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• Electric Vehicle Modeling and Simulation of Volkswagen Crafter with 2.0 TDI CR Diesel Engine: VW Vehicle 2020 Based PMSM Propulsion

  1-6

  Aminu Babangida

  Péter Tamás Szemes

  Views:

  342

  The Internal Combustion Engine (ICE) used by conventional vehicles is one of the major causes of environmental global warming and air pollutions. However, the emission of toxic gases is harmful to the living. Electric propulsion has been developed in modern electric vehicles to replace the ICE.

  The research is aimed at using both Simulink and SIMSCAPE toolboxes in a MATLAB to model the vehicle. This research proposes a Volkswagen (VW) crafter with a 2.0 diesel TDI CR engine, manufactured in 2020. An electric power train, a rear-wheel driven, based on Permanent Magnet Synchronous Motor (PMSM) was designed to replace the front-wheel driven, diesel engine of the VW conventional vehicle.

  In this research, a Nissan leaf battery of a nominal voltage of 360 V, 24 kWh capacity was modeled to serve as the energy source of the overall system. A New European Drive Cycle (NEDC) was used in this research. Another test input such as a ramp was also used to test the vehicle under different road conditions. However, a Proportional Integral (PI) controller was developed to control both the speed of the vehicle and that of the synchronous motor. Different drive cycles were used to test the vehicle. The vehicle demonstrated good tracking capability with each type of test. In addition, this research found out that there is approximately about 19% more benefit in terms of fuel economy of electric vehicles than the conventional vehicles.

• Linear Identification of a Servo-pneumatic System

  1-8.

  Károly Széll

  András Czmerk

  Views:

  70

  The identification of a nonlinear system is quite challenging for engineers. This paper presents the automatic identification of a servo-pneumatic cylinder based on a framework implemented in MATLAB. The introduced application shortens the process length of identification and gives areference model, important for controlling.

• Computing The Kinematics Study of a 6 DOF Industrial Manipulator Prototype By Matlab

  1-5.

  Alaa Saadah

  Husam Abdulkareem

  Géza Husi

  Views:

  535

  Since the mechanical parts in the robot are designed to do the movement, studying and analyzing the motion considered a primary issue that should be taken into consider when studying and designing the robot.

  In this research 6-DOF sample of the industrial manipulator based on ABB IRB 4400 model had been studied. The mathematical model of manipulator is established by DH (Denavait Hartenberg) method. The forward kinematics was done using DH Parameters in order to get the final transformation matrix. The inverse kinematics was done using geometrical and analytical methods in order to get the end effector final position and direction by calculate Euler angles values.

  Finally, the forward and inverse kinematics equations were computing by MATLAB to get angles, end effector, position, direction and Euler angles values.

  The kinematics study and the arm movement’s equations were compered with the practical measurements to make sure it fulfills the desired purpose.     

• PID Controller Tuning Optimization with Genetic Algorithms for a Quadcopter

  1-7.

  Komal Khuwaja

  Noor-u-Zaman Lighari

  Ioan Constantin Tarca

  Radu Catalin Tarca

  Views:

  638

  This paper is focused on the dynamic of mathematical modeling, stability, nonlinear gain control by using Genetic algorithm, utilizing MATLAB tool of a quadcopter. Previously many researchers have been work on several linear controllers such as LQ method; sliding mode and classical PID are used to stabilize the Linear Model. Quadcopter has a nonlinear dynamics and unstable system. In order to maintain their stability, we use nonlinear gain controllers; classical PID controller provides linear gain controller rather than nonlinear gain controller; here we are using modified PID control to improve stability and accuracy. The stability is the state of being resistant to any change. The task is to maintain the quadcopter stability by improving the performance of a PID controller in
  term of time domain specification. The goal of PID controller design is to determine a set of gains: Kp, Ki, and Kd, so as to improve the transient response and steady state response of a system as: by reducing the overshoot; by shortening the settling time; by decrease the rise time of the system. Modified PID is the combination of classical PID in addition to Genetic Algorithm. Genetic algorithm consists of three steps: selection, crossover, and mutation. By using Genetic algorithm we correct the behavior of quadcopter.