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Sprung mass estimation for off-road vehicles via base-excitation suspension dynamics and recursive least squares

机译:通过基本激励悬架动力学和递推最小二乘估算越野车的弹簧质量

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This paper presents a novel method for identifying in real time the mass of an off-road vehicle using measurements of sprung and unsprung mass acceleration. The online estimate can be used for vehicle control strategies such as active safety control, traction control, and powertrain control. The online estimate is needed for vehicles whose mass varies significantly from one loading condition to another. Existing off-road mass estimation strategies that use suspension measurements typically require either known suspension force actuation or a priori knowledge of terrain characteristics. Our unique method for estimating online the mass of an off-road vehicle addresses existing limitations by applying base-excitation concepts to make the measured unsprung mass acceleration become a known input to the recursive least-squares estimator. We present computer simulations to demonstrate the method, and conclude that the method provides a practical solution for real-time, off-road vehicle mass estimation.
机译:本文提出了一种新方法,可通过测量簧上和簧下质量加速度来实时识别越野车的质量。在线估计可用于车辆控制策略,例如主动安全控制,牵引力控制和动力总成控制。在线估计对于质量从一种装载状态到另一种装载状态有显着变化的车辆是必需的。使用悬架测量的现有越野质量估计策略通常需要已知的悬架力致动或对地形特征的先验知识。我们用于在线估算越野车辆质量的独特方法通过应用基本激励概念来解决现有的局限性,以使测得的未悬挂质量加速度成为递归最小二乘估算器的已知输入。我们目前通过计算机仿真来演示该方法,并得出结论,该方法为实时,越野车辆质量估计提供了实用的解决方案。

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