The effects of drive cycle accessory load and degree of hybridization on fuel economy and emissions for hybrid electric buses.

摘要

Hybrid Electric Vehicles (HEVs) have gained much attention in recent years. This is mainly due to rising fuel prices and increasing environmental awareness. By implementing electricity as one of the power sources, a HEV can not only reduce fuel consumption but can also decrease tailpipe emissions.;In this thesis, the software package Powertrain Systems Analysis Toolkit (PSAT) was chosen as the simulation tool to model several bus powertrain configurations---conventional, three different degrees of hybridization parallel hybrid electric (PHEB), and a series hybrid electric (SHEB) to predict fuel economy and emissions level. The simulations were run with a typical accessory load, 15 kW, for a 40-foot transit bus as well as for no accessory load. The effect of accessory load on fuel economy was identified. Four different drive cycles---Manhattan, UDDS, CBD, and WVU City cycles---that covered a wide range of driving conditions were chosen as the testing cycles for the simulations.;For no accessory load, it was found that the PHEB1, which had the highest degree of hybridization, yielded the best fuel economy improvement on all four drive cycles. The highest fuel economy improvement without accessory load, 121.9%, was found for the Manhattan cycle. The maximum fuel economy improvement, 51.8%, for a 15 kW accessory load also occurred running the Manhattan cycle, and was achieved by the PHEB1 as well. The maximum fuel economy reduction with a 15 kW accessory load was 48.9%.;The largest emissions reductions with a 15 kW of accessory load were achieved by the PHEB1 operated in the Manhattan cycle, with NOx and PM emissions reductions of 73.4% and 45.9% over the conventional bus, respectively. Based on the emissions analysis, a bus with better fuel economy tends to have lower emissions and a bus with lower gas mileage usually produces more emissions, although there were some exceptions in the inverse relationship between gas mileage and emissions level.