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Islas Munoz, JuanAutomotive design aesthetics: Harmony and its influence in semantic perception
MDES, University of Cincinnati, 2013, Design, Architecture, Art and Planning: Design
Aesthetics play a crucial role in a consumer's purchase decision of a vehicle. While creating aesthetically pleasing vehicle designs is already challenging for automakers, it is even more challenging to do so while constantly being in the cutting edge of design, generating new and fresh aesthetics that allow them to differentiate themselves from other companies and stand out. All those iterations seeking new aesthetics make designers take risks, generating sophisticated and provocative designs that challenge conventional aesthetic features. In addition, design modifications to accommodate manufacturing criteria can potentially disrupt the original design concept. This can result in a controversial design, communicating negative semantic messages to the consumer. This thesis proposes the use of harmony (where the visual unified whole, in which the sensation that every aesthetic feature belongs together is created) as a crucial variable for generating positive semantic messages. A survey was conducted using vehicle images with different levels of harmony and complexity. These images were rated in a positive-negative semantic scale based on concepts related to a design's communication of quality (price, build quality, and design execution), and performance (safety, driveability, driving performance). Results show the importance of creating and preserving harmonious car designs so that the transmission of positive semantics is achieved, which can contribute to a vehicle's commercial success.

Committee:

Peter Chamberlain, M.F.A. (Committee Chair); Raphael Zammit (Committee Member)

Subjects:

Design

Keywords:

automotive design;automotive aesthetics;automotive semantics;automotive design harmony;automotive design complexity;automotive aesthetics harmony complexity;

Gurusubramanian, SabarishA comprehensive process for Automotive Model-Based Control
Master of Science, The Ohio State University, 2013, Mechanical Engineering
The global automotive industry continually strives to develop advanced automotive control systems that can reduce fuel consumption and emissions towards a greener future, while improving efficiencies and enhancing safety and comfort.This effort is collaborative, with not just OEMs and their suppliers working amidst stiff competition and strict regulations, but various research organizations, both independent as well as academic collaborating with these OEMs. As a result of this collaborative effort, there is a huge potential for synergy, but also the possibility of huge disconnects in the process itself. Model-Based System Development methodologies that use simulation models representing the controlled and controlling systems have a very important role to play in today's scenario when developing control systems. For a research organization with strong academic background such as the Center for Automotive Research at The Ohio State University, a comprehensive process for automotive model-based control that encapsulates various practice and standards already in place in the industry can help develop better solutions when collaborating with industry. While systematic and detailed approaches exist already, there are sufficient variations amongst internal approaches and methodologies which calls for a more unified approach that is industry-inspired. This thesis presents a comprehensive process that helps a developer gain an overall perspective to the bigger problem. The proposed methodology starts right at the fundamental opportunity identification phase, and is driven in the early stages by product development methodologies. Systematic approaches towards identifying opportunities, generating concepts and selecting concepts, with a case-study based on the usage of model-based simulations tools to select concepts are presented. With constantly changing requirements in the automotive industry, the need for traceability to the initial requirements has been highlighted. To serve as an example throughout this thesis, a specific engineering problem aimed at optimizing the electrical system is chosen from an ongoing project on fuel economy improvement with Chrysler LLC. The objective of improving fuel economy by optimizing the usage of the alternator, and making better use of the existing vehicle battery to meet electrical load demands in the vehicle is achieved by means of an Adaptive Equivalent consumption Minimization Strategy (A-ECMS) based controller.The A-ECMS controller thus designed is implemented on a vehicle test-setup using Rapid Control Prototyping (RCP) tools. Verification and Validation techniques that ensure that the system is built to specifications and meets requirements identified are presented in detail with the same example.Finally, future recommendations are made on implementation and testing as well as other model-based tools and approaches that can be considered. An overall process that gives a developer the bigger picture that encompasses the control system development process has been attempted in this thesis, drawing inspiration from various product development methodologies as well as industry-standard practices. Staying updated with relevant standards and methodologies can promote better industry collaborations and provide greater learning, and this thesis aims to support that with the proposed methodology for automotive model-based control.

Committee:

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

Subjects:

Automotive Engineering

Keywords:

Automotive Model-Based Control, Rapid Control Prototyping, MiL, SiL, HiL, Alternator Control, Controls Implementation, Automotive software Verification and Validation

Duan, ChengwuDynamic analysis of dry friction path in a torsional system
Doctor of Philosophy, The Ohio State University, 2004, Mechanical Engineering
Traditionally, dry friction non-linear elements have been treated as vibration dampers, in parallel with elastic elements. However, in some practical systems (including automotive drivelines) the dry friction element (with high saturation torque) exists by itself and it functions as a key power transmission path for both mean and dynamic loads. First, to address such path issues, we examine multi-degree of freedom torsional systems with time-invariant normal load. A procedure to predict pure stick to stick-slip boundaries, based on a linear system theory, is developed when the torsional system is excited by harmonic excitation. For non-linear studies, both discontinuous and smoothened friction formulations are examined. The effects of a secondary inertia are analytically and numerically investigated. Results show that the secondary mass significantly affects the quasi-discontinuous nature of the system response. Next, in order to fully understand the non-linear frequency characteristics generated by stick-slip vibration, a new analytical method is developed based on assumed torque and velocity profiles. Super-harmonics are efficiently calculated and effect of the mean torque is qualitatively identified. Further, a refined multi-term harmonic balance proposed and associated computational issues are addressed. Studies show that the mean load significantly affects the response as it could induce asymmetric stick-slip motions. Second, the effect of time varying actuation pressure (or the normal load) on the dry friction element on transient and steady state responses has been studied. Analytical solution for pure slip motion is obtained based on an approximate linear system model. Effects of time-varying parameters, such as phase, frequency and amplitude of the actuation pressure are observed over several frequency regimes. The negative friction slope is found to be the major cause of judder-induced phenomena such as bifurcations and quasi-periodic or chaotic responses. Some instabilities such as abrupt jumps in the amplitude-frequency maps of relative velocity are also seen around the super-harmonic peak frequencies.

