Multi-Objective Optimization of Bogie Stability for Minimum Radius Curve of Battery Track Engineering Vehicle DOI Creative Commons
Yang Shen, Jiayi Zhao, Chongyu Wang

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(12), P. 5231 - 5231

Published: June 17, 2024

A battery track engineering vehicle faces challenges such as derailment and other safety concerns when navigating an R20m minimum radius curve, primarily owing to its low vertical horizontal stabilities. To address these issues, a methodology integrating genetic optimization algorithms with rigid flexible coupled multi-body dynamics simulation is proposed optimize the primary suspensions of bogie vehicle. Initially, multi-objective model combining vehicles algorithm was formulated. Subsequently, optimal Latin hypercube design applied analyze sensitivity stability various suspension parameters. Finally, non-dominated sorting (NSGA-II) archive-based micro (AMGA) were enhance stability. Consequently, set parameter combinations obtained. notable enhancement observed in lateral optimized by 23.33% 3.5% traversing thereby establishing theoretical foundation for further improving running railway resolving shortcomings less research on smallest curve.

Language: Английский

Form-finding and multidisciplinary design of high-speed railway catenary based on collaborative optimization and machine learning-based surrogate model DOI
Jing Zhang, Shiyong Liu,

Yanbing Tian

et al.

Engineering Optimization, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 26

Published: Feb. 14, 2025

As the speed of train increases, current collection quality (CCQ) faces more challenges. In this article, an adaptive catenary form-finding method is proposed based on variable-length nonlinear cable and truss elements. Through machine-learning training, optimal parameters six surrogate models are obtained. By comparing performance models, best model selected to replace physical model. With model, a multidisciplinary design with collaborative optimization presented optimize 400 km/h catenary. CCQ taken as objective. The selected, including dropper space wire tensions. obtained by differential evolution, results verified bench tests. show system-level objective reduced 17.68%, standard deviation contact force maximum uplift at support 19.51% 14.25%.

Language: Английский

Citations

0
An efficient multi-objective algorithm based on Rao and differential evolution for solving bi-objective truss optimization DOI

Manh-Cuong Nguyen,

Hoang-Anh Pham, Viet-Hung Truong

et al.

Engineering Optimization, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 31

Published: Feb. 24, 2025

Language: Английский

Citations

0
Reliability assessment of the mining monorail crane drive system under heavy load and steep slope conditions DOI
Hao Lu,

Zhenhao Song,

Yu Tang

et al.

Mechanics Based Design of Structures and Machines, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 23

Published: March 30, 2025

Language: Английский

Citations

0
Adaptive operator selection with bandits for scaled problems based on decomposition-based MOEAs DOI
Yuan Yan Tang, Shuang Li, Wei Li

et al.

Engineering Optimization, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 16

Published: May 6, 2025

Language: Английский

Citations

0
Multi-strategy improved seagull optimization algorithm and its application in practical engineering DOI
Peng Chen, Huilin Li, Feng He

et al.

Engineering Optimization, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 39

Published: July 24, 2024

Metaheuristic algorithms play a crucial role in engineering optimization, as they can find the optimal parameter configuration systems. This article proposes multi-strategy improved seagull optimization algorithm (OPSOA) to solve application problems. Aiming problems of slow search speed and low convergence accuracy standard (SOA), four strategies, including Lévy flight Cauchy mutation, were introduced improve its performance. Comparison shows that OPSOA incomplete are better than SOA, indicating each improvement is effective. By testing benchmark functions CEC 2017 2022, it shown has strong ability solution superior other terms speed. The this practical proves significant advantages solving complex

Language: Английский

Citations

3
The Pareto Tracer for the treatment of degenerated multi-objective optimization problems DOI
Oliver Schütze, Oliver Cuate

Engineering Optimization, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 26

Published: Dec. 3, 2024

Multi-objective continuation algorithms are very powerful tools for the numerical treatment of continuous multi-objective optimization problems (MOPs). All these methods, however, based on certain regularity assumptions that imply solution set given MOP forms, at least locally, objects below a dimension. While this is indeed case most problems, there exist examples where Pareto set/front lower-dimensional, which called degenerated cases. This article presents and discusses new predictor step designed use within methods automatically detects (numerical) degeneration performs movements in essential directions. Furthermore, integrated into method 'Pareto Tracer'. The effectiveness demonstrated selected benchmark illustrating its capability to handle both non-degenerated MOPs efficiently.

Language: Английский

Citations

1
Multi-Objective Optimization of Bogie Stability for Minimum Radius Curve of Battery Track Engineering Vehicle DOI Creative Commons
Yang Shen, Jiayi Zhao, Chongyu Wang

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(12), P. 5231 - 5231

Published: June 17, 2024

A battery track engineering vehicle faces challenges such as derailment and other safety concerns when navigating an R20m minimum radius curve, primarily owing to its low vertical horizontal stabilities. To address these issues, a methodology integrating genetic optimization algorithms with rigid flexible coupled multi-body dynamics simulation is proposed optimize the primary suspensions of bogie vehicle. Initially, multi-objective model combining vehicles algorithm was formulated. Subsequently, optimal Latin hypercube design applied analyze sensitivity stability various suspension parameters. Finally, non-dominated sorting (NSGA-II) archive-based micro (AMGA) were enhance stability. Consequently, set parameter combinations obtained. notable enhancement observed in lateral optimized by 23.33% 3.5% traversing thereby establishing theoretical foundation for further improving running railway resolving shortcomings less research on smallest curve.

Language: Английский

Citations

0