Apart from being emission-free, electric vehicles enjoy benefits such as low maintenance and operating costs, noise-free, easy to drive, and the convenience of charging at home. All these benefits are directly dependent on the performance of the battery used in the vehicle. In this paper, one-dimensional modeling of Li-ion and NiMH batteries was developed, and their performances were studied. The performance characteristics of the batteries, such as the charging and discharging characteristics, the constituent losses of over-potential voltage, and the electrolyte concentration profile at various stages of charge and discharge cycles, were also studied. It is found that the electrolyte concentration profiles of Li-ion batteries show a drooping behavior at the start of the discharge cycle and a rising behavior at the end of discharge because of the concentration polarization due to the low diffusion coefficient. The electrolyte concentration profiles of NiMH batteries show rising behavior throughout the discharge cycle without any deviations. The reason behind this even behavior throughout the discharge cycle is attributed to the reduced concentration polarization due to electrolyte transport limitations. It is found that the losses associated with the NiMH battery are larger and almost constant throughout the battery’s operation. Whereas for the Li-ion batteries, the losses are less variable. The electrolyte concentration directly affects the overpotential losses incurred during the charging and discharging phases.

Human Machine Interfaces and biomedical prosthetics are advancing rapidly, merging human and machine capabilities. These innovations offer tremendous benefits, but the effectiveness of implantable medical devices (IMDs) hinges on the reliability of their batteries. This article explores the various battery technologies used to power IMDs. The review focuses on the unique characteristics, identifies current challenges and future opportunities in the design and enhancement of batteries for IMDs. The review delves into different battery technologies, emphasizing advancements in electrode materials, biocompatible electrolytes, innovative power delivery systems, and novel energy harvesting techniques. It explores the potential of incorporating new nanomaterials, wireless charging solutions, and bio-energy harvesting methods in battery design. Furthermore, the review discusses recent progress in AI-powered implantable battery health monitoring. The study identifies key challenges in existing battery technologies, such as issues with energy density, cycling stability, and longevity, and points out possible enhancements facilitated by introducing advanced materials and cutting-edge technologies. The review also highlights the promise of AI techniques in improving the health monitoring of implantable batteries. The review highlights the critical need to address the stringent requirements of implantable battery design to drive the advancement of healthcare technologies. By adopting novel materials, innovative charging, and energy harvesting methods, along with AI-driven health monitoring, substantial improvements in implantable battery performance can be achieved, thereby enhancing the reliability and effectiveness of biomedical prosthetics and implantable devices. Graphical abstract

Lithium‐ion batteries have a very wide application range. They can power up small electronic devices such as smart watches to larger electric vehicles. Due to its varied range of applications, they come in different packaging and in such battery packs, even when individual cell voltage exceeds by a few milli‐volts above 4.2 V, it may result in thermal runaway and explode the cell. During discharge cycle, cell imbalances hinder the use of battery to its full capacity. This in turn decreases the battery lifetime. The individual battery cells should be equalized on a regular basis to keep the imbalances to a minimum and to have a good battery life. The process of balancing the individual cell charges by measuring the cell state of charge (SoC) and its voltage in a battery pack is known as cell balancing. This paper details an active cell balancing technique that uses a buck converter for balancing a series connected battery pack of lithium‐ion cells. A buck converter along with a pair of MOSFET switches for each cell, one turned on for charging the cell and the other one turned on while discharging the cell is used in this experiment. An algorithmic model suitable for reconfigurable battery systems that measures the individual cell voltages and is developed for balancing a pack of series connected Li‐ion battery cells. The developed model is simulated using MATLAB for verifying its performance. A state of charge of 25% is maintained across the cells and when SoC value drops below this even a difference of 0.02% is sensed by the algorithm to initiate balancing function. This balancing is found to take 275 ms to balance three 3.7 V batteries and thus the model is found to respond faster. The results show that this method can self‐adaptively attain satisfactory performance within a limited equalizing period.

Renewable and distributed energy generation includes wind turbines, fuel cells, solar cells, and batteries. These distributed energy sources need special power converters in order to connect them to the grid and make the generated power available for public use. Solar energy is the most readily available energy source; hence, if utilized properly, it can power up both domestic and industrial loads. Solar cells produce DC power, and this should be converted to an AC source with the help of inverters. A multi-level inverter for an application is selected based on a trade-off between cost, complexity, losses, and total harmonic distortion (THD). A packed U-cell (PUC) topology is composed of power switches and voltage sources connected in a series-parallel fashion. This basic unit can be extended to a greater number of output voltage levels. The significance of this design is the reduced use of power switches, gate drivers, protection circuits, and capacitors. The converter presented in this paper is a 31-level topology switched by a variable switching frequency-based model predictive controller that helps in achieving optimal output with reduced harmonics to a great extent. The gate driver circuit is also optimized in terms of power consumption and size complexity. A comparison of the 9-level and the 31-level PUC inverters is carried out to study the impact of the number of levels on the total harmonic distortion. The simulation results depict that the total harmonic distortion (THD) for a nominal modulation index of 0.8 is 11.54% and 3.27% for the 9-level multi-level inverter (MLI) and the 31-level modified packed U-cell multi-level inverter (MPUC-MLI), respectively. The reduction in THD is attributed to the increased number of steps in the output when using the model predictive controller.

Need for non-toxic materials especially for biomedical application remains the most important driving force for the discovery of nature-derived biomaterials. In particular, fibers and extracts from plants with medicinal value are vastly investigated. One such source is the banana fiber. The lignocellulosic and protein-based structures of banana fibers contribute to their biodegradability and biocompatibility, which are essential attributes for medical use. Despite their promising biocompatibility, banana fibers face challenges such as variability in their mechanical properties and limited raw state performance. This necessitates precise fiber synthesis and advanced processing to obtain biocompatible fibers for biomedical use. This review discusses the chemical constituents, extraction methods, characterization of natural fiber derived from banana pseudo stem, along with the antimicrobial and tissue regeneration potential of banana fiber based biomedical materials recently developed. Further, steps involved in the conversion of banana fiber to useful biomedical material are presented along with fabrication techniques. In addition, challenges and limitations that hurdle research progress, and potential for future biomaterials through functionalization are discussed. Review findings support potential for research intervention at the integration of banana fibers, biopolymers and nanotechnology towards development of efficient wound healing materials. Inherent to the comprehensive coverage of topics, the authors assure that this review will potentially act as a valuable source of information that could boost research and development of banana fiber-based wound healing biomaterials. Graphical Abstract