Chapters authored
Design, Simulation and Analysis of the Propulsion and Control System for an Electric Vehicle
The problems of global warming, a decrease of the available natural resources and many other problems in the world that happen recently become the major cause for increasing the demand for a new type of vehicle. That vehicle can be an environmental friend and so that a new generation of vehicles has been invented and tried to solve and avoid many problems. In this chapter, the proposed system is called the Multi-Converter/Multi-Machine system (MCMMS) which consists of two Synchronous Reluctance Motor (SynRM) that drive the two rear wheels of Pure Electric Vehicle (PEV). The SynRM speed and torque are controlled by using three different strategies of the PID controller. The PSO algorithm has been used as an optimization technique to find the optimal PID parameter to enhance the drive system performance of the PEV. In this system, the space vector pulse width modulation inverter for voltage source (VS-SVPWMI) has been employed to convert the DC battery voltage to three-phase AC voltage that feeds the SynRM motor in the PEV. The linear speed of the vehicle is controlled by an Electronic Differential Controller (EDC) which gives the reference speed for each driving wheel which depends on the driver reference speed and the steering angle. The specified driving route topology with three different road cases has been applied to acting and show the resistive forces that affected on the PEV during its moving on the road. In addition, to test the efficiency and stability of the PEV on the roads. Hence, this chapter has a full design, simulation and several comparison results for the propulsion electric vehicle system and it has tested implemented in the Matlab/Simulink environment version R2020a.
Part of the book: New Perspectives on Electric Vehicles
Improving Communication System for Vehicle-to-Everything Networks by Using 5G Technology
Next-generations of wireless communication systems (5G scheme & beyond) are rapidly evolving in the contemporary life. These schemes could propose vital solutions for many existing challenges in various aspects of our lives, eventually to ensure stable communications. Such challenges are even greater when it comes to address ubiquitous coverage and steady interconnection performance in fast mobile vehicles (i.e., trains or airplanes) where certainly blind spots exist. As an early initiative, the Third Generation Partnership Project (3GPP) has proposed a regulation for Long Term Evolution (LTE)-based Vehicle-to-Everything (V2X) network in order to offer solid solutions for V2X interconnections. V2X term should comprise the following terminologies: vehicle-to-vehicle (V2V), vehicle-to-network (V2N) communications, vehicle-to-infrastructure (V2I), and vehicle-to-pedestrian (V2P). Superior V2X communications have a promising potential to improve efficiency, road safety, security, the accessibility of infotainment services (any service of user-interface exists inside a vehicle). In this chapter, the aforementioned topics will be addressed. In addition, the chapter will open the door on investigating the role of wireless cooperative and automatic signal identification schemes in V2X networks, and shedding light on the machine learning techniques (i.e, Support Vector Machines (SVMs), Deep Neural Networks (DNNs)) when they meet with the next-generations of wireless networks.
Part of the book: New Perspectives on Electric Vehicles