Master of Science, The Ohio State University, 2007, Graduate School

Committee: Not Provided (Other) Subjects:

Master of Science, The Ohio State University, 2006, Graduate School

Committee: Not Provided (Other) Subjects:

Master of Science, The Ohio State University, 2007, Graduate School

Committee: Not Provided (Other) Subjects:

Master of Science, The Ohio State University, 2007, Graduate School

Committee: Not Provided (Other) Subjects:

Master of Science, The Ohio State University, 2006, Graduate School

Committee: Not Provided (Other) Subjects:

Master of Science, The Ohio State University, 2007, Graduate School

Committee: Not Provided (Other) Subjects:

Master of Science, The Ohio State University, 2014, Mechanical Engineering

Finding an effective alternative energy source to fossil fuels is a significant concern in today's primarily ground-transportation-heavy society. While hybrid-electric vehicles offer a good compromise of power and efficiency, pure electric vehicles are showing increasing promise as a transportation option that can utilize a truly renewable energy sources. The problem up until now, however, has been that vehicles powered only by batteries have severely limited travel ranges. This thesis, therefore, investigates methods for optimizing the travel distance of a pure electric ground vehicle. Previous research has shown a two-stage optimization of both vehicle velocity as well as in-wheel motor torque distribution can offer up to a 25% increase in efficiency. The next step, investigated here, is the effect that more realistic traffic conditions such as other vehicles and traffic lights have on the optimal solution. While these constraints obviously result in less energy savings, they still allow for a substantial increase over a naively actuated system.

Committee: Junmin Wang (Advisor); Manoj Srinivasan (Committee Member) Subjects: Mechanical Engineering

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

This dissertation addresses a thorough investigation and development on general problem formulations, control/optimization algorithm designs, and experimental validations of energy-efficient control allocation (EECA), with application to an over-actuated pure electric ground vehicle (EGV) with four independent in-wheel motors. For single-mode actuators which have only one working mode, either consuming or gaining energy, the existing CA scheme for over-actuated systems, which is usually in the form of different kinds of optimization problems, is extended to the EECA scheme by explicitly introducing efficiency functions of actuators as a portion of the power consumption expressions into the cost function. For dual-mode actuators which can work in both power-consuming and power-gaining modes, though not simultaneously, a virtual actuator concept and the corresponding compatibility condition is introduced to complete the novel EECA design frame in a general manner. Based on the proposed EECA scheme, different optimization algorithms with various characteristics are developed for the EGV in order to achieve real-time implementations. For the vehicle longitudinal motion control, since the front and rear two in-wheel motors of the EGV can be lumped together as two pairs, a Karush-Kuhn-Tucker (KKT)-based EECA algorithm is proposed to find all the local optimal solutions, and consequently the global minimum through a further simple comparison among all the realistic local minima and boundary values for a non-convex optimization problem. The KKT-based algorithm is also independent on the selections of initial conditions by transferring the standard nonlinear optimization problem into classical eigenvalue problems. Consequently, the KKT-based algorithm is real-time implementable and is validated through both Simulink-CarSim® co-simulations and experimental results. Since the computational load will exponentially grow along with the increase of the number of actuators, (open full item for complete abstract)

Committee: Junmin Wang (Advisor) Subjects: Mechanical Engineering