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Sideslip estimation algorithm comparison between Euler angles and quaternion approaches with black box vehicle model

机译:黑匣子车辆模型的欧拉角和四元数方法的侧滑估计算法比较

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A black-box sideslip angle estimation scheme is presented in this paper. Here, two rotation approaches are considered and further compared while developing the complete algorithm. On the one hand the well known Euler angles and on the other hand an unitary quaternion approach. Both schemes, use measurements from an Inertial Measurement Unit as input without requiring further information about the vehicle. Extended Kalman Filter is used to estimate the stochastic states and provide robustness while improving algorithm's precision. The estimation response accuracy, robustness and performance is validated through real-time experiments with different road conditions and a wide speed range (20-190 km/h) without requiring further filter tunning. Moreover, the estimation scheme is able to provide the roll and pitch angles of the car.
机译:提出了一种黑匣子侧滑角估计方案。在这里,在开发完整算法时,考虑并进一步比较了两种旋转方法。一方面众所周知的欧拉角,另一方面是统一的四元数方法。两种方案都使用来自惯性测量单元的测量作为输入,而不需要有关车辆的更多信息。扩展卡尔曼滤波器用于估计随机状态并提供鲁棒性,同时提高算法的精度。估计响应的准确性,鲁棒性和性能可通过在不同路况和较宽的速度范围(20-190 km / h)上进行的实时实验进行验证,而无需进行进一步的过滤调整。而且,估计方案能够提供汽车的侧倾角和俯仰角。

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