M.S. Curriculum in Energy Systems | Course Recommendations for eCAL Research
CE 186 - Design of Cyber Physical Systems | A Jacobs Institute for Design Innovation Course
Design and prototype of large-scale technology intensive systems. Design project incorporating infrastructure systems and areas such as transportation and hydrology; for example, watershed sensor networks, robot networks for environmental management, mobile Internet monitoring, open societal scale systems, crowd-sources applications, traffic management. Design of sensing and control systems, prototyping systems, and measures of system performance. Modeling, software and hardware implementation.
CE 191 - Civil and Environmental Engineering Systems Analysis
This course is organized around five real-world large-scale CEE systems problems. The problems provide the motivation for the study of quantitative tools that are used for planning or managing these systems. The problems include design of a public transportation system for an urban area, resource allocation for the maintenance of a water supply system, development of repair and replacement policies for reinforced concrete bridge decks, traffic signal control for an arterial street, scheduling in a large-scale construction project.
CE 295 - Energy Systems & Control
* A 12-hour short-course version of CE 295 is taught at Tsignhua-Berkeley-Shenzhen Institute (TBSI)
Introduction to energy system management and the underlying control system tools. Applications of interest include batteries, electric vehicles, renewable energy, power systems, and smart buildings/homes. Technical tools include system modeling, state-space representations, stability, parameter identification, state observers, feedback control, and optimization.
ME 499/599-006 - Battery Systems and Control (University of Michigan)
This course covers battery modeling, control and diagnostic methodologies associated with battery electric and battery hybrid electric vehicles. Emphasis is placed upon system-level modeling, model order reduction from micro-scale to macro-scale and surrogate models for load control, estimation, on-board identification and diagnostics for Lithium Ion batteries. The electrochemical, electrical, and transport principles for battery modeling are reviewed. Spatiotemporal models of coupled concentration, potential, and thermal phenomena are introduced. Simulation of the resulting partial differential equations using software tools will be introduced with selected topics on numerical issues. Model order reduction techniques, parameter estimation, filtering, and control theory will be covered and applied to state of charge estimation. Additionally, electric-circuit battery models, DC/DC converters, and other vehicle implementation issues of power management and balancing will be introduced.
| Course | Semester | Enrollment | Overall teaching effectiveness* (Dept Avg) | Overall quality of this course* (Dept Avg) |
|---|---|---|---|---|
| CE 186 | FA 2015 | 34 | 6.5 (5.9) | 6.6 (6.0) |
| FA 2016** | 43 | 6.57 (5.76) | 6.51 (5.47) | |
| FA 2017** | 44 | 6.59 (5.81) | 6.48 (5.55) | |
| FA 2018** | 36 | 6.25 (5.87) | 6.08 (5.58) | |
| CE 191 | FA 2013 | 28 | 6.1 (5.8) | 6.3 (5.9) |
| FA 2014 | 63 | 6.7 (5.9) | 6.7 (5.9) | |
| CE 295 | SP 2014 | 19 | 6.4 (6.0) | 6.4 (6.0) |
| SP 2015 | 48 | 6.8 (6.0) | 6.8 (6.1) | |
| SP 2016 | 45 | 6.7 (5.9) | 6.8 (6.0) | |
| SP 2017** | 48 | 6.61 (5.83) | 6.69 (5.62) | |
| SP 2018** | 56 | 6.56 (5.56) | 6.56 (5.48) | |
| SP 2019** | 57 | 6.58 (5.42) | 6.40 (5.38) | |
| ME 499/599 @UMICH | W 2010 | 59 | - | - |
| W 2011 | 50 | - | - |
**UC Berkeley converted to a new online system in FA 2016
