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Zeng, XiangruiOptimally-Personalized Hybrid Electric Vehicle Powertrain Control
Doctor of Philosophy, The Ohio State University, 2016, Mechanical Engineering
One of the main goals of hybrid electric vehicle technology is to improve the energy efficiency. In industry and most of academic research, the powertrain control is designed and evaluated under standard driving cycles. However, the situations that a vehicle may encounter in the real world could be quite different from the standard cycles. Studies show that the human drivers have a great influence on the vehicle energy consumptions and emissions. The actual operating conditions that a vehicle faces are not only dependent on the roads and traffic, but also dependent on the drivers. A standard driving cycle can only represent the typical and averaged driving style under the typical driving scenarios, therefore the control strategies designed based on a standard driving cycle may not perform well for all different driving styles. This motivates the idea to design optimally-personalized hybrid electric vehicle control methods that can be adaptive to individual human driving styles and their driving routes. Human-subject experiments are conducted on a driving simulator to study the driving behaviors. A stochastic driver pedal model that can learn individual driver’s driving style is developed first. Then a theoretic investigation on worst-case relative cost optimal control problems, which is closely related to vehicle powertrain optimal control under real-world uncertain driving scenarios, is presented. A two-level control structure for plug-in hybrid electric vehicles is proposed, where the parameters in the lower-level controller can be on-line adjusted via optimization using historical driving data. The methods to optimize these parameters are designed for fixed-route driving first, and then extended to multi-routes driving using the idea similar to the worst-case relative cost optimal control. The performances of the two proposed methods are shown through simulations using human driving data and stochastic driver model data respectively. The energy consumption results in both situations are close to the posteriori optimal result and outperform other existing methods, which show the effectiveness of applying optimally-personalized energy management strategy on hybrid electric vehicles. Finally, a route-based global energy-optimal speed planning method is also proposed. This off-line method provides a useful tool to evaluate the potential of other speed planning methods, for either eco-driving guidance applications or future automated vehicle controls. The contributions of this dissertation include 1) a novel stochastic driver pedal behavior model which can learn independent drivers’ driving styles is created, 2) a new worst-case relative cost optimal control method is proposed, 3) a real-time implementable stochastic optimal energy management strategy for hybrid electric vehicles running on fixed routes is designed using the statistics of history driving data, 4) the fix-route strategy is extended to the multi-route situation, and 5) an off-line global energy-optimal speed planning solution for road vehicles on a given route is presented.

Committee:

Junmin Wang (Advisor); Ryan Harne (Committee Member); Chia-Hsiang Menq (Committee Member); Haijun Su (Committee Member)

Subjects:

Automotive Engineering; Mechanical Engineering

Keywords:

Hybrid electric vehicle; energy management strategy; optimal control; speed planning; driver model

Shivaprasad, ShreyasModel Based Investigation of Lean Gasoline PM and NOx Control
Master of Science, The Ohio State University, 2014, Mechanical Engineering
A flexible model-based vehicle platform was developed with all the appropriate aftertreatment components and sensors for a GDI engine having the ability to perform diagnostic analysis. This model was developed by integrating aftertreatment and sensor models available in the public domain to develop a platform capable of running different drive cycles and scaling across different vehicle platforms with minor changes. Faults were identified for each system and the model was added with the capability to inject those faults to analyze the ability of the sensor set to diagnose those faults. Results have been presented representing the working of the model when the faults are injected. A Design of Experiments (DOE) study was conducted to explore the design space of the GPF and understand the impact of the design parameters on the performance of the filter. It was concluded from the study that smaller filters can be used due to low soot loading and soot can be regenerated passively without any need for external heating. It was observed that ash loading in the filter may be a critical issue during the long run.

Committee:

Shawn Midlam-Mohler (Advisor); Yann Guezennec (Committee Member)

Subjects:

Automotive Engineering; Mechanical Engineering

Keywords:

Gasoline direct injection , Lean NOx trap , Particulate matter , Gasoline particulate filter

Zhang, QuanshengModeling, Energy Optimization and Control of Vapor Compression Refrigeration Systems for Automotive Applications
Doctor of Philosophy, The Ohio State University, 2014, Mechanical Engineering
In recent years, the increasing fuel consumption in the transportation sector has forced the automotive industry to improve their fleet-average fuel economy without sacrificing the vehicle performance. The primary path towards achieving fuel economy improvements consists of improving the energy conversion efficiency of powertrain components and mitigating various forms of losses. Ancillary loads, such as the Air Conditioning (A/C) system, fans and blowers or the alternator, are considered as a significant source of energy dissipation on the vehicle, but represent also an opportunity to improve vehicle fuel economy through the implementation of advanced design and control solutions. To this extent, this dissertation focuses on the fundamental and applied research that leads to the development of control algorithms for the energy optimization of the Air Conditioning system for a light-duty vehicle. Two types of mathematical models for characterizing the dynamics of vapor compression refrigeration systems were developed and validated. A high-fidelity, controloriented model was initially developed through an original formulation of the Moving Boundary Method using the Reynolds Transport Theorem with moving control surface, providing a generic template for characterizing mass and energy transfer in presence of a phase changing fluid. Then, an energy-based model was derived from first principles to capture the relevant refrigerant pressure dynamics in the heat exchangers and the compressor power consumption affecting the fuel economy with limited complexity. In addition, this dissertation addresses two different control problems in the field of A/C systems. First, a low-level controller was designed for tracking performance and disturbance rejection, then a high-level supervisory controller was developed for system-level energy optimization and performance tracking. A local H-infinity controller was designed to track prescribed trajectories of two output variables, namely the pressure difference dp between the condenser and the evaporator, and the superheat temperature SH at the evaporator. The problem of system-level A/C optimization was then introduced by defining appropriate objective functions to characterize the fuel energy consumption, cooling performance and components durability. This led to the formulation of a constrained multi-objective optimal control problem, which was approached numerically to analyze the behavior of the system and identify the potential to reduce the energy consumption while maintaining acceptable cooling performance. The results of this study were used as a starting point for the design of a forwardlooking energy-based strategy. The Pontryagin’s Minimum Principle for continuoustime optimal control problems, the Hybrid Minimum Principle (HMP) theory and the Embedding Method for switching hybrid systems were considered in this study to design an optimal control policy for the A/C compressor clutch. The results obtained by applying these method were evaluated in simulation, using the energy-based A/C model.

