Problem: According to the U.S. Department of Energy, heating ventilation and air conditioning (HVAC) systems are the largest consumers of energy in buildings. The Department of Defense has mandated directives to reduce high energy consumption. Fixed thermostat temperature and on/off controls are examples of current DoD energy consumption directives.
On/off control is only effective during predetermined times. This control method does not account for variations in workforce due to vacation, compensatory time, sick days, etc. This leads to HVAC systems running in zones where personnel are absent. Fixed Temperature Control has limited use. It lacks adequate feedback from disparate locations within a zone or a building. This leads to zone control determined by a specific location.
Objective: The objective is to optimize energy consumption of HVAC systems by using model predictive control driven by a multisensory system. Existing HVAC control technology will be modified to yield better control decisions. See white paper for detailed information.
Education and Learning Opportunities: Computer engineering intern/s will learn about and work with microcontrollers. They will help design and implement a state machine for optimization of energy consumption of HVAC systems by using model predictive control driven by a multisensory system. In addition, they will learn the control protocol of SIEMENS ladder logic for potential integration of a facility scale test and evaluation.
Qualifications: At minimum a junior student perusing a computer engineering degree and who can work with minimal supervision. Student who has knowledge and experience with embedded systems programming. (Arduino, PIC controllers, ARM Cortex). Student will run the programming portion of the project, so strong programming skills is a must.
To apply, follow the application process and mention this opportunity when you fill out the form.