This work proposes an augmented extended Kalman filter based state-input estimator for mechanical systems defined by implicit equations of motion which is then applied to estimate the six wheel center loads and the strain field on a vehicle suspension test rig.Implicit equations of motion typically arise in the definition of flexible multibody models and also in their time resolution, because implicit time-discretization schemes are normally employed to obtain a stable solution. The presented methodology can be applied to such case and analytical expressions are derived for the necessary linearizations, providing the means for a computationally efficient estimation procedure.The six wheel center loads and the strain field on a vehicle suspension system are valuable quantities during the vehicle design phase (e.g. for durability analysis), hence they are often directly measured during elaborate full vehicle testing campaigns. This work demonstrates that a flexible multibody model representation allows to accurately reconstruct the time domain signals of the six loads and of the full strain field, starting from a minimal set of six measured strains, hence providing an appealing alternative to direct measurement methods. The experimental validation on the suspension test rig shows that all estimated quantities can be accurately reconstructed, given that the system simulation model incorporates an adequate level of accuracy.

Summary This paper introduces the novel flexible natural coordinates formulation to model small‐deformation multibody dynamics. The main contribution of this work is its resulting constant mass matrix and quadratic constraint equations devoid of any other nonlinearities. These properties are similar to those of a natural coordinates formulation for rigid multibody systems with the addition of constant damping and stiffness matrices to model the flexibility under the assumption of small deformations. As such, it is a straightforward extension to natural coordinates while maintaining its beneficial properties. The main concept of the current approach is to introduce ample redundancy in the set of generalized coordinates to simplify the kinematics ensuring the aforementioned properties and the similarity to a natural coordinates approach. This is not achievable by standard techniques that introduce redundancy. Not only does this offer a very simple equation structure but also interesting properties toward the development of system‐level model order reduction techniques for flexible multibody systems as well as a straightforward parameter gradient extraction. The formulation accuracy is validated with a floating frame of reference implementation.

Model-based force estimation is an emerging methodology in the mechatronic community given the possibility to exploit physically inspired high-fidelity models in tandem with ready-to-use cheap sensors. In this work, an inverse input load identification methodology is presented combining high-fidelity multibody models with a Kalman filter-based estimator and providing the means for an accurate and computationally efficient state-input estimation strategy. A particular challenge addressed in this work is the handling of the redundant state-description encountered in common multibody model descriptions. A novel linearization framework is proposed on the time-discretized equations in order to extract the required system model matrices for the Kalman filter. The presented framework is experimentally validated on a slider-crank mechanism. The nonlinear kinematics and dynamics are well represented through a rigid multibody model with lumped flexibilities to account for localized interaction phenomena among bodies. The proposed methodology is validated estimating the input torque delivered by a driver electro-motor together with the system states and comparing the experimental data with the estimated quantities. The results show the stability and accuracy of the estimation framework by only employing the angular motor velocity, measured by the motor encoder sensor and available in most of the commercial electro-motors.