Committee:

Marcello Canova (Advisor); Giorgio Rizzoni (Committee Member); Xiaodong Sun (Committee Member); Vadim Utkin (Committee Member)

Subjects:

Automotive Engineering

Agarwal, Neeraj R.Modeling, Validation and Analysis of an Advanced Thermal Management System for Conventional Automotive Powertrains
Master of Science, The Ohio State University, 2012, Mechanical Engineering
Reducing vehicle fuel consumption while maintaining same or better performance characteristics has been one of the main focuses of auto car manufacturers. In this sense, OEMs are introducing thermal management system (TMS) in modern vehicles that help attain rapid fluid warm-up during cold-start conditions. This leads to lower fluid viscosities early on in a drive cycle and hence reduced losses in the engine and powertrain components, resulting in lower fuel consumption. Rapid fluid warm-up also helps improve passenger comfort by providing necessary heating or cooling on demand. Through this work, a model characterizing the low frequency energy and power transfer in the engine and powertrain components is formulated. An advanced TMS consisting of components for waste heat energy recovery is proposed and its model is formulated. The combined set of these models is called the Vehicle Energy Simulator (VES). The model is thoroughly calibrated and validated using experimental data from steady state and transient testing; results are included in detail. The validated VES is then used to investigate control strategies for valves that are part of the TMS, used to control fluid flow to the various heat exchangers in order to attain rapid warm-up of coolant, engine oil and transmission fluid. It is seen that, the use of advanced TMS, over a conventional thermal management system, results in 3.4% reduction in fuel consumption. The investigation leads to recommendation of a reasonable first generation for a genetic algorithm optimization to be used to find the “optimal trajectory” for thermal-system-valve actuation during a drive cycle for reducing fuel consumption.

Committee:

Marcello Canova, PhD (Advisor); Giorgio Rizzoni, PhD (Committee Member); Fabio Chiara, PhD (Committee Member); Shawn Midlam-Mohler, PhD (Committee Member)

Subjects:

Automotive Engineering; Engineering

Keywords:

Engine Thermal Management; Engine Modeling; Heat Exchanger Modeling; Thermal Management System; Control-Oriented Model

Bezaire, Beth AnnModeling and Control of an Electrically-Heated Catalyst
Master of Science, The Ohio State University, 2011, Mechanical Engineering

Current model-based design research on automotive catalytic converters mainly fall into three basic categories: either modeling the catalyst as a continuous system based on physics, discretizing the system to reduce modeling complexity, or developing a highly-simplified, mean-value model for control. Continuous models are computationally intensive and therefore not well-suited for implementation into a vehicle model for Hardware in the Loop or control design. Highly-simplified models are calibrated for a particular system without incorporating the governing physical laws into the model, and mean-value models are only able to predict the response for a single lumped element. Although a simplified, mean-value model can be developed to accurately predict system response, it does not lend itself to being extended to broader applications without significant re-calibration efforts. Therefore, a model is needed that can account for the physics of the system so it can be extended to further applications while decreasing computation time to allow the model to be implemented for Hardware in the Loop and vehicle control design.

This research investigates the development of such a model to predict automotive catalytic converter thermal response during warm-up. A one-dimensional, lumped-parameter model of a three-way catalyst was developed in Matlab/Simulink. The catalyst length was divided into discrete elements. Each discrete element contained states for the temperatures of the gas, substrate, and can wall. Heat transfer mechanisms were modeled from physics-based equations. For each discrete element, these equations modeled the enthalpy of the gas flow axially through the catalyst, convective heat transfer between the gas and substrate, conduction between discrete elements axially along the catalyst for the substrate and for the can, conduction between the substrate and can wall, and convection from the can wall to ambient. Model predictions were validated against experimental results for thermal transients.

The application of this model was analysis for a plug-in electric vehicle application with electrically-heated catalyst (EHC). The model was used to compare the catalyst thermal response with and without the EHC. These results facilitated the development of a control strategy for the EHC, as well as recommendations for improving the overall vehicle control strategy. For further development, this model can also be extended to a two- or three-dimensional application. A two-dimensional catalyst model would be of interest to account for temperature gradients in the radial direction through the catalyst.

Committee:

Shawn Midlam-Mohler, PhD (Advisor); Giorgio Rizzoni, PhD (Advisor); Yann Guezennec, PhD (Committee Member)

Subjects:

Automotive Engineering; Mechanical Engineering

Keywords:

emissions; hybrid vehicle; electrically-heated catalyst; EHC; PHEV

Garimella, Venkata Naga RavikanthExhaust Emissions Analysis for Ultra Low Sulfur Diesel and Biodiesel Garbage Trucks
Master of Science in Civil Engineering, University of Toledo, 2010, Civil Engineering
The main objective of this experimental thesis is to study the exhaust emissions of in-use garbage trucks for different idling modes fuelled with alternate fuels. The emission concentrations of carbon monoxide, sulfur dioxide, oxides of nitrogen (NO, NO2, and NOX), and carbon dioxide were examined with respect to engine parameters such as fuel temperature, coolant temperature and percent fuel. A Testo350 XL portable emission monitoring instrument was used to collect second by second data for the pollutants. Performance of engine parameters was also monitored simultaneously using on-board diagnostic (OBD) software. The tail pipe emissions from Ultra-Low Sulfur Diesel (ULSD) are compared with emissions from biodiesel blends. Hotter engines produced lower emissions compared to colder engines for all fuel blends and vehicle makes. Significant reductions in emission concentrations were observed due to the inspection and maintenance programs. The performance of biodiesel blends in reducing emission concentrations of pollutants across different vehicle makes was found to be inconsistent. A comprehensive study on various vehicle, fuel and operating parameters that effect the exhaust emission concentrations was conducted to find an alternative to ULSD.

Committee:

Ashok Kumar, PhD (Committee Chair); Brian Randolph, PhD (Committee Member); Dong-Shik Kim, PhD (Committee Member)

Subjects:

Alternative Energy; Automotive Engineering; Civil Engineering; Environmental Engineering; Environmental Health; Environmental Science; Environmental Studies; Experiments; Sustainability; Transportation; Urban Planning

Keywords:

biodiesel; ultra low sulfur diesel; diesel; emission; exhaust; garbage truck; portable emission; blends; Idle engine; Alternative fuels; fuel

