The Perceptual Eigenmode Distortion (PEMD), an extension to the Eigenmode Distortion (EMD), is a method for objectively evaluating simulator motion fidelity, developed over the last few years. EMD assesses how the Motion Cueing Algorithm (MCA) distorts the vehicle's perceived eigenmodes. In this paper, EMD is extended by a human perception model, which helps to balance the various motion cue contributions in a more human-centered context. Additionally, a new automatic MCA tuning approach is introduced to create an MCA parameter set that is optimal in terms of eigenmode distortion. The method is applied to a combined linear model of the Cessna Citation 500 for asymmetrical flight and the Classical Washout Algorithm (CWA). A pilot-in-the-loop experiment was performed, with six pilots in the SIMONA Research Simulator, to compare the PEMD method's parameter set with sets designed with the current state-of-the-art method of the Objective Motion Cueing Test (OMCT), and with a baseline motion configuration, as well as a condition without any simulator motion. Throughout each run of the double-blind pairwise comparisons, the Dutch roll eigenmode was externally excited with a gust of semi-random amplitude and direction. Two hypotheses were tested using subjective preferences and through measuring the Dutch roll suppression performance. Subjective preferences varied between and within pilots, and similar results for PEMD and OMCT were found. A significant improvement in performance was found, however, between the no-motion condition and the PEMD. Although the perceived differences between a PEMD-tuned and alternative MCA settings seem very subtle, the improved mode suppression performance suggests the method having merit in flight scenarios where the aircraft's dynamic modes play an important role.