In order to reduce carbon emissions and address global environmental concerns, the automobile industry has focused a great deal of attention on electric vehicles, or EVs. However, the performance and health of batteries can deteriorate over time, which can have a negative impact on the effectiveness of EVs. In order to improve the safety and reliability and efficiently optimize the performance of EVs, artificial intelligence (AI) approaches have received massive consideration in precise battery health diagnostics, fault analysis and thermal management. Therefore, this study analyzes and evaluates the role of AI approaches in enhancing the battery management system (BMS) in EVs. In line with that, an in-depth statistical analysis is carried out based on 78 highly relevant publications from 2014 to 2023 found in the Scopus database. The statistical analysis evaluates essential parameters such as current research trends, keyword evaluation, publishers, research classification, nation analysis, authorship, and collaboration. Moreover, state-of-the-art AI approaches are critically discussed with regard to targets, contributions, advantages, and disadvantages. Additionally, several significant problems and issues, as well as a number of crucial directives and recommendations, are provided for potential future development. The statistical analysis can guide future researchers in developing emerging BMS technology for sustainable operation and management in EVs.

In this letter, a new tri-band antenna is designed for a wireless body area network (WBAN) device. The proposed antenna consists of two new landolt ring-shaped strips connected by a rectangular strip and symmetrical stubs extended from the coplanar waveguide (CPW) ground plane. By integrating these techniques, an antenna with three operating bands, covering 3.19-4.57, 5.37- 5.6, and 7.56-10.67 GHz, is obtained. The proposed antenna is optimized to satisfy the required band with good radiation patterns. The characteristics of the proposed antenna in on-body environment are also analyzed. In this scenario, a tri-band antenna for VSWR ≤ 2 is also achieved successfully. The fabricated antenna has a compact size of 35 × 26.6 × 1.6 mm ³ . These features demonstrate that the proposed antenna is a suitable candidate for WBAN applications.

Fuel cell electric vehicles (FCEVs) have received significant attention in recent times due to various advantageous features, such as high energy efficiency, zero emissions, and extended driving range. However, FCEVs have some drawbacks, including high production costs; limited hydrogen refueling infrastructure; and the complexity of converters, controllers, and method execution. To address these challenges, smart energy management involving appropriate converters, controllers, intelligent algorithms, and optimizations is essential for enhancing the effectiveness of FCEVs towards sustainable transportation. Therefore, this paper presents emerging energy management strategies for FCEVs to improve energy efficiency, system reliability, and overall performance. In this context, a comprehensive analytical assessment is conducted to examine several factors, including research trends, types of publications, citation analysis, keyword occurrences, collaborations, influential authors, and the countries conducting research in this area. Moreover, emerging energy management schemes are investigated, with a focus on intelligent algorithms, optimization techniques, and control strategies, highlighting contributions, key findings, issues, and research gaps. Furthermore, the state-of-the-art research domains of FCEVs are thoroughly discussed in order to explore various research domains, relevant outcomes, and existing challenges. Additionally, this paper addresses open issues and challenges and offers valuable future research opportunities for advancing FCEVs, emphasizing the importance of suitable algorithms, controllers, and optimization techniques to enhance their performance. The outcomes and key findings of this review will be helpful for researchers and automotive engineers in developing advanced methods, control schemes, and optimization strategies for FCEVs towards greener transportation.

In this paper, a new compact wideband monopole antenna is presented for wireless communication applications. This antenna comprises of a new radiating patch, a new arc-shaped strip, microstrip feed line, and a notched ground plane. The proposed radiating patch is combined with a rectangular and semi-circular patch and is integrated with a partial ground plane to provide a wide impedance bandwidth. The new arc-shaped strip between the radiating patch and microstrip feed line creates an extra surface on the patch, which helps further widen the bandwidth. Inserting one step notch on the ground plane further enhances the bandwidth. The antenna has a compact size of 16×20×1.6mm³. The measured result indicated that the antenna achieves a 127% bandwidth at VSWR≤2, ranging from 4.9GHz to 22.1GHz. Stable radiation patterns with acceptable gain are achieved. Also, a measured bandwidth of 107.7% at VSWR≤1.5 (5.1-17GHz) is obtained, which is suitable for UWB outdoor propagation. This antenna is compatible with a good number of wireless standards, including UWB band, Wimax 5.4 GHz band, MVDDS (12.2–12.7GHz), and close range radar and satellite communication in the X-band (8-12GHz), and Ku band (12-18GHz).

In this paper, a miniaturized Egret-Beak shaped patch tri-band implantable antenna for Medical Implant Communication Services (MICS) (402-405 MHz), Wireless Medical Telemetry Service (WMTS) (1430MHz) and Industrial Scientific and Medical (ISM) (2.4-2.48GHz) band is proposed. The antenna is composed of an Egret-Beak shaped radiation patch and a ground plane. A shorting pin is directly connects from the radiating patch to the ground plane to reduce the size of the antenna. The antenna occupies a small size of 10×12mm². The antenna is optimized to achieve the triple band designed antenna. The results indicates that the antenna can achieve 260MHz (74%) band for MICS, 150MHz (11%) band for WMTS and 680MHz (27%) band for ISM band. The proposed antenna (implanting in the arm) with significant impedance bandwidth and its compactness shows that the antenna is suitable for wireless telemetry applications.

Diabetes is a serious health concern, and it became more and more common to the people due to its rapidly increasing cases. People with diabetes are required to monitor their blood glucose level regularly in order to control their blood glucose concentration level (BGCL). Common monitoring methods which taken recently are either laboratory chemical analysis or using invasive device such as glucometer to do self-checking. The process is painful and intimidating as it requires to collect blood sample from fingertips or arms. To minimize the pain and suffer, a non-invasive system for BGCL measurement is highly demanded. In this research, A small pair of ultra-wide band (UWB) antenna was utilized for BGCL measurement through human earlobe. Due to its high data rate lower transmission capacity and the power is below the noise floor level, which does not affect the human body, the UWB based system is commonly used in biomedical applications. A pair of UWB antennas attached to the P400 RCM transceivers are used in the integrated device to produce a 4.7 GHz frequency and pass through the earlobe. The scattered signal pulse obtained was translated from analogue to digital discrete values and afterwards decreased discrete values were used as artificial neural network data (ANN). In this work, feed-forward backpropagation neural network (FFBPNN) has been used as an ANN module. Several experiments were carried out to investigate the optimal ANN learning algorithm (levenberg-marquardt (LM), resilient backpropagation (RP) and scaled conjugate gradient (SCG)) for performance comparison. During the investigations, LM, RP, SCG shows the performance with 89.47%, 85.96% and 82.85% respectively.