Virtual Occupant Model with Active Joint Torque Control for Muscular Reflex

2018-01-1316

04/03/2018

Features
Event
WCX World Congress Experience
Authors Abstract
Content
Riding comfort on the seat is one of the important factors for vehicle comfort. To analyze riding comfort, there were some models for predicting human vibrations in the past studies. On the other hand, it is strongly affected by human body motion caused by vehicle excitation during driving especially low frequency, but it is difficult to predict human motion due to an unclear mechanism of muscle reflex. The purpose of this study is to construct virtual riding comfort testing simulation based on virtual prototyping of the seat. In this study, a virtual occupant model that predicts occupant motion on the seat against external excitation including muscle reflex for maintaining sitting posture constructed. The whole body was modeled as 15 segments biomechanical model (1D) with wobbling mass. Each joint has passive elastic torque and damping torque springs. Human body surface was modeled as rigid shape. The muscle reflex modeled as active joint torque with PID control for maintaining posture. Intrinsic, such as elastic spring forces that connect wobbling mass in the abdominal cavity, and extrinsic parameters, such as active torque control gain, were determined by 2 step optimization process for fit measured data for calibrating. Whole body model and seat FE model (3D) with excitation calculated at the same time to make it possible to predict human body motion on the seat. As the results of validations, simulated results were well agreed with measurement data of subjects on the conditions of translational excitations. And, further development issues and visions were discussed.
Meta TagsDetails
DOI
https://doi.org/10.4271/2018-01-1316
Pages
10
Citation
Hirao, A., Choi, H., Han, M., and Matsuoka, H., "Virtual Occupant Model with Active Joint Torque Control for Muscular Reflex," SAE Technical Paper 2018-01-1316, 2018, https://doi.org/10.4271/2018-01-1316.
Additional Details
Publisher
Published
Apr 3, 2018
Product Code
2018-01-1316
Content Type
Technical Paper
Language
English