Committee:

Rajendra Singh (Advisor)

Subjects:

Engineering, Mechanical

Keywords:

Dry Friction Path; Torsional System; Non-linear Vibration; Automotive Drivetrain

Sharma, Balaji R.Feasibility of use of four-post road simulators for automotive modal applications
MS, University of Cincinnati, 2010, Engineering : Mechanical Engineering
Modal analysis is a critical part of the automotive development process. Identification of the vehicle's modal signature, especially in the low-frequency end of the spectrum, is essential for tuning the dynamic performance of the vehicle structure for optimal ride and handling comfort. Traditional methods to characterize the system - in terms of its natural frequencies, associated damping values and mode shapes - have typically employed conventional impact and shaker tests. While these tests are able to accurately study the modal behavior of the vehicle under static conditions, they are not truly reflective of the real-world operating conditions of the vehicle A four-post road simulator is used in automotive development to simulate on-road conditions in the laboratory primarily for durability, transmissibility, noise and vibration studies, etc. Some of these studies often involve a similar setup of response sensors across the automotive structure as conventional modal tests. Utilization of the road-simulator for modal analysis can potentially reduce the duration of the automotive development cycle in the testing phase, allowing for a faster time-to-market, in addition to improved accuracy of estimation of the vehicle's dynamic performance under simulated operating conditions. This thesis work explores the feasibility of using a four-post road simulator for experimental modal analysis (EMA) of automotive structures. The MTS 320 Road Simulator in the Structural Dynamics Research Laboratory, University of Cincinnati, is employed for the study, with a truck frame being the test structure. Frequency response functions (FRFs) are estimated with displacement and pressure measurements at the hydraulic excitation posts of the simulator, provided by transducers built into the four-poster, replacing force measurements as inputs. The applicability of these non-conventional FRF formulations for modal parameter identification using existing parameter estimation algorithms is studied. Additionally, response-only data based on random excitations from the simulator is processed under the framework of Operational Modal Analysis (OMA) for parameter estimation. Modal estimates from these tests are compared with one another and with those from conventional EMA-based impact tests, and a summary of results is presented based on the findings therein. The thesis begins with a general overview of the automotive testing process, and the role of experimental modal analysis and the four-post road simulator therein. Thesis objectives are presented in terms of utilizing the four-post road simulator for estimation of the modal parameters of automotive structures in the absence of force measurements, and the motivation for the same is discussed. Fundamental principles of experimental and operational modal analysis are presented further, in addition to the theory behind the use of non-force measurements in the measurement of modified FRFs and consequently the estimation of modal parameters. The document then proceeds to describe the experimental setup and the various tests conducted as a part of the study, with a summary of results from each test. A detailed discussion follows on the comparison of results between the tests, and an overall summary of results is presented. Conclusions from this research work are presented along with recommendations for future work in this area.

Committee:

Randall Allemang, PhD (Committee Chair); Allyn Phillips, PhD (Committee Member); David Brown, PhD (Committee Member)

Subjects:

Mechanical Engineering

Keywords:

Experimental Modal Analysis;Operational Modal Analysis;Automotive Testing;Four-post road simulators

Yacinthe, SamuelSystem Safety Development of a Performance PHEV Through a Model-Based Systems Engineering Approach
Master of Science, The Ohio State University, 2016, Mechanical Engineering
The Ohio State University is participating in EcoCAR 3, which is a four-year long competition amongst 16 North American university teams to redesign the 2016 Chevrolet Camaro to reduce its environmental impact, while maintaining the muscle and performance expected from the iconic American car. To effectively assess and increase overall product quality and readiness of Ohio State’s vehicle, this work defines and deploys a state of the art Model-Based Systems Engineering (MBSE) approach for managing engineering complexity as it relates to requirements management, traceability, and fulfillment. To demonstrate the effectiveness of the implemented approach, this work presents system safety development activities that have been conducted during the first two years of the competition. As EcoCAR 3 transitions into year-three, this work has already contributed to over a dozen awards by increasing overall documentation, traceability and workflow management as part of the overall engineering development process.

Committee:

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

Subjects:

Automotive Engineering; Mechanical Engineering

Keywords:

Model-Based Systems Engineering, Automotive, Mechanical Engineering

Ward, Jason JModeling and Simulating a Performance Hybrid Electric Vehicle
Master of Science, The Ohio State University, 2015, Mechanical Engineering
As part of EcoCAR 3, an Advanced Vehicle Technology Competition, The Ohio State University is among sixteen teams challenged with the task of re-engineering a stock 2016 Chevrolet Camaro into a hybrid electric vehicle. Part of the Ohio State design process entails using model based design to develop a full vehicle model of the hybrid Camaro that can simulate energy consumption for various testing purposes. This thesis describes the design process behind developing the plant and control models, integrating everything together in a full vehicle model, performing fault insertion testing for mitigation development, and constructing the model architecture such that transfer between In-the-Loop platforms is easier than conventional methods. The full vehicle model developed will be refined and used by the Ohio State team throughout the four year EcoCAR 3 competition.

Committee:

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

Subjects:

Automotive Engineering

Keywords:

EcoCAR; hybrid; modeling; simulation; controls; vehicle; automotive; plant; models

Yu, HaiThe adaptive seeking control strategy and applications in automotive control technology
Doctor of Philosophy, The Ohio State University, 2006, Electrical Engineering
In this dissertation, the adaptive seeking control strategy for nonlinear systems is investigated to solve control problems like online optimization and system stabilization. The adaptive seeking control strategy developed includes the gradient-seeking control method and the adaptive seeking sliding mode control method. The gradient-seeking control algorithm is designed to solve online convex optimization problems in which it adaptively locates and tracks a priori unknown optimal set-point that extremizes/optimizes the value of a nonlinear performance index function. The gradient-seeking control is applicable to systems that involve a continuous and convex nonlinearity. The proposed gradient-seeking strategy is consistently simple in structure. It is also robust to unknown disturbances and modeling uncertainties while adaptively locating and tracking an optimal set-point online. Based on the same concept of gradient-seeking control strategy, a new sliding mode control method, namely adaptive seeking sliding mode control, is proposed in this dissertation to solve system stabilization problems for a class of nonlinear systems. While reserving the properties of the sliding mode control, like insensitivity to parameter variations and complete rejection of disturbances, the adaptive seeking sliding mode control offers a promising robust sliding mode control solution for real-life engineering applications with continuous control input. The proposed sliding mode control method applies a floating feedback control gain and it helps to relieve the chattering problem accompanying some sliding mode control systems in the presence of parasitic dynamics and continuous disturbances. This method is especially promising for control systems with limited actuation capabilities and bandwidth. The dissertation concludes with a summary of the current work and a discussion on possible extensions of the proposed control strategy in future work.

