A Novel Virtual Weighting-Based Pre-Design Method for Geometric Stability Assessment and Force Allocation in Hyperstatic Heavy-Duty Vehicles

Abstract

In the preliminary vehicle design process, Finite Element Analysis (FEA) and Multi-Body Dynamics (MBD) simulations require detailed physical parameters that are not available during the conceptual design phase. This study proposes a novel analytical algorithm that uses a virtual weighting approach to rapidly establish a reasonable baseline for these parameters, serving as an efficient analytical precursor to the physical tests, complex dynamic simulations, and optimization methods conventionally applied in later stages. In this study, a dual-layer model for rapid geometric assessment of stability indices and vertical loads in hyperstatic 8 × 8 vehicles is proposed. The model consists of a prognostic Weighted Singular Value Decomposition (SVD) layer and an operative Weighted Pseudo-Inverse (WPI) layer. In the SVD layer, a spectral mode alignment technique is proposed to evaluate the load transmission capacity to predict the stability limits under worst-case operating conditions including extreme maneuvers and wheel failures. In the WPI layer, the optimal distribution of wheel loads is computed under different operating conditions. For a uniform vehicle configuration, a high-resolution continuous sweep of lateral acceleration identifies the exact wheel lift-off point at 0.8621 g, perfectly aligning with the theoretical Static Stability Factor (SSF). By employing a virtual weighting strategy instead of relying on traditional exhaustive physical parameters, this parameter-independent framework provides an analytical load-boundary evaluation and determines the theoretical topological capacity, thereby acting as an essential tool for preliminary conceptual design prior to detailed MBD and FEA analyses.