Research on Subjective Rating Prediction Method for Ride Comfort with Learning Hitachi, Limited

Format:

Book

Conference/Event

Author/Creator:

Akai, Akihito, author.

Contributor:

Hirao, Ryusuke

Ichimaru, Nobuyuki

Conference Name:

11th International Styrian Noise, Vibration & Harshness Congress: The European Automotive Noise Conference (2020-11-03 : Graz, Austria)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2020

Summary:

Suspension is an important chassis part which is vital to ride comfort [1]. However, it is difficult to achieve our targeted comfortability level in a short time. Therefore, improving efficiency of damper development is our primary challenge. We have launched a project which aims to reduce the workload on developing dampers by introducing analytical approaches to the improvement of ride comfort. To be more specific, we have been putting effort into developing the damping force prediction, the vehicle dynamics prediction and subjective rating prediction. This paper describes subjective rating prediction method which output a subjective rating corresponding to the physical value of the vehicle dynamics with deep learning. As a result of verification using objective data which was not used for learning process, DNN (Deep Neural Network) prediction method could fairly precisely predict subjective rating of the expert driver

Notes:

Vendor supplied data

Publisher Number:

2020-01-1566

Access Restriction:

Restricted for use by site license