Integrated Powertrain Control for Gear Shifting

Wan, Guoqiang; Huang, Ying; Zhang, Fu Jun; Chen, Yingjie

doi:10.4028/www.scientific.net/amm.148-149.725

Cited by 4 publications

(3 citation statements)

References 11 publications

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“…It's noteworthy that there are number of studies carried out recently in relation to these gears [39,40]. Many applications, e.g., automobile [41,42] and tunnel boring machines [43,44] require high reliability of gearboxes. Some neural network methods are also used for gear manufacturing to improve the accuracy of machine-tools [45,46].…”

Section: Introductionmentioning

confidence: 99%

A Gear Form-Grinding Optimization Method Based on Neural Network

ZHU

GENG²

2023

International Journal of Automotive Science and Technology

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Since the contact line equation is a transcendental equation, the relationship between the installation angle and the shape could not be expressed by explicit functions, which made it difficult to obtain the optimal shape, this paper firstly took three evaluation parameters of the shape, overrun, shift and offset as the objective function as well as the installation angle as variables the contact line optimization model was establish. Secondly, a neural network was introduced to solve the evaluation parameters. Through training the neural network by setting the installation angle as the input, the evaluation parameters as the output, the results show that the trained neural network can respond correctly, and has the advantages which the other method do not obtain. As an example of end relief modified helical gear, the results shows that the method can reduce the grinding errors effectively. Finally, the grinding experiments proven the effectiveness of the method.

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Section: Introductionmentioning

confidence: 99%

A Gear Form-Grinding Optimization Method Based on Neural Network

ZHU

GENG²

2023

International Journal of Automotive Science and Technology

View full text Add to dashboard Cite

show abstract

Section: Introductionmentioning

confidence: 99%

A Reliability-Enhanced Forming Grinding Method of Cylindrical Involute Gears for Electrical Vehicles

Geng¹,

2022

International Journal of Automotive Science and Technology

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A new form-grinding method of cylindrical involute gears for electrical vehicles (EVs) is proposed to obtain stable contact performance of gear tooth surfaces and improve their reliability based on a predesigned controllable second-order transmission error function. The predesigned second-order transmission error function is assigned to a gear drive based on design specifications of EVs. Mathematical models of modified gear tooth surfaces of the gear pair can be obtained by the predesigned second-order transmission error function. Moreover, a section profile of a form-grinding wheel for cylindrical involute gears can be determined by a coordinate transformation matrix during form-grinding and settings of computer numerical control form-grinding programs for this active design method. This approach is ultimately conducted on three cylindrical involute gear pairs to demonstrate its feasibility and effectiveness.

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“…100 Some studies focus on influences of fillet curves on bending strength of involute spur gears. One of the reasons is that analysis of gear bending strength becomes more difficult when several gear teeth are contacting in space simultaneously, especially for modified helical gears [5,26]. However, dedendum single circular gears have been used in most of gearboxes in Japan, also in some gearboxes.…”

Section: Introductionmentioning

confidence: 99%

Gear Bending Stress Analysis of Automatic Transmissions with Different Fillet Curves

Geng²

2021

International Journal of Automotive Science and Technology

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Gear bending strength is a core indicator to indicate reliability and operation performances of automotive transmissions. Fillet curve design of dedendum of gear teeth can improve their bending stress and complex tooth contact perfor-mance. Geometrical parameters of gears are considered important for the varia-tion of stresses in the design of gears. Bending stress analysis has been a key area of research to minimize failure and optimize design. This work presents a finite element (FE)-based analysis method of gear bending stress, which can be used for multiple spatial meshing gear teeth simultaneously. Three-dimensional (3D) models of helical gear with double and single circular fillet curves are estab-lished by using Pro/ENGINEER. By changing of meshing positions of gears, tooth contact analysis results along their paths of contact are obtained. Since FE-based tooth contact analysis are performed based on 3D models, the results of bending stress are reliable and authoritative. It is proved that bending stress of the gear with double circular fillet curves is 1.3~1.5 times as that of the gear with single circular fillet curves, which means that gear with single circular fillet curves has better loading capacity than gear with double circular fillet curves. The study will provide a good method for studying gear bending stress to improve gear de-sign of automotive transmissions.

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Integrated Powertrain Control for Gear Shifting

Cited by 4 publications

References 11 publications

A Gear Form-Grinding Optimization Method Based on Neural Network

A Gear Form-Grinding Optimization Method Based on Neural Network

A Reliability-Enhanced Forming Grinding Method of Cylindrical Involute Gears for Electrical Vehicles

Gear Bending Stress Analysis of Automatic Transmissions with Different Fillet Curves

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