MS Engineering-ECE-Advanced Mobility Featured Courses
Set yourself apart in this high demand industry and earn your MSECE - Advanced Mobility Focus degree from Kettering University. Below is a sample list of courses you will take while enrolled in the online Electrical and Computer Engineering degree at Kettering University Online:
ECE-610 | Modeling of Dynamic Systems
This course covers modeling, simulation, and analysis of multivariable dynamic systems. Approaches to modeling a variety of dynamic physical systems are discussed using examples of dynamic systems taken from a variety of fields. The course places emphasis on modeling and analysis of electric vehicle systems and components. Transient and steady-state behavior of power electronic circuits using state-space models is included in this course. These systems are simulated using MATLAB simulation tools. Most of the course is devoted to the analysis of linear systems using classical techniques based on linear algebra, state-space representations, and the state transition matrix.
ECE-630 | Digital Signal Processing Techniques for Automotive Engineering
This graduate-level course is designed to introduce critical digital signal/ image processing principles/theories and techniques applied to a variety of automotive engineering applications. Special focus is given to autonomous driving and NVH analysis. Examples include but are not limited to edge detection methods in traffic sign recognition and identification; Kalman filtering for vehicle state estimation; Modal analysis (frequency domain) and expansion to time-frequency domain analysis of dynamic response using techniques such as wavelets and Empirical Mode Decomposition (EMD). MATLAB will be heavily used for analysis and simulations.
ECE-642 | Machine Drives for Electric Vehicles
Methods of controlling electric machines and their applications in electric vehicles are discussed. Topics include solid-state devices; various switching schemes; types of drives; characteristics of motors; controlling motors including vector control; braking of motors; and dynamics of electric drives and applications.
CE-652 | Artificial Intelligence for Autonomous Driving
This course will provide introductory theories and technologies in artificial intelligence focusing on machine learning, covering a wide range of machine learning methods, concepts, and applications. Machine learning studies algorithms that learn from large quantities of data, identify patterns and make predictions on new data. The major machine learning fields are computer vision, robotics, autonomous driving, voice/gesture recognition, and automated planning & scheduling, etc. Students will study the concepts that underlie intelligent systems and investigate advanced topics in intelligent systems through a course project.
EE-626 | Advanced Power Electronics for Vehicle Electrification
This is an advanced class in power electronics. Advanced converter topologies, control methods and analyses used in electric-vehicle and power-system domains will be discussed. Topics include state-variable modeling of DC-DC converters for closed-loop control system design; isolated DC-DC converter topologies (half, full and dual bridges) and resonant DC-DC converter topologies (series, parallel and series-parallel) for wireless power transfer and battery charging; soft-switching concepts and control methods for isolated DC-DC converters; single-phase and three-phase inverter design; inverter control methods, including six-step, Sine PWM, Space Vector PWM and Discontinuous PWM; and the design and control of multilevel and modular multilevel inverters.
ECE-632 | Automotive Control Systems
This class will focus on applying students’ knowledge of fundamental principles of control systems to a variety of systems within automobiles. Specific topics will include the control of the air-fuel ratio, spark timing, idle speed, transmissions, cruise and headway, lane-keeping and active suspensions. Other topics may include anti-lock brakes, traction control, and vehicle stability control. Simulations will be used, and students will be using MATLAB/Simulink for many of the assignments.
CE-642 | Mobile Robotics
Fundamentals of robotics with an emphasis on mobile robots, which are intelligent integrated mechanical, electrical and computational systems functioning in the physical world. Topics include state-of-the-art technologies in mobile robotics, such as locomotion, sensing, control, communication, localization, mapping, navigation, etc. Advanced topics such as coordination of multiple mobile robots will also be explored. The course aims to provide both theoretical and practical experience to students through lectures and simulation software. Students will also complete independent projects or research on current topics covering mobile robotics technologies and related fields.
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