Balagurunathan, JayakishanInvestigation of Ignition Delay Times of Conventional (JP-8) and Synthetic (S-8) Jet Fuels: A Shock Tube Study
Master of Science (M.S.), University of Dayton, 2012, Mechanical Engineering
The global depletion of petroleum-based fuels has led the world to more closely examine alternate fuels. Therefore, alternate fuels produced from feedstocks such as coal, soybeans, palm oil or switch grass through methods such as coal liquefaction, biomass gasification, and Fischer-Tropsch synthesis have been tested. Among these techniques, fuels generated using Fischer-Tropsch technologies are of interest because they produce clean burning hydrocarbons similar to those found in commercial fuels. Therefore, in this study the Fischer-Tropsch derived S-8 fuel was evaluated as a drop-in replacement for the jet fuel JP-8. The jet fuel JP-8 is comprised of n-, iso- and cyclo- alkanes as well as aromatics while the S-8 fuel is primarily comprised of n- and iso- alkanes. The composition of the fuel affects its ignition characteristics chemically and physically by either advancement or delay of time to ignition. Since this study focused on the chemical effects, the fuels were completely pre-vaporized and pre-mixed. A high pressure, high temperature heated single pulse shock tube was used for this study. The shock tube is an established experimental tool used to obtain ignition delay data behind reflected shock waves under operating conditions relevant to modern engines. The experiments were conducted over a temperature range of 1000-1600 K, a pressure of 19±2 atm, equivalence ratios of 0.5, 1 and 3, within a dwell time of 7.6±0.2 ms and an argon dilution of 93% (v/v). Ignition delay times were measured using the signal from the pressure transducer on the end plate with guidance from the optical diagnostic signal. Along with JP-8 and S-8, the ignition delay of n-heptane was also studied. N-heptane was chosen to represent the n-alkanes in the fuels for this study since it was present in both fuels and also to prove the fact that the n-alkanes were rate controlling. The results indicate that both S-8 and JP-8 fuels have similar ignition delays at corresponding equivalence ratios. The fuel-rich mixtures ignited faster at lower temperatures (<1150 K) and the fuel-lean mixtures ignited faster at higher temperatures (>1150 K). In the transition period between lower to higher temperatures (~1100-1200 K), the equivalence ratio had no significant effect on the ignition delay time. The results also show that the ignition delay time measurements of S-8 and JP-8 fuels are similar to the ignition delay of n-heptane at the equivalence ratio of Φ=0.5 and thereby indicate that the n-alkanes present in these fuels controlled the ignition under these conditions. The ignition delay results of S-8 and JP-8 at Φ=3.0 from this study were also compared to prior work (Kahandawala et al., 2008) on 2-methylheptane and n-heptane/toluene (80/20 liquid vol.%), respectively and found to be indistinguishable. This data serves to extend the gas phase ignition delay database for both JP-8 and S-8 and is the first known data taken for both these fuels at higher temperatures (>1000 K) for an equivalence ratio of 3.0 with argon as the diluent gas.

Committee:

Sukh Sidhu, Dr (Committee Chair); Philip Taylor, Dr (Committee Member); Moshan Kahandawala, Dr (Committee Member)

Subjects:

Aerospace Engineering; Aerospace Materials; Alternative Energy; Automotive Engineering; Automotive Materials; Chemical Engineering; Chemistry; Energy; Engineering; Environmental Engineering; Mechanical Engineering; Petroleum Engineering; Technology

Keywords:

Ignition delay; shock tube; S-8; JP-8; Jet fuels; Fuel characteristics; heated shock tube; Fischer-Tropsch; Alternate fuels; alkanes; synthetic fuel; fuel; iso-alkanes; jayakishan balagurunathan

Khasawneh, Hussam JihadANALYSIS OF HEAT-SPREADING THERMAL MANAGEMENT SOLUTIONS FOR LITHIUM-ION BATTERIES
Master of Science, The Ohio State University, 2011, Mechanical Engineering
Electrical storage technologies (i.e., batteries) play a ubiquitous role in all facets of modern technologies for applications ranging from very small to very large scale, both stationary and mobile. In the past decade, Li-ion batteries are quickly emerging as the preferred electrical energy storage technology due to the intrinsic power and energy storage density compared to older battery chemistries. All electrochemical batteries are strongly linked to their thermal state: on one hand, their electrical characteristics are strongly dependent on temperature and, on the other hand, their thermal state is a result of both their environmental temperature, but also their electrical usage due to internal heat generation. Furthermore, their life (and potentially safety) is also strongly affected by their thermal state. Li-ion batteries, due to their high electrical power capability and density tend to be used aggressively in many applications, rendering the thermal issues more acute. Finally, Li-ion battery packs (like all packs) are made of many cells interconnected in various series/parallel arrangements in tightly confined spaces. Hence, thermal management solutions need to be implemented for two primary reasons: rejecting the heat generated inside the pack to the environment to avoid high (or unsafe) temperatures leading to premature (or catastrophic) failure and providing a good thermal uniformity among all the cells so that their electrical performance (and aging) in well matched in a pack. This thesis focuses on the thermal modeling of Li-ion packs and the development of passive thermal management solutions for such packs. The thesis first provides an extensive review of the current literature on Li-ion batteries electrical and thermal modeling and current approaches for thermal management solutions of Li-ion packs. This study then focuses on a particular current application using a small Li-ion pack, namely a contractor-grade 36v cordless drill. This particular application was chosen as it encapsulates many of the features of larger automotive packs and represent and leads to an aggressive usage pattern where battery life is always an issue. This pack was experimentally studied to establish typical usage patterns and to measure the thermal and electrical state of the stock pack during such usage. The study then developed and validated a FEM computational pack model in the stock configuration. This experimentally validated models was then used as a proxy to reality to numerically investigate multiple possible configurations of passive thermal management solutions using a high thermal conductivity, Graphite-based heat spreading material to both reduce temperature non-uniformities within the pack and decrease of overall pack temperature (better heat rejection) during aggressive use. Finally, a preliminary experimental validation of one of the promising configurations of heat spreaders was investigated. The work described in this thesis clearly demonstrates that passive heat spreading technology can be very beneficial to reduce thermal stress on batteries and lead to more thermally homogenous packs. Furthermore, this study demonstrated that the investigation of such solutions can be performed with validated thermal FEM models to speed up the development of actual solution and reduce experimental prototype building. Future work will include more configurations, but also experimental investigation of battery life for both thermally managed and unmanaged packs under similar (aggressive) usage patterns. Finally, the conclusions from this study conducted on a cordless power tool are probably equally applicable to large automotive battery packs where life and costs are critical.

Committee:

Yann Guezennec, PhD (Advisor); Marcello Canova, PhD (Committee Member)

Subjects:

Automotive Engineering; Mechanical Engineering

Keywords:

Li-ion Battery; Thermal Management Systems; Graphite Heat Spreaders; FEM Model

Meyer, JasonCalibration reduction in internal combustion engine fueling control: modeling, estimation and stability robustness
Doctor of Philosophy, The Ohio State University, 2011, Mechanical Engineering

Controlling the fuel injection system of an internal combustion engine is a challenging and multifaceted problem. Current control algorithms rely heavily on lengthy experimentally-based calibration techniques. Even with these extensive calibration processes, suboptimal performance is often achieved because the selected control gains depend on calibrator experience and intuition instead of objective metrics. The cost and manpower required to calibrate a fueling controller can be staggering. Recent advances in air path actuation technologies such as the variable geometry turbocharger for diesel engines and variable cam timing for gasoline engines have expanded the dimensionality of the fueling control problem, further increasing the calibration burden of conventional controllers.