Committee:

Umit Ozguner (Advisor)

Keywords:

Adaptive control; gradient seeking; sliding mode control; automotive control

Kumar, Sri Adarsh A.Cloud Computing based Velocity Profile Generation for Minimum Fuel Consumption
Master of Science, The Ohio State University, 2012, Electrical and Computer Engineering

Vehicle fuel management problem is a promising field of research in light of the recently proposed CAFE standards. Previous works in this field mostly cater to Hybrid Electric vehicles or Plug-in Hybrid Electric Vehicles that compose only a minority of total vehicles on road. Our research is aimed at effective fuel management strategies that can be applied to everyday conventional vehicles using the hardware already on-board the vehicles. The minimal need for additional hardware, transferability to other vehicles and effective optimization techniques would be the main achievement of this research.

Vehicle velocity profile is optimized using dynamic programming to consume minimal fuel. The backwards model of the vehicle is constructed to calculate of fuel consumption of velocity profiles. Using the fuel consumption as a cost, spatial domain dynamic programming method is used to calculate the optimal velocity profile to minimize fuel consumption. A novel method of dynamic programming is proposed to achieve highly accurate results with reduced run-time. A majority of this thesis is dedicated to constructing driving scenarios that test the performance of the dynamic programming. These scenarios increase the complexity of optimization, gradually from a mere simulation to fully integrated stand-alone processing module to optimize off-site vehicles through wireless communication.

Committee:

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

Subjects:

Automotive Engineering; Electrical Engineering; Engineering

Keywords:

automotive control; optimization; dynamic programming; control; energy management; fuel;

Merical, Kyle IModel-Based Control Development for an Advanced Thermal Management System for Automotive Powertrains
Master of Science, The Ohio State University, 2013, Mechanical Engineering
Rising fuel prices and tightening vehicle emission regulations have led to a large demand for fuel efficient passenger vehicles. Among several design improvements and technical solutions, advanced Thermal Management Systems (TMS) have been recently developed to more efficiently manage the thermal loads produced by internal combustion engines and thereby reduce fuel consumption. Advanced TMS include complex networks of coolant, oil and transmission fluid lines, heat exchangers, recuperators, variable speed pumps and fans, as well as active fluid flow control devices that allows for a greatly improved freedom to manage the heat rejection and thermal management of the engine and transmission components. This control authority can be exploited, for instance, to rapidly warm the powertrain fluids during vehicle cold-starts, and then maintain them at elevated temperatures. Increasing the temperatures of the engine oil and transmission fluid decreases their viscosity, ultimately leading to a reduction of the engine and transmission frictional losses, and improved fuel economy. On the other hand, robust and accurate TMS controllers must be developed in order to take full advantage of the additional degrees of freedom provided by the available actuators and system hardware configuration. To this extent, this work focuses on developing model-based TMS controls for a prototype light-duty automotive powertrain during fully warmed-up vehicle operation. The design of the models and control algorithms is conducted in parallel with the development of a prototype TMS, hence realizing a co-design of the TMS hardware and control system. In order to achieve this goal, first-principle models are created to characterize the thermal dynamics of the TMS components, and calibrated on specific components' data. The submodels are then integrated into a complete TMS model predicting the temperature dynamics of the powertrain fluids in response to commands to the available system actuators as well as operating and boundary conditions. The developed model is then used as a tool for model-based system analysis, optimization and control design. Specifically, a proof-of-concept control design is conducted to verify the feasibility of the TMS in maintaining the temperatures of the powertrain fluids within the recommended range. In particular, a model-based optimization is conducted to define the open-loop actuator positions for various engine operating conditions that maintain the coolant temperature at the desired set-points. The open-loop strategy is then combined with a feedback control loop that combines rule-based and PI controllers to regulate the actuator position based on coolant temperature tracking error, compensating for disturbances and modeling errors. The prototype TMS controller developed in this work is shown to be effective in reducing the fluctuations in the coolant temperatures during the FTP driving cycle, compared to a baseline rule-based controller. Based on the preliminary results obtained, indications on the design of a state-space multi-variable feedback controller are made. This will further reduce the coolant temperature tracking error and allow all TMS actuators to work together in unison.

Committee:

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

Subjects:

Automotive Engineering

Keywords:

thermal management systems; thermal system control; automotive thermal management; thermal system modeling

Gershenzon, MichaelGovernment Intervention in the 2008-2009 U.S. Automotive Crisis: Laissez-Faire Economics Abandoned
Bachelor of Science in Business, Miami University, 2010, School of Business Administration - Finance
As most are aware, 2008 and 2009 were defined by economic turmoil and uncertainty. The automotive industry was not immune to the panic, arguably feeling the wrath of the chaos more than any other industries. Believing the recession would persist lacking the health of the automotive sector, many experts turned to the U.S. government for a safety net. The government responded with two main tools in an effort to staunch the hemorrhaging of the auto industry: governmental loans (“bailouts” as they have come to be called) and an automotive sector specific policy, the Cash Allowance Rebate System (CARS), colloquially known as Cash for Clunkers. In this thesis, I analyze the government's decisions and test stock market sentiment of each pertinent intervention. Contrary to Adam Smith's revolutionary work with laissez-faire economics, I find that the market overwhelmingly supports government aid. The thesis centers around explaining these implications.

Committee:

Thomas Boulton (Advisor); David Shull (Committee Member); Terry Nixon (Committee Member)

Subjects:

Business Community

Keywords:

