Johnson, Troy, authorBradley, Thomas, advisorPasricha, Sudeep, committee memberWeinberger, Chris, committee member2019-09-102019-09-102019https://hdl.handle.net/10217/197431The Colorado State University Vehicle Innovations Team (VIT) participates in numerous Advanced Vehicle Technology Competitions (AVTC's) as well as several hybrid-electric vehicle projects with outside sponsors. This study seeks to develop and quantify the accuracy of simulation and testing methods that will be used in the VIT's predictive optimal energy management strategy research that is to be used in these projects. First, a backward facing vehicle simulation model is built and populated with real-world OBD-II drive data collected from a 2019 Toyota Tacoma. This includes the creation of both an engine speed vs accelerator position vs engine load map as well as an engine speed vs engine load vs engine fuel rate map. Acceleration events (AE's) are performed with a baseline shift schedule and vehicle performance is recorded. The backward facing vehicle simulation model is used to predict how a modified shift schedule will affect the vehicle's fuel consumption. Further AE's are performed with the modified shift schedule and the performance data is compared to the vehicle simulation. The backward facing simulation model was capable of predicting average engine speed within 0.3 RPM, average engine load within 5.2%, and average total fuel consumption within 0.2 grams of the actual testing data. This study concludes that the vehicle simulation methods are capable of predicting fuel consumption changes within 1.4% of what is actual measured during real-world testing with a 95% confidence.born digitalmasters thesesengCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.modelingtestingsimulationfuel consumptionText