Mindy Wagenmaker

  • Resume
  • View Mindy Wagenmaker's profile on LinkedIn
  • mindajw2@illinois.edu
  • M.S. Mechanical Engineering – The University of Illinois (August 2021)
  • B.S. Mechanical Engineering – The University of Alabama (May 2019)







Research Summary:

As the trend towards electrification continues, improving thermal management control has become an important consideration in designing reliable systems. Mindy’s current research involves building graph-based models of electro-thermal systems and developing sensitivity analysis tools for these models. The graphical structure of these models is useful in that they can be used to model multi-domain power systems, and the modular structure makes them easily extendable to large systems.

A sensitivity analysis is useful for understanding a model because it helps quantify how dependent the model outputs are on modelling assumptions or characteristics such as parameter values, initial conditions, and inputs.

The motivation behind developing a sensitivity analysis methodology for graph-based models is to help inform the design process—this information will help the plant and controller designers know which modelling characteristics are insensitive and can be removed from the design optimization problem, and which ones have the largest impact on the system, and thus should be the focus of the majority of time, effort, and money spent on optimization. The results of this sensitivity analysis will determine which system inputs or parameters have the highest effect on the system, and thus, where most co-design efforts to optimize the plant and controller should be focused.

Research Interests:

  • Dynamic Modeling and Control
  • Sensitivity Analysis
  • Plant and Controller Co-Design

This research is supported by:


[1] Wagenmaker, Minda and Middleton, Robert, “Transmission Shift Strategies for Electrically Supercharged Engines,” SAE Technical Paper 2019-01-0308, World Congress Experience Conference, April 2019.

[2] Cook, James and Wagenmaker, Mindy. “Improved Diesel Engine Load Control For Heavy-Duty Transient Testing Using Gain Scheduling And Feed Forward Algorithms”†International Journal of Engine Research. 2021 (accepted).