Automotive; Abnormal Returns; Government Intervention

Roychowdhury, SayakData-Driven Policies for Manufacturing Systems and Cyber Vulnerability Maintenance
Doctor of Philosophy, The Ohio State University, 2017, Industrial and Systems Engineering
This research explores deterministic and stochastic policies to help organizations make data-driven optimal decisions. The two major application areas identified in this research are manufacturing and cyber security. In a recent report published by McKinsey Analytics, the manufacturing industry uses only 20%-30% of the potential of data analytics. This suggests that there are still plenty of opportunities to use analytics in manufacturing processes. In the first part of my research, I formulate an Integer Programming model for the “stamping” process in automotive manufacturing. I develop a production scheduling method for automotive stamping to maintain optimal inventory positions. In stamping, different types of parts are scheduled for processing in the press, which requires different die-sets to be mounted on the press. This has all the elements of conventional scheduling problems with tardiness objectives and setup costs. Yet, it also has capacity constraints and part production constraints. We show that these constraints make solution with branch and bound difficult for problem sizes of interest. In this research, I use the structure of the scheduling problem and implemented heuristic methods like Genetic Algorithm alongside Earliest Due-date (EDD) rules to prioritize production of parts with low inventory as well as minimize the number of die-set changeovers. I call this new method Genetic Algorithm with Generalized Earliest Due-date (GAGEDD). I illustrate the computational advantages compared with alternatives and show its benefits using data from a real life automotive stamping press scheduling problem to build a decision support tool for the schedulers. The second part of this research is motivated towards improving cyber vulnerability maintenance policies under uncertainty. A conservative estimate by McAfee in 2014 puts annual cost of cybercrime at US$375B. This is an important contemporary issue where role of data analytics and optimization have a lot to offer. Here I implement stochastic optimization procedures for cybersecurity applications, where learning is incorporated to account for future rewards. First, I formulate a Partially Observable Markov Decision Process (POMDP) model to derive policies for cases when the state of compromise of a host is uncertain. This method assumes there is no parametric uncertainty. Next, I implement Bayes Adaptive Markov Decision Process model (BAMDP) on a dataset obtained from the cyber logs of an organization using finite numbers of model scenarios. Earlier BAMDP formulations use infinite model scenarios. I also describe the benefits of using finite scenarios including the ability to solve the problem optimally as a POMDP. The resulting BAMDP formulation accounts for the parametric uncertainty caused by the lack of data for certain events. I use a point based value iteration method known as PERSEUS to solve both of these problems to generate a-vectors, that can be used to design optimal policies based on the belief-state of the system. Another benefit of using finite numbers of model scenarios relates to decision making for multiple identical systems, e.g., a “fleet” of identical Linux computer hosts. The issue of identical systems in machine learning has apparently received little attention despite the widespread relevance in data analytics. I propose a method for solving multiple identical system policy problems. The proposed method is based on a relatively large POMDP formulation with methods to compute the relevant transition, expected reward, and observation methods being provided. Then, I explore additional advantages of finite model scenario BAMDPs relating to the ability to incorporate reward-based or other learning in intuitive ways. Also, the speed of learning and the concept of “fast learning” and average learning time are proposed and explored computationally. In concluding, I offer suggestions about how this research can be extended to build more powerful models with faster learning capabilities to help decision makers.

Committee:

Theodore T. Allen, PhD (Advisor); Cathy H. Xia, PhD (Committee Member); Gagan Agrawal, PhD (Committee Member)

Subjects:

Industrial Engineering; Operations Research

Keywords:

Operations Research; Scheduling ; Automotive Manufacturing; Stamping; Genetic Algorithm ; Partially Observable Markov Decision Process ; Bayesian Adaptive Markov Decision Process; Cyber security; Cyber vulnerability maintenance;

Spiegel, Andrew WilliamA Soft ECU Approach to Develop a Powertrain Control Strategy
Master of Science, The Ohio State University, 2015, Mechanical Engineering
Automotive control systems are becoming increasingly complex as consumers and government regulations demand vehicles with better fuel economy, reduced emissions, improved safety, and increased functionality while maintaining performance. The short development time frames of embedded control software in automotive Electronic Control Units (ECUs) has put additional attention on methods for rapid control development. Model-based control design is used widely in the automotive industry for the development of embedded control systems for attributes such as reducing development times, lowering cost, and preventing revisions while ensuring quality of complex control systems [1]. The Ohio State University’s Center for Automotive Research (CAR) is working on a research project to develop a novel powertrain control strategy using model-based design techniques. To develop the new control strategy, the Ohio State University (OSU) needed a simplified version of a target vehicle’s state-of-the-art powertrain control strategy. Because OSU is under time constraints to develop and demonstrate the control strategy, a soft ECU model representing the target vehicle’s powertrain control strategy was developed. The soft ECU model will help speed the development process of the novel powertrain control strategy by serving as a benchmark and starting point for control design. This thesis describes the approach of developing, verifying, and utilizing a soft ECU model in the development process of the novel powertrain control strategy. The soft ECU model was developed in Simulink using model-based control techniques. The soft ECU model, a driver model, and a vehicle plant model were combined to create a complete vehicle model. The complete vehicle model was verified through Model-In-the-Loop simulations. The accuracy of the components in the complete vehicle model were compared with their respective isolated system accuracies. The complete vehicle model’s components show good accuracy to their corresponding drive cycle data collected from the target vehicle. The soft ECU model is an accurate benchmark of the target vehicle’s powertrain control strategy. Further modifications can be made to the soft ECU model and driver model to improve the overall accuracy of the complete vehicle model. The soft ECU model will be used as a starting point for the design of the new powertrain control strategy.

Committee:

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

Subjects:

Automotive Engineering

Keywords:

Automotive Model-Based Control Design, Soft ECU Models, MIL Techniques

Wei, XiModeling and control of a hybrid electric drivetrain for optimum fuel economy, performance and driveability
Doctor of Philosophy, The Ohio State University, 2004, Mechanical Engineering
Automotive manufacturers have been striving for decades to produce vehicles which satisfy customers’ requirements at minimum cost. Many of their concerns are on fuel economy, road performance and driveability. A hybrid electric vehicle (HEV) is one of the most promising alternatives to a conventional engine-powered vehicle which satisfies the above requirements. Investigations indicate that how to allocate the total tractive force between the engine and the electric machine has significant influences on vehicle fuel economy, performance and driveability. Therefore, designing an optimal control strategy which considers all three criteria is of great interest. Model based control design requires control oriented models and the complexity of these models are determined by their applications. Since the control strategy is developed in two steps (finding the solution for the best fuel economy and performance first and then taking driveability into consideration), two models, i.e., the quasi-static model and the low-frequency dynamic model are built for each step in the control design. Defining objective metrics for vehicle fuel economy, performance and driveability is also very important. Evaluations in both simulations and real vehicles require objective and quantitative metrics. Vehicle fuel economy is estimated under various driving cycles. Performance criteria consist of acceleration performance, gradeability and towing capability. Driveability measures deal with pedal responsiveness, operating smoothness and driving comfort, which include interior noise level, jerk, tip-in/tip-out response, MTVV, acceleration RMS and VDV. The optimal control solution is then found hierarchically with the help of Pontryagin’s minimum principle. Fuel economy optimization contains three steps: finding the optimal solution for known constant power requests, for known time-varying power requests and for unknown time-varying power requests with short-term predictions. An innovative interpretation of the minimum principle is applied when minimizing fuel consumption for the vehicle with constant battery parameters and fixed CVT ratio under constant power requests. This so-called sliding optimal control which switches between two control values has been theoretically proven to be the optimal solution. The control strategy developed with the minimum principle is compared with a simple heuristic one and simulation results demonstrate an improvement on vehicle fuel economy.

