Rollover Index for the Diagnosis of Tripped and Untripped Rollovers

Kazemian, Amir Hossein; Fooladi, M.; Darijani, H.

doi:10.1590/1679-78253576

“…Saga et al [11] investigated possibilities of a fuzzy technique in a vehicle dynamic analysis by computer simulations. Kazemian et al [12][13] presented the rollover index and new dynamics of suspension system in order to study the vehicle's dynamic behavior by computer simulations. Rajamani [14] and Gillespie [15] studied the vehicle dynamics and its subsystems such as tire in order to study on the vehicle's dynamic behavior, such as roll and yaw dynamics, by considering the dynamics' basics [16].…”

Section: Issn 1335-4205 (Print Version) Issn 2585-7878 (Online Version)mentioning

confidence: 99%

Dynamic Behavior of the Full-Car Model in the J-Turn Maneuver by Considering the Engine Gyroscopic Effects

Shahabi¹,

Kazemian²,

Farahat³

et al. 2021

Komunikácie

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This study presents a new dynamic modeling of a vehicle by considering the engine dynamics. By selecting the vehicle coordinate system as the reference frame, all the force-torque equations of the sprung mass and unsprung masses are derived in this coordinate system by using the Newton’s equations of motion. Unlike the previous researches, in this work the sprung mass of the vehicle is not considered as a rigid body. The dynamics of the sprung mass components, such as gyroscopic effects of the engine crankshaft, is considered. In order to study the vehicle's dynamic behavior, in the J-turn maneuver, the governing equations of the full-car model are evaluated and validated by the numerical simulation method and ADAMS/Car software. Based on the results, the maximum roll angle and roll rate of a vehicle reach about 8 degrees and 40 degrees per second, respectively.

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“…This research dealt with only simulations of the UGV to prove the applicability of adaptive control technique in mitigating the vehicle rollover; therefore, further research needs to be conducted on the real UGV. ; f [1] = intgData->f [1]; f [2] = intgData->f [2]; f [3] = intgData->f [3]; f [4] = intgData->f [4]; f [5] = intgData->f [5]; f [6] = intgData->f [6]; f [7] = intgData->f [7]; f [8] = intgData->f [8]; f [9] = intgData->f [9]; f [10] = intgData->f [10]; f [11] = intgData->f [11]; f [12] = intgData->f [12]…”

Section: Future Workmentioning

confidence: 99%

Unmanned ground vehicles: adaptive control system for real-time rollover prevention

Mlati

¹

,

Wang

²

2021

IJVAS

1

0

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Real-Time Rollover prevention of Unmanned Ground Vehicle (UGV) is very paramount to its reliability and survivability mostly when operating on unknown and rough terrains like mines or other planets.Therefore this research presents the method of real-time rollover prevention of UGVs making use of Adaptive control techniques based on Recursive least Squares (RLS) estimation of unknown parameters, in order to enable the UGVs to adapt to unknown hush terrains thereby increasing their reliability and survivability.The adaptation is achieved by using indirect adaptive control technique where the controller parameters are computed in real time based on the online estimation of the plant's (UGV) parameters (Rollover index and Roll Angle) and desired UGV's performance in order to appropriately adjust the UGV speed and suspension actuators to counter-act the vehicle rollover.A great challenge of indirect adaptive control system is online parameter identification, where in this case the RLS based estimator is used to estimate the vehicles rollover index and Roll Angle from lateral acceleration measurements and height of the centre of gravity of the UGV.RLS is suitable for online parameter identification due to its nature of updating parameter estimate at each sample time.The performance of the adaptive control algorithms and techniques is evaluated using Matlab Simulink ® system model with the UGV Model built using SimMechanics physical modelling platform and the whole system runs within Simulink environment to emulate real world application.The simulation results of the proposed adaptive control algorithm based on RLS estimation, show that the adaptive control algorithm does prevent or minimize the likely hood of vehicle rollover in real time

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“…But Formula (2.6) is more appropriate for accurate calculation of the rollover index as indicated in [9]. "Fig.…”

Section: Rollover Indexmentioning

confidence: 99%

“…The first step in enhancing the rollover resistance is to determine the rollover index (RI), where Rollover index is defined as the variable that indicates the likelihood for vehicle to roll over [9], and it has to be determined or calculated in real time for appropriate action to be taken to prevent roll over.…”

Section: Adaptive Rollover Preventionmentioning

confidence: 99%

Unmanned ground vehicles: adaptive control system for real-time rollover prevention

Wang¹,

Mlati²

2021

IJVAS

0

View full text Add to dashboard Cite

Real-Time Rollover prevention of Unmanned Ground Vehicle (UGV) is very paramount to its reliability and survivability mostly when operating on unknown and rