Optimization Design of Distributed Drive Vehicle Reducer Based on Improved Particle Swarm Optimization Algorithm

Lin, Zhongyan; Zhang, Jiantao; Xu, Xipeng; Chen, Jiawei; Chen, Xinbo

doi:10.1109/wcmeim52463.2020.00162

Cited by 2 publications

(2 citation statements)

References 5 publications

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“…The application of the ADAMS software to analyze the dynamic characteristics of the gear drive has become an important research direction in recent years. 28,29 To verify the above design method of the ACG reducer, a virtual prototype model of the ACG reducer is established with the finite module of the ADAMS software and its dynamic characteristics are analyzed under the given drag torque ( T = 100 N · m ).…”

Section: Characteristics Of Acg Reducermentioning

confidence: 99%

Geometric design and dynamic characteristics of a novel abnormal cycloidal gear reducer

Gong

Luo

et al. 2023

Advances in Mechanical Engineering

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A precision reducer with a high ratio and a small size is essential for precise control of the position of a robotic arm. The rotate vector (RV) is a reducer widely applied in robotic joints. However, its complex structure, over-positioning and difficult assembly restrict its application industrial robots. Herein, a novel abnormal cycloidal gear (ACG) reducer is proposed. In comparison to the RV reducer, the proposed reducer has the characteristics of compact structure, less over-positioning and high ratio. The compound tooth profile of “epicycloid-involute hypocycloid” is used as the driving teeth for improving the performance of the reducer. The operating principle, mechanism design and reduction ratio of the proposed reducer is investigated, and the design method of the ACG tooth profile is also introduced. A dynamic characteristic model is established to verify the correctness of the design method of the reducer. A prototype of the ACG reducer is fabricated by using the computer numerical control (CNC) machining technology. Results show that the ACG reducer is capable to cover a wide range of reduction ratios with a simple mechanism. The numerical and theoretical results are in agreement, which depict the structural feasibility and correctness of the design method of the reducer. The adaptation of the ACG tooth profile as the driving teeth helps in improving the performance of the reducer.

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Section: Characteristics Of Acg Reducermentioning

confidence: 99%

Geometric design and dynamic characteristics of a novel abnormal cycloidal gear reducer

Gong

Luo

et al. 2023

Advances in Mechanical Engineering

View full text Add to dashboard Cite

show abstract

“…Therefore, it is critical to select an applicable tooth width. Here, the tooth width coefficient Φ d is the primary indicator of the tooth width design, which needs to meet the following constraints [42]:…”

Section: Tooth Width Coefficientmentioning

confidence: 99%

Optimization Design for the Planetary Gear Train of an Electric Vehicle under Uncertainties

Chen

Lin

et al. 2022

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The planetary gear train is often used as the main device for decelerating and increasing the torque of the drive motor of electric vehicles. Considering the lightweight requirement and existing uncertainty in structural design, a multi-objective uncertainty optimization design (MUOD) framework is developed for the planetary gear train of the electric vehicle in this study. The volume and transmission efficiency of the planetary gear train are taken into consideration as optimization objectives. The manufacturing size, material, and load input of the planetary gear train are considered as uncertainties. An approximate direct decoupling model, based on subinterval Taylor expansion, is applied to evaluate the propagation of uncertainties. To improve the convergence ability of the multi-objective evolutionary algorithm, the improved non-dominated sorting genetic algorithm II (NSGA-II) is designed by using chaotic and adaptive strategies. The improved NSGA-II has better convergence efficiency than classical NSGA-II and multi-objective particle swarm optimization (MOPSO). In addition, the multi-criteria decision making (MCDM) method is applied to choose the most satisfactory solution in Pareto sets from the multi-objective evolutionary algorithm. Compared with the multi-objective deterministic optimization design (MDOD), the proposed MUOD framework has better reliability than MDOD under different uncertainty cases. This MUOD method enables further guidance pertaining to the uncertainty optimization design of transportation equipment, containing gear reduction mechanisms, in order to reduce the failure risk.

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Optimization Design of Distributed Drive Vehicle Reducer Based on Improved Particle Swarm Optimization Algorithm

Cited by 2 publications

References 5 publications

Geometric design and dynamic characteristics of a novel abnormal cycloidal gear reducer

Geometric design and dynamic characteristics of a novel abnormal cycloidal gear reducer

Optimization Design for the Planetary Gear Train of an Electric Vehicle under Uncertainties

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