Combined quasi-static backward modeling and look-ahead fuzzy control of vehicles

Authors:
Behnam Ganji;Abbas Z. Kouzani
Affiliations:
School of Engineering, Deakin University, Geelong, VIC 3217, Australia;School of Engineering, Deakin University, Geelong, VIC 3217, Australia
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

Citing 2
Cited 0

Autonomous intelligent cruise control using a novel multiple-controller framework incorporating fuzzy-logic-based switching and tuning

Neurocomputing
Intelligent transportation systems-Enabling technologies

Mathematical and Computer Modelling: An International Journal

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Abstract

Vehicle modeling can play an important role in vehicle power train design, control and energy management investigation. This paper presents a method for vehicle power train modeling. The key feature of the method is its presentation of the dynamic of vehicle based on the road information. This ability makes the method suitable for look-ahead energy management and fuel economy optimal control problems. With the aid of a road slope database, road geometry ahead of the vehicle is extracted. A fuzzy controller is developed that receives this information and controls the velocity of the vehicle with respect to its fuel consumption. In order to maintain the operation of the combustion engine near its efficient region, the fuzzy controller commands a continuously variable transmission. Simulations are carried out using real road data. The results are presented and discussed.