Electric vehicle

Open Access Article

1 - Lateral Stabilization of a Four Wheel Independent Drive Electric Vehicle Using a Three Layer Controller and Sliding Mode Control
H. Alipour M. Sabahi M. B. B. Sharifia

20.1001.1.16823745.1394.13.3.3.2

In this paper, a new controller, for lateral stabilization of four wheel independent drive type electric vehicles without mechanical differential, is proposed. The proposed controller has three levels includes high, medium and low control level. Desired vehicle dynamics More

In this paper, a new controller, for lateral stabilization of four wheel independent drive type electric vehicles without mechanical differential, is proposed. The proposed controller has three levels includes high, medium and low control level. Desired vehicle dynamics such as reference longitudinal speed and reference yaw rate are determined by higher level of controller. In this paper, a new sliding mode controller is proposed and its stability is proved by Lyapunov stability theorem. This sliding mode control structure is faster, more accurate, more robust, and with smaller chattering than common sliding mode controllers. Based on the proposed sliding mode controller, the medium control level is designed to determine the desired traction force and yaw moment. In the lower level controller, suitable wheel forces and torques are calculated by an optimal cost function minimizing. Finally, the effectiveness of the introduced controller is investigated through conducted simulations Manuscript profile

Open Access Article

2 - Optimal Sitting and Sizing of Renewable Energy Sources and Charging Stations Simultaneously Based on Improved GA-PSO Algorithm
M. Rezaei Mozafar M. Rezaei Mozafar

20.1001.1.16823745.1396.15.4.3.8

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, a More

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 Manuscript profile

Open Access Article

3 - Optimal and Simultaneously Compensation of Active, and Reactive Powers in Power System Using of Plug in Electric Vehicle
f. rashidi H. Feshki Farahani

20.1001.1.16823745.1396.15.4.5.0

Plug in electric vehicles besides environment pollution reduction can help power system operation. One of the most important capabilities of them is providing activeand reactive power. This paper considers grid constraints, technical concerns and market price and propos More

Plug in electric vehicles besides environment pollution reduction can help power system operation. One of the most important capabilities of them is providing activeand reactive power. This paper considers grid constraints, technical concerns and market price and proposes a framework to allocate the PEV capacity such that operational cost paid by distribution system operator (DSO) to power provider of active and reactive power is minimized. For this purpose, an objective function is defined that includes the payment for each power provider. This objective function is minimized based on particle swarm optimization subject to grid and vehicles constraints. In this framework, the PEVs compete with generator to produce active and reactive power. In order to accelerate the optimization process and prevent the algorithm from being trapped in local optima, new heuristic approaches are included to the original PSO algorithm. To evaluate the effectiveness of the propose method, it is implemented on the low voltage with 134 customer and including the other power providers and the amount of each participants production and payment cost to each component is determined. Manuscript profile

Open Access Article

4 - Optimal Operation of AC Microgrid in the Presence of Plug-in Electric Vehicles under Demand Side Managemen
A. Mehdizadeh N. Taghizadegan J. Salehi

20.1001.1.16823745.1397.16.3.6.6

In the recent years, integrations of renewable energy sources as well as plug-in electric vehicles are increased in the AC microgrid. Also, demand side management can be used to manage peak load in order to improve optimal performance of AC microgrid. Therefore, this pa More

In the recent years, integrations of renewable energy sources as well as plug-in electric vehicles are increased in the AC microgrid. Also, demand side management can be used to manage peak load in order to improve optimal performance of AC microgrid. Therefore, this paper proposes optimal operation of AC microgrid in the presence of plug-in electric vehicles under demand side management. The proposed model describes optimal operation of microgrid including the exchange power with the upstream grid, the production of DG units including wind turbines, battery storage, diesel generators, charging and discharging of electric vehicles and the manner of participation of large industrial consumers and aggregators of small consumers in demand side management that minimize the operation cost of microgrid. The proposed formulation is considered the mathematical model of various energy sources in a microgrid and the AC load flow constraints and the bus voltage and feeder current limitations has been considered.In the proposed model, charge and discharge management of plug-in electric vehicles and demand side management are simultaneously proposed to reduce operation cost of AC microgrid subject to technical and economic constraints. A 33-bus microgrid is used as test system in order to investigate effects of plug-in electric vehicles and demand side management on optimal operation of AC microgrid. The proposed model is formulated via mixed-integer non-linear programming which is solved using CPLEX solver under GAMS optimization software. Manuscript profile

Open Access Article

5 - Probabilistic Modeling of Fast Charging Station Load Demand for Public Electric Vehicles
Hossein Yousefi Meghdad Tourandaz Kenari Mohammad Sadegh Sepasian

20.1001.1.16823745.1398.17.1.5.8

Considering economic and environmental factors, it is expected that the number of plug-in electric vehicles (PEVs) will be increased, rapidly. The high penetration of EVs, can affect the power system. Therefore, in recent years, various studies have paid their attention More

