Standard

SAE 2016-01-1630

Apr 2016 Current

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Language English

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Abstract

In this paper, a soft computing approach to a model-free vehicle stability control (VSC) algorithm is presented. The objective is to create a fuzzy inference system (FIS) that is robust enough to operate in a multitude of vehicle conditions (load, tire wear, alignment), and road conditions while at the same time providing optimal vehicle stability by detecting and minimizing loss of traction. In this approach, an adaptive neuro-fuzzy inference system (ANFIS) is generated using previously collected data to train and optimize the performance of the fuzzy logic VSC algorithm. This paper outlines the FIS detection algorithm and its benefits over a model-based approach. The performance of the FIS-based VSC is evaluated via a co-simulation of MATLAB/Simulink and CarSim model of the vehicle under various road and load conditions. The results showed that the proposed algorithm is capable of accurately indicating unstable vehicle behavior for two different types of vehicles (SUV and Sedan). The algorithm can do this without any significant parameter adjustment, illustrating its robustness against the considered uncertainty.

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Standard from SAE International
Published: April 5 2016
Document type: IS
Pages
ISBN:

Publisher: SAE International
Distributor: SAE International

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Abstract

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