This dissertation presents model based alternatives to the current calibration-heavy fueling controllers used in production gasoline and diesel engines. The novelty of these controllers is derived from both the underlying plant models and the application of estimation/control theory to these models. One of the most unique aspects of these control problems is the time varying delay which characterizes the plant (i.e. the engine air path system). From a deep understanding of the physical phenomena involved, new types of air path models that directly capture the oxygen transport and mixing dynamics are developed. An experimental validation demonstrates that such a model can even account for cylinder-to-cylinder response variations caused by asymmetrical exhaust runner lengths.

Advanced model based estimation and control techniques are applied to these models to develop more effective methods of estimating the most important dynamic variables (i.e. in-cylinder oxygen concentration and cylinder imbalance) and controlling fuel delivery in diesel and gasoline engines. During the design processes, particular emphasis is placed on stability robustness, and comprehensive stability proofs are provided for the controllers and estimators developed. Because of the practical issues involved in dynamically measuring the in-cylinder oxygen concentration, the in-cylinder oxygen concentration estimator and the diesel fueling controller are validated in simulation using the engine modeling software GT-Power. Experimental validations demonstrate the capabilities of the cylinder imbalance estimator and comprehensively quantify the performance of the gasoline fueling controller through direct comparisons to the existing production controller. Above even their performance and robustness benefits, the most compelling reasons to adopt these estimators and controllers over their production counterparts are their modest calibration requirements.

Committee:

Stephen Yurkovich, PhD (Advisor); Marcello Canova, PhD (Committee Member); Yann Guezennec, PhD (Committee Member); Giorgio Rizzoni, PhD (Committee Member); Junmin Wang, PhD (Committee Member)

Subjects:

Automotive Engineering; Electrical Engineering; Mechanical Engineering

Keywords:

Internal Combustion Engines; Air Path Modeling; Oxygen Concentration Estimation; Fueling Control; Cylinder Imbalance; Robustness; Cailbration Reduction; Diesel Engines; Gasoline Engines; AFR Control; Oxygen Dynamics; Gas Mixing and Transport Dynamics

Fogarty, Kevin JohnTurbocharger Turbines: An Experimental Study on the Effects of Wastegate Size and Flow Passage Design
Master of Science, The Ohio State University, 2013, Mechanical Engineering

The present study experimentally investigates three different automotive turbochargers of varying turbine/wastegate combination: two of similar turbine housing (BorgWarner) but different bypass throat diameter (20 and 26 mm), and a third of both different housing (Honeywell) and throat size from the former two (21 mm). The effects of turbine housing flow passage design and bypass throat size on open wastegate turbine performance and wastegate flow efficiency were examined at discrete wastegate valve openings: 5¿¿, 10¿¿, 20¿¿, and 40¿¿. The study also analyzes the effects of these geometrical differences on change in flow rate through the wastegate when examined independent of or in parallel with the rotor. Steady flow experiments were performed on a flow bench and cold-flow turbocharger experimental stand. A semi-empirical physical model has also been developed in this study for 1-D engine simulation codes to better characterize the parallel flow paths through the turbines and thus improve predictive accuracy of open wastegate performance. Measured turbine characteristics with closed wastegate were extrapolated and interpolated with a custom preprocessor and input to the code for the rotor, while wastegate flow was simulated in two ways: as an effective orifice area applied at the rotor (default approach) or as a physical parallel path (proposed alternative).

As the wastegates were opened under parallel flow, total turbine mass flow parameter (MFP) increased in proportion to wastegate size at 5¿¿ and 10¿¿ positions for similar total-to-static expansion ratio (ER-ts) and speed parameter. At larger openings, the combined effect of housing design and wastegate flow efficiency are of greater effect; the Honeywell turbine exhibited a similar increase in total MFP from 20¿¿ to 40¿¿ as from 10¿¿ to 20¿¿, while the BorgWarner turbines showed a substantially diminished gain in total MFP from 20¿¿ to 40¿¿ for a given ER-ts and speed parameter.

Wastegate-alone flow efficiency experiments revealed that the Honeywell wastegate discharge coefficient is higher than both BorgWarner wastegates at 40¿¿ for fixed ER-ts, and it was either equivalent to or slightly greater than the 26 mm BorgWarner wastegate at smaller openings. The discharge coefficient for the 20 mm BorgWarner wastegate was greater than the 26 mm variant for all fixed openings and ER-ts. All wastegates exhibited a slight increase in discharge coefficient with ER-ts. Estimation of combined rotor-and-wastegate flow by adding wastegate-alone and rotor-alone flows resulted in significant over-estimation of total MFP for the BorgWarner turbines. The error increased with bypass opening and, with few exceptions, was greater for the 26 mm than the 20 mm wastegate turbine for fixed opening degree and ER-ts. For the Honeywell turbine, estimated total turbine MFP was generally within ¿¿5% of measured quantities for all openings and ER-ts.

Using rotor-alone MFP characteristics and wastegate-alone flow efficiency measurements, the predictive accuracy of open wastegate turbine flow in a 1-D code was improved by physically modeling the parallel bypass path. The rotor-and-wastegate flow predictions for the 26 mm wastegate BorgWarner turbine were particularly more accurate, most significantly at ER-ts>1.4: error ranged from -0.50 to 22.94% under the default approach, whereas in the proposed model the error was confined to -4.62 to 3.21%.

Committee:

Ahmet Selamet (Advisor); Shaurya Prakash (Committee Member)

Subjects:

Automotive Engineering; Mechanical Engineering

Keywords:

turbocharger; turbine; wastegate

Hansen, Matthew Martin KennethOptimization of Conformal Joints in Axial Tension
Master of Science, The Ohio State University, 2012, Mechanical Engineering

Electromagnetic forming uses high current to form conductive material. It has been a possible manufacturing technique for joining materials since the 1960s. In the past decade the process has seen a resurgence due to the desire for lightweight manufacturing. The process provides a means to join dissimilar metals, reduce material costs, and the potential for energy savings in manufacturing. One issue that the process faces is the lack of a model to predict the forming process and effectiveness of resulting joints. There has been work done to characterize high strain rate deformation and to couple electro-mechanical systems, but there are still opportunities to provide better and more specific models of joint formation and behavior. A model was developed to describe the process of electromagnetically compressing aluminum tubes onto a steel mandrel. The model was then used to assess potential mandrel geometries for a tensile joint.

The process of characterizing the joint formation uses a combination of a numerical code to describe the tube compression pressure and an LS-DYNA computer model to describe the tube compression. The resulting conformal joint predicted by the model was experimentally verified and compared to three purposed mandrel geometries. The purposed mandrel designs were an attempt to evenly distribute the tensile load using three gradually increasing groove depths. The simulation then tested the tensile strength of the joints, verified with physical testing, and identified possible improvements in groove design. A test matrix was used to assess the effect of groove radius and groove depth on joint strength. The results showed that, in terms of strength, the groove depth is the most critical dimension and that the groove entry radius had little effect. The final optimized joint had a rectangular groove profile, with a groove entry radius the same size as the depth. The joint evenly distributed the tensile load and was shown to be more resistant to a reduction in friction than previously purposed geometries.