Considering economic and environmental factors, it is expected that the number of plug-in electric vehicles (PEVs) will be increased, rapidly. The high penetration of EVs, can affect the power system. Therefore, in recent years, various studies have paid their attention to the impacts of PEVs charging on the network. In this paper, a probabilistic model based on the queueing theory is extracted using Monte Carlo simulation for modeling EV charging station load. It is assumed that the vehicles are the taxis of Amol city in Mazandaran province. Required data such as the time of arrival and the state of charge of the battery before charging, were collected and extracted using three methods from intra-city taxis in the city of Amol. To obtain the demand load of EV charging, the traffic-based behavior of drivers is needed. This behavior is stochastic. Therefore, its related variables will not be deterministic and must be evaluated using probabilistic methods. Manuscript profile

Open Access Article

6 - Robust Optimal Stable Fuzzy Controller Design for Stabilization of Electric Vehicle Speed, in Presence of Parametric Uncertainties and External Disturbances
Mohammad Veysi M. Shasadeghi M. R. Soltanpour

20.1001.1.16823745.1398.17.2.1.6

In electric vehicle’s nonlinear dynamic equations, some parameters has uncertainty such as the coefficient of rolling resistance, drag coefficient, armature resistance and field winding resistance. Design of a controller that is robust in the presence of these parametri More

In electric vehicle’s nonlinear dynamic equations, some parameters has uncertainty such as the coefficient of rolling resistance, drag coefficient, armature resistance and field winding resistance. Design of a controller that is robust in the presence of these parametric uncertainties and also in presence of external disturbances, and on the other hand simultaneously satisfies the optimality criteria, is a challenging issue. In practical applications, in addition to the above problem, the computational load of the control input should also be considered and provide a rational interaction between the controller's desirable performance and the calculations volume. In the present paper, a robust optimal stable fuzzy controller based on the parallel distributed compensation is designed, using Takagi-Sugeno fuzzy model of electric vehicle. The stabilizer feedback gains of fuzzy model, the upper bound of the uncertainties, the upper bound of the disturbances effect, and the upper bound of the cost function are obtained completely offline, through the solving of a minimization problem based on the linear matrix inequality. Therefore, the calculation volume of the control input is extremely low. This allows the practical implementation of the proposed controller. The favorable performance of the proposed controller is demonstrated in five-step simulations. Manuscript profile

Open Access Article

7 - Preventive and Probabilistic-Possibilistic Scheduling of Microgrid against the Natural Phenomena in the Presence of Electric Vehicles
Amirhossein Nasri A. Abdollahi M. Rashidinejad

20.1001.1.16823745.1399.18.3.6.0

This paper proposes a preventive and probabilistic–possibilistic framework for day-ahead scheduling of Electric Vehicles (EVs) parking lot and distributed generation in a microgrid. The suggested scheduling is performed in normal and emergency conditions when a natural More

This paper proposes a preventive and probabilistic–possibilistic framework for day-ahead scheduling of Electric Vehicles (EVs) parking lot and distributed generation in a microgrid. The suggested scheduling is performed in normal and emergency conditions when a natural phenomenon appears and the microgrid is disconnected from the upstream network. Furthermore, the uncertainty of EVs number in a parking lot is considered by Z-number as a probabilistic-possibilistic model. Moreover, the uncertainties of photovoltaic units generation, wind turbine output power, market price, and load demand are modeled by Monte Carlo as a probabilistic method. Furthermore, natural phenomena occurrences are modeled by considering multifarious scenarios according to when the phenomenon unfolds and how much it takes. In the suggested framework, the operation of parking lots is based on the uncertainty and EVs charging/discharging schedule. The operational cost in normal condition and load shedding cost in addition to operational cost are considered as the objective functions of the proposed structure. To evaluate the performance of the suggested structure, the modified 33-bus IEEE distribution network is employed. Manuscript profile

Open Access Article

8 - Model Predictive Control of Permanent Magnet Synchronous Machine Based on Finite and Continuous Control Sets in Two Functional Quarters
ehsan ghasemi madani Mohammad Reza Alizadeh Pahlavani Arash Dehestani Kolagar

20.1001.1.16823745.1401.20.1.9.3

In this paper, two schemes of model predictive control (MPC) method, named finite control set model predictive control (FCS-MPC) and dead-beat model predictive control (DB-MPC) as a continuous control set model predictive control (CCS-MPC) are applied and compared to co More

