Curriculum

Automotive systems for light duty vehicles are examined from the perspectives of requirements, design, technical, and economic analysis for advanced mobility needs. This course links the content for the automotive systems graduate certificate in controls, powertrain, vehicle dynamics, connected and autonomous vehicles.

• Credits: 3.0
• Lec-Rec-Lab: (0-3-0)
• Semesters Offered: Fall
• Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following Major(s): Automotive Systems & Controls, Electrical Engineering, Computer Engineering, Electrical & Computer Engineer

Introduction to automotive control systems. Modeling and control methods are presented for: air-fuel ratio, transient fuel, spark timing, idle speed, transmission, cruise speed, anti-lock brakes, traction, active suspension systems, and hybrid electric vehicles, Advanced control methodologies are introduced for appropriate applications.

• Credits: 3.0
• Lec-Rec-Lab: (0-3-0)
• Semesters Offered: Spring
• Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following Major(s): Electrical & Computer Engineer, Electrical Engineering, Computer Engineering
• Pre-Requisite(s): EE 3261 or MEEM 4775 or ME 4775

Provides a thorough understanding of how electric machines can be used to drive loads with control of speed, torque and position. Topics include basic electro-mechanics, rotating machinery, dc machines, ac machines, power electronics and load modeling. Applications include industrial systems, hybrid/electric vehicles and electric power systems.

• Credits: 3.0
• Lec-Rec-Lab: (3-0-0)
• Semesters Offered: Spring
• Pre-Requisite(s): (EE 2112 or EE 3010) and EE 3120

Provides a thorough understanding of how electric machines can be used to drive loads with control of speed, torque and position. Topics include basic electro-mechanics, rotating machinery, dc machines, ac machines, power electronics and load modeling. Applications include industrial systems, hybrid/electric vehicles and electric power systems.

• Credits: 3.0
• Lec-Rec-Lab: (3-0-0)
• Semesters Offered: Spring
• Pre-Requisite(s): (EE 2112 or EE 3010) and EE 3120

Digital signal processing techniques with emphasis on applications. Includes sampling, the Z-transform, digital filters and discrete Fourier transforms. Emphasizes techniques for design and analysis of digital filters. Special topics may include the FFT, windowing techniques, quantization effects, physical limitations, image processing basics, image enhancement, image restoration and image coding.

• Credits: 4.0
• Lec-Rec-Lab: (3-0-2)
• Semesters Offered: Fall
• Pre-Requisite(s): EE 3160

Practical implementation of digital signal processing concepts as developed in EE4252. Emphasis on applications of DSP to communications, filter design, speech processing, and radar. Laboratory provides practical experience in the design and implementation of DSP solutions.

• Credits: 3.0
• Lec-Rec-Lab: (2-0-2)
• Semesters Offered: Spring
• Pre-Requisite(s): EE 4252

Computer network architectures and protocols; design and implementation of datalink, network, and transport layer functions. Introduction to the Internet protocol suite (TCP, UDP, IP), domain name service and protocols, file sharing protocols, wireless networks, and network security.

• Credits: 3.0
• Lec-Rec-Lab: (3-0-0)
• Semesters Offered: Fall, Spring, Summer
• Restrictions: May not be enrolled in one of the following Class(es): Freshman, Sophomore
• Pre-Requisite(s): CS 3411

Fundamentals of circuits for electrical energy processing. Covers switching converter principles for dc-dc, ac-dc, and dc-ac power conversion. Other topics include harmonics, pulse-width modulation, feedback control, magnetic components and power semiconductors.

• Credits: 3.0
• Lec-Rec-Lab: (3-0-0)
• Semesters Offered: Fall, Summer
• Pre-Requisite(s): EE 3120 and (EE 3130(C) or EE 3131)

Hands-on course on vehicle electrification. Covers propulsion architecture, vehicle and component testing, fuel consumption, aerodynamics, rolling resistance, engines, batteries, electric machines, and power electronics. Emphasis on system interactions, powertrain modes, and regenerative braking for efficiency.

• Credits: 3.0
• Lec-Rec-Lab: (0-2-2)
• Semesters Offered: Fall, Spring
• Restrictions: Must be enrolled in one of the following College(s): College of Engineering; May not be enrolled in one of the following Class(es): Freshman, Sophomore, Junior

Advanced topics of circuits for electrical energy processing. Covers switching converter principles for dc-dc, ac-dc, and dc-ac power conversion. Other topics include harmonics, pulse-width modulation, classical feedback control, nonlinear control, magnetic components, power semiconductors, and digital simulation.

• Credits: 3.0
• Lec-Rec-Lab: (3-0-0)
• Semesters Offered: Fall, in even years
• Restrictions: Must be enrolled in one of the following Level(s): Graduate
• Pre-Requisite(s): EE 4227

This course will explore the Mobile network issues including routing and mobility management strategies in ad hoc networks, sensor networks, and personal area networks such as Bluetooth.

