A Data-driven Ergonomic Optimization Method for the eVTOL Intelligent Pilot Seat to Suppress Pilot BDFT

LI Bo; WU Hao; LU Xiaohui

doi:10.19554/j.cnki.1001-3563.2026.14.004

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Packaging Engineering ›› 2026, Vol. 47 ›› Issue (14) : 36-48. DOI: 10.19554/j.cnki.1001-3563.2026.14.004

Special subject: Innovation in Human Factors Engineering andIndustrial Design for Aviation Equipment

A Data-driven Ergonomic Optimization Method for the eVTOL Intelligent Pilot Seat to Suppress Pilot BDFT

LI Bo¹, WU Hao^1,*, LU Xiaohui^2,3

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Abstract

To address the problem that pilots of electric vertical takeoff and landing (eVTOL) aircraft in single-pilot mode experience biodynamic feedthrough (BDFT) induced by low-altitude turbulence and composite multi-rotor vibration, which degrades control precision and causes cumulative upper limb muscle compensation, the work aims to propose an ergonomic collaborative optimization design method for intelligent seats integrating aeronautical human factors expert experience with data-driven optimization. A four-stage design process was established, consisting of expert prior weighting, digital twin optimization, physical hard constraint projection, and human factor empirical verification. Aviation experts were organized via the Delphi method. The Analytic Hierarchy Process (AHP) was adopted to conduct pairwise comparisons of five ergonomic indicators, namely vibration comfort, control precision, attitude stability, muscle compensatory load and airworthiness safety response, to construct judgment matrices, followed by consistency tests. The normalized weights were taken as the prior coefficients of the multi-objective reward function in the Proximal Policy Optimization (PPO) algorithm. Secondly, a safety projection module defined by airworthiness geometric envelopes was embedded in the PPO action output layer to prevent out-of-bound states during training. Subsequently, the digital twin system was driven by typical Urban Air Mobility (UAM) vibration time series to iteratively obtain optimal schemes of seat design parameters. Subjective and objective dual-standard verification was conducted on test subjects relying on a single-axis electromagnetic vibration exciter bench and surface electromyography (sEMG). Experimental data demonstrated that the root-mean-square displacement of BDFT at the control stick under the optimal scheme was reduced by approximately 83% compared with the passive seat. All average indicators of the 12 test subjects exhibited positive improvements: the RMS value of surface electromyography (sEMG) for forearm flexors decreased by 38% (P<0.01), the Borg CR10 local fatigue score dropped from 6.8 to 2.3 (P<0.01) and the ISO 2631-1 subjective vibration comfort rating improved from 4.7 to 2.1 (P<0.01). These results verified the effectiveness of the proposed optimization method. The proposed method incorporates expert consensus data into the data-driven optimization loop in a structured manner, and guarantees flight safety boundaries via physical hard constraints. It can provide valuable references for the multi-objective ergonomic optimization design of eVTOL pilot seats.

Key words

eVTOL / intelligent pilot seat / biodynamic feedthrough (BDFT) / proximal policy optimization (PPO) / surface electromyography(sEMG)

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LI Bo, WU Hao, LU Xiaohui. A Data-driven Ergonomic Optimization Method for the eVTOL Intelligent Pilot Seat to Suppress Pilot BDFT[J]. Packaging Engineering. 2026, 47(14): 36-48 https://doi.org/10.19554/j.cnki.1001-3563.2026.14.004

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