Publication Detail

The Influence of Grade on the Operating Characteristics of Conventional and Hybrid Electric Transit Buses

UCD-ITS-RP-01-33

Presentation Series

Suggested Citation:
Dwyer, Harry A., Jennifer Tang, Christie-Joy Brodrick, Steven M. Khau, Christine Becker, John P. Wallace (2002) The Influence of Grade on the Operating Characteristics of Conventional and Hybrid Electric Transit Buses. Society of Automotive Engineers Technical Paper Series (2002-01-3118)

Presented at the International Truck & Bus Meeting & Exhibition, Detroit, MI

Session: Further Developments in Hybrid Buses

At the present time there are rapid changes occurring in the fleets of transit buses that are used in cities. These changes involve improvements in conventional diesel buses, Compressed Natural Gas, CNG, and more recently hybrid electric vehicles. In order to evaluate the performance of the transit buses, driving cycles have been developed, and two of the most popular are the New York City, NYC, and the Central Business District, CBD. These cycles have proven to be very valuable for predicting both performance and emissions of the transit buses, however they do not well characterize some of the unique characteristics of certain cities, such as San Francisco with its hills and high grade. In this paper we present the results of Chassis dynamometer measurements and modeling of the performance of four different types of transit buses on the typical grades that exist in San Francisco.

The general performance of the vehicles was that the hybrid electric and diesel buses had the most climbing power, and the CNG bus the least. The performance of the hybrid electric bus at high load and grade was excellent, and this lead to a detailed investigation for the specific reasons. The basic reason was that the diesel and CNG buses have hydraulic torque converters, HTC, and the hybrid electric bus has a direct drive from the electric motor. Both the Chassis dynamometer testing and the ADVISOR modeling have confirmed this result, however more extensive testing and modeling will be needed in the future.