Gear pair design optimization by Genetic Algorithm and FEA

Padmanabhan, S.; Ganesan, S.; Chandrasekaran, M.; Raman, V. Srinivasa

doi:10.1109/fame.2010.5714820

Cited by 29 publications

(5 citation statements)

References 14 publications

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“…Multi-objective optimizations (MOO) of cylindrical gears have also been performed, sometimes associated with contradictory require-ments. As an example, the following studies can be emphasised: (i) Sanghvi et al optimized the load carrying capacity and volume [5]; (ii) Yao optimized the bearing capacity coefficient, spur gear efficiency and centre distance [6]; (iii) Padmanabhan et al minimized the centre distance and overall mass, while improving performance in terms of transmitted power and gear efficiency [7]; (iv) Li et al minimized, the transmission error, contact stress and gearbox volume [8]; (v) Patil et al minimized the power losses and gearbox volume [9]. In these works, the gear design macrogeometry parameters were chosen as decision variables.…”

Section: Introductionmentioning

confidence: 99%

Optimization of energy efficiency and NVH behaviour of a helical gear unit

Ben Younes,

Rigaud,

Perret-Liaudet

et al. 2024

Mechanics & Industry

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The goal of this study is to perform a multi-objective optimization of a gear unit in order to improve its performance in terms of mechanical power losses, gear dynamics and equivalent sound power radiated by the housing. All these key performance indicators are closely related to the gear macro- and micro-geometry parameters. Decision variables chosen are the helix and pressure angles as macro-geometry parameters, and the amount and dimensionless roll length of tip relief as micro-geometry parameters corresponding to gear profile modifications. The multi-objective optimization is carried out under geometric and load capacity constraints using the evolutionary NSGA-II algorithm. Various results, observed in the form of 3D Pareto front confirm that improvements in energy efficiency and vibroacoustic performance are antagonistic. Nevertheless, a significant decrease of mechanical power losses is possible without degrading the vibroacoustic performance much. Otherwise, the correlation between the gear dynamic response and the equivalent radiated sound power (ERP) is partial. The minimization of the equivalent sound power radiated by the housing is not equivalent to the minimization of the gear transmission error fluctuation. These results underline the interest of modelling the whole gear unit to optimize its efficiency and NVH behaviour.

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Section: Introductionmentioning

confidence: 99%

Optimization of energy efficiency and NVH behaviour of a helical gear unit

Ben Younes,

Rigaud,

Perret-Liaudet

et al. 2024

Mechanics & Industry

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“…In this work, the investigation was on the structural soundness of current wheels and compute the stresses within them by use of finite element modelling and solution techniques. The accounted for the impact of the stress value range we acquired from Finite Element Analysis (FEA) to derive more precise estimates of the pressure needed to cause the wheel to expand (Padmanabhan et al 2010;Joel et al 2021;Somayaji et al 2022). The purpose of the research is to find, with the use of finite element analysis ways in which the existing wheels-over design might be made easier to implement.…”

Section: Introductionmentioning

confidence: 99%

Investigation of alloy materials on a sports bike wheel rim designs using finite element analysis

Padmanabhan,

Boopathi,

Kumar

et al. 2023

Multidiscip. Sci. J.

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Investigators are dedicating more work to the creation of lightweight vehicles as a result of the rising emphasis placed by the automotive industry on energy efficiency and environmental responsibility. While developing a wheel, it is important to keep both technology and safety considerations in mind simultaneously. Alloy materials are commonly used in the design of sports bike wheel rims due to their lightweight, strength, and durability. The ultimate goal of this study is to lay the groundwork for coming up with new designs for wheels and spokes that can be used on sports bike. In this work, it would be possible to compare how alloys of magnesium and titanium respond to stress and strain compared to structural steel materials. Using an equivalent stress and deformation investigation, two modern designs of wheel spokes for the sports bikes and three materials were compared. This study makes some insightful projections about the reliability of the structural design and provides useful references for the manufacture of alloy wheels. According to the stress analysis, the Ti alloy produces a stress concentration that is about 0.5% lower than on Model A and around 1% lower value for stainless steel on the Model B wheel rim design. Mg alloy has a deflection of about 77% and 53% more than stainless steel and titanium alloy, respectively, in the construction of the model A and B wheel rim.

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“…center distance, bearing capacity coefficient, and meshing efficiency of the spur gear using NSGA-II algorithm and decision maker which consists to select the optimal solution from Pareto frontier obtained from NSGA-II [20]. Padmanabhan et al used GA and analytic method, to minimize overall weight and center distance while maximizing the power delivered by the gear pair and efficiency of a spur gear pair, by considering module, tooth number and thickness as design variables [21]. Wei et al used an adaptive genetic algorithm to minimize gearbox volume, transmission error and contact stress using various design variables [22].…”

Section: Introductionmentioning

confidence: 99%

Multi-objective optimization of gear unit design to improve efficiency and transmission error

Younes

Changenet

Bruyère

et al. 2022

Mechanism and Machine Theory

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This study aims to implement multi-objective optimization of a gear unit in order to minimize the power loss and the vibrational excitation generated by the meshing, via a multi-scale approach that extends from gear contact to the complete transmission. All these indicators are closely linked to the macro and micro-geometry definition of the gear pair. The optimization is carried out using a genetic algorithm, namely the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). The design variables chosen for the problem are the pressure angle and the helix angle, as macro-geometry characteristics of the gear, and/or the length and the amount of tooth profile modifications, as micro-geometry characteristics of the gear. Constraints are imposed in order to not exceed a maximum bending stress at the tooth root of the gear and to not fall below a minimum total contact ratio. From the results obtained, it is found that the multi-objective optimization with both micro and macro-geometry parameters simultaneously gives different results than those obtained with macro-geometry first and then micro-geometry parameters. In order to study the importance, or not, to take into account the complete gear unit, a comparison is made between the local power loss generated by gear tooth friction and the total power loss in the single stage gear unit in terms of design variables values.

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Gear pair design optimization by Genetic Algorithm and FEA

Cited by 29 publications

References 14 publications

Optimization of energy efficiency and NVH behaviour of a helical gear unit

Optimization of energy efficiency and NVH behaviour of a helical gear unit

Investigation of alloy materials on a sports bike wheel rim designs using finite element analysis

Multi-objective optimization of gear unit design to improve efficiency and transmission error

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