| A combination of stricter emissions regulatory standards and rising oil prices is leading many automotive manufacturers to explore alternative energy vehicles. In an effort to achieve zero tail pipe emissions, many of these manufacturers are investigating electric drive vehicle technology. In an effort to provide University of Kansas students and researchers with a stand-alone tool for predicting electric vehicle performance, this work covers the development and validation of various models and techniques.;Chapter 2 investigates the practicality of vehicle coast down testing as a suitable replacement to moving floor wind tunnel experimentation. The recent implementation of full-scale moving floor wind tunnels is forcing a re-estimation of previous coefficient of drag determinations. Moreover, these wind tunnels are relatively expensive to build and operate and may not capture concepts such as linear and quadratic velocity dependency along with the influence of tire pressure on rolling resistance. The testing method explained here improves the accuracy of the fundamental vehicle modeling equations while remaining relatively affordable.;The third chapter outlines various models used to predict battery capacity. The authors investigate the effectiveness of Peukert's Law and its application in lithium-based batteries. The work then presents the various effects of battery temperature on capacity and outlines previous work in the field. This paper then expands upon Peukert's equation in order to include both variable current and temperature effects. The method proposed captures these requirements based on a relative maximum capacity criterion. Experimental methods presented in the paper provide an economical testing procedure capable of producing the required coefficients in order to build a high-level, yet accurate state of charge prediction model. Moreover, this work utilizes automotive grade lithium-based batteries for realistic outcomes in the electrified vehicle realm.;The fourth chapter describes an advanced numerical model for computing vehicle energy usage performance. This work demonstrates the physical and mathematical theories involved, while building on the principles of Newton's second law of motion. Moreover, this chapter covers the equipment, software, and processes necessary for collecting the required data. Furthermore, a real world, on-road driving cycle provides for a quantification of accuracy. Multiple University of Kansas student project vehicles are then studied using parametric studies applicable to the operating requirements of the vehicles. Further investigation demonstrates the accuracy and trends associated with the advanced models presented in Chapters 2 and 3.;Lastly, chapter 5 investigates the design and building of a graphical user interface (GUI) for controlling the models created in the previous three chapters. The chapter continues to outline the creation of a stand-alone GUI as well as instructions for implementation, usage, and data analysis. |
