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Technical Paper

Optimal SCR Control Using Data-Driven Models

2013-04-08
2013-01-1573
In this paper, we develop a method for optimizing urea dosing to minimize the downstream readings from a production NOx sensor that has cross-sensitivity to ammonia. This approach favors high NOx conversion and reduced ammonia slip. The motivation for this work is to define a process to identify the maximum selective catalytic reduction SCR performance bounds for a given drive cycle. The approach uses a model structure that has a closed-form optimal solution for the urea injection. Every aftertreatment system has its own, unique model, which must be identified and validated. To demonstrate the approach, a model is identified and validated using experimental SCR input/output NOx sensor data from a 2010 Cummins 6.7L ISB production engine. The optimal control law is then simulated and its performance compared against the simulated performance of the SCR using experimental data for its inlet conditions.
Technical Paper

Characterization of the Three Phase Catalytic Wet Oxidation Process in the International Space Station (ISS) Water Processor Assembly

2000-07-10
2000-01-2252
A three phase catalytic mathematical model was developed for analysis and optimization of the volatile reactor assembly (VRA) used on International Space Station (ISS) Water Processor. The Langmuir-Hinshelwood Hougen-Watson (L-H) expression was used to describe the surface reaction rate. Small column experiments were used to determine the L-H rate parameters. The test components used in the experiments were acetic acid, acetone, ethanol, 1-propanol, 2-propanol and propionic acid. These compounds are the most prevalent ones found in the influent to the VRA reactor. The VRA model was able to predict performance of small column data and experimental data from the VRA flight experiment.
Technical Paper

Energy Storage Requirements and Implementation for a Lunar Base Microgrid

2023-09-05
2023-01-1514
Future lunar missions will utilize a Lunar DC microgrid (LDCMG) to construct the infrastructure for distributing, storing, and utilizing electrical energy. The LDCMG’s energy management, of which energy storage systems (ESS) are crucial components, will be essential to the success of the missions. Standard system design currently employs a rule-of-thumb approach in which design methodologies rely on heuristics that may only evaluate local power balancing requirements. The Hamiltonian surface shaping and power flow control (HSSPFC) method can also be utilized to analyze and design the lunar LDCMG power distribution network and ESS. In this research, the HSSPFC method will be utilized to determine the ideal energy storage requirements for ESS and the optimally distributed control architecture.
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