论文标题
一种在线牵引参数标识和映射的方法
A method of online traction parameter identification and mapping
论文作者
论文摘要
由于其操作范围，拖拉机，推土机等重型车辆（例如拖拉机，推土机等）的燃油消耗相当高。操作设置通常是固定的，并且不调整为环境因素，例如地面条件。然而，恰好的地面单位特性在能源效率方面具有决定性作用。优化后者将需要一种识别这些属性的方法。这是当前研究的核心问题。更具体地说，目标是从可用测量值（例如驱动列车信号）中估算地面条件，并建立对这些测量的地图。使用自适应的无气体卡尔曼滤波器估算地面条件参数。为案例研究提供了实际和估计的地面条件图。这样的映射可以看作是重型车辆最佳操作控制的关键里程碑。
Fuel consumption of heavy-duty vehicles such as tractors, bulldozers etc. is comparably high due to their scope of operation. The operation settings are usually fixed and not tuned to the environmental factors, such as ground conditions. Yet exactly the ground-to-propelling-unit properties are decisive in energy efficiency. Optimizing the latter would require a means of identifying those properties. This is the central matter of the current study. More specifically, the goal is to estimate the ground conditions from the available measurements, such as drive train signals, and to establish a map of those. The ground condition parameters are estimated using an adaptive unscented Kalman filter. A case study is provided with the actual and estimated ground condition maps. Such a mapping can be seen as a crucial milestone in optimal operation control of heavy-duty vehicles.
