Electric vehicles (EVs) are widespread, and their usage is increasing as a result of air pollution and rising fuel costs. EVs are quickly gaining popularity as a green means of transportation. By 2030, most cars will probably be battery-powered EVs. However, the development of EV power transmission is packed with important challenges and is an active topic of research. In EVs, the battery serves to store electrical energy. The DC-DC converter provides a direct current (DC) link between the battery and the inverter. A motor provides the transmission for the vehicle's motion. Hence, this state-of-the-art provides exhaustive information about battery management systems (BMS), power electronics converters, and motors. Lithiumion batteries are more efficient for EV applications, and boost converters and full bridge converters are commonly used in EVs. EVs use permanent magnet synchronous motors (PMSM) and induction motors (IM). The renewable energy-based charging station and the fast charging specifications are also clearly addressed for EV applications. INDEX TERMSElectric vehicle, BMS, power converters, motors, charging station, cyber security. NOMENCLATURE ABBREVIATION BLDC Brushless DC Motor. BMS Battery Management Systems. CO Carbon monoxide. CO 2 Carbon dioxide. DC Direct Current. EVs Electric Vehicles. EIS Electro-chemical impedance spectroscopy. ESS Energy storage systems. FC Fuel cell. HEVs Hybrid Electric Vehicles. IM Induction Motor.The associate editor coordinating the review of this manuscript and approving it for publication was Ramazan Bayindir .

Electric vehicles (EVs) have acquired significant popularity in recent decades due to their performance and efficiency. EVs are already largely acknowledged as the most promising solutions to global environmental challenges and CO2 emissions. Li-ion batteries are most frequently employed in EVs due to their various benefits. An effective Battery Management System (BMS) is essential to improve the battery performance, including charging–discharging control, precise monitoring, heat management, battery safety, and protection, and also an accurate estimation of the State of Charge (SOC). The SOC is required to provide the driver with a precise indication of the remaining range. At present, different types of estimation algorithms are available, but they still have several challenges due to their performance degradation, complex electrochemical reactions, and inaccuracy. The estimating techniques, average error, advantages, and disadvantages were examined methodically and independently for this paper. The article presents advanced SOC estimating techniques, such as LSTM, GRU, and CNN-LSMT, and hybrid techniques to estimate the average error of the SOC. A detailed comparison is presented with merits and demerits, which helped the researchers in the implementation of EV applications. This research also identified several factors, challenges, and potential recommendations for an enhanced BMS and efficient estimating approaches for future sustainable EV applications.

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This study presents the boost converter-based cascaded H-bridge (CHB) multilevel inverter with improved reliability for solar PV (photovoltaic) applications. The solar PV is associated with the boost converter to enhance DC link voltage by using the maximum power point tracking-perturb and observe (MPPT-P & O) technique. The proposed configuration is aimed toward the performance analysis of the boost converter-based CHB MLI by reducing the number of components, low total harmonic distortion (THD), reduced power, less cost function, low total standing voltage (TSV), improved reliability, and switching losses for solar PV application. In this study, a CHB multilevel inverter is used to obtain stepped pure sinusoidal AC from the solar PV array. The proposed boost converter extracts maximum power and enhances higher DC link voltage which provides high efficiency. The boost converter is integrated with a 27-level CHB multilevel inverter to generate near-sinusoidal output voltage with lower THD. The inverter is tested with linear and nonlinear loads for robustness, and during dynamic loads, inverter is stable and well suited to grid-connected applications. A detailed comparison is presented on the component count and reliability aspects with existing MLIs and 27-level MLIs. The simulation outcomes of the implemented arrangement are presented with the help of MATLAB/Simulink, an experimental prototype is developed using a dSPACE RTI1104 controller and also tested in the research laboratory for checking the possibility of the implemented arrangement.