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Optimization calculation for parameters of heavy vehicle transmission system based on PARETO optimality solution

机译:基于Pareto Optimaly解决方案的重型车辆传输系统参数优化计算

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摘要

Heavy Vehicle (HV) transmission system parameter matching is very crucial for improving the performance of vehicle. In this paper, PARETO optimal theory is used for the multi-objective optimization design of the HV transmission system, a multi-objective optimization model is established with considering the two conflicting objective functions, which is namely, dynamic performance (DP) and fuel economy (FE) of the HV, and the transmission ratio of the system as design variable. With a case study of certain HV, the approximate model (AM) of the HV's CRUISE model is first built as a surrogate in the process of multi-objective optimization (MOO) in order to improve the accuracy and speed of the optimization calculation. Then, the MATLAB genetic algorithm (GA) toolbox is applied to solve this optimization problem, and some PARETO optimal sets are obtained. From the results, it could be seen that a well-distributed POS of the AM could be obtained from the proposed optimal approach. Furthermore, the PARETO set can provide more choices for engineering staff as they are given more design schemes, from which to select the most suitable transmission parameters according to the requirements of the vehicle's DP and FE.
机译:重型车辆(HV)传动系统参数匹配对于提高车辆性能非常重要。本文在考虑两种冲突的客观函数时建立了一种多目标优化设计的帕累托最优理论,这是一种多目标优化模型,即动态性能(DP)和燃料经济性(FE)的HV,以及系统的传输比为设计变量。通过对某些HV的案例研究,HV巡航模型的近似模型(AM)首先在多目标优化(MOO)过程中作为替代品,以提高优化计算的准确性和速度。然后,应用MATLAB遗传算法(GA)工具箱来解决该优化问题,并且获得了一些Pareto最佳集合。从结果中,可以看出,AM的分布良好的POS可以从所提出的最佳方法获得。此外,帕累托集可以为工程人员提供更多选择,因为它们具有更多的设计方案,可根据车辆DP和FE的要求选择最合适的传输参数。

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