Control of the 2S1 tracked vehicle suspension system based on sky-hook strategy and Kalman filter

2016 ◽  
Author(s):  
Jurkiewicz Andrzej ◽  
Janusz Kowal ◽  
Zajac Kamil
Keyword(s):  
Kalman Filter ◽  
Suspension System ◽  
Vehicle Suspension ◽  
Tracked Vehicle ◽  
Vehicle Suspension System

scholarly journals Sky-Hook Control and Kalman Filtering in Nonlinear Model of Tracked Vehicle Suspension System

2017 ◽  
Vol 11 (3) ◽  
pp. 222-228 ◽  
Author(s):  
Andrzej Jurkiewicz ◽  
Janusz Kowal ◽  
Kamil Zając
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Control Strategy ◽  
Ride Comfort ◽  
Logarithmic Spiral ◽  
Suspension System ◽  
Vehicle Suspension ◽  
Tracked Vehicle ◽  
Stiffness Characteristic ◽  
Vehicle Suspension System

AbstractThe essence of the undertaken topic is application of the continuous sky-hook control strategy and the Extended Kalman Filter as the state observer in the 2S1 tracked vehicle suspension system. The half-car model of this suspension system consists of seven logarithmic spiral springs and two magnetorheological dampers which has been described by the Bingham model. The applied continuous sky-hook control strategy considers nonlinear stiffness characteristic of the logarithmic spiral springs. The control is determined on estimates generated by the Extended Kalman Filter. Improve of ride comfort is verified by comparing simulation results, under the same driving conditions, of controlled and passive vehicle suspension systems.

A study of a Kalman filter active vehicle suspension system using correlation of front and rear wheel road inputs

2000 ◽  
Vol 214 (5) ◽  
pp. 493-502 ◽  
Author(s):  
F Yu ◽  
J-W Zhang ◽  
D. A. Crolla
Keyword(s):  
Kalman Filter ◽  
Rear Wheel ◽  
Suspension System ◽  
Estimation Accuracy ◽  
Vehicle Suspension ◽  
Vehicle Speed ◽  
State Variables ◽  
Performance Improvements ◽  
Vehicle Suspension System ◽  
Active Vehicle Suspension System

Based on a half-vehicle model, an algorithm is proposed for a Kalman filter optimal active vehicle suspension system using the correlation between front and rear wheel road inputs. In this paper, two main issues were investigated, i.e. the estimation accuracy of the Kalman filter for state variables, and the potential improvements from wheelbase preview. Simulations showed good estimations from the state observer. However, if the wheelbase preview algorithm is incorporated, the estimation accuracy for the additional states significantly decreases as vehicle speed and the corresponding measurement noises increase. Significant benefits from wheelbase preview were further proved, and the available performance improvements of the rear wheel station could be up to 35 per cent. Because of the feasibility and effectiveness of the proposed algorithm, and no additional cost for measurements and sensing needs, wheelbase preview can be a promising algorithm for Kalman filter active suspension system designs.

scholarly journals Thermal load evaluation of the tracked vehicle suspension system

2016 ◽  
Author(s):  
Е.Б. Сарач ◽  
◽  
А.А. Ципилев ◽  
О.А. Наказной ◽  
◽  
...  
Keyword(s):  
Thermal Load ◽  
Suspension System ◽  
Vehicle Suspension ◽  
Tracked Vehicle ◽  
Vehicle Suspension System ◽  
Load Evaluation
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