Committee:

Anthony Luscher, PhD (Advisor); Gary Kinzel, PhD (Committee Member); Glenn Daehn, PhD (Committee Member)

Subjects:

Automotive Engineering; Electromagnetism; Engineering; Materials Science; Mechanical Engineering; Mechanics

Keywords:

electromagnetic forming; EMF; LS-DYNA; mechanical joints; lightweight structures; joining methods;

Adams, William A.Analysis of Robustness in Lane Detection using Machine Learning Models
Master of Science (MS), Ohio University, 2015, Electrical Engineering (Engineering and Technology)
An appropriate approach to incorporating robustness into lane detection algorithms is beneficial to autonomous vehicle applications and other problems relying on fusion methods. While traditionally rigorous empirical methods were developed for mitigating lane detection error, an evidence-based model-driven approach yields robust results using multispectral video as input to various machine learning models. Branching beyond the few network structures considered for image understanding applications, deep networks with unique optimization functions are demonstrably more robust while making fewer assumptions. This work adopts a simple framework for data collection; retrieving image patches for comparison via regression through a learning model. Along a horizontal scanline, the most probable sample is selected to retrain the network. Models include simple regressors, various autoencoders, and a few specialized deep networks. Samples are compared by robustness and the results favor deep and highly specialized network structures.

Committee:

Mehmet Celenk (Advisor); Jeffrey Dill (Committee Member); Maarten Uijt de Haag (Committee Member); Rida Benhaddou (Committee Member)

Subjects:

Artificial Intelligence; Automotive Engineering; Computer Science; Engineering

Keywords:

Machine Learning; ADAS; Lane Detection; Autoencoder; Regressor; Deep Network; Deep Learning

Walters, David MichaelDesign, Validation, and Optimization of a Rear Sub-frame with Electric Powertrain Integration
Master of Science, The Ohio State University, 2015, Mechanical Engineering
Government regulations and consumer desire continue to aggressively push automotive manufacturers to improve the fuel economy and emissions of new vehicle designs. Vehicle weight reduction and the use of hybrid electric powertrains are becoming more commonly used methods for addressing a need for improved fuel economy and reduced vehicle emission. EcoCAR 2 is a three year collegiate design competition that involves 15 teams from universities across North America, competing to develop a vehicle with improved fuel economy and reduced emissions. Each team starts with a 2013 Chevrolet Malibu and replaces the powertrain with the primary objective being the reduction of fuel consumption and emissions. The team from The Ohio State University incorporated a rear electric powertrain featuring an electric machine and single-speed transmission into their vehicle architecture. This resulted in the need for a customized rear cradle to support the addition of a rear electric powertrain. An initial custom cradle design was created by modifying an existing steel rear sub-frame to accommodate the addition of the rear electric powertrain. However, in order to reduce total vehicle weight and thus improve fuel economy and reduce emissions, a reduced mass, aluminum rear cradle was created for Ohio State's final vehicle design. This study covers the methodology surrounding the design, validation, and optimization of that final rear cradle design.

Committee:

Giorgio Rizzoni (Advisor); Shawn Midlam-Mohler (Committee Member)

Subjects:

Automotive Engineering; Design; Engineering

Keywords:

Sub-frame; Rear Electric Power-train; EcoCAR 2; Aluminum Cradle; Aluminum Sub-frame; FEA; Design Cycle

Jing, JunboVehicle Fuel Consumption Optimization using Model Predictive Control based on V2V communication
Master of Science, The Ohio State University, 2014, Electrical and Computer Engineering
As people are working hard on improving vehicle's fuel economy, a large portion of fuel consumption in everyday driving is wasted by vehicle driver's inexperienced operations and inefficient judgments. This thesis proposes a system that optimizes the vehicle's fuel consumption in automated car-following scenarios. The system is designed able to work in the initial stage of implementing Vehicle-to-Vehicle (V2V) communications. The system is developed based on Model Predictive Control (MPC). With a given prediction of the preceding vehicle's speed, the system controls the vehicle's throttle and brake to follow the preceding vehicle with an optimal velocity profile. The control problem is formed into a quadratic programming optimization problem using real vehicle parameters. Active-set algorithm is adopted for optimization, and the computation speed can satisfy real-time computations. The control results show a significant fuel saving benefit of up to 15%, with car-following safety ensured and ride comfort cared. To provide the prediction horizon for the MPC based system, a preceding vehicle speed prediction algorithm and a leading vehicle speed prediction algorithm are developed in this thesis. The preceding vehicle's speed is predicted by analyzing the transmission of speed disturbances along the convoy using Intelligent Driver Model (IDM). The information needed is obtained through V2V communication, and the algorithm does not require a high V2V penetration rate. The estimated car-following behavioral parameters are clustered online for improved prediction accuracy. The algorithm can provide a prediction horizon of seconds depending on the convoy length. The leading vehicle speed prediction algorithm is developed to extend the prediction horizon. The algorithm predicts the leading vehicle's free road driving and approaching speed when a rather large gap to the next vehicle appears. The leading vehicle's historical speed profile is decoded into a driver operation state sequence and forms a Markov chain. Markov Model is used for speed prediction. The information required by the algorithm is simply speed profiles and car-following distance profiles, which can be easily obtained by cooperating with the already existing Adaptive Cruise Control (ACC) systems.

Committee:

Umit Ozguner (Advisor); Giorgio Rizzoni (Committee Member)

Subjects:

Automotive Engineering; Electrical Engineering; Energy; Engineering

Keywords:

Vehicle Fuel Consumption Minimization, Model Predictive Control, Quadratic Programming, V2V, Vehicle Speed Prediction, Markov Model

Waldman, Colin ADevelopment and Implementation of an Adaptive PMP-based Control Strategy for a Conventional Vehicle Electrical System
Master of Science, The Ohio State University, 2014, Mechanical Engineering
This thesis details the development, implementation, and experimental testing of a supervisory energy management control strategy for the vehicle electrical system of a passenger car. The control strategy commands the alternator duty cycle such that vehicle fuel economy is optimized whilst the instantaneous load current demand is met and constraints on the system voltage and battery state of charge are satisfied. To this extent, Pontryagin's Minimum Principle (PMP) is utilized alongside a vehicle plant model in order to evaluate the behavioral characteristics of the vehicle electrical system subjected to optimal control. These observations are employed in the development of an adaptive, PMP-based supervisory strategy capable of real-time control. Experimental testing of the in-house developed control strategy, termed "A-PMP", is benchmarked against a baseline production control strategy, demonstrating consistent improvements in vehicle fuel economy.

