Piston-Seals Friction Modeling Using a Modified Maxwell Slip Formation and Genetic Identification Algorithm

• Published in: IEEE access Vol. 10; p. 1
• Main Authors: Mustafa, Rashad, Abdo, Ali, Siam, Jamal, Kucukay, Ferit
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Actuators; Friction; Friction Modeling; Generalized Maxwell Model; Genetic Algorithm Optimization; Genetic algorithms; Modelling; Modified Generalized Maxwell Model; O ring seals; Parameter identification; Piston Seal; Pressure dependence; Proportional-Integral Observer; Slip
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2022.3225412

Improving spontaneity, shifting control, and efficiency are the main goals of actuators for hydraulic automated transmissions. Friction losses of piston-seals play an essential role in achieving these goals. Therefore, modeling the complex friction behavior of piston seals leads to a better understanding of the determinant factors of energy losses and, consequently, the realization of more efficient transmission actuators. This paper proposes a piston-seal friction model based on the Generalized Maxwell-Slip model. The proposed model introduces an additional hydraulic-pressure dependency that emulates the influence of cylinder-pressure on the displacement variable while accounting for various piston-seal structures. A Genetic Algorithm is also applied to identify and optimize the parameters of the proposed friction model. Simulations with O-Ring, D-Ring, and Bonded Piston seals were developed to show the validity of the proposed model in practical scenarios. The results were also compared with the original Generalized Maxwell Slip friction model to show the superiority of the proposed model in representing the experimental data.