Nonsmooth dynamics algorithms have been widely used to solve the problems of frictional contact dynamics of multibody systems. The linear complementary problems (LCP) based algorithms have been proved to be very effective for the planar problems of frictional contact dynamics. For the spatial problems of frictional contact dynamics, however, the nonlinear complementary problems (NCP) based algorithms usually achieve more accurate results even though the LCP based algorithms can evaluate the friction force and the relative tangential velocity approximately. In this paper, a new computation methodology is proposed to simulate the nonsmooth spatial frictional contact dynamics of multibody systems. Without approximating the friction cone, the cone complementary problems (CCP) theory is used to describe the spatial frictional continuous contact problems such that the spatial friction force can be evaluated accurately. A prediction term is introduced to make the established CCP model be applicable to the cases at high sliding speed. To improve the convergence rate of Newton iterations, the velocity variation of the nonsmooth dynamics equations is decomposed into the smooth velocities and nonsmooth (jump) velocities. The smooth velocities are computed by using the generalized-\(\mathbf{a}\) algorithm, and the nonsmooth velocities are integrated via the implicit Euler algorithm. The accelerated projected gradient descend (APGD) algorithm is used to solve the CCP. Finally, four numerical examples are given to validate the proposed computation methodology.

非光滑动力学算法已被广泛用于解决多体系统的摩擦接触动力学问题。事实证明，基于线性互补问题（LCP）的算法对于摩擦接触动力学的平面问题非常有效。但是，对于摩擦接触动力学的空间问题，尽管基于LCP的算法可以近似地评估摩擦力和相对切向速度，但基于非线性互补问题（NCP）的算法通常可以获得更准确的结果。本文提出了一种新的计算方法来模拟多体系统的非光滑空间摩擦接触动力学。在不逼近摩擦锥的情况下，圆锥互补问题（CCP）理论用于描述空间摩擦连续接触问题，以便可以准确评估空间摩擦力。引入预测项以使建立的CCP模型适用于高滑动速度的情况。为了提高牛顿迭代的收敛速度，将非光滑动力学方程的速度变化分解为平滑速度和非平滑（跳跃）速度。平滑速度是通过使用以下公式来计算的：非光滑动力学方程的速度变化分解为平滑速度和非平滑（跳跃）速度。平滑速度是通过使用以下公式来计算的：非光滑动力学方程的速度变化分解为平滑速度和非平滑（跳跃）速度。平滑速度是通过使用以下公式来计算的：\（\ mathbf {a} \）算法，并通过隐式Euler算法集成了非平滑速度。加速投影梯度下降（APGD）算法用于求解CCP。最后，给出了四个数值例子来验证所提出的计算方法。