Committee:

Marcello Canova (Advisor); Shawn Midlam-Mohler (Committee Member)

Subjects:

Automotive Engineering; Engineering; Mechanical Engineering

Keywords:

Automotive; Model-based Control; Electrical System; Optimal Control; Energy Management

Varia, Adhyarth CIn-Situ Capacity and Resistance Estimation Algorithm Development for Lithium-Ion Batteries Used in Electrified Vehicles
Master of Science, The Ohio State University, 2014, Mechanical Engineering
Battery life, cost and weight are some of the most important factors considered while designing battery packs for electrified vehicles. These factors directly affect the appeal of electric vehicles in the market. While, performance, cost and weight can be evaluated at the production and design stage, battery life is a dynamic parameter influenced by a multitude of factors and is hard to accurately predict, often leading to conservative designs with oversized and more expensive battery packs. Expensive batteries and complex, multi-factor aging phenomena ideally would require continuous tracking of the battery state of health. Battery capacity and internal resistance are commonly used to quantify battery state of health, as these metrics translate directly into range and power at the user level. While resistance growth is relatively easy to estimate in a vehicle, capacity fade requires measurements typically done at the laboratory level and conditions never encountered in a vehicle. This thesis aims to develop an algorithm capable of tracking in situ these two parameters throughout the life of battery. By far the most challenging aspects of battery state of health estimation is to only use information available in the vehicle during its normal use, and furthermore, suitable with available on-board computing resources for real-time implementation. To that effect, the `needs and wants’ of an ideal in situ capacity estimator were clearly defined at the beginning of this work and algorithms that satisfy all the constraints were developed, tested and validated. This work leverages the experimental results of an aging campaign conducted in out laboratories on a total of 17 cells aged under a variety of realistic operating conditions. A sensitivity analysis of the output of the algorithm was then carried out to assess accuracy of the algorithms in the presence of parameter variations and sensor errors. Next, the separate capacity and resistance estimation algorithms were integrated into a single framework to estimate both parameters simultaneously and hence tracking both metrics required to assess the state of health. Finally, tools for post-processing the raw capacity and resistance estimation results were developed to deal with data drops and other issues. In summary, a computationally inexpensive algorithm that could be imbedded on a micro-processor on board an electric or hybrid vehicle was developed to accurately track capacity and internal resistance during normal vehicle operations. This algorithm produces a data rich stream of estimates (1 per charge depleting driving event) which can then be fed into a state of health estimator to make remaining useful life predictions. Having such an in situ tool provides feedback to continuously refine life prediction in light of possibly changing usage conditions in actual vehicles in operation. The capabilities of the novel algorithms developed and validated in this thesis led to the filing of a provisional US patent (Application Number: 62/010, 671) in June 2014 to protect the intellectual property resulting from work done in this project.

Committee:

Yann Guezennec, PhD (Advisor); Giorgio Rizzoni, PhD (Committee Member)

Subjects:

Automotive Engineering; Energy; Mechanical Engineering

Keywords:

Capacity estimation, State of health estimation, Lithium-ion batteries, Hybrid electric vehicles, Resistance estimation, State of charge estimation, Battery management systems, Battery aging

Bloomfield, Aaron PaulA High Frequency Alternating Current Battery Heater for Military Vehicles
Master of Science in Electrical Engineering, University of Toledo, 2011, College of Engineering

Energy storage devices such as electrochemical batteries typically do not perform well at low temperatures where energy density and peak power suffer. One battery chemistry that is particularly susceptible to this phenomenon is lead-acid which is used predominantly in automobile and truck applications for cranking internal combustion engines during starting. Several approaches have been implemented to aid in cold engine cranking which include external battery preheat techniques as well as using temperature-independent parallel energy storage devices such as ultracapacitors.

An alternative approach proposed in U.S. Patent No. 6,259,229 teaches the use of alternating currents for internal heating of the battery electrolyte. This approach was examined and its implementation was studied for 24-volt battery systems intended for cold cranking diesel engines in large military vehicles. Prototype high-frequency heaters were developed and tested for operation in extreme cold climates to -40°C with peak-to-peak currents up to 600 Amps in the frequency range of 5 kHz to 50 kHz.

Experimental results demonstrate significant improvement in pulse discharge performance (approaching that of room temperature) using large alternating currents to heat small and medium size battery packs. The research suggests a scale factor that relates the magnitude of heating current to the ampere-hour rating of the battery. However, for large battery packs it is estimated that currents may approach or exceed 1000 Amps peak-to-peak making a compact, cost-effective solution impractical. Additionally, an alternative approach was tested on a large-size battery pack which combines efficient low-current external and internal heating.

Committee:

Thomas Stuart, PhD (Advisor); Mohsin Jamali, PhD (Committee Member); Richard Molyet, PhD (Committee Member)

Subjects:

Automotive Engineering; Electrical Engineering

Keywords:

lead-acid; battery heating; alternating current; high frequency; military vehicles; pulse discharge; internal heating; external heating; heat electrolyte; discharge improvement

Chandavarkar, Rohan VivekEco-inspired Robust Control Design for Linear Time-Invariant systems with Real Parameter Uncertainty
Master of Science, The Ohio State University, 2013, Aero/Astro Engineering
This thesis addresses the importance and issues of the robust control design of linear time-invariant (LTI) systems with real-time parameter uncertainties. It is known that most of the existing robust control techniques are fairly conservative when dealing with real time parameter uncertainty. Also, majority of these existing techniques use control gains that are essentially functions of the perturbation information. The robust control design algorithm proposed in this thesis differs from these traditional techniques by focusing on the control design in achieving a specific structure of the closed loop system matrix that guarantees a maximum stability robustness index as possible without the using any of the perturbation information. The determination of this specific desired structure of closed loop system matrix forms the focal point of this algoithm and is inspired by already existing principles in the field of ecology. Using this ecological backdrop, the desired closed loop matrix is determined to contain self regulated species with predator-prey interactions among these species. In matrix nomenclature, such a set of matrices are labelled as Target Pseudo-Symmetric (TPS) matrices and hence form the class of desirable closed-loop system matrices. Based on these TPS matrices, which capture the maximum robustness index for any LTI system, a robust control design is carried out such that the final closed loop system possesses a robustness index as close to this maximum as possible. The robust control design algorithm presented is based on minimizing the norm of an implicit error and is supported with several illustrative examples. This eco-inspired robust control algorithm exemplifies the strong correlation that exists between natural systems and engineering systems. Hence, the main goal of this thesis is to aid in the revival of research in the field of robust control using insights from ecological principles.

