Master of Business Administration, The Ohio State University, 1950, Graduate School

Committee: Not Provided (Other) Subjects:

Master of Science, The Ohio State University, 2021, Mechanical Engineering

The problem of engine idling for long haul Class 8 trucks has been under study for decades, with APUs and Truck Stop Electrification as the most compelling solutions. With the electrification of trucks approaching feasibility in terms of cost effective technology, hybridization offers another degree of freedom to tackle the problem. The research aims at exploiting the battery pack of a 48V mild hybrid Class 8 truck to store the sufficient energy for powering auxiliaries at night. This problem is not trivial, as the battery packs typically cannot recover the entire energy required through regeneration alone; hence an optimal energy management strategy needs to be employed to charge the battery through the engine during drive operation. Moreover, a tool needs to be developed to evaluate component bottlenecks, identify trends in engine torque requests and to establish a best-case baseline for an online energy management system. The work presented aims to develop a Dynamic Programming framework that employs a multi-objective cost function to minimize fuel consumption and maximize regeneration. A typical Class 8 truck drive cycle is used to represent the drive phase, with mandatory stops as per regulations. The dynamic programming employs 3 control inputs: the engine on-off state, clutch engagement state and power request at the electric machine. An optimal SOC trajectory for the battery pack can then be established through the DPM function on Matlab. The framework also highlights the challenges associated with DPM such as rapid engine on-off scenarios, details the approach to tackle those and the compromises in fuel cost with those approaches. Finally, full cycle simulations with 2 candidate battery packs are presented and potential fuel savings are compared against ANL's report on idle reduction technologies.

Committee: Qadeer Ahmed Dr. (Advisor); Giorgio Rizzoni Dr. (Committee Member) Subjects: Mechanical Engineering

Master of Science (M.S.), University of Dayton, 2019, Civil Engineering

Large trucks play a key role in the overall safety of the highway transportation system. Previous studies have shown that in Ohio large trucks are over-represented in crashes that lead to serious and fatal injuries. A previous study that analyzed factors affecting truck-related crashes in Ohio found that posted speed limit and speed-related factors were among the significant factors impacting crash severity of truck-related crashes. Several studies have shown that increasing speed limits on roadways has a significant impact both on safety and operating speeds. On July 1, 2013, the Ohio's legislature raised the speed limits on rural freeways from 65 mph to 70 mph for passenger vehicles, buses and trucks and to date the safety impact of this speed limit raise has not been evaluated. The current study investigated the impact of raising the speed limit on crash severity specifically with interest in large trucks and buses on rural freeways in Ohio. Statewide crash data from January 1, 2010 to December 31, 2018 were obtained from the Ohio Department of Public Safety (ODPS). Given that the numbers of rural freeway segments located all over the state and traffic volumes for each segment over the study period are not easily obtainable; therefore, the use of standard observational before/after study Empirical Bayes (EB) method was not feasible for the current study. Because of the model requirement for stationarity on a response series, this study utilized the Autoregressive Integrated Moving Average (ARIMA) time series intervention analysis method using monthly and seasonal crash data. A time series statistical method takes care of differences in crashes occurring in different years and recognizes trends in different periods of times. Time series analysis is a statistical technique that deals with time series data or trend analysis. Time series data means that data is in a series of time periods or intervals. Results of the current study show that the increase of speed in t (open full item for complete abstract)

Committee: Deogratias Eustace (Advisor); Maher Qumsiyeh (Committee Member); Philip Appiah-Kubi (Committee Member) Subjects: Civil Engineering; Transportation

Master of Science (MS), Ohio University, 2019, Civil Engineering (Engineering and Technology)

Due to recent innovations with horizontal drilling and hydraulic fracturing, the oil and gas industry has witnessed significant growth in the State of Ohio. This growth has resulted in large trucks using county roads that were originally not designed to support such volumes or loads. This study focuses on damages caused to local roads in Ohio as a result of the unplanned increase in truck traffic. Ohio Senate Bill 315 requires that energy development companies enter a Road User Maintenance Agreement (RUMA) prior to obtaining a drilling permit. However, no clear guidance is available on this topic-how to implement? What constitutes a RUMA? etc. To explore this topic, a survey was developed to understand the usage of RUMAs in Ohio. Using the survey results, further in-depth interviews were carried out with select local officials with the hope of generating a RUMA best practice matrix which can be used as a guidance tool by local officials. Additionally, this study also developed a Finite Element model using ABAQUS CAE with the purpose of finding the Equivalent Axle Load Factor (EALF) for a typical county road in Ohio using data from previously done studies. Here, amount of possible repetitive passes to cause fatigue cracking and permanent deformation was studied. Using the results obtained, along with pavement repair and maintenance costs for local roads that were provided by ODOT District 10 pavement engineers, the study predicts the number of trucks that can pass on a typical road section until pavement failure occurs as part of a life cycle cost analysis.

Committee: Issam Khoury Ph.D. (Advisor); Naik Bhaven Ph.D. (Committee Member); Daniel Che Ph.D. (Committee Member); Luke Pittaway Ph.D. (Committee Member) Subjects: Civil Engineering

Doctor of Philosophy, The Ohio State University, 1986, Graduate School

Committee: Not Provided (Other) Subjects: Business Administration

Doctor of Philosophy, The Ohio State University, 2013, Mechanical Engineering

According to NHTSA's 2011 Traffic Safety Facts, large-truck occupant fatalities increased from 530 in 2010 to 635 in 2011, which is a 20% increase. This was a second consecutive year in which large truck fatalities have increased (9% increase from 2009 to 2010). There was also a 15% increase in large truck occupant injuries from 2010. Moreover, the fatal crashes involving large trucks increased by 1.9%, in contrast to other-vehicle-occupant fatalities that declined by 3.6% from 2010. Given the high accident involvement rate of heavy trucks, the research presented in this dissertation focussed on methods of improving and testing heavy truck ESC performance. The first part of the research, aimed at estimating trailer parameters and states using sensors on the tractor to enhance the capabilities of the tractor based ESC unit. The mass of the vehicle and road grade are first estimated using recursive least square estimation. The trailer CG position is then estimated using the load on the tractor drive axels. This is followed by a planar model of an articulated vehicle to calculate the lateral acceleration, longitudinal acceleration and yaw rate of the trailer CG. Finally a Dual Extended Kalman Filter is developed to estmate trailer roll angle and roll parameters. The second phase of the research involved the development of a state of the art Hardware in the Loop simulation setup to test heavy truck ESC systems. The design of the HIL system is briefly discussed followed by the modeling of the vehicles in TruckSim. This is followed by a rigorous validation of the vehicle models and the HIL setup. Finally some of the applications of the validated HIL setup is discussed. This includes an indepth study of the Sine with Dwell maneuver and effects of vehicle speed, surface friction and CG height on the vehicle stability. This is followed by the design of a steering controller which is used to study the advantages afforded by the ESC system in an actual crash sc (open full item for complete abstract)

Committee: Dennis Guenther Dr. (Advisor); Gary Heydinger Dr. (Committee Member); Ahmet Kahraman Dr. (Committee Member); Junmin Wang Dr. (Committee Member) Subjects: Automotive Engineering; Mechanical Engineering

Master of Science, The Ohio State University, 2007, Mechanical Engineering

Heavy trucks are involved in many accidents every year - rollovers and loss of control of tractor-trailers contribute significantly to these accidents. Electronic Stability Control (ESC) is viewed as a solution to mitigate this problem. ESC systems reduce the incidence of single vehicle loss of control, which might lead to rollover or jackknife. The National Highway Traffic Safety Administration (NHTSA) has recently mandated ESC on light vehicles by 2012 and is now investigating the possibility of mandating ESC on heavy trucks. As a step toward this, NHTSA has started studying the effectiveness of ESC in preventing loss of control (e.g., rollovers and jackknifes) in tractor-trailers. As the working details and control strategies of commercially available ESC systems are not available, NHTSA is developing a generic ESC system that mimics the basic logical functionality of commercial systems. NHTSA has conducted tests on a 6x4 tractor-trailer, recording data for maneuvers including J-turns and single and double lane changes. Based on the response of the ESC system during these test maneuvers, the logical sequences of ESC braking is implemented in Simulink and applied with a TruckSim vehicle dynamics model, which has previously been developed and validated by NHTSA. The development of this model will provide NHTSA with an analytical tool to augment their studies of heavy truck ESC capabilities and effectiveness.

Committee: Dennis Guenther (Advisor) Subjects: