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Mechatronics and Robotics Engineering Department, Egypt-Japan University for Science and Technology, Alexandria, Egypt, On leave from Mechanical Eng. Department, Assiut University and Egypt
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1 Papers

Finite Control Augmented with Fuzzy Logic for Automotive Air-spring Suspension System

Topics: Genetic Algorithms; Fuzzy Control; Engineering Applications on Intelligent Control Systems and Optimization

Authors: Mohamed Essam Shalabi 1 , Haitham El-Hussieny 2 , A. A. Abouelsoud 3 and Ahmed M. R. Fath Elbab 4

Affiliations: 1 Mechatronics and Robotics Engineering Department, Egypt-Japan University for Science and Technology, Alexandria and Egypt , 2 Electrical Engineering Department, Faculty of Engineering (Shoubra), Benha University, Cairo and Egypt , 3 Electronics and Communication Department, Cairo University, Cairo and Egypt , 4 Mechatronics and Robotics Engineering Department, Egypt-Japan University for Science and Technology, Alexandria, Egypt, On leave from Mechanical Eng. Department, Assiut University and Egypt

Digital Object Identifier: 10.5220/0007922002890294

Proceedings of ICINCO 2019, ISBN: 978-989-758-380-3

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This paper investigates the spring stiffness control of air suspension systems working under different operating conditions of road profile frequencies and amplitudes. Usually changing the stiffness of the air spring involves variations of the enclosed air pressure by pumping air into or out of the air chamber, or by changing its volume. Since, changing spring stiffness through controlling its pressure consumes power and is not instantaneous, controlling the stiffness through finite volume control is merged with a PI-like Fuzzy Logic Control (PI-FLC) in this paper. This is achieved by connecting the air spring volume to two additional unequal volumes. By controlling the total spring volumes through ON-OFF switching valves, four different stiffness settings are available, and one can achieve an improved performance of air suspension system. A nonlinear quarter-car model is used to evaluate the proposed approach while a Genetic Algorithm (GA) optimization is applied to estimate the PI-FLC optimal gains and the finite levels for switching the spring volumes. Numerical simulations results demonstrate the performance of the proposed control under different road profile. The vehicle body acceleration decreases by a value that reaches 4 cm/s2 which means improving the passenger ride comfort as well as maintaining the passenger safety. This in turns encourages the implementation of the proposed approach on an actual vehicle air suspension in the near future to further verify the system performance.
Collapse Button Related Ontology Subjects/Areas/Topics (9)
Artificial Intelligence

Fuzzy Control

Informatics in Control, Automation and Robotics

Computational Intelligence

Fuzzy Systems

Intelligent Control Systems and Optimization

Evolutionary Computing

Genetic Algorithms

Soft Computing

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