Committee:

Rama Yedavalli, Dr. (Advisor); Chia-Hsiang Menq, Dr. (Committee Member)

Subjects:

Aerospace Engineering; Applied Mathematics; Automotive Engineering; Ecology; Engineering; Mathematics Education; Mechanical Engineering

Keywords:

ecology; controls; robust control; engineering; norm minimization; linear algebra; closed-loop system; robustness; qualitative and quantitative robustness

Huster, Andrew ChristianDesign and Validation of an Active Stereo Vision System for the OSU EcoCAR 3
Master of Science, The Ohio State University, 2017, Electrical and Computer Engineering
The EcoCAR 3 project is a four-year Advanced Vehicle Technology Competition sponsored by General Motors and the U.S. Department of Energy. The competition challenges sixteen university teams to reengineer a 2016 Chevrolet Camaro into a performance hybrid electric vehicle. The competition also challenges teams to develop stereo camera Advanced Driver Assistance Systems (ADAS), and requires that each team completes an Innovation project, with the goal of taking on a risky project that can advance the state of the art in an area of the automotive industry. This paper discusses the development of The Ohio State University’s Innovation project, which was based on an active stereo vision system, which allows each camera to pan and tilt. This paper also analyzes and discusses the ramifications of distance estimation uncertainty caused by camera misalignments and other kinds of error.

Committee:

Giorgio Rizzoni (Advisor); Keith Redmill (Committee Member); Shawn Midlam-Mohler (Committee Member)

Subjects:

Automotive Engineering; Electrical Engineering

Tang, LiOptimal energy management strategy for hybrid electric vehicles with consideration of battery life
Doctor of Philosophy, The Ohio State University, 2017, Mechanical Engineering
The dissertation offers a systematic analysis on the interdependency between fuel economy and battery capacity degradation in hybrid electric vehicles. Optimal control approaches including Dynamic Programming and Pontryagin's Minimum Principle are used to develop energy management strategies, which are able to optimally tradeoff fuel consumption and battery aging. Based on the optimal solutions, a real-time implementable battery-aging-conscious Adaptive Equivalent Consumption Management Strategy is proposed, which is able to achieve performance that is comparable to optimal results. In addition, an optimal control based charging strategy for plug-in hybrid electric vehicles and battery electric vehicles is developed, which minimizes battery capacity degradation incurred during charging by optimizing the charging current profile. Combining a generic control-oriented vehicle cabin thermal model with the battery aging model, the benefit of this strategy in terms of decreasing battery aging is significant, when compared with the existing strategies, such as the widely accepted constant current constant voltage (CC-CV) protocol. Thus this dissertation presents a complete set of optimal control solutions related to xEVs with consideration of battery aging.

Committee:

Giorgio Rizzoni (Advisor)

Subjects:

Automotive Engineering; Engineering; Mechanical Engineering

Keywords:

hybrid electric vehicles, energy management strategy, battery life

Cardinale, Luke AAutomating the Subjective Analysis of Knock during Hot Engine Starts
Master of Science, The Ohio State University, 2016, Mechanical Engineering
The engine start serves a crucial point of interaction with the end user of a vehicle. It is a unique operating condition for a motorist in that there is no requirement to focus on anything outside of the engine starting. This provides the opportunity for the motorist to gauge the state of reliability. A good engine start brings maintains confidence in the vehicle. A short crank, followed by a quiet roar of the exhaust and the motorist can be on their way without concern. Any indicator of unreliability during the start of the engine, however, may influence the motorist’s decision on whether to depart on their journey or to halt and schedule maintenance. Evaluation of engine starts is thus highly subjective in nature. This creates a challenge in the task of calibration. The present investigation focuses on developing a method to translate subjective assessment practices for calibration into measureable objective metrics. Knock during hot engine starts is selected for detailed demonstration of the method, however the method was also applied to additional aspects of hot engine starts. In practice, the subjective requirements for this set of aspects is used to tune a calibration table referenced to mitigate hot engine start knock. A full factorial experiment was performed with respect to the calibration table. The recorded data was evaluated using the scoring method and compared to a manually tuned calibration with satisfactory results.

Committee:

Shawn Midlam-Mohler, Dr. (Advisor); Giorgio Rizzoni, Dr. (Committee Member)

Subjects:

Acoustics; Automotive Engineering; Engineering; Mechanical Engineering

Keywords:

Knock;Engine Knock;Start;Engine Start;Hot Start;Subjective Analysis;Marketability;Subjective;Subjective Mapping;key-on

Dehner, Richard D.An Experimental and Computational Study of Surge in Turbocharger Compression Systems
Doctor of Philosophy, The Ohio State University, 2016, Mechanical Engineering
The objective of the present study is to predict compression system surge instabilities, including discrete sound peaks at low frequencies and their amplitudes at key locations. One-dimensional (1D) gas dynamics models were created for a turbocharger stand and a twin, parallel turbocharged V6 gasoline turbocharged direct injection (GTDI) engine, which have a common turbocharger design. In addition, a three-dimensional (3D) computational fluid dynamics (CFD) model was developed for the compression system of the turbocharger stand, and prediction results are utilized to study the details of compressor flow-field breakdown and the resulting instabilities at reduced flow rates. The turbocharger stand isolated surge from engine airborne pulsations, thereby providing a simplified bench-top environment for in-depth studies of pertinent physics and model development. Two different compression system configurations were studied on the turbocharger stand. The first configuration incorporated a plenum (large volume), which produced surge as the flow rate was reduced. To facilitate surge predictions, a compressor performance map from an extended flow range small volume system (second configuration) was incorporated into a 1D model of the large volume configuration. Mild and deep surge predictions were completed with the 1D model of the large volume turbocharger stand compression system and the dominant sound peaks of simulations agreed reasonably well with the corresponding measurements. Engine experiments and modeling were carried out in two phases, where the first phase was steady-state, full load operation at low engine speeds and the second phase perturbed one of the compressors into surge. The engine model incorporated loss coefficients from flow bench experiments with induction system components, and modified air cleaner box and charge air cooler models that accurately captured the frequency dependent interaction of pressure waves. Steady-state engine data confirmed the accuracy of predicted performance, pressure drops, and wave dynamics in the induction system. Once the models for compressor surge and stable engine operation were independently validated with experimental data from the turbocharger stand and engine dynamometer, respectively, the engine model was then utilized for predictions with the right-bank compressor in both mild and deep surge. The mild surge prediction provided reasonable agreement with experimental data, and the accuracy of predictions improved as the load was increased and the right-bank compressor entered deep surge. Simulations with a 3D CFD model were initially performed during stable operation with a domain that was confined to the compressor with short inlet and outlet duct extensions. Resulting predictions agreed well with measurements from the turbocharger stand, including compressor performance and the onset of temperature rise near the inducer blade tips. Next, the computational domain was expanded to include the (full) large volume turbocharger stand compression system. As the compressor flow rate was reduced below that at the peak pressure ratio, rotating stall cells formed near the shroud-side diffuser wall. A further reduction in flow rate resulted in the system entering mild surge, where two cycles were simulated. Mild surge predictions from this CFD model provided good agreement with compressor inlet and outlet pressure measurements, in terms of reproducing the amplitude and frequency.

