Design of a Suspension Controller with an Adaptive Feedforward Algorithm for Ride Comfort Enhancement and Motion Sickness Mitigation
Open Access
Abstract
This paper presents a design method of a suspension controller with an adaptive feedforward algorithm for ride comfort enhancement and motion sickness mitigation. Recently, it was shown that motion sickness is caused by combined heave and pitch motions of a sprung mass within the range of 0.8 and 8 Hz. For this reason, it is necessary to design a suspension controller for the purpose of reducing the heave and pitch vibration of a sprung mass within this range. To represent the heave acceleration and the pitch rate of a sprung mass, a 4-DOF half-car model is adopted as a vehicle model. For easy implementation in a real vehicle, a static output feedback control is adopted instead of a full-state one. To reduce the heave acceleration of a sprung mass for ride comfort enhancement, a linear quadratic SOF controller is designed. To reduce the pitch rate of a sprung mass for motion sickness mitigation, a filtered-X LMS algorithm is applied. To validate the method, simulation on vehicle simulation software is conducted. From the simulation results, it is shown that the proposed method is effective for ride comfort enhancement and motion sickness mitigation.Keywords
This publication has 36 references indexed in Scilit:
- Autonomous driving system: A comprehensive surveyExpert Systems with Applications, 2023
- Inducers of motion sickness in vehicles: A systematic review of experimental evidence and meta-analysisTransportation Research Part F: Traffic Psychology and Behaviour, 2023
- An Improved FXLMS Algorithm Based on Error Weight for Active Vibration Control of PlatesJournal of Vibration Engineering & Technologies, 2023
- A survey on active noise control in the past decade—Part I: Linear systemsSignal Processing, 2021
- A survey on active noise control in the past decade–Part II: Nonlinear systemsSignal Processing, 2021
- Preview-based techniques for vehicle suspension control: a state-of-the-art reviewAnnual Reviews in Control, 2021
- On-line estimation of road profile in semi-active suspension based on unsprung mass accelerationMechanical Systems and Signal Processing, 2020
- Energy consumption sensitivity analysis and energy-reduction control of hybrid electromagnetic active suspensionMechanical Systems and Signal Processing, 2019
- Self-driving carsicknessApplied Ergonomics, 2016
- Survey and performance evaluation on some automotive semi-active suspension control methods: A comparative study on a single-corner modelAnnual Reviews in Control, 2012