Optimization of Energy-Efficient Speed Profile for Electrified Vehicles

This work presents a study of the energy-efficient operation of all-electric vehicles leveraging route information, such as road grade, to adjust the velocity trajectory Minimization of energy consumption is one of the main targets of research for both passenger vehicles in terms of economic benefit, and army vehicles in terms of mission success and decision making. The optimization of a speed profile is one of the tools used to achieve energy minimization and it can also help in the useful utilization of autonomy in vehicles. The optimization of speed profile is typically addressed as an Optimal Control Problem (OCP). The obstacle that disrupts the implementation of optimization is the heavy computational load that results from the number of state variables, control inputs, and discretization, i.e., the curse of dimensionality. In this work, Pontryagin's Maximum Principle (PMP) is applied to derive necessary conditions and to determine the possible discrete operating modes. The analysis shows that only five modes are required to achieve minimum energy consumption; full propulsion, cruising, coasting, full regeneration, and full braking. Then, the problem is reformulated and solved in the distance domain using Dynamic Programming to find the optimal speed profiles. Various simulation results are shown for a lightweight autonomous military vehicle. Army Programs use various drive cycles including time, speed, and grade, for testing and validating new vehicle systems and models. Among those cycles, two different drive conditions are studied: relatively flat, Convoy, and hilly terrain, Churchville B. For the Convoy cycle, the optimal speed cycle uses 21% less energy for the same trip duration or reduces the time by 14% with the same energy consumption while for the Churchville B cycle, it uses 24% less energy or provides 24% reduction in time. Furthermore, the sensitivity of energy consumption to regenerative-braking power limits and trip time is investigated. These studies provide important information that can be used in designing component size and scheduling operation to achieve the desired vehicle range. Lastly, the work provides parametric studies about the influence of the efficiency of an electric motor on performance including energy consumption and control modes.Master of Science in EngineeringAutomotive Systems Engineering, College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttps://deepblue.lib.umich.edu/bitstream/2027.42/146793/1/Hadi_Abbas_Thesis (1).pdfDescription of Hadi_Abbas_Thesis (1).pdf : Thesi