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A NOVEL APPROACH TO REAL-TIME FLEXIBLE MULTIBODY SIMULATION:SUB-SYSTEM GLOBAL MODAL PARAMETERIZATION.

机译:实时灵活的多体仿真的一种新方法:子系统全局模态参数化。

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摘要

This paper introduces a novel model reduction technique, namely Sub-System Global Modal Parameterization (SS-GMP), for real-time simulation of flexible multibody systems. In the past, other system-level model reduction techniques have been proposed for this purpose, but these were limited in applicability due to the large storage requirements for systems with many rigid degrees-of-freedom (DOFs). However, in the SS-GMP approach, the motion of a mechanism is split up into a global motion and a relative motion of the (sub-)system. The relative motion is then reduced according to the Global Modal Parameterization, which is a model reduction procedure suitable for closed chain flexible multibody systems. In combination with suitable explicit solvers, the SS-GMP approach enables (hard) real-time simulations due to the strong reduction in the number of DOFs and the conversion of a system of differential-algebraic equations into a system of ordinary differential equations. The proposed approach is validated numerically with a quarter-car model. This fully flexible mechanism is simulated faster than real-time on a regular PC with the SS-GMP approach while providing accurate results.
机译:本文介绍了一种新颖的模型简化技术,即子系统全局模态参数化(SS-GMP),用于柔性多体系统的实时仿真。过去,已为此目的提出了其他系统级模型简化技术,但是由于具有许多刚性自由度(DOF)的系统对存储的需求量很大,因此这些方法的适用性受到限制。但是,在SS-GMP方法中,机制的运动分为(子系统)的全局运动和相对运动。然后根据“全局模态参数化”(Global Modal Parameterization)减少相对运动,这是一种适用于闭链柔性多体系统的模型简化程序。结合合适的显式求解器,SS-GMP方法可实现(硬)实时仿真,这是因为自由度的数量大大减少并且将微分代数方程组转换为常微分方程组。所提出的方法在四分之一汽车模型上得到了数值验证。使用SS-GMP方法在完全正常的PC上模拟这种完全灵活的机制的速度比实时更快,同时提供了准确的结果。

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