Committee:

Giorgio Rizzoni (Advisor)

Subjects:

Engineering, Mechanical

Keywords:

system dynamics; modeling and control of automotive powertrains; hybrid electric vehicles; driveability objective metrics

Komarabathuni, Ravi V.Performance Assessment of a 77 GHz Automotive Radar for Various Obstacle Avoidance Application
Master of Science (MS), Ohio University, 2011, Electrical Engineering (Engineering and Technology)

Human safety is one of the highest priorities in the automotive industry. The demands made for reliable safety systems have been increasing tremendously in the past decade. The radar sensors used for safety systems should be capable of detecting not only automobiles but also motorcycles, bicycles, pedestrians, roadside objects and any other obstacles the vehicle may come in contact with.

This thesis investigates several performance aspects and test procedures for a 77 GHz long range radar sensor with different test target objects. This assessment helps to investigate the potential to use these radar sensors for obstacle detection and/or avoidance for smaller objects like bicycles, humans, traffic barrels, 4” poles, metal sheets, and also for bigger objects like vans, motorcycles, aircraft, etc. For these purposes, different test cases were developed to evaluate the performance. The different test cases used to test a 77 GHz radar sensor includes: finding maximum range, range accuracy, finding maximum field of view, detection (& separation) of two target objects (similar & different) at different radial distances, and maximum range for detecting an aircraft. Observations were made with the radar sensor mounted on a moving cart and the measurements were logged. The results from these tests will provide insight into analyzing the possibilities and limitations of these radar sensors for different applications.

The tests were successfully conducted on a flat, open field at Ohio University Airport, Albany, OH.

Committee:

Chris Bartone, PhD, P.E. (Advisor); Jeffrey Dill, PhD (Committee Member); Bryan Riley, PhD, PMP (Committee Member); William Kaufman, PhD (Committee Member)

Subjects:

Automotive Engineering; Electrical Engineering

Keywords:

Long Range Radar (LRR); Adaptive Cruise Control (ACC); 77 GHz Radar Sensor; Obstacle Detection and/or Avoidance Application;Target Object Detection by Radar Sensor; Safety in Automotive Industry

Lydick, Cheryl L.Development of a database system concept for obtaining specification approval for a new plastics product in the automotive market place
Master of Science (MS), Ohio University, 1990, Industrial and Manufacturing Systems Engineering (Engineering)
Development of a database system concept for obtaining specification approval for a new plastics product in the automotive market place

Committee:

E. Sims, Jr. (Advisor)

Subjects:

Engineering, Industrial

Keywords:

Development; Database System Concept; Obtaining Specification Approval; Plastics Product; Automotive Market Place

Farfan-Ramos, LuisReal-time Fault Diagnosis of Automotive Electrical Power Generation and Storage System
Master of Science in Engineering (MSEgr), Wright State University, 2011, Electrical Engineering
Automobiles depend more and more on electric power. Analysis of warranty data by automotive OEMs shows that faults in the automotive electrical power generation and storage (EPGS) system are often misdiagnosed. Therefore, monitoring of the state of health (SOH) of the automotive EPGS system is vital for early and correct diagnosis of faults in it, ensuring a reliable supply of electric power to the vehicle and reducing maintenance costs. In this research project, a model-based SOH monitoring method for the EPGS system is developed without the requirement of an alternator current sensor. A model representing the dynamic relationship between the battery current and the alternator filed duty voltage cycle is presented. An important model parameter that characterizes the current generation efficiency of the alternator system is adaptively estimated by using a recursive least square algorithm. Based on fault modes and effect analysis, a model-based fault detection and isolation decision scheme is developed for the EPGS system faults under consideration. The SOH monitoring method has been implemented using an EPGS system experimental test bench at GM R and D Center. Real-time evaluation results have shown its effectiveness and robustness.

Committee:

Xiaodong Zhang, PhD (Committee Chair); Kefu Xue, PhD (Committee Co-Chair); Kuldip Rattan, PhD (Committee Member); Marian Kazimierczuk, PhD (Committee Member); Andrew Hsu, PhD (Other)

Subjects:

Automotive Engineering; Electrical Engineering; Energy; Engineering; Technology

Keywords:

automotive; vehicular; electric; power; generation; storage; EPGS; real time; state of health; SOH; diagnosis; prognosis; fault; detection; isolation; model; parameter estimation; alternator; battery; belt

Couch, Jeremy RobertAn ECMS-Based Controller for the Electrical System of a Passenger Vehicle
Master of Science, The Ohio State University, 2013, Mechanical Engineering
A primary concern for automotive manufacturers is increasing the fuel economy of their vehicles. One way to accomplish this is by reducing the losses associated with operating the ancillary loads such as the loads of the vehicle’s electrical system. In the electrical system of a vehicle, the alternator provides current to the electrical loads. The difference between the load current demand and the current provided by the alternator is either accepted or supplied by the battery. Therefore, the current demand of the electrical loads can be met by the alternator, the battery or a combination thereof. While improving the efficiency of the actual components of the electrical system (alternator, battery and electrical loads) is beneficial, additional gains can be realized with a smart control strategy for the alternator. Conventional alternator control strategies make little use of the battery; the power demand from the electrical loads is almost solely met by the alternator. However, since the alternator is directly connected to the engine, this results in increased fuel consumption, particularly at idle speed conditions. To this extent, more advanced control strategies could be implemented to make use of the battery energy buffer to limit the use of the alternator at low engine efficiency conditions. The focus of this thesis is the design of an advanced alternator control strategy. First, a model of a vehicle’s electrical system is developed with control design in mind. The system is modeled starting from a lumped-parameter, energy-based characterization of the battery and alternator. This is followed by a thorough calibration using experimental data and, finally, validation on a vehicle chassis dynamometer considering a standard (production) alternator control strategy. Next, a novel alternator control algorithm is designed by applying the Equivalent Consumption Minimization Strategy (ECMS), a well known energy management approach often used to control the powertrain of hybrid electric vehicles. This strategy works by determining the optimal alternator current to minimize the instantaneous fuel consumption while complying with input and state of charge constraints. The ECMS algorithm was extensively calibrated for a variety of drive cycles and load current profiles. This proposed control strategy was then compared in simulation to the production alternator controller and fuel consumption reductions of up to 2.18% have been shown. An adaptive ECMS (A-ECMS) is then defined, using feedback from the battery’s state of charge to dynamically tune the ECMS calibration parameter in real-time. Simulation results for the A-ECMS show fuel savings compared to the baseline alternator control strategy that are on the same order of magnitude as the ECMS. Furthermore, a robustness study verifies the A-ECMS is insensitive to model inaccuracies, poor tuning of the parameters and variations in the load current profile.

