2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM) 2017
DOI: 10.1109/aim.2017.8014069
|View full text |Cite
|
Sign up to set email alerts
|

Model-based longitudinal vibration suppression control for electric vehicles with geared in-wheel motors

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
4
0

Year Published

2020
2020
2022
2022

Publication Types

Select...
3
1

Relationship

1
3

Authors

Journals

citations
Cited by 4 publications
(4 citation statements)
references
References 12 publications
0
4
0
Order By: Relevance
“…4) The combination of feedforward and feedback controllers (indicated as FF+FB) in [37], see Fig. 8, for which the road profile is an unknown disturbance.…”
Section: Benchmarking Controllersmentioning
confidence: 99%
See 2 more Smart Citations
“…4) The combination of feedforward and feedback controllers (indicated as FF+FB) in [37], see Fig. 8, for which the road profile is an unknown disturbance.…”
Section: Benchmarking Controllersmentioning
confidence: 99%
“…In the pioneering study in [36], Fukudome proposes a proportional controller based on the longitudinal speed difference between the unsprung and sprung masses of an EV with in-wheel motors. A control structure consisting of feedforward and feedback contributions is presented in [37], where the road input is an unknown disturbance. The controller is tuned with the longitudinal dynamics model validated in [34], and the feedback contribution includes a deadtime compensator observer to provide robustness against communications delays.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…The resonance characteristics of components such as the suspension and tyres with respect to drivetrain inputs obtained using these analysis results were then applied to design a flattening feedforward controller based on a Nyquist plot. The resulting proposal greatly expanded the controllable driving range of IWMs [73].…”
Section: Sprung Mass Motion Controlmentioning
confidence: 99%