The optimal planning of electric vehicle (EV) charging stations (ECSs) with advanced control algorithms is very important to accelerate the development of EVs, which is a promising solution to reduce carbon emissions of conventional internal combustion engine vehicles (ICEVs). The large and fluctuant load currents of ECSs can bring negative impacts to both EV-related power converters and power distribution systems if the energy flow is not regulated properly. Recent review papers related to EVs found in open literature have mainly focused on the design of power converter-based chargers and power interfaces, analyses of power quality (PQ) issues, the development of wireless charging techniques, etc. There is currently no review paper that focuses on key technologies in various system configurations, optimal energy management and advanced control issues in practical applications. To compensate for this insufficiency and provide timely research directions, this paper reviews 143 previously published papers related to the aforementioned topics in recent literature including 17 EV-related review papers found in Institute of Electrical and Electronics Engineers (IEEE)/Institution of Engineering and Technology (IET) (IEEE/IET) Electronic Library (IEL) and ScienceDirect OnSite (SDOS) databases. In this paper, existing system configurations, related design methods, algorithms and key technologies for ECSs are systematically reviewed. Based on discussions given in the reviewed papers, the most popular ECS configuration is a hybrid system design that integrates renewable energy (RE)-based power generation (REBPG), various energy storage systems (ESSs), and utility grids. It is noteworthy that the addition of an ESS with properly designed control algorithms can simultaneously buffer the fast, fluctuant power demand during charging, smooth the intermittent power generation of REBPG, and increase the overall efficiency and operating flexibility of ECSs. In addition, verifying the significance of the flexibility and possible profits that portable ESSs provide in ECS networks is a potential research theme in ECS fields, in which the potential applications of portable ESSs in the grid-tied ECSs are numerous and could cover a full technical spectrum.

https://www.mdpi.com/1996-1073/12/21/4201/pdf

System Planning of Grid-Connected Electric Vehicle Charging Stations and Key Technologies: A Review

This article studied the load frequency control (LFC) of a multi-source microgrid with the presence of renewable energy sources. To maintain a sustainable power supply, the frequency of the system must be kept constant. A Proportional–Integral–Derivative (PID) controller is presented as a secondary controller to control the frequency of the microgrid in island mode, and the integral of squared time multiplied by error squared (ISTES) is used as a performance index. The use of the Craziness-Based Particle Swarm Optimization (CRPSO), which is an improved version of Particle Swarm Optimization (PSO), improves the convergence speed in optimizing the nonlinear problem of load and frequency controller design. The test microgrid is composed of the load and distributed generation units such as diesel generators, photovoltaics and wind turbines. The proposed controller provided the desired response to adjusting the microgrid frequency, achieving the final response after a short time and making it more stable and less oscillatory compared with the conventional system.

Optimal Load Frequency Control of Island Microgrids via a PID Controller in the Presence of Wind Turbine and PV

A new wireless charging system for electric vehicles using two receiver coils

Assessment of charging technologies, infrastructure and charging station recommendation schemes of electric vehicles: A review

Novel hybrid improved bat algorithm and fuzzy system based MPPT for photovoltaic under variable atmospheric conditions

This paper presents a straightforward power management algorithm that supervises the contribution of more than one energy source for charging a vehicle, even if the car is in motion. The system is composed of a wireless charging system, photovoltaic (PV) generator, fuel cell (FC), and a battery system. It also contains a group of power converters associated with each energy resource to make the necessary adaptation between the input and output electrical signals. The boost converter relates to the PV/FC, and the boost–buck converter is connected with the battery pack. In this work, the wireless charging, FC, and PV systems are connected in parallel via a DC/DC converter for feeding the battery bank when the given energy is in excess. Therefore, for each of these elements, the mathematical model is formulated, then the corresponding power management loop is built, which presents the significant contribution of this paper. The efficient power management methodology proposed in this work was verified on Matlab/Simulink platforms. The battery state of charge and the hydrogen consumption obtained results were compared to show the effectiveness of this multi-source system.

Efficient Power Management Strategy of Electric Vehicles Based Hybrid Renewable Energy

https://onlinelibrary.wiley.com/doi/pdf/10.1002/est2.117

Analysis of battery‐EV state of charge for a dynamic wireless charging system

A photovoltaic-powered electric vehicle is a complex system that necessitates the use of a high-performance control algorithm. This paper aims to boost the performance of a photovoltaic system by employing a suitable algorithm to control the power interface. The main goal is to find an effective and optimal control law that will enable the photovoltaic generator (GPV) to generate the maximum amount of power possible. The main facts dealt with in this article are the mathematical simulation of the photovoltaic system, its function, and its characteristics, considering the synthesis of the step-up converter and the analysis of the maximum power point tracking algorithm. This study examines and compares two control techniques for extracting full power from the solar energy system. These two techniques are the classical “perturbation and observation” (P&O) method and the intelligent solution “particle swarm optimization (PSO) method.” The PSO solution is tested for two versions: the online PSO version and the table PSO version. The Simulink/MATLAB tool is used for simulation and comparative experiments based on the performance metrics provided. The study revealed that smart technology delivers improved efficiency than the classic edition.

/pdf/increasing-electric-vehicle-autonomy-using-a-photovoltaic-12xq1ooz8v.pdf

Increasing Electric Vehicle Autonomy Using a Photovoltaic System Controlled by Particle Swarm Optimization

Having robust, autonomous and efficient charging stations in our homes or outside seems necessary in order to make EVs more comfortable and encourage cars users to buy this novel generation of cars. Currently, the real problem is related to two essentials points, the charging time and the station of recharge availability. However, finding the best charger mode, that guarantee the efficiency and the minimum charging time is related to numerous exigencies. It is expected that the minimum of recharge time is related to the fixed station of recharge and this mode is efficient only in fixed cars. However, the real problem is related to the running cars, where it is unacceptable that at the middle of travel, the vehicle is stopped and we cannot found a real station of recharge. Therefore, we try to present all charging method and modes that guarantee all needs for users when car is stopped or running.

Naoui Mohamed

Papers

A new wireless charging system for electric vehicles using two receiver coils

Efficient Power Management Strategy of Electric Vehicles Based Hybrid Renewable Energy

Analysis of battery‐EV state of charge for a dynamic wireless charging system

Increasing Electric Vehicle Autonomy Using a Photovoltaic System Controlled by Particle Swarm Optimization

Review on autonomous charger for EV and HEV