Committee:

Ahmet Selamet (Advisor); Jen-Ping Chen (Committee Member); Sandip Mazumder (Committee Member); Junmin Wang (Committee Member); Philip Keller (Committee Member)

Subjects:

Acoustics; Aerospace Engineering; Automotive Engineering; Engineering; Experiments; Fluid Dynamics; Mechanical Engineering; Transportation

Keywords:

turbocharger; automotive; internal combustion engine; engine; centrifugal compressor; compressor; instabilities; surge; rotating stall; one-dimensional model; three-dimensional computational fluid dynamics; 3D CFD

Maley, Evan DSuspension Design and Vehicle Dynamics Model Development of the Venturi Buckeye Bullet 3 Electric Land Speed Vehicle
Master of Science, The Ohio State University, 2015, Mechanical Engineering
For over a dozen years the Buckeye Bullet Electric Land Speed Racing Team has developed electric land speed vehicles that have set numerous national and international land speed records over 300 miles per hour. These vehicles have been powered by various battery chemistries as well as hydrogen fuel cells. The vehicles have been platforms for advanced vehicle research and training for future engineers. Taking such advanced vehicles to tremendous speeds has its difficulties associated with it. There are two related challenges that are covered in this document. The first challenge is the design, analysis and implementation of a custom fully-independent suspension for the Venturi Buckeye Bullet 3 which is targeting to set an international land speed record over 400 miles per hour. Many of the considerations that went into the design and analysis will be presented. The second challenge addressed is the development of a vehicle dynamics model of the land speed vehicle. There is a significant emphasis on the development of the models and obtaining the necessary vehicle parameters required to build a vehicle dynamics model. The model is developed to begin to quantify the vehicle performance, handling and stability. In the end an analysis of the vehicle stability in crosswinds is considered. The results of the work will be used to validate the vehicles performance and identify any areas of improvement.

Committee:

Giorgio Rizzoni, Dr. (Committee Member); Shawn Midlam-Mohler, Dr. (Committee Member)

Subjects:

Automotive Engineering; Mechanical Engineering

Metka, MatthewApplication of Fluidic Oscillator Separation Control to a Square-back Vehicle Model
Master of Science, The Ohio State University, 2015, Mechanical Engineering
Aerodynamic drag is an increasingly important factor in ground vehicle design due to its large impact on overall fuel economy. The average vehicle drag coefficient has improved significantly since the advent of the automobile, however the marginal gains possible with traditional shape optimization are beginning to decrease. There is increased need to improve the drag coefficient as a means of reducing global fossil fuel consumption, which prompts the automotive industry to investigate additional methods of drag mitigation. One method may be the use of active flow control (AFC) aimed at large scale changes in the flowfield through the introduction of energy perturbations at strategic locations on the vehicle surface. In this study, separation control with fluidic oscillators was examined on a modified square-back Ahmed vehicle model to advance the possibility of AFC application to production vehicles. A fluidic oscillator is a simple pneumatic device that converts a steady flow input into a spatially oscillating jet. This AFC actuator was selected due to its proven separation control efficiency and robustness. Studies involving the application of fluidic oscillator separation control to simplified vehicle models have been conducted by other researchers, however the large parameter space related to oscillator effectiveness yields many unanswered questions. The goal of this work was to answer more of the relevant questions needed to bridge the gap between lab and application. The majority of this experimental study was done in a scale wind tunnel facility owned and operated by a North American automaker at a Reynolds number based on model length of 1.4x10^6 or higher. A modified aft section containing boat-tail flaps and fluidic oscillators was added to the square-back Ahmed model and various parameter sensitivity trends were examined. Parameters of interest included flap angle, oscillator jet location, jet velocity, jet spacing, jet size, moving ground plane simulation, ride height, speeds changes, underbody turbulence, actuation symmetry, and model geometric scaling. Studies related to fluidic oscillator acoustics, separation control mechanism, and energy consumption were also conducted to build practical implementation knowledge. The results indicated that drag reduction was sensitive to many of the examined parameters. The character of the underbody flow and the use of symmetric actuation were shown to be of critical importance for optimal drag reduction, however exploitation of underbody flow modification may lend the most efficient use of actuator energy. Parameters such as Re (test speed), ride height, and simulated ground plane weakly affected the drag coefficient changes experienced with actuation. A model scaling study indicated that the actuator momentum requirements for a given drag reduction decreased as the model size was increased, partially because the number of oscillators required scales with base perimeter. A notional energy analysis suggested that the actuator energy consumption relative to drag reduction estimate on a full scale vehicle are within reason. The trends and sensitivity information gathered over the course of this study prompt further investigation into this flow control method.

Committee:

James Gregory, Dr. (Advisor); Jeffrey Bons, Dr. (Committee Member)

Subjects:

Aerospace Engineering; Automotive Engineering; Mechanical Engineering

Keywords:

separation control; aerodynamics; drag reduction; bluff body; Ahmed model; fluidic oscillator; bluff body wake; active flow control;

Mukherjee, TamalOne Dimensional Air System Modeling of Advanced Technology Compressed Natural Gas Engines.
Master of Science, The Ohio State University, 2014, Mechanical Engineering
With oil prices always being on the rise and CNG emerging as a cheaper and cleaner alternative. This study was carried out to observe the performance characteristics of a 2012 Honda Civic CNG engine (only dedicated OEM passenger vehicle for CNG in USA). With CNG having lower CO2 emissions, higher octane number and being roughly half the price compared to gasoline, it is truly important to develop this emerging CNG market. In this thesis a 1&#x2013;D engine modeling software, GT-Power, was used to model a 2012 Honda Civic CNG engine. Experimental data of that particular engine running on liquid fuel E-85 was available through the EcoCAR 2 competition team&#x2019;s engine data. The 1-D model was calibrated and validated for accurate predictions of mass air flow (MAF) with E-85 as a baseline and then validated for CNG engine data, which was available from chassis dyno runs of the vehicle under study. Actual turbocharger maps for compressors and turbines were used during the matching procedure in order to select the best fit for the engine from a range of available products. The baseline model developed was modified to easily account for different engine configurations and the quantities of volumetric efficiency, air per cylinder manifold pressure and mass air flow were observed for comparison between different configurations and checking the accuracy of the model wherever experimental data was available. It was seen that the results obtained followed proper physical trends with the boosted direct injection engine showing the maximum air per cylinder, which directly relates to brake torque. The naturally aspirated cases also predicted proper results with the volumetric efficiency of the direct injection being more than the regular port fuel injection for CNG fuel and lesser than the volumetric efficiency of the liquid fueled E-85 engine. A complete exercise of experimentally characterizing the engine of the vehicle was also carried out to provide with the experimental data from a chassis dyno test. The experimental characterization is not covered in this study but will be published as a separate graduate thesis.

Committee:

Shawn Midlam-Mohler (Advisor); Giorgio Rizzoni (Committee Member); Fabio Chiara (Committee Member)

Subjects:

Automotive Engineering; Mechanical Engineering

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