基于神经网络的空气悬架系统匹配优
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Network Optimization on Matching of Air Suspension System
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    摘要:

    建立了空气悬架双质量模型,提出了基于RBF神经网络优化的系统阻尼和空气弹簧匹配的优化方法。匹配求优时,选取车身加速度和轮胎动载荷加权和最小值为优化目标,以悬架动行程最大值为约束。仿真结果表明,客车的平顺性和轮胎接地性都得到改善。台架试验与仿真结果基本吻合。

    Abstract:

    A double-mass model of air suspension was established. The method based on RBF network for matching optimization of air suspension systems damping and air spring was proposed. When the best match was chose, the vehicle body acceleration and wheels dynamic load were selected for minimum optimization objectives and the suspension dynamic travel was the constraint condition. Simulation results show that the bus ride comfort and road holding ability were improved. The simulation results agree with the testing data of the test bench.

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杨启耀,周孔亢,李敬东,徐兴,袁春元.基于神经网络的空气悬架系统匹配优[J].农业机械学报,2009,40(4):18-22. Network Optimization on Matching of Air Suspension System[J]. Transactions of the Chinese Society for Agricultural Machinery,2009,40(4):18-22.

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