Gearbox parameter optimization method and system based on combined intelligent algorithm

An optimization method and technology of intelligent algorithm, applied in multi-objective optimization, design optimization/simulation, calculation, etc., can solve the problems of increasing the difficulty of optimal matching scheme of gearbox, high error rate, long development time, etc., to achieve accurate and fast The effect of multi-objective optimization, improving efficiency and accuracy

Pending Publication Date: 2022-07-15
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] The inventor found that in the existing gearbox design process, engineers mostly determine the gearbox parameters based on experiments and formula calculations, which takes a long time to develop and has a high error rate, which greatly increases the difficulty of obtaining the optimal matching solution for the gearbox

Method used

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  • Gearbox parameter optimization method and system based on combined intelligent algorithm
  • Gearbox parameter optimization method and system based on combined intelligent algorithm
  • Gearbox parameter optimization method and system based on combined intelligent algorithm

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Embodiment 1

[0059] like figure 1 As shown, Embodiment 1 of the present invention provides a gearbox parameter optimization method based on a combined intelligent algorithm, which combines the transition probability of the ant colony algorithm with the foraging behavior of the artificial fish swarm algorithm, and the pheromone concentration of the ant colony algorithm is combined. Incorporating the swarming behavior of the fish swarm algorithm to combine the ant colony algorithm to quickly converge to the local optimum and the artificial fish swarm algorithm to obtain a wide range of robustness advantages.

[0060] The ant colony algorithm is inspired by the foraging behavior of ants in nature. When ants search for food, they will release a pheromone on the path they pass through. The pheromone will accumulate and volatilize on the path over time. Ants have a higher probability to choose the direction with high pheromone concentration and continue to increase the concentration of pheromone...

Embodiment 2

[0095] Embodiment 2 of the present invention provides a gearbox parameter optimization system based on a combined intelligent algorithm, including:

[0096]The initial parameter determination module is configured to: determine the number of gears, the maximum transmission ratio and the minimum transmission ratio;

[0097] The transmission ratio equal-ratio series distribution module is configured to obtain the combination scheme of the transmission transmission ratio of the gearbox according to a certain value range and value step size for the transmission ratios of each gear assigned by the equal-ratio series;

[0098] The combination scheme acquisition module is configured to: determine the value range of each gear according to the transmission ratio of each gear allocated by the proportional series, and obtain the combination scheme of the transmission ratio of the gearbox;

[0099] The optimal transmission ratio scheme generation module is configured to: according to the o...

Embodiment 3

[0102] Embodiment 3 of the present invention provides a computer-readable storage medium on which a program is stored, and when the program is executed by a processor, implements the method for optimizing gearbox parameters based on a combined intelligent algorithm as described in Embodiment 1 of the present invention. step.

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Abstract

The invention provides a gearbox parameter optimization method and system based on a combined intelligent algorithm. The gearbox parameter optimization method comprises the steps that according to the gearbox gear number, the maximum transmission ratio and the minimum transmission ratio, the transmission ratio of each gear distributed by geometric progression is obtained; obtaining a combination scheme of the transmission ratio of the gearbox according to a certain value range and a certain value step length for the transmission ratio of each gear distributed by the geometric progression; according to the obtained gearbox transmission ratio combination scheme, a preset dynamic property model and a fuel economy model, based on a combination algorithm of an ant colony algorithm and an artificial fish swarm algorithm, multi-objective optimization is carried out to determine a Pareto optimal solution, and an optimal gearbox transmission ratio scheme is selected according to different requirements; according to the method, the ant colony algorithm can rapidly converge to a local optimal value and the artificial fish swarm algorithm can obtain a wide robustness advantage, a combined intelligent algorithm is formed, the dynamic property and the fuel economy are considered, more accurate and rapid multi-objective optimization is realized, and an optimal gearbox matching scheme is efficiently and accurately obtained.

Description

technical field [0001] The invention relates to the technical field of gearbox design optimization, in particular to a gearbox parameter optimization method and system based on a combined intelligent algorithm. Background technique [0002] The statements in this section merely provide background related to the present disclosure and do not necessarily constitute prior art. [0003] The gearbox can change the power output from the internal combustion engine to change the speed and torque, and the matching of the transmission ratio directly determines the power performance and fuel economy of the whole vehicle. Because the actual operating conditions are very complex, the number of gears for heavy commercial vehicles and tractors is very large, generally reaching 20 to 40 gears, which makes the combination scheme of the transmission ratio increase exponentially. [0004] The inventor found that in the existing gearbox design process, engineers mostly determined gearbox param...

Claims

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Application Information

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IPC IPC(8): G06F30/17G06F30/27G06K9/62G06N3/00G06F111/06G06F111/08
CPCG06F30/17G06F30/27G06N3/006G06F2111/06G06F2111/08G06F18/2411G06F18/214
Inventor 闫伟王俊博李国祥蔡彦彬张继伟穆松
Owner SHANDONG UNIV
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