Doctor of Philosophy / Department of Chemical Engineering / Keith L. Hohn / Extensive research has gone into developing and modeling the three-way catalyst (TWC) to reduce the emissions of hydrocarbons, NOx and CO from gasoline-fueled engines level. However, much less has been done to model the use of the three-way catalyst to treat exhaust from natural gas-fueled engines. Our research address this gap in the literature by developing a detailed surface reaction mechanism for platinum based on elementary-step reactions. A reaction mechanism consisting of 24 species and 115 elementary reactions was constructed from literature values. All reaction parameters were used as found in the literature sources except for steps modified to improve the model fit to the experimental data. The TWC was simulated as a one-dimension, isothermal plug flow reactor (PFR) for the steady state condition and a continuous stirred-tank reactor (CSTR) for the dithering condition. This work describes a method to quantitatively simulate the natural gas engine TWC converter performance, providing a deep understanding of the surface chemistry in the converter. Due to the depletion of petroleum oil and recent volatility in price, synthesizing value-added chemicals from biomass-derived materials has attracted extensive attention. 1, 3-butadiene (BD), an important intermediate to produce rubber, is conventionally produced from petroleum. Recently, one potential route is to produce BD by dehydration of 2, 3-butanediol (BDO), which is produced at high yield from biomass. This reaction was studied over two commercial forms of alumina. Our results indicate acid/base properties greatly impact the BD selectivity. Trimethylamine can also modify the acid/base properties on alumina surface and affect the BD selectivity. Scandium oxide, acidic oxide or zirconia dual bed systems are also studied and our results show that acidic oxide used as the second bed catalyst can promote the formation of BD, while 2,5-dimethylphenol is found when the zirconia is used as the second bed catalyst which is due to the strong basic sites.

With increasing concerns about the harmful effects of conventional liquid fossil fuel emissions, natural gas has become a very attractive alternative fuel to power prime movers and stationary energy conversion devices. This research studies the injection and ignition numerically for natural gas (mainly methane) as a fuel applied to diesel engine. Natural gas injector and glow plug ignition enhancement are two of the most technical difficulties for direct injection natural gas engine design. This thesis models the natural gas injector, and studies the characteristics of the internal flow in the injector and natural gas jet in the combustion chamber during the injection process. The poppet valve model and pintle valve model are the first reported models to simulate the natural gas injector to improve the traditional velocity and pressure boundary conditions. This thesis also successfully models the glow plug assisted natural gas ignition and combustion processes by developing a glow plug discretized model and a novel virtual gas sub-layer model. Glow plug discretized model can describe the transient heat transfer, and adequately represents the thin layers of heat penetration and the local temperature difference due to the cold gas jet impingement. The virtual gas sub-layer model considers complicated physical processes, such as chemical reaction, heat conduction, and mass diffusion within the virtual sub-layers without significantly increasing computational time and load. KIVA-3V CFD code was chosen to simulate the fluid flow. Since the KIVA-3V is designed specifically for engine research application with conventional liquid fuels, many modifications have been implemented to facilitate this research.

With increasing concerns about the harmful effects of conventional liquid fossil fuel emissions, natural gas has become a very attractive alternative fuel to power prime movers and stationary energy conversion devices. This research studies the injection and ignition numerically for natural gas (mainly methane) as a fuel applied to diesel engine. Natural gas injector and glow plug ignition enhancement are two of the most technical difficulties for direct injection natural gas engine design. This thesis models the natural gas injector, and studies the characteristics of the internal flow in the injector and natural gas jet in the combustion chamber during the injection process. The poppet valve model and pintle valve model are the first reported models to simulate the natural gas injector to improve the traditional velocity and pressure boundary conditions. This thesis also successfully models the glow plug assisted natural gas ignition and combustion processes by developing a glow plug discretized model and a novel virtual gas sub-layer model. Glow plug discretized model can describe the transient heat transfer, and adequately represents the thin layers of heat penetration and the local temperature difference due to the cold gas jet impingement. The virtual gas sub-layer model considers complicated physical processes, such as chemical reaction, heat conduction, and mass diffusion within the virtual sub-layers without significantly increasing computational time and load. KIVA-3V CFD code was chosen to simulate the fluid flow. Since the KIVA-3V is designed specifically for engine research application with conventional liquid fuels, many modifications have been implemented to facilitate this research.

