TY  - JOUR
AU  - Chen, Ramesh
AU  - García, Rafiqul
TI  - On Vehicle Suspension Dynamics
JO  - Open Access Journal of Engineering Applications
PY  - 2012
VL  - 36
IS  - 2
SP  - 918
EP  - 921
AB  - As industrial automation continues to expand, ensuring the reliability of vehicle suspension dynamics grows steadily more important. In this study, Kalman filtering was employed to analyse and characterise the system under investigation. The model predicted vehicle suspension dynamics with an average error of less than 40%. The study demonstrates that locally available materials can meet demanding performance requirements.
KW  - vehicle suspension dynamics
KW  - Kalman filtering
KW  - harmonic analysis
KW  - cognitive radio
KW  - cryptography
KW  - computational fluid dynamics
SN  - 3105-7004
DO  - 10.55555/oajea.2012.3602.048
UR  - https://journal.bsaps.com/article/8965
ER  -