Committee:

Marcello Canova (Advisor); Lisa Fiorentini (Committee Member); Giorgio Rizzoni (Committee Member)

Subjects:

Automotive Engineering; Mechanical Engineering

Keywords:

automotive; energy management; vehicle electrical system; control oriented model; adaptive ECMS

Gunduz, AydinMulti-Dimensional Stiffness Characteristics of Double Row Angular Contact Ball Bearings and Their Role in Influencing Vibration Modes
Doctor of Philosophy, The Ohio State University, 2012, Mechanical Engineering

A new analytical stiffness model for the double row angular contact ball bearings is proposed since the current methods do not provide stiffness matrix formulations for double row bearings except for self-aligning (spherical) bearings in which angular deflections and tilting moments are negligible. The moment stiffness terms and the cross-coupling stiffness elements in double row angular contact ball bearings are significant; and the stiffness coefficients are highly dependent on the configuration of the rolling elements. Also, unlike roller-type bearings, the contact angle of ball-type bearings depends on the static load(s). The five-dimensional bearing stiffness matrix is first developed for three configurations (face-to-face, back-to-back, and tandem) from basic principles. The diagonal and off-diagonal (cross-coupling) elements of the matrix are calculated from the explicit expressions given the mean bearing load or displacement vector. Modeling approaches between a double row bearing vs. two single row bearings are also analyzed from statics and stiffness perspective. The proposed stiffness matrix is valid for duplex (or paired) bearings assuming all structural elements (such as the shaft and bearing rings) are sufficiently rigid.

Next, a new modal experiment consisting of a vehicle wheel bearing assembly with a double row angular contact ball bearing in a back-to-back arrangement is designed. The bearing is subjected to axial or radial preloads in a controlled manner. Modal experiments with two preloading mechanisms (under non-roatating conditions) show that the nature and extent of bearing preloads considerably affect the natural frequencies and resonant amplitudes, thus influencing the vibration behavior of the shaft-bearing assembly. A five-degree-of freedom vibration model of the shaft-bearing assembly (including the proposed bearing stiffness matrix) is developed to describe the modal experiment. Two alternate (preload-dependent and preload-independent) viscous damping models are then proposed to describe the effect of bearing preload on the resonant amplitudes, similar to those observed experimentally. The proposed bearing stiffness model is then validated by comparing predicted natural frequencies and accelerance spectra with modal measurements.

Finally, four calculation methods are comparatively evaluated by critically examining bearing loads, deflections and stiffness elements; predicted modal properties of the shaft-bearing assembly using each method are also compared with measurements. In particular, the diagonal elements of the proposed stiffness matrix are compared with a commercial code; and, the effects of critical geometric and kinematic parameters on the stiffness coefficients are explored. A finite element based contact mechanics tool is employed to verify certain assumptions of the new matrix formulation. Preliminary modal experiments with a faulty bearing are included to motivate further research.

Committee:

Rajendra Singh, PhD (Advisor); Marcelo Dapino, PhD (Committee Member); Ahmet Kahraman, PhD (Committee Member); Ahmet Selamet, PhD (Committee Member)

Subjects:

Mechanical Engineering

Keywords:

Bearing stiffness matrix; analytical formulation; double row angular contact ball bearings; modal experiment; bearing dynamics; damping models; automotive wheel bearings

Koprubasi, KeremModeling and Control of a Hybrid-Electric Vehicle for Drivability and Fuel Economy Improvements
Doctor of Philosophy, The Ohio State University, 2008, Mechanical Engineering

The gradual decline of oil reserves and the increasing demandfor energy over the past decades has resulted in automotive manufacturers seeking alternative solutions to reduce the dependency on fossil-based fuels for transportation. A viable technology that enables significant improvements in the overall tank-to-wheel vehicle energy conversion efficiencies is the hybridization of electrical and conventional drive systems.

Sophisticated hybrid powertrain configurations require careful coordination of the actuators and the onboard energy sources for optimum use of the energy saving benefits. The term optimality is often associated with fuel economy, although other measures such as drivability and exhaust emissions are also equally important. This dissertation focuses on the design of hybrid-electric vehicle (HEV) control strategies that aim to minimize fuel consumption while maintaining good vehicle drivability.

In order to facilitate the design of controllers based on mathematical models of the HEV system, a dynamic model that is capable of predicting longitudinal vehicle responses in the low-to-mid frequency region (up to 10 Hz) is developed for a parallel HEV configuration. The model is validated using experimental data from various driving modes including electric only, engine only and hybrid. The high fidelity of the model makes it possible to accurately identify critical drivability issues such as time lags, shunt, shuffle, torque holes and hesitation.

Using the information derived from the vehicle model, an energy management strategy is developed and implemented on a test vehicle. The resulting control strategy has a hybrid structure in the sense that the main mode of operation (the hybrid mode) is occasionally interrupted by event-based rules to enable the use of the engine start-stop function. The changes in the driveline dynamics during this transition further contribute to the hybrid nature of the system.

To address the unique characteristics of the HEV drivetrain and to ensure smooth vehicle operation during mode changes, a special control method is developed. This method is generalized to a broad class of switched systems in which the switching conditions are state dependent or are supervised. The control approach involves partitioning the state-space such that the control law is modified as the state trajectory approaches a switching set and the state is steered to a location within the partition with low transitioning cost. Away from the partitions that contain switching sets, the controller is designed to achieve any suitable control objective. In the case of the HEV control problem, this objective generally involves minimizing fuel consumption.

Finally, the experimental verification of this control method is illustrated using the application that originally motivated the development of this approach: the control of a HEV driveline during the transition from electric only to hybrid mode.

Committee:

Giorgio Rizzoni, PhD (Advisor); Yann Guezennec, PhD (Committee Member); Andrea Serrani, PhD (Committee Member); Steve Yurkovich, PhD (Committee Member)

Subjects:

Mechanical Engineering

Keywords:

Hybrid electric vehicles; hybrid vehicles; automotive control systems; vehicle modeling; model validation; driveline control; control of switched systems; energy management in hybrid vehicles;

Stammen, Jason AnthonyBiomechanical Characterization of the Human Upper Thoracic Spine – Pectoral Girdle (UTS-PG) System: Anthropometry, Dynamic Properties, and Kinematic Response Criteria for Adult and Child ATDs
Doctor of Philosophy, The Ohio State University, 2012, Mechanical Engineering

The dynamic response of the human thoracic spine is not well understood in the field of injury biomechanics, largely because of experimental challenges in isolating the properties of the upper thoracic spine segment from the rest of the thorax. Research suggests that increased flexibility in the anthropomorphic test device (ATD) posterior thorax improves the biofidelity of head kinematics, and this effect is especially important in child ATDs for evaluating booster seat performance.

