工程车辆并行自适应神经网络自动换挡控制

Parallel Self-adaptive Neural Network Control for Engineering Vehicle Automatic Shift

为了解决工程车辆在重载作业时传动系统效率大幅下降的问题,以工程车辆"两参数"换挡规律为依据,提出一种并行自适应神经网络自动换挡控制的方法。结构上由神经网络控制、自适应神经网络模型、网络评价和运行监控模型组成。仿真结果表明,该控制方法提高了工程车辆液力机械传动系统效率,有效地克服了神经网络控制实时性差,难以在工程实际中应用的问题,实现了换挡控制的智能化。

The powertrain efficiency of the engineering vehicle under the heavy load is decreased obviously. In order to solve this problem, the method of parallel self-adaptive neural network was employed based on ＂two parameters＂ shift schedule, which of structure include neural network control, self-adaptive neural network model, network evaluation and running monitor model. The simulation results showed that the intelligent shift control could improve the powertrain efficiency of the engineering vehicle, and could overcome the low realtime behavior of neural network in the meantime.