The Electric transit buses (ETBs) are the main source for public transit to get the cleaner environment. The ETBs have gained popularity around the globe since the last decade. The ETBs are 14 % of the total transit buses around the world. The ETBs are heavy EVs and need more power to charge the high capacity batteries. The batteries used in these buses have the energy capacities between 80 kWh to 550 kWh. Such high capacity batteries take more to get charged. In order to increase the adoption of ETBs, a suitable number of high power dc charging infrastructures need to be installed in various main cities of the nations. The ETBs can operate with battery alone or fuel cell or combination of these two. Such ETBs are named as battery electric transit bus (BETB), fuel cell electric transit bus (FCETB) and hybrid electric transit bus (HETBs). As of 2020, out of total ETBs around the globe, 70 % are HETBs, 20 % are FCETBs and 10 % are BETBs. In this paper, the key parameters and comparison among these three batteries are shown. The major EV market holders are China, US, Europe and japan. The charging protocol used in the US and Europe is combined charging system. The charger capacity has reached up to 500 kW as of 2020. With such high power chargers it takes only less than half an hour to charge the high power batteries.

For the purpose of minimizing passive and receptive losses and giving the lowest possible voltage deviation, the IEEE standard 33-bus network is utilized in the current research to evaluate the capacity and position of EV charging stations. Therefore, according to their location, the current passing through the lines, the voltage of the phases, and, of course, the location of the loads, the voltage of the buses changes and can change the network expenses and the network voltage deviation profile. A charge is applied to the network since electric car owners show their likelihood of recharging based on a number of behavioral criteria, including the average charging time, the distance to the charging location, whether the charging location is busy or quiet, and other considerations. Therefore, this probabilistic behavior is dynamically modeled by queuing theory (modeled using Poisson's function), The uncertainty of other loads except for charging stations is modeled using the Monte Carlo distribution function, and finally, with the help of two cumulative algorithms, PSO and genetics, the ideal station placement is addressed, and the simulation's outcomes show appropriate operation. In terms of optimal positioning, particle algorithms outperform genetic algorithms.

In recent years, the popularity of wireless inductive power transfer (WIPT) system for electric vehicle battery charging (EVBC) is always ever-increasing. In the WIPT inductively coupled coil structure is the heart of the system and the mutual inductance (MI) between the coupled coils is the key factor for effective power transfer. This paper presents the analysis of mutual inductance between the spiral square coils based on the crosssectional area ratio of spiral circular and spiral square coupled coils. The analytical computed MI values are compared with FEM (ANSYS Maxwell) simulation and Experimental computed values. Finally, the designed spiral square coils are implemented in a laboratory prototype model and at the receiver side for effective electric vehicle (EV) battery charging a closed-loop PID controller is implemented for DC-DC buck converter. The effectiveness of the proposed controller has been tested by providing sudden changes in mutual coupling and change in reference value. The proposed system is suitable for both stationary and dynamic wireless EVBC.

Due to increasing air pollution and fuel supply problems, the use of electric vehicles has been considered as a clean alternative to traditional cars. Extensive studies have been conducted on the environmental effects of these cars and their benefits in reducing air pollution have been proven. However, the high penetration of electric vehicles can create new challenges in the power system, especially concerning their charging demands. The change in demand due to electric vehicles creates challenges and concerns for the electric system. The electrical system must be ready to respond to a new load called “the demand for electric vehicles”. In this paper, by providing the optimal charging price and considering traffic restrictions, remained charging limits and charging rates, it is possible to choose the right charging station. This action reduces the possibility of damage to the network and leads to the improvement of network technical parameters, including losses and voltage profile. The results shows the effectiveness of the model.

Finding effective solutions to enhance the process of electric vehicle charging has been the main subject of numerous studies. This paper presents a novel bidirectional multiport rectifier that can be used as a wall-box converter that is installed in the parking lot of smart buildings and is capable of providing DC-link for local DC loads, such as DC home appliances and charge connected EV, simultaneously. The proposed converter is capable of working in G2H/G2VH/V2H/V2G modes, enabling the utility grid and costumers to use the EV as a mobile power source and reactive power compensator. A control method is also presented that enables the converter to control active and reactive power according to the smart grid or customer processed commands. To validate the features of the proposed converter, it is simulated in MATLAB/SIMULINK and the results are analyzed. A reduced-scale experimental setup of the proposed converter is built and tested, and the experimental results confirm the simulation ones.

Air conditioning systems are used in industries and residential environments with the aim of improving environmental conditions and creating a comfortable temperature for users. Considering the production of sound and vibration in most of its components, the lack of control of the production sound level always exposes the users to unwanted sound, which in addition to hearing complications, also causes fatigue and dissatisfaction with the environmental conditions. . Compressors are one of the most important sources of sound production in air conditioning systems, and screw compressors are one of the most widely used in air conditioning industries. Therefore, the compressor shell should be designed to minimize the transmission of sound from inside to outside. Since the maximum working temperature of compressors is up to 80 degrees Celsius, therefore, in this research, an acoustic test was performed on a sample of a screw compressor shell in two modes of ambient temperature and maximum working temperature inside the acoustic room, and the effect of temperature increase on the sound pressure level. transferred from the shell to the external environment is discussed. Finally, based on the frequency analysis performed in two conditions of ambient temperature and maximum working temperature and comparing the amount of sound transmitted to the environment at different frequencies, practical solutions to reduce the amount of transmitted sound pressure have been presented.

Due to the stochastic nature of renewable energy sources (RES) and electric vehicles (EV) load demand, large scale penetration of these resources in the power systems can stress the reliable network performance, such as reducing power quality, increasing power losses, and voltage deviations. These challenges must be minimized by optimal planning based on the variable output from RES to meet the additional demand caused by EV charging. In this paper, a novel method for optimal locating and sizing of RES and EV charging stations simultaneously and managing vehicle charging process is provided. A multi-objective optimization problem is formulated to obtain objective variables in order to reduce power losses, voltage fluctuations, charging and demand supplying costs, and EV battery cost. In this optimization problem, the location and capacity of RES and EV charging stations are the objective variables. Coefficients which are dependent on wind speed, solar radiation, and hourly peak demand ratio for the management of the EV charging pattern in low load hours are introduced. GA-PSO hybrid improved optimization algorithm is used to solve the optimization problem in five different scenarios. The performance of the proposed method on IEEE 33-bus system has been investigated to validate the effectiveness of the novel GA-PSO method to optimal sitting and sizing of RES and EV charging stations simultaneously.

Due to the presence of power electronic converters in electric vehicle battery chargers, the electrical power drawn from the distribution system has severe distortions which pose many problems to the power quality. Herein, the impact of chargers in terms of indicators, e.g., penetration level, battery state of charge, type of charging stations, the time of connection of chargers to the network, and the location of charging stations was comprehensively studied on a sample distribution network. The effect of these chargers was investigated based on power quality parameters, e.g., total harmonic distortion (THD) and voltage profile, and the effect of each indicator on these parameters was determined. To minimize the effects of the chargers, an IEEE 33-bus distribution sample network was optimized with the objective functions of voltage drop and THD. Based on this optimization algorithm, the installation placement and the power capacity of the charging stations were obtained to achieve the lowest voltage drop and THD.