Search Results

This paper presents a model-based approach to detect unintended acceleration (UA) as well as other vehicle problems. A diagnostic system is formulated by detecting several specific vehicle events such as acceleration peaks and gear shifting. Mathematical models are created for these events based on simulation data and the final diagnostic conclusion is drawn from the voting result of all these models. The detection algorithm is validated using independent data sets obtained from Matlab/Simulink. A three dimensional vehicle model is built to implement traffic simulation. Vehicle problems and drivers' reactions are simulated and added during the process. Sensor noise is also considered and corresponding filters are designed and applied. The results show that the fault diagnostic system is successful in detecting UA.

A concept of “driving situation awareness”-driven energy management system for parallel hybrid electric vehicles (HEVs) is introduced. The essential feature of the proposed energy management system is to assess the driving environment (in terms of facility type combined with traffic congestion level) using long and short term statistical features of the drive cycle. Subsequently, this knowledge is provided to a system that makes intelligent decisions with respect to the torque distribution and charge sustenance tasks. Simulation work was carried out for the validation of proposed system, and the results reveal its viability for energy management of parallel hybrid vehicles.

In this paper, a number of issues of concern in relation to hybrid electric vehicles (HEVs) and fuel cell vehicles (FCVs) are discussed and comparatively reviewed. Currently, almost all the activities in the development of new generation of vehicles are focused on FCVs and HEVs. However, there are still uncertainties as to which provides the maximum benefits in terms of performance, energy savings, impact on environment etc. In particular, potential control strategies for FCVs and HEVs will be discussed and compared. For FCVs, these include power-averaging control as well as control based on maximum conversion efficiency, among others. HEV control strategies include electrically peaking hybrid propulsion, and parameter optimization approaches such as battery SOC maximization, emissions minimization, and optimal power management.

Currently, almost all the activities in the development of new generation of vehicles are focused on fuel cell powered vehicles (FCVs) and hybrid electric vehicles (HEVs). However, there are still uncertainties as to which provides the maximum benefits in terms of performance, energy savings and impact on the environment. This paper compares the performance and parameter characteristics of FCVs and HEVs with a view towards an objective assessment of the relative performance of these vehicles. In particular, this paper reviews major characteristics of FCVs as zero or ultra-low emission vehicles (ZEV/ULEVs), their presumed high efficiency and potential for using alternative fuels, while also considering their limited performance at high power demands.