In this paper, two schemes of model predictive control (MPC) method, named finite control set model predictive control (FCS-MPC) and dead-beat model predictive control (DB-MPC) as a continuous control set model predictive control (CCS-MPC) are applied and compared to control the current of a permanent magnet synchronous machine in energy recovery mode for the use of electric vehicles. The FCS-MPC strategy selects the optimal voltage vector and applies the control pulses directly to the inverter without using any modulators. In other side, DB-MPC is implemented through space vector pulse width modulation (SVPWM). The performance and results of both types of control strategies are extracted and compared using MATLAB Simulink software. The comparisons are made mainly in steady state and transient modes. Both control strategies are applied to a permanent magnet synchronous machine with the same parameters and with the same operating mode. The results show that the current steady state fluctuation is further reduced in the DB-MPC strategy and the transient state response is faster in the FCS-MPC strategy. Manuscript profile

Open Access Article

9 - Optimal Robust Controller Design for the Electrical Vehicle Charging Process in the Presence of Uncertainty
mahsa karami roohollah barzamini reza sharifi

20.1001.1.16823745.1400.19.4.4.7

Wireless power transmission technology with titles such as contactless power transmission, magnetic coupling power transfer, etc.are known and in fact, this method safely and reliably transmits power in such a way that does not require a mechanical connection between th More

Wireless power transmission technology with titles such as contactless power transmission, magnetic coupling power transfer, etc.are known and in fact, this method safely and reliably transmits power in such a way that does not require a mechanical connection between the source and the load. In this method, power transmission is done wirelessly using resonance induction coupling. By operating the transducer in the resonant mode, it will be possible to transfer a significant amount of power over an air distance of a few tens of centimeters, while the system efficiency is high and the voltage and current stress of the transducer are reasonable. In this paper, by presenting a method based on robust control and meta-heuristic algorithms, we improve the charging process of electric vehicles by considering uncertainty conditions. The simulation results show the better performance of the proposed controller compared to other controllers. Also, in this paper, the effect of connecting the charging station of electric vehicles to the distribution network is investigated by considering the optimal charging and discharging scheduling systems to maximize the economic profit of the vehicles and the charging station. In the proposed method, the best program for charging and discharging cars in order to maximize their profit is extracted based on genetic algorithm. According to the simulation results, optimal charging and discharging planning has reduced the value of losses to the total network energy to load the station in some trains, so that network targets such as losses and voltage deviation index are minimized and voltage stability index is maximized. In this study, minimization of losses, voltage deviation as well as maximization of voltage stability index have been investigated and the optimal location of the station has been obtained by considering these goals along with the profit of the station and vehicles. Finally, according to the results, with the planning of charging and discharging cars, in addition to providing the required charge, the profit of the station and cars has also increased. Manuscript profile

Open Access Article

10 - A Semi-Intelligent Method for Charging Electric Vehicles in Unbalanced Four-Wire Distribution Networks
Saeed Zolfaghari Moghaddam

20.1001.1.16823745.1401.20.2.15.1

The growing penetration of electric vehicles (EVs) in distribution networks (DNs) has posed many challenges for electricity distribution companies, such as: increasing the amount of voltage drop, network losses and the number of outages due to the overload. To overcome More

The growing penetration of electric vehicles (EVs) in distribution networks (DNs) has posed many challenges for electricity distribution companies, such as: increasing the amount of voltage drop, network losses and the number of outages due to the overload. To overcome this, it is recommended to use coordinated charging methods. However, these methods require telecommunication, measurement and processing infrastructure with high costs and can only be implemented in smart grids. In this paper, a semi-intelligent method for charging EVs is presented that does not require complex infrastructure. This method, using a simple and inexpensive local automation system, charges EVs in the off-peak periods of the DN and thus improves its parameters. Since the EVs are charged at the low tariff time intervals, the proposed method will also benefit the EV owners. To achieve real results, four-wire DN is considered to model the effect of neutral conductor. To confirm the effectiveness of the proposed method, it is compared with different uncontrolled charging methods. A standard 19 bus test system is used for simulations. Manuscript profile

Open Access Article

11 - Multi-Objective Economic-Environment Scheduling of Microgrids in the Presence of Hybrid Electric Vehicles and Demand Response to Smooth the Distribution Nodal Prices
ali mirzaei NAVID TAGHIZADEGAN KALANTARI Sajad Najafi Ravadanegh

Today, with the growing demand for hybrid electric vehicles in microgrids, electricity supply, environmental issues, and rescheduling are among the challenges of microgrids that must be solved and suitable solutions provided. To overcome these challenges, this paper int More

Today, with the growing demand for hybrid electric vehicles in microgrids, electricity supply, environmental issues, and rescheduling are among the challenges of microgrids that must be solved and suitable solutions provided. To overcome these challenges, this paper introduces a new multi-objective optimization model, which in the first objective, minimizes the total operation cost of the microgrid, and in the second objective, improves the reliability index by reducing the amount of energy not supplied. Due to these two objectives, a multi-objective evolutionary seagull optimization algorithm is used to find the optimal global solutions. In this regard, hybrid electric vehicles and demand response programs are used to smooth out distribution nodal prices and reduce CO2 emissions. The 69-bus distribution network has been used to evaluate the efficiency of the proposed method. Manuscript profile

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