controller is employed based on a rule-based scheme and the Mamdani model to control the power distribution of the hybrid system, driven by the state of charge and duty cycle parameters. An active topology with one bi-directional DC-to-DC converter at each source is exploited in the MATLAB/Simulink environment, and five power states like acceleration and coasting are identified. Results show that the ideal duty cycle is within 0.40–0.50 as a universal value for all power states, which may vary depending on the available state of charge. Total efficiency is enhanced by 6%, sizing is increased by 22%, leading to a more compact layout, and battery life is extended by 20%. Future work includes testing with larger energy sources and the application of this management strategy in real-time operations.

The adoption of electric vehicles (EVs) has emerged as a significant measure to reduce greenhouse gas emissions and promote cleaner transportation towards the goal of decreasing temperature increase over 0.5°C by 2050. The evolution of battery technology allows for massive exploitation of EVs as they require low maintenance and have over 200% higher efficiency in total than conventional vehicles. However, the need for rapid implementation of charging stations poses unique challenges for electrical distribution networks. This paper investigates the influence of electric vehicle (EV) charging stations on the electricity utility grid, focusing on their technological frameworks. The capabilities and challenges of lithium-ion battery technologies are examined, including their high energy density and reliability, while addressing concerns over performance limitations due to aging cause by high temperatures. The work outlines current charging technologies, classifying them into AC and DC wired systems, wireless charging methods, and battery exchange systems. Rapid advancements have reduced charging times to 10–15 minutes for 80% capacity using high-voltage systems. Furthermore, the integration of Vehicle-to-Grid (V2G) systems, where the EV as an separate energy storage system exchanges power with the utility grid, was found to reduce peak load by over 4% and improve energy efficiency, lowering energy costs by 40% and scheduling costs by 14%. V2G technology enables real-time bidirectional energy transfer, supporting grid stability and sustainability. Challenges such as communication reliability, data privacy, and battery degradation due to increased charging cycles were discussed. The study concludes that the adoption of EVs and their integration with utility grids through V2G systems presents a promising approach to enhance sustainability, although overcoming technical challenges and optimizing battery life are crucial for widespread implementation. The findings emphasize the pivotal role of aggregators in managing power exchanges, predicting load fluctuations, and ensuring a reliable energy supply.

Manual intravenous (IV) monitoring delays, put patients at risk, as the reaction time of nursing staff can be critical to the patient’s health. The widespread use of LoRa networks today is a reality. The deployment of devices and applications based on LoRa networks in healthcare environments, such as hospital facilities, is of great interest and can offer both time savings for medical and nursing staff and improvements in medical care. In this work an integrated low-cost, real-time monitoring system for fluid infusion based on a LoRa network is presented. The measured (monitoring) data are the weight of the fluid infusion flask and the number of fluid drops. The design of the system and the affordability of the materials (low-cost devices) give the possibility for immediate application in healthcare environments. As the system consists of low-cost sensors, and given that it is intended for health purposes, extensive research has been carried out on the evaluation and reliability of the measurements. The proposed system is intended for medical care; in this sense it should have the lowest possible measurement error. The evaluation of the system has revealed a polynomial equation as a corrective factor for weight and shows an improvement of the error from 2% of the raw measurements to 0.6% of the corrected measurements, while regarding the calculation of the weight from the measurement of the droplets, it shows an error of 1.6%. The proposed system contributes directly to both the valuable time of the medical staff and the improvement of patient care. The evolution of technology should be applied to the health sector and low-cost and internet of things (IoT) devices can be applied to healthcare after thorough evaluation and calibration procedures.