No description available.

<div>The commercial vehicle sector is an important enabler of the economy and is heavily dependent on fossil fuels. In the fight against climate change, reduction of emissions by improving fuel economy is a key step for the commercial vehicle sector. Improving fuel economy deals with reducing energy losses from fuel to the wheels. This study aims to analyze efficiency improvements for two systems that are important in reducing CO2 emissions - hybrid powertrains and natural gas engines. At first, a prototype series hybrid powertrain was analyzed based on on-highway data collected from its powertrain components. Work done per mile by the electrical components of the powertrain showed inefficient battery operation. The net energy delivery of the battery was close to zero at the end of the runs. This indicated battery was majorly used as an energy storage device. Roughly 15% of losses were observed in the power electronics to supply power from battery and generator to the motor. Ability of the hybrid system to capture regenerative energy and utilize it to propel the vehicle is a primary cause for fuel savings. The ability of this system to capture the regenerative energy was studied by modeling the system. The vehicle model demonstrated that the system was capturing most of the theoretically available regenerative energy. The thesis also demonstrates the possibility of reduction of vehicular level losses for the prototype truck. Drag and rolling resistance coefficients were estimated based on two coast down tests conducted. The ratio of captured regenerative to the drive energy energy for estimated drag and rolling resistant coefficients showed that the current system utilizes 4%-9% of its drive energy from the captured regenerative energy. Whereas a low mileage Peterbilt 579 truck could increase the energy capture ratio to 8%-18% for the same drive profile and route. Decrease in the truck’s aerodynamic drag and rolling resistance can potentially improve the fuel benefits.</div><div>The second study aimed to reduce the engine level pumping losses for a natural gas spark ignition engine by cylinder deactivation (CDA). Spark ignited stoichiometric engines with an intake throttle valve encounter pumping/throttling losses at low speed, low loads due to the restriction of intake air by the throttle body. A simulation study for CDA on a six cylinder natural gas engine model was performed in GT- Power. The simulations were ran for steady state operating points with a torque range 25-560 ftlbs and 1600 rpm. Two , three and four cylinders were deactivated in the simulation study. CDA showed significant fuel benefits with increase in brake thermal efficiency and reduction in brake specific fuel consumption depending on the number of deactivated cylinders. The fuel benefits tend to decrease with increase in torque. Engine cycle efficiencies were analyzed to investigate the efficiency improvements. The open cycle efficiency is the main contributor to the overall increase in the brake thermal efficiency. The work done by the engine to overcome the gas exchange during the intake and exhaust stroke is referred to the pumping losses. The reduction in pumping losses cause an improvement in the open cycle efficiency. By deactivating cylinders, the engine meets its low torque requirements by increase in the intake manifold pressure. Increased intake manifold pressure also resulted in reduction of the pumping loop indicating reduced pumping losses. A major limitation of the CDA strategy was ability to meet EGR fraction requirements. The increase in intake manifold pressure also caused a reduction in the delta pressure across the EGR valve. At higher torques with high EGR requirements CDA strategy was unable to meet the required EGR fraction targets. This limited the benefits of CDA to a specific torque range based on the number of deactivated cylinders. Some variable valve actuation strategies were suggested to overcome this challenge and extend the benefits of CDA for a greater torque range.</div><div><br></div>

