No abstract

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 .

Pulse width modulation (PWM) methods are used to control the switching sequence operations of conventional multilevel inverters (MLIs) and reduced switch multilevel inverters (RSMLIs). Many researchers proposed various RSMLIs with their switching sequence operation and PWM control techniques. However, the switching operations of RSMLIs are not similar to conventional MLIs, which are a major problem of switch control. Logical equations are proposed for the operation of RSMLIs with the multi-carrier PWM methods like alternative phase opposition disposition (APOD), phase opposition disposition (POD), and phase disposition (PD). To operate the individual switch in symmetrical and asymmetrical RSMLI, logical operators are used to produce required pulse sequence from the sequence of PWM method and their analysis is not present in previous works. The proposed methodology can be applied to PV systems for efficient operation. The proposed methodology and binary representation of PWM method are analyzed on various RSMLIs for seven-level output voltage to operate each individual switch. Control of individual switching sequence and the operation of RSMLIs are simulated using MATLAB/Simulink. THD comparison is presented for RSMLI, DCL MLI, and SCSD MLI with various PWM methods.

The modeling of a solar PV system is challenging due to its nonlinear current vs. voltage characteristics. Although various optimization techniques have been applied for the parameter estimation of the solar PV system, there is still a scope to attain the best-optimized results. This paper uses a new meta-heuristic optimization algorithm and a classical technique named Ali Baba and the Forty Thieves (AFT) with Newton Rapson (NR) method to estimate solar PV system parameters. The well-known story of Ali Baba and the Forty Thieves has inspired the AFT. Besides, the inappropriate objective function used in earlier research to extract parameters from solar PV models is recognized. The experimental findings demonstrate that the suggested approach performs better when compared to state-of-the-art algorithms. Between the measured data and the computed data for AFT, the root mean square error values for the five PV models, such as single diode model (SDM), double diode model (DDM), Photowatt-PWP201, STM6-40/36, and STP6-120/36, are respectively 7.72 × 10−04 ± 6.121 × 10−16, 7.412 × 10−04 ± 9.52 × 10−06, 2.052 × 10−03 ± 3.05 × 10−17, 0.001721922 ± 2.19 × 10−17, and 0.014450817 ± 3.42 × 10−16. In terms of accuracy, the obtained results indicate that the proposed AFT algorithm is more efficient than the other optimization techniques available in the literature. The excellent correlation between the estimated parameters from characteristic curves and observed data for SDM, DDM, Photowatt-PWP201, STM6-40/36, and STP6-120/36 demonstrates that the proposed AFT is a potential option among the techniques available in the literature. The Friedman and Wilcoxon tests have been used to assess the statistical validity of the proposed algorithms.

The network contingencies in power system often contribute to over-loading of network branches, unsatisfactory voltages and also to voltage collapse. To maintain security against voltage collapse, it is desirable to estimate the effect of contingencies. For security enhancement, remedial action against possible network overloads in the system following the occurrence of contingencies is required. Line overloads can be removed by means of generation re-dispatching and by adjustment of reactive power control variables such as tap-changing transformers, generator excitations, and shunt reactive power compensating devices. This paper presents fuzzy logic composite criteria to evaluate the degree of severity of the network contingency. A Particle Swarm Optimization (PSO) based algorithm was also proposed for solving the Optimal Power Flow (OPF) problem to alleviate line overloads. The proposed PSO algorithm identifies the optimal values of generator active-power output and the adjustment of reactive power control devices. Simulation results on IEEE 14, 30, and 118-bus test systems are presented and compared with the results of other approaches reported in the literature.