The instrumented wheelset (IWS) is the most commonly used wheel–rail force test method, playing a crucial role in assessing the risk of derailment of railway vehicles. To enhance the accuracy of IWS, the study first investigates error sources and addresses the importance of eliminating the errors caused by contact point shift and wheel rotation. Functions related to the angular and radial position of strain gauges, the wheel–rail force amplitude and the wheel profile have been obtained. Parametric models for IWS error estimation have been established and used to transform the problem into an objective optimization problem. Validation through a case study using Particle Swarm Optimization with nonlinear constraints has confirmed the model’s convergence and stability. Comparative analysis, alongside stationary test, demonstrated a significant reduction in crosstalk and ripple errors, verifying the method’s effectiveness in enhancing the accuracy of wheel–rail force measurement.
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