Evaluating Vehicle Energy Efficiency in Urban Transport Systems Based on Fuzzy Logic Models

Vasyl Mateichyk (), Nataliia Kostian, Miroslaw Smieszek, Jakub Mosciszewski and Liudmyla Tarandushka
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Vasyl Mateichyk: Department of Technical Systems Engineering, Rzeszow University of Technology, al. Powstancow Warszawy 10, 35-959 Rzeszow, Poland
Nataliia Kostian: Department of Automobiles and Technologies for their Operating, Cherkasy State Technological University, Shevchenko 333, 18006 Cherkasy, Ukraine
Miroslaw Smieszek: Department of Technical Systems Engineering, Rzeszow University of Technology, al. Powstancow Warszawy 10, 35-959 Rzeszow, Poland
Jakub Mosciszewski: Department of Technical Systems Engineering, Rzeszow University of Technology, al. Powstancow Warszawy 10, 35-959 Rzeszow, Poland
Liudmyla Tarandushka: Department of Automobiles and Technologies for their Operating, Cherkasy State Technological University, Shevchenko 333, 18006 Cherkasy, Ukraine

Energies, 2023, vol. 16, issue 2, 1-22

Abstract: This work solves the task of developing a fuzzy logic model for evaluating the energy efficiency of vehicles as part of the control unit of an intelligent transport system. Within the scope of this study, the previously obtained morphological model of the transport system was modified. A mathematical dependence is proposed to determine the vehicle energy efficiency indicator. This dependence characterizes the energy consumption of the vehicle in relation to the energy consumption of the vehicle under the reference operating conditions. Synthesis of system configurations was performed, and procedures were used to transform the morphological formulas of the received configurations into a base of logical derivation rules. Parameters of the membership functions of system parameters to fuzzy terms of the area of their definition are defined. Based on the results of the morphological analysis, two fuzzy derivation models were developed: the Mamdani type and the Sugeno type. The accuracy of the modeling was evaluated using different defuzzification algorithms in the control sample. The most accurate model is the fuzzy Mamdani model, with an accuracy value of 98.8%. Using the developed model, the nature of the mutual influence of the transport system parameters on the level of vehicle efficiency was assessed. The results of the study can be used to justify the choice of the vehicle under the specified operating conditions and in the settlement design of the road infrastructure.

Keywords: fuzzy logic model; membership function; morphological matrix; urban transport system; vehicle energy efficiency (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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