The use of global positioning systems, or GPS, as a means of logistical organization for fleet vehicles has become more widespread in recent years. The system has the ability to track vehicle location, report on diagnostic trouble codes, and keep tabs on maintenance schedules thus helping to improve the safety and productivity of the vehicles and their operators. In addition, the increasing use and implementation of yaw and roll stability control in heavy trucks has contributed to an increased level of safety for truck drivers and other motorists. However, these systems require the vehicle to begin a yaw or roll event before they assist in maintaining control. The aim of this paper is to present a new method for utilizing the GPS signal in conjunction with the fuzzy based stability index to create a truly active safety system. A new Fuzzy based predictive control was developed which is capable of predicting the vehicle instability level through use of GPS data and predictive vehicle modeling. The simulation results for two case scenarios, a multi mass case as well as the baseline vehicle case, showed the applicability of the methodology for heavy trucks where the output of the fuzzy controller would be used as an input into a Decision Making block which in turn would command the EBS to take the necessary actions to keep the vehicle within the specified safety regions, thus remaining under control.


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    Titel :

    A new fuzzy based stability index using predictive vehicle modeling and GPS data


    Beteiligte:


    Erscheinungsdatum :

    2008


    Format / Umfang :

    14 Seiten, 14 Bilder, 2 Tabellen, 11 Quellen




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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