This dissertation focuses on the introduction and development of an integrated model-based design and optimization platform to solve the optimal design and optimal control, or hardware and software co-design, problem for hybrid electric propulsion systems. Specifically, the hybrid and plug-in hybrid electric powertrain systems with diesel and natural gas (NG) fueled compression ignition (CI) engines and large Li-ion battery energy storage system (ESS) for propelling a hybrid electric marine vessel are investigated. The combined design and control optimization of the hybrid propulsion system is formulated as a bi-level, nested optimization problem. The lower-level optimization applies dynamic programming (DP) to ensure optimal energy management for each feasible powertrain system design, and the upper-level global optimization aims at identifying the optimal sizes of key powertrain components for the powertrain system with optimized control. Recently, Li-ion batteries became a promising ESS technology for electrified transportation applications. However, these costly Li-ion battery ESSs contribute to a large portion of the powertrain electrification and hybridization costs and suffer a much shorter lifetime compared to other key powertrain components. Different battery performance modelling methods are reviewed to identify the appropriate degradation prediction approach. Using this approach and a large set of experimental data, the performance degradation and life prediction model of LiFePO4 type battery has been developed and validated. This model serves as the foundation for determining the optimal size of battery ESS and for optimal energy management in powertrain system control to achieve balanced reduction of fuel consumption and the extension of battery lifetime. In modelling and design of different hybrid electric marine propulsion systems, the life cycle cost (LCC) model of the cleaner, hybrid propulsion systems is introduced, considering the investment, replacement and operational costs of their major contributors. The costs of liquefied NG (LNG), diesel and electricity in the LCC model are collected from various sources, with a focus on present industrial price in British Columbia, Canada. The greenhouse gas (GHG) and criteria air pollutant (CAP) emissions from traditional diesel and cleaner NG-fueled engines with conventional and optimized hybrid electric powertrains are also evaluated. To solve the computational expensive nested optimization problem, a surrogate model-based (or metamodel-based) global optimization method is used. This advanced global optimization search algorithm uses the optimized Latin hypercube sampling (OLHS) to form the Kriging model and uses expected improvement (EI) online sampling criterion to refine the model to guide the search of global optimum through a much-reduced number of sample data points from the computationally intensive objective function. Solutions from the combined hybrid propulsion system design and control optimization are presented and discussed. This research has further improved the methodology of model-based design and optimization of hybrid electric marine propulsion systems to solve complicated co-design problems through more efficient approaches, and demonstrated the feasibility and benefits of the new methods through their applications to tugboat propulsion system design and control developments. The resulting hybrid propulsion system with NG engine and Li-ion battery ESS presents a more economical and environmentally friendly propulsion system design of the tugboat. This research has further improved the methodology of model-based design and optimization of hybrid electric marine propulsion systems to solve complicated co-design problems through more efficient approaches, and demonstrated the feasibility and benefits of the new methods through their applications to tugboat propulsion system design and control developments. Other main contributions include incorporating the battery performance degradation model to the powertrain size optimization and optimal energy management; performing a systematic design and optimization considering LCC of diesel and NG engines in the hybrid electric powertrains; and developing an effective method for the computational intensive powertrain co-design problem. / Graduate

<p> One primary focus on internal combustion engines is that these engines create multiple harmful exhaust gases that can cause damage to the environment. There are a number of advanced strategies that are currently being investigated to help reduce the amount of these harmful emissions that are emitted from IC engines. One such method of reducing harmful emission gases focuses on the three-way-catalyst. A three-way-catalyst (TWC) is an exhaust emission control device that is designed in such a way to take harmful exhaust gases and convert them into less harmful gases through various chemical reactions within the TWC. To help further the reduction of these harmful gases in the TWC, a novel two-loop control and estimation strategy is used. This control and estimation strategy involves the use of two loops with an inner-loop controller, outer-loop robust controller, and an estimator in the outer-loop. The estimator consists of a TWC model and an extended Kalman filter which is used to estimate the fractional oxidation state (FOS) of the TWC. This estimated FOS is then used by the robust controller, along with other parameters, to produce a desired engine lambda reference signal, λup. This desired lambda signal is then used by the inner-loop controller to control the engine lambda. Accurate control of lambda is important because the air-fuel-ratio range for a TWC to effectively achieve oxidation and reduction simultaneously is extremely narrow. Another primary focus in the field of internal combustion engines is designing and tuning advanced models within GT-Power that can accurately predict what will happen when running an actual engine. Designing, troubleshooting, and testing a GT-Power model is an extensive but rewarding process. Creating an accurate engine model can not only provide one with primary engine data that is also measurable in a test cell, but can also provide insight into some of the intricate processes and nature of the engine that are difficult or impossible to physically measure. Cummins has an extensive process of tuning GT-Power engine models. This process include items such as initial model calibrations, model discretizations, turbocharger tunings, and other items. Some of these processes are used to calibrate both Cummins Power Systems Business Unit engines as well as a Purdue B6.7N natural gas engine. </p>