• Credits: 3.0
• Lec-Rec-Lab: (3-0-0)
• Semesters Offered: Spring, Summer
• Restrictions: May not be enrolled in one of the following Class(es): Freshman, Sophomore, Junior
• Pre-Requisite(s): EE 4272 or CS 4461

Building blocks of wireless sensor networks, sensor node design, wireless communications, network protocols, data storage and retrieval, sensor localization and clock synchronization. Example application areas: robotics, autonomous vehicles and networks, power engineering, smart-grid, environment monitoring, and disaster relief.

• Credits: 3.0
• Lec-Rec-Lab: (3-0-0)
• Semesters Offered: On Demand
• Pre-Requisite(s): (CS 4461 or EE 4272 or EE 5722) and (EE 3170 or EE 3173) and (CS 1129 or CS 2141)

This course will explore the foundational techniques of machine learning. Topics are pulled from the areas of unsupervised and supervised learning. Specific methods covered include naive Bayes, decision trees, support vector machine (SVMs), ensemble, and clustering methods.

• Credits: 3.0
• Lec-Rec-Lab: (3-0-0)
• Semesters Offered: Spring
• Restrictions: Permission of instructor required; May not be enrolled in one of the following Class(es): Freshman, Sophomore, Junior

Special topics in electrical engineering selected by the student and approved by his/her advisor and the faculty member who will approve the study.

• Credits: variable to 5.0; May be repeated
• Semesters Offered: Fall, Spring, Summer
• Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following Major(s): Electrical & Computer Engineer, Electrical Engineering, Computer Engineering

Designing energy storage solutions for grid, vehicle and portable/autonomous systems. Quantitative and qualitative analysis of energy storage aging, cost, and performance improvement.

• Credits: 3.0
• Lec-Rec-Lab: (0-3-0)
• Semesters Offered: Spring

Hybrid electric vehicles (HEV) will be studied and simulated using advanced powertrain component analysis and modeling. An in-depth analysis and study of power flows, losses, and energy usage are examined for isolated powertrain components and HEV configurations. Simulation tools will be developed and applied to specify powertrain and vehicle components and to develop control and calibration for a constrained optimization to vehicle technical specifications.

• Credits: 3.0
• Lec-Rec-Lab: (0-3-0)
• Semesters Offered: Spring
• Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following College(s): College of Engineering
• Pre-Requisite(s): MEEM 4295 or ME 4295 or EE 4295

Lab-based, hands-on course examining propulsion integration for vehicle electrification. Covers requirements, vehicle development process, component specification, thermal management, controls, safety, and calibration. Course project on optimizing electrified vehicle performance through modeling and experimentation.

• Credits: 3.0
• Lec-Rec-Lab: (0-2-2)
• Semesters Offered: Spring, Summer
• Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following College(s): College of Engineering
• Pre-Requisite(s): MEEM 4296(C) or EE 4296(C)

This course introduces embedded control system design using a model-based approach. Course topics include model-based embedded control system design, discrete-event control, sensors, actuators, electronic control unit, digital controller design, and communication protocols. Prior knowledge of hybrid electric vehicles is highly recommended.

• Credits: 3.0
• Lec-Rec-Lab: (0-2-2)
• Semesters Offered: Fall
• Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following Major(s): Electrical Engineering, Electrical & Computer Engineer
• Pre-Requisite(s): MEEM 4700 or ME 4700 or MEEM 4775 or ME 4775 or EE 3261 or EE 4261

General introduction to cybersecurity of industrial control systems and critical infrastructures. Topics include NIST and DHS publications, threat analysis, vulnerability analysis, red teaming, intrusion detection systems, industrial networks, industrial malware, and selected case studies.

• Credits: 3.0
• Lec-Rec-Lab: (0-3-0)
• Semesters Offered: On Demand
• Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following Major(s): Electrical & Computer Engineer, Cybersecurity, Mechatronics, Computer Science, Computer Engineering, Electrical Engineering

Special topics in electrical engineering selected by the student and approved by his/her advisor and the faculty member who will approve the study.

• Credits: variable to 5.0; May be repeated
• Semesters Offered: Fall, Spring, Summer
• Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following Major(s): Electrical & Computer Engineer, Electrical Engineering, Computer Engineering

High-level review of geospatial data acquisition systems, sensors and associated processing technologies. Course considers geospatial metadata generation principles, interoperability, and major tools for manipulation with geospatial data. Course may help in transition of non-geospatial majors to geospatial field.

• Credits: 3.0
• Lec-Rec-Lab: (0-3-0)
• Semesters Offered: Spring
• Restrictions: Must be enrolled in one of the following Major(s): Integrated Geospatial Tech, Surveying Engineering, Geospatial Engineering