Modeling Diesel Bus Fuel Consumption and Dynamically Optimizing Bus Scheduling Efficiency

Abstract

There are currently very few models that estimate diesel and hybrid bus fuel consumption levels. Those that are available either require significant dynamometer data gathering to calibrate the model parameters and also produce a bang-bang control system (optimum control entails maximum throttle and braking input). This thesis extends the Virginia Tech Comprehensive Power-Based Fuel Consumption Model (VT-CPFM) to model diesel buses and develops an application for it. A procedure is developed to calibrate the bus parameters using publicly available data from the Altoona Bus Research and Testing Center. In addition, calibration is also made using in-field bus fuel consumption data. The research presented in this thesis calibrates model parameters for a total of 10 standard diesel buses and 3 hybrid buses from Altoona and 10 buses from Blacksburg Transit. In the case of the Altoona data, the VT-CPFM estimated fuel consumption levels on the Orange County bus cycle dynamometer test produce an average error of 4.7%. The estimation error is less than 6% for all but two buses with a maximum error of 10.66% for one hybrid bus. The VT-CPFM is also validated using on-road fuel consumption measurements that are derived by creating drive cycles from acceleration information producing an average estimation error of 22%. These higher errors are attributed to the errors associated with constructing the in-field drive cycles given that they are not available. In the case of the Blacksburg Transit buses, the calibrated parameters produce a low sum of mean squared error, less than 0.002, and a coefficient of determination greater than 0.93. Finally an application of the VT-CPFM is presented in the form of a dynamic bus scheduling algorithm.