Research on Parameter Optimization of Tracked Vehicle Transmission System Based on Genetic Algorithm
| Autor: | Huiyan Chen, Haiou Liu, Lingjun Wei, Hongyan Zhang, Ziye Zhao, Xu Yi |
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| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9783030152345 CSIA |
| Popis: | The transmission system of tracked vehicle has great influence on the fuel economy and power performance of the whole vehicle. Its drivetrain parameter design is a multi parameter, multi-objective and nonlinear optimization problem, which is an important part of vehicle design. Based on the theoretical analysis of the optimization parameters and evaluation target, established the Smulink simulation model and normalization of tracked vehicle transmission system, according to the basic principle of genetic algorithm, computer simulation technology and optimization theory is applied to vehicle power transmission system parameter optimization design, the transmission ratio and the main reduction ratio as design variables, to guarantee the basis of fuel consumption as the target function to measure the tracked vehicle fuel economy, to the acceleration time and gradient optimization mathematical model of vehicle transmission system with a target shoe as constraint conditions. By comparing the optimization scheme and the original scheme, the traction characteristics and fuel economy are greatly improved. In the scheme, the objective function is greatly improved by improving the transmission ratio parameters of tracked vehicles, which proves that the optimization design method of tracked vehicles transmission system using genetic algorithm has been greatly improved. |
| Databáze: | OpenAIRE |
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