Mechanical Engineering – Engineering Mechanics Graduate Seminar: Thurs., April 4 at 4:00 in 112 MEEM. Greg Shaver, associate professor of Mechanical Engineering at Purdue University, will be the ME-EM graduate seminar speaker for Thursday, April 4 at 4:00 in 112MEEM. His presentation is entitled ‘Model-Based Engine Algorithm Development for Control and Virtual Sensing’.
Greg Shaver is an associate professor of Mechanical Engineering at Purdue University. He is also a graduate of Purdue University’s School of Mechanical Engineering, having obtained a Bachelor’s degree with highest distinction, and holds a Masters degree and a Ph.D. in Mechanical
Engineering from Stanford University. His research interests and background include the modeling and control of advanced combustion processes. Greg is an active member of ASME, participating in the Dynamic Systems and Controls Division and the Automotive and
Transportation Systems Panel. He is an associate editor for the IFAC Control Engineering Practice and ASME Journal of Dynamic Systems, Measurement and Control journals, and is an awardee of the Kalman award for the best paper published in the Journal of Dynamic Systems,
Measurement, and Control, and is a recent awardee of the 2011 SAE Max Bentele Award for Engine Technology Innovation.
“Model-Based Engine Algorithm Development for Control and Virtual Sensing”
Abstract: Greg is an associate professor of Mechanical Engineering at Purdue University who has developed a research program focused on developing generalizable, experimentally validated, model-based estimation and control strategies to enable: i.) advanced high efficiency, low emission IC engine combustion strategies, and ii.) clean and efficient combustion of domestically available alternative fuels. Dr. Shaver’s ongoing research efforts include: Physics-based, closed-loop estimation and control of variable biodiesel/diesel blends Dr. Shaver’s students have demonstrated that closed-loop control can be used to eliminate the 30+% increase in biodiesel-induced NOx, and increasing efficiency, while retaining significant particulate matter (PM) reductions (> 50%) with variable biodiesel blend fractions. Specifically, through a combination of: i.) a change of closed-loop control variables (combustible oxygen mass fraction (COMF) instead of exhaust gas recirculation fraction, and injected
fuel energy instead of injected fuel mass), and ii.) model-based biodiesel blend estimation; the NOx increases for any biodiesel blend or feedstock can be eliminated in a generalizable way, without the need for additional engine calibration. This strategy was derived from a fundamental understanding of the impact on combustion of the presence
of oxygen in, and lower energy content of, biodiesel derived from any feedstock. Modeling and estimation of next generation, piezo-electric fuel injection systems The dynamic response capabilities of piezo-electric actuators are superior to solenoids, allowing: 1) a 65% reduction
injector flow rate response during convention injection events, and 2) realization of complex injection “rate shaping” – to enable promotion and control of advanced combustion strategies. Dr. Shaver’s research team has developed generalizable model-based strategies for estimating the fuel injection rate, an un-measurable quantity on-engine, for use
during closed-loop control on both a cycle-to-cycle, and “within-a-cycle” basis. Estimated injection quantities exhibit errors less than 5%, while estimated injection pulse duration and separation are within 10×10-6 seconds. Variable Valve actuation to enable highly efficient compression ignition engines Advanced mode combustion and more efficient gas exchange, enabled via variable valve actuation (VVA) and closedloop
control, are projected to allow an increase in the brake thermal efficiency (BTE) of compression ignition engines to 55+% (today’s most efficient engines have BTEs of ~40%). VVA breaks the kinematic link between the piston and the intake and exhaust valves, providing flexibility in the valve closure/opening timing and lift – allowing more precise manipulation of the in-cylinder reactant (fuel, oxygen) concentrations, temperature, mixing, and amount of compression, both prior to, and during the combustion process. Dr. Shaver’s students have dynamically modeled, and developed closed-loop estimation (i.e., “virtual sensing”) and control strategies for, compression ignition engines incorporating VVA. As in all of his team’s research efforts, there is a heavy emphasis on the experimental validation/demonstration of all models and algorithms.