The objectives of this study were to (a) characterize the dynamic response of the intact human upper thoracic spine while considering the effects of pectoral girdle restraint configuration, speed, and anthropometry, (b) quantify the link between upper thoracic system dynamics and whole-body thoracic spine kinematics in crash simulation (sled) testing, and (c) develop a methodology to estimate large child UTS-PG properties using anthropometry, kinematics, and adult UTS-PG material properties.

A novel approach, Isolated Segment Manipulation (ISM), was introduced to quantify the intact upper thoracic spine – pectoral girdle (UTS-PG) dynamic response of nine adult post-mortem human subjects (PMHS). The ISM dynamic properties were confirmed to be applicable in more realistic crash conditions by applying them in a sled model with an input acceleration applied directly to the mid-thoracic spine. Thoracic spine displacements were measured in twelve HYGE sled tests conducted on three of the nine PMHS at various speeds (3.8 – 7.0 m/s) associated with spine velocities observed in typical belted sled tests. Using two different models, it was determined that the dynamic properties from ISM testing could be used to accurately predict T3 spine displacements for multiple sizes of PMHS and various combinations of restraint and speed. Head, shoulder, and spine kinematics were calculated through three-dimensional kinematic measurement, and T3 displacement vs. T6 force relationships were presented as preliminary ATD response targets.

Anatomic and kinematic statistical analyses were then completed to aide in translating the adult UTS-PG data to the child population. Structural anatomy measurements were taken from radiology data of both adult PMHS and pediatric patients, and statistically significant age-dependent measures were identified for scaling purposes. Head displacements of both child and adult occupants from sled evaluations in the literature were statistically analyzed and supported qualitatively by crash data occupant available space (OAS) calculations, and it was determined that the mean 10YO displacement, when normalized by stature, is 46% greater than that of an adult. A distributed parameter analysis was employed to estimate the elastic modulus of the adult UTS-PG to be 7.5 – 16.5 MPa using anthropometric, ISM, and sled kinematic data from this study. Extension of this methodology to the large child using age-dependent scale factors from this study and the literature resulted in normalized mode shape differences between large child and adult that were consistent with kinematic differences from experimental literature. Using the techniques, findings, and tools from this study, it is believed that biofidelity response corridors and a test method can be developed for the upper thoracic region of large child ATDs used to evaluate booster seat designs.

Committee:

Rebecca Dupaix, PhD (Advisor); John Bolte, PhD (Committee Member); Dennis Guenther, PhD (Committee Member); Ahmet Kahraman, PhD (Committee Member)

Subjects:

Anatomy and Physiology; Automotive Engineering; Biomechanics; Biomedical Engineering; Engineering; Mechanical Engineering; Mechanics; Transportation

Keywords:

thoracic spine; biomechanics; anthropomorphic test device; crash test dummy; system dynamics; pectoral girdle; head kinematics; automotive safety; injury criteria; biofidelity

Gingerich, Mark BryantJoining Carbon Fiber and Aluminum with Ultrasonic Additive Manufacturing
Master of Science, The Ohio State University, 2016, Mechanical Engineering
Due to increasing emphasis on lightweighting to increase fuel efficiency, integration of carbon fiber reinforced polymers (CFRP) with metal structures is necessary. Current adhesive and mechanical fastening methods used for joining CFRP to metals are not ideal due to poor mechanical properties and incompatibility with current manufacturing infrastructure. Consequently, new joining techniques are needed for increasing the use of CFRP. In this research project, a method of creating joints between CFRP and 6061-H18 aluminum was developed by using ultrasonic additive manufacturing (UAM). The UAM process was used to embed dry carbon fiber tows within an aluminum matrix, creating a mechanical joint between the two materials. The joints were then integrated with additional CF fabrics and epoxy, forming a fully integrated CF-Al structure. This technique was used to create CF-Al joints for tensile, cross tensile, and three-point-bend testing. Mechanical test results showed that the UAM constructed joints had superior strength when compared to adhesive single lap joints. Throughout the UAM joint manufacturing process, experimental observations paired with FEA were used to help solve issues with foil tearing, which is a common problem experienced when materials are embedded with UAM.

Committee:

Marcelo Dapino (Advisor); Anthony Luscher (Committee Member)

Subjects:

Aerospace Engineering; Automotive Engineering; Automotive Materials; Engineering; Experiments; Materials Science; Polymers

Keywords:

UAM; ultrasonic additive manufacturing; CFRP to metal joining; automotive joining; aluminum; carbon fiber; ultrasonic consolidation; hybrid transition structures; adhesive benchmarking; carbon fiber integration

Zhou, YitongMechanical Characterization of Automotive Electrical Wires and Wire Harnesses
Master of Science, The Ohio State University, 2016, Mechanical Engineering
An automotive wire harness is an organized set of individual electrical wires, terminals and connectors that run throughout the entire vehicle transmitting information and electric power. Wire harnesses may be exposed to tensile, bending and torsion loads during and after being assembled in cars, causing stress and strain in the individual electrical wires without accurate validation from CAE tools. The lack of accurate CAE tools for wire harnesses has been generating extra costs to automotive OEMs for many years due to issues like rattling and interference with other parts. Present CAE software packages are not developed specifically for wire harness simulation and oversimplified models have been used such as elasticity behavior as well as ignoring taping and contact forces. To be able to develop an accurate CAE tool to simulate wire harnesses, the mechanical properties of harnesses and harness components must be fully characterized. However, due to the complexity, flexibility and high variation in wire harnesses and individual electrical wires, their mechanical properties have not been studied systematically and thoroughly in previous studies. In addition, no standards and very few experimental methods for mechanical testing of single electrical wires and wire harnesses have been developed, which led to few empirical data for CAE simulation resulting in inaccurate models. In this study, mechanical experiments have been categorized, developed and conducted on individual electrical wires and wire bundles under different loading conditions to identify key mechanical properties and behaviors. FEA researchers utilized these empirical data to create computational models for electrical wires and wire bundles. The experiments for individual electrical wires were categorized into tensile, bending and torsion tests. From tensile tests, stress-strain curves of three different wires were obtained, and elastic modulus, yield strength, elongation as well as ultimate tensile strength (UTS) were identified. Wires of different types and dimensions showed different properties especially in elongation and UTS. Two bending tests including compression and cantilever bending tests were set up and conducted. In both tests, motion capture was utilized to identify the deflection of wires throughout the whole deformation process. Compression bending tests were conducted under compression load similar to fixed end buckling for four different wires. Results show that there is a large difference in initial force between the samples, which indicates difficulty in FEA simulation. In addition, motion capture plots and pictures showed large differences in deflection orientation but minor out of plane deflection. Cantilever bending test showed more consistency in the load, especially in the initial regime. Torsion tests were conducted based on a force controlled method. The results showed that the rotation angle is highly rate dependent due to creep behavior. Cyclic compression bending tests were conducted on wire bundles with a different and larger setup. Shape deflection was captured by motion capture and force data was collected by load cell. The force data at the first load showed large differences at the beginning for different samples while were very consistent when bent and in other cycles. Plasticity behavior was found in all tests, using which the simulation aspects were able to develop more accurate plastic models for electrical wires and wire bundles under different loading conditions.

Committee:

Marcelo Dapino (Advisor); Soheil Soghrati (Committee Member)

Subjects:

Mechanical Engineering

Keywords:

Mechanical Engineering, Automotive, Electrical

Peer, Andrea JPerformance Testing and Modeling of Ultra-High Strength Steel and Complex Stack-Up Resistance Spot Welds
Master of Science, The Ohio State University, 2017, Materials Science and Engineering
Hot stamped boron steels, such as Usibor® 1500, have been increasingly used in automotive structural components for light-weighting and impact resistance. Classified as an ultra-high strength steel, these alloys have superior strength with tensile strengths exceeding 1500 MPa. The rapid heating and cooling thermal cycle during resistance spot welding can significantly alter the martensitic base metal microstructure, resulting in formation of coarse-grained and subcritical heat-affected zones (CGHAZ and SCHAZ) with inferior mechanical properties. The martensitic CGHAZ is adjacent to the weld nugget and experiences the most time above the AC3, which allows for austenite grain growth. The SCHAZ is next to the unaffected base metal and does not reach the AC1¬ during welding, thus the base metal microstructure is over-tempered into cementite and ferrite. The present research aims at developing the fundamental knowledge of plastic deformation and fracture behaviors of ultra-high strength steel resistance spot welds. As a resistance spot weld comprises highly inhomogeneous microstructure, the overall research approach is based on studying the local (or microstructure-dependent) mechanical properties for individual regions in the weld as well as their interactions with weld geometry on the deformation behavior. Specifically, optimal welding parameters are determined to produce welds of appropriate nugget diameter for 2T Usibor 1500 with a gauge thickness of 1.5 mm. Micro-hardness mapping and metallographic analysis allow for characterization of the weld metal, CGHAZ, SCHAZ, and base metal of the spot weld. Quasi-static tensile testing with digital image correlation (DIC) is used to determine the local stress-strain behaviors of each region using bulk microstructural samples created in a Gleeble® thermal-mechanical simulator. Conventional and innovative resistance spot weld mechanical testing methods are used to generate more knowledge on the deformation of joints under various loading conditions. Sectioned tensile shear testing and single-sided wedge testing procedures have been established to use 2-D DIC for in situ observations of local deformation on the exposed weld cross-section during testing. A mechanical model, developed using Abaqus finite element analysis (FEA) code by incorporating the local constitutive behaviors of RSW joints, is used to better understand the effect of weld nugget profiles on the stress state present during loading. The FEA model is validated by comparing the simulated strain fields to the experimentally measured strain fields. The knowledge generated in this study can help improve the accuracy of predicting spot weld fracture of ultra-high strength steels in the automotive industry. Particularly, the fine-resolution, coupon-scale model developed in this research will be useful for implementation into coarse-resolution, full-scale models for crash simulation and optimization of vehicle components.

Committee:

Wei Zhang, PhD (Advisor); Menachem Kimchi (Advisor); David Phillips, PhD (Committee Member)

Subjects:

Automotive Engineering; Automotive Materials; Engineering; Materials Science; Metallurgy; Transportation

Keywords:

Welding; Resistance Spot Welding; Automotive; Mechanical Testing; Finite Element Analysis; Mechanical Properties; Metallurgy; Crash Simulation;

Wolfe, Sage M.Integration of CarSim into a Custom Cosimulation Program for Automotive Safety
Master of Science, The Ohio State University, 2011, Mechanical Engineering
Modern passenger vehicles possess many advanced safety features such as sensors to detect collision. However, a network-level crash predictor does not exist. The overall goal of this project is to study the feasibility of a network-level crash estimator using GPS/INU data from individual vehicles. To simulate this, CarSim (a vehicle dynamics simulation program) and VISSIM (a microscopic traffic simulation program) were integrated into a custom cosimulation program. This work focuses on the integration of CarSim into the cosimulation program and simulation of the dynamic behavior of individual vehicles.

Committee:

Dennis A. Guenther, PhD (Advisor); Gary J. Heydinger, PhD (Committee Member)

Subjects:

Automotive Engineering; Mechanical Engineering

Keywords:

automotive safety; collision avoidance; simulation; CarSim; vehicle dynamics; traffic safety; GPS; GNSS; INU; IMU; FHWA; SSAM

Thornton, Ben JohnstonParameter Evaluation and Sensitivity Analysis for an Automotive Damper Model
Master of Science, The Ohio State University, 2012, Mechanical Engineering
Physical models are commonly used in the automotive industry. Accurate models exist for most automotive systems. However, few accurate models have been developed to model the individual components of automotive suspension dampers. Damper modeling is challenging due to the complexities associated with fluid flow and clearance nonlinearities, fluid-structure coupling, and overall sensitivity to parameter variations. This thesis focuses on the evaluation of gas bulk modulus, oil bulk modulus, Coulomb friction, effective mass of the body and valve resistance. The effect of these parameters on damper performance are analytically evaluated. The results show that the model is most sensitive to valve fluid resistance. Two experiments are presented. In the first experiment a simplified loading pattern was applied to the shims using steel forks. In the second experiment the displacement of the shims was measured while fluid was flowing through the valve. Although these experiments did not match exactly, valve shim stiffness calculated from each experiment led to accurate results when the model was run with these stiffness values. The overall model accuracy is adequate, though further work is needed to improve the modeling of shims and other components.

Committee:

Marcelo Dapino, PhD (Advisor); Gary Heydinger, PhD (Committee Member)

Subjects:

Automotive Engineering; Mechanical Engineering

Keywords:

Automotive Suspension; Damper; Modeling; Bulk Modulus; Shim Stiffness; Check Valve

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