Optimal design of the toggle mechanism in servo presses

Abstract To augment the stretching capabilities of servo presses, an optimal transmission mechanism design is imperative. Firstly, a kinematic model of the servo press transmission system was established by employing the closed-vector formulation. A normalized composite fitness function, integrating the mechanism’s mechanical advantage, transmission angle, and slider velocity fluctuation as optimization criteria, was constructed to quantify the overall performance. Subsequently, a genetic algorithm was implemented to execute the optimization design under geometric, kinematic, transmission angle, and stroke-speed ratio constraints. The findings indicate that the optimized transmission mechanism reduces the maximum speed during the working stroke by 54.40%, increases the slider displacement during the working stage by 2.27%, and increases the proportion of the working stroke by 96.01%, effectively improving the overall forging performance of the press.

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Publication Details

Journal
Journal of Physics Conference Series
Published
2025-09-01
DOI
https://doi.org/10.1088/1742-6596/3097/1/012021
Primary Topic
Iterative Learning Control Systems
Type
article
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article

Optimal design of the toggle mechanism in servo presses

Xiang‐Guo Li, Chengyuan Wu
Journal of Physics Conference Series
Iterative Learning Control Systems
article

Optimal design of the toggle mechanism in servo presses

Xiang‐Guo Li, Chengyuan Wu
article en

Abstract

Abstract To augment the stretching capabilities of servo presses, an optimal transmission mechanism design is imperative. Firstly, a kinematic model of the servo press transmission system was established by employing the closed-vector formulation. A normalized composite fitness function, integrating the mechanism’s mechanical advantage, transmission angle, and slider velocity fluctuation as optimization criteria, was constructed to quantify the overall performance. Subsequently, a genetic algorithm was implemented to execute the optimization design under geometric, kinematic, transmission angle, and stroke-speed ratio constraints. The findings indicate that the optimized transmission mechanism reduces the maximum speed during the working stroke by 54.40%, increases the slider displacement during the working stage by 2.27%, and increases the proportion of the working stroke by 96.01%, effectively improving the overall forging performance of the press.

Journal of Physics Conference SeriesVol. 3097(1)
Hohai University (CN)
Openalex Percentile: Top 70%
Iterative Learning Control Systems
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