UCLA

Energy consumption and efficiency continue to be an area of high interest with the diminishing supply and rising costs of fossil fuels. In the United States, the industrial and transportation sectors consume a significant portion of the resources and total energy, accounting for significant fossil-fuel-related environmental impacts such as greenhouse gas pollution and global warming. It has been estimated that between 20 to 50\% of the energy consumed is lost as waste heat in the form of hot exhaust gases, cooling water, and hot equipment surfaces. By converting the heat to a more useful energy form, waste heat recovery (WHR) technologies are capable of creating emission-free, low-cost, and sustainable energy sources. However, WHR systems, if not properly designed and operated, may not be economically and or even feasible, particularly with low-grade and highly-transient heat sources. The aim of this dissertation is to predict WHR performance and feasibility through physics-based static and dynamic Rankine Cycle (RC) modeling for low- and medium-grade transient heat sources. The dynamic models provided are low-order, control-oriented, and suitable for tractable estimation and control methods that improve operational performance and observability of key process variables. Thermoproperties for water and steam are obtained from equations of state formulations based on Helmholtz and Gibbs free energy. For general fluids and their mixtures, equations of state can be obtaned from a presented least squares property fit routine. This dissertation applies the modeling, estimation, and control methods on a WHR application for heavy-duty diesel powertrain where important RC variables are captured and monitored while satisfying specified design and operating constraints. An organic working fluid mixture of ethanol and water is considered for this organic RC (ORC) application. Estimation and control methods are simulated on a dynamic ORC model of different architectures and actuator configurations. Power load following is also examined. The simulation results indicate improved ORC operation with feedback controls over the open-loop case. Multi-input multi-output controllers that rely on state estimation feedback show better tracking performance than single-input single-output controllers. Finally, a library of static and dynamic component models are provided as a useful aid for designing general WHR systems.