Doctor of Philosophy, The Ohio State University, 2022, Mechanical Engineering

In recent years, the trend in the automotive industry has been favoring the reduction of fuel consumption in vehicles with the help of new and emerging technologies. This drive stemmed from the developments in communication technologies for Connected and Autonomous Vehicles (CAV), such as Vehicle to Infrastructure (V2I), Vehicle to Vehicle (V2V) and Vehicle to Everything (V2X) communication. Coupled with automated driving capabilities of CAVs, a new and exciting era has started in the world of transportation as each transportation agent is becoming more and more connected. To keep up with the times, research in the academia and the industry has focused on utilizing vehicle connectivity for various purposes, one of the most significant being fuel savings. Motivated by this goal of fuel saving applications of Connected Vehicle (CV) technologies, the main focus and contribution of this dissertation is developing and evaluating a complete Eco-Driving strategy for CAVs. Eco-Driving is a term used to describe the energy efficient use of vehicles. In this dissertation, a complete and comprehensive Eco-Driving strategy for CAVs is studied, where multiple driving modes calculate speed profiles ideal for their own set of constraints simultaneously to save fuel as much as possible while a High Level (HL) controller ensures smooth transitions between the driving modes for Eco-Driving. The first step in making a CAV achieve Eco-Driving is to develop a route-dependent speed profile called Eco-Cruise that is fuel optimal. The methods explored to achieve this optimally fuel economic speed profile are Dynamic Programming (DP) and Pontryagin's Minimum Principle (PMP). Using a generalized Matlab function that minimizes the fuel rate for a vehicle travelling on a certain route with route gradient, acceleration and deceleration limits, speed limits and traffic sign (traffic lights and STOP signs) locations as constraints, a DP based fuel optimal velocity profile is found. The ego CAV (open full item for complete abstract)

Committee: Levent Guvenc (Advisor); Mrinal Kumar (Committee Member); Bilin Aksun-Guvenc (Committee Member) Subjects: Automotive Engineering; Computer Science; Design; Energy; Engineering; Experiments; Mechanical Engineering; Systems Design; Technology; Transportation

Master of Science, The Ohio State University, 2019, Mechanical Engineering

The automotive industry is driving towards electrification. As the emission and fuel economy standards get more stringent, manufactures are electrifying their vehicle platforms by developing more hybrid electric vehicles. Although new technology boosts the fuel economy, it also brings new challenges. One of them is that customers often find discrepancies between the rated fuel economy number and the number they get during real world operation. Therefore, there is a need to investigate the issue and develop a new calibration process for optimizing the HEV fuel economy over both certification and real-world operation. In this research, a model-based calibration process is developed. The process uses meta-heuristic algorithms to optimize five look-up tables that are relevant to fuel economy of the HEV. Four different meta-heuristic algorithms, namely PSO, GA and two hybrids, are investigated and compared. It is found that PSO has reasonably good performance and can deliver its performance consistently under different conditions. Other algorithms may have better performance under certain scenarios, but they are sensitive to constraints in test problems and fail to get rational solutions in the real problem. The research also investigates methods to reduce number of parameters to optimize, the initialization of the optimization set and ways to generate representative drive cycles based on real-world driving data. The important thing is that these methods are not vehicle-specific and therefore can be migrated to calibration of other HEVs easily.

Committee: Giorgio Rizzoni (Advisor); Marcello Canova (Committee Member) Subjects: Mechanical Engineering

Master of Science (MS), Ohio University, 2003, Mechanical Engineering (Engineering)

In conventional vehicles, the entire power is derived from the IC engine, so, it is obligatory to size the engine larger than necessary for its cruising speed. The engine is to be designed to account for peak power requirements like acceleration. This over sizing the engine shifts the operating point from its efficient zone and this adversely affects the fuel economy and emissions. The idea of hybridization is that a part of the total power required can be replaced by an auxiliary power source, generally a motor powered by batteries. Hence, the IC engine can be designed for average load and can be operated with better fuel rfficiency. A simulation tool called ADVISOR (Advanced Vehicular Simulator) is used for this study. The software takes the vehicle input and the drive cycle from the user, simulates the vehicle drive and gives fuel economy, acceleration performance and emissions. In this study, each of the three vehicle platforms (light SUV, full size SUV and Heavy Truck) is selected and a reasonable power level for that vehicle platform is taken from the data of the current conventional vehicle type. The powertrain is then hybridized by replacing (in steps) this power by an equivalent motor power and a simulation is run, such simulations are run in Advisor at three different battery charge capacities to understand the effect of on board charge. The fuel economy and the time to accelerate from rest to 60 mph are noted down from the ADVISOR results. The cost optimization is also done by considering the cost of the motor along with the cost and space of the batteries. It also includes the replacement cost of the batteries. The benefits due to the decrease of operating costs will be shown in the fuel economy and the penalty due to the weight of the batteries is shown both in performance and fuel economy of the vehicle. Results showed that hybridization can improve the overall performance of the vehicle, but with the current cost of the batteries it may be a little co (open full item for complete abstract)

Committee: Gregory Kremer (Advisor) Subjects: Engineering, Mechanical