Merve Yildirim

A survey on comparison of electric motor types and drives used for electric vehicles

In this study, Switched Reluctance Motor (SRM), Induction Motor (IM), Brushless DC Motor, and Permanent Magnet Motor (PM), and their drives have been compared with the efficiency, cost, weight, cooling, maximum speed, reliability, fault tolerance, power ratings, and vehicle acceleration time. Hence, a comprehensive literature research on motor types and their drives used in EV has been made. According to these researches, some conclusions have been obtained. It has been seen that PM BLDC motors and their drives are the most efficient and have high power density, brushless DC motors and their drives have low cost, IM is appropriate for controllability and cost, the weight of SRM is low, its reliability is high, it operates fault-tolerance and according to the acceleration time, its performance is better than IM and BLDC. Hence, SRM is the most appropriate motor for EV.

Designing in-wheel switched reluctance motor for electric vehicles

Estimation of dimension parameters for an electrical machine has great importance before manufacturing. For this reason, analytical design should be performed in an optimum form. While motor analysis is accomplished by package programs, initial size parameters are intutivily provided and then various trials are examined to get optimum results. In this study, we are trying to find dimensional and electrical parameters generating mathematical equations in analytic approaches for In-Wheel Switched Reluctance Motor (IW-SRM), which will be employed by Electric Vehicle (EV). Therefore, optimum motor parameters for required speed and torque have been estimated by solving generated equations for in-wheel SRM with 18/12 poles via MATLAB. Using the parameters, analysis of in-wheel SRM has been carried out 3D Finite Element Method (FEM) by Ansoft Maxwell 15.0 Package Software. Consequently, the accuracy of the estimated parameters has been validated by the results of Maxwell 3D FEM.

Electronic differential system for an electric vehicle with in-wheel motor

This paper presents modeling and simulation of Electronic Differential System (EDS) for the dual-front-wheel independently driven Electric Vehicle (EV). Electronic differential is utilized in EVs due to some drawbacks of traditional mechanical differential such as being heavy and bulky systems which are not convenient for EV, and mechanical losses caused by the powertrains. In this study, an EDS for front wheels of an EV with in-wheel motor is modelled instead of rare wheels which has commonly been studied in the literature. The front wheel speeds are estimated by equations derived from Ackermann-Jeantand model using Codesys Software Package. Then, the simulation of EDS is also realized by Matlab/Simulink. According to the change of the vehicle speed and steering angle of EV, front wheel speeds estimated by Codesys are verified by Simulink results. It is observed that the modelled EDS is appropriate for EVs with in-wheel motors.

Estimation of optimal locations for electric vehicle charging stations

Electric Vehicles (EV) have been commonly started to use due to some advantages such as less emission, lower noise pollution, maintenance requirement and power consumption. The number of charging stations have also increased based on rising the usage of EVs. Therefore, determination of optimal location for EV charge stations has a great importance for charging process. This localization is highly related with the range of EV and traffic density on areas. The distribution of charging stations is a basically optimization problem. For this reason, estimation of optimum locations for EV charging stations in Ankara, Turkey is realized by using data mining methods in this paper. Some parameters for determining of optimum locations which are the average number of EVs on the road and the average range are examined. Ankara road map is derived by using Mapbox Software obtained from the satellite via spectral clustering. Then, some of the image processing methods such as thresholding, erosion and dilation are used for eliminating clustering errors. Furthermore, optimal charging locations of EVs for Ankara are estimated by various clustering approaches such as spectral clustering and Gaussian Mixture Model (GMM) using a total number of charging stations. In conclusion, this paper is a novel study for Turkey which has not been worked in the literature and it can be easily applied to any region in the future works.

INFLUENCE OF STATOR EMBRACE ON TORQUE OF IN-WHEEL SWITCHED RELUCTANCE MOTOR

In this paper, influence of stator pole embrace on torque of In-Wheel Switched Reluctance Motor (IW-SRM) is investigated by numerical modeling based on Finite Element Method (FEM). For this reason, 3D numerical model of IW-SRM is built by using Ansys Maxwell Software Package. IW-SRM is analyzed and output torque and magnetic flux density of the IW-SRM are calculated. The analysis of IW-SRM is realized for different stator pole embraces and the results of the output torque and magnetic flux density of IW-SRM taken for various stator pole embraces are compared with each other. As seen from the results, when the value of stator pole embrace reduces, the output torque of IW-SRM increases. As a result in this study, the effects of different stator pole embraces are examined on the output torque of IW-SRM.

Design of Electronic Differential System for an Electric Vehicle with in-wheel motor

This paper presents design of Electronic Differential System (EDS) for an Electric Vehicle (EV) with in-wheel motor. EDS is generally used in EVs due to some drawbacks of mechanical differential such as being heavy systems and mechanical losses caused by the powertrains. According to the turning angle of the wheel, task of EDS for front wheels is to adjust rpm of the wheels. On the contrary for rear wheels, only rpm control is realized due to not steering. Hence, there are less studies on EDS for front wheels of EV in the literature. In this study, an EDS for front wheels of EV is designed. According to steering angle and speed of EV, the speeds of the front wheels are estimated by equations derived from Ackermann-Jeantand model using Codesys Software Package. The estimated speeds are sent to Induction Motor (IM) Drives via Controller Area Network-Bus (CAN-Bus). EDS is also simulated by Matlab/Simulink. Then, the speeds of the front wheels are experimentally measured by a tachometer. Codesys results are verified by both Simulink and experimental results. It is observed that the designed EDS is convenient for EVs with in-wheel motor.

Modelling and estimation parameters of electronic differential system for an electric vehicle using radial basis neural network

This paper proposes modelling and estimation parameters of Electronic Differential System (EDS) for an Electric Vehicle (EV) with in-wheel motor using Radial Basis Neural Network (RBNN). In this study, EDS for front wheels is analysed instead of rear wheels which are commonly investigated in the literature. According to steering angle and speed of EV, the speeds of the front wheels are calculated by equations derived from Ackermann-Jeantand model using CoDeSys Software Package. The simulation of EDS is also realized by MATLAB/Simulink using the mathematical equations. Neural Network (NN) types including RBNN and Back-Propagation Feed-Forward Neural Network (BP-FFNN) are used for estimation the relationship between the steering angle and the speeds of front wheels. Besides, the different levels of noise are added to steering angle as sensor noise for realistic modelling. To conclude, the results estimated from types of NN are verified by CoDeSys and Simulink results. RBNN is convenient for estimation of EDS parameters due to robustness to different levels of sensor noise.

Optimal component selection for image segmentation via Parallel Analysis

In this paper, an image segmentation method is presented to analyze the clusters of Computed Tomography (CT) image. Target image is divided to small parts called as observation screens. Principal Component Analysis (PCA) is used for better representation of features about observation screens. The optimal number of component related with observation screen is determined by Horns Parallel Analysis (PA). Besides, Local Standard Deviation (LSD) which is a method for extracting meaningful sub-features is applied to whole image for successful segmentation. The effect of segmentation success rate is analyzed by selected features. Consequently, a novel algorithm is proposed for minimizing total computation time and error of dimension reduction significantly. It is seen that the results of the algorithm are approximately same as conventional segmentation algorithms.

Estimation of Trajectory and Location for Mobile Sound Source

In this paper, we present an approach to estimate mobile sound source trajectory. An artificially created sound source signal is used in this work. The main aim of this paper is to estimate the mobile object trajectory via sound processing methods. The performance of generalized cross correlation techniques is compared with that of noise reduction filters for the success of trajectory estimation. The azimuth angle between the sound source and receiver is calculated during the whole movement. The parameter of Interaural Time Difference (ITD) is utilized for determining azimuth angle. The success of estimated delay is compared with different types of Generalized Cross Correlation (GCC) algorithms. In this study, an approach for sound localization and trajectory estimation on 2D space is proposed. Besides, different types of pre-filter method are tried for removing the noise and signal smoothing of recorded sound signals. Some basic parameters of sound localization process are also explained. Moreover, the calculation error of average azimuth angle is compared with different GCC and pre-filtered methods. To conclude, it is observed that estimation of location and trajectory information of a mobile object from a stereo sound recording is realized successfully.

Examination of radial force with Finite Element Method in Switched Reluctance Motor

The aim of this study is computation of radial forces shown as one of the main and important reasons of noise in Switched Reluctance Motor (SRM). In this paper, radial forces in saturation and unsaturation regions of a standart submersible pump type 8/6-pole SRM have been calculated and their changes have been obtained. ANSYS 10.0 package program which makes a solution with Finite Element Method (FEM) has been used for computation of radial forces. After geometric shapes are given, radial forces have been calculated from unaligned position of rotor towards aligned position with angle of one degree according to different current values.