Title :
Fuzzy diagnostic gear determination
Author :
Shaout, Adnan ; Breton, Dennis ; Awad, Selim
Author_Institution :
Electr. & Comput. Eng. Dept., Univ. of Michigan, Dearborn, MI, USA
Abstract :
This paper outlines a Diagnostic Signal Backup/replacement strategy to determine the current driving gear of a vehicle in the case that the ordinarily responsible message is lost or corrupted. The strategy is implemented in software. The source data for the evaluations was empirical measured data from a vehicle under normal operating conditions. This paper explores the use of a Fuzzy Logic Inference System (FIS) to improve or replace an existing software algorithm for gear determination. The Fuzzy software system is developed using MATLAB Fuzzy Tool Box and simulated in the MATLAB Simulink environment. A Fuzzy Logic Mamdani computational model is employed to process dynamic sensor/ECU input. The result of the FIS defuzzified output is an integer number representative of the gear in which the vehicle under test is estimated to be under any given instantaneous vehicle operating conditions. The process for development of the FIS is outlined and the results are compared between the Fuzzy and Non-Fuzzy determinations.
Keywords :
fuzzy reasoning; gears; mechanical engineering computing; FIS; MATLAB Simulink environment; MATLAB fuzzy tool box; fuzzy diagnostic gear determination; fuzzy logic Mamdani computational model; fuzzy logic inference system; fuzzy software system; vehicle driving gear; Artificial intelligence; Automotive engineering; Fuzzy logic; Gears; MATLAB; Vehicles; Fuzzy Automotive Sensor Applications; Fuzzy Inference System; Fuzzy Vehicle In-gear Determination; Fuzzy system Modeling; MATLAB Fuzzy Tool Box; Substitute Data Diagnostics; Vehicle Diagnostics;
Conference_Titel :
Computer Engineering Conference (ICENCO), 2014 10th International
Print_ISBN :
978-1-4799-5240-3
DOI :
10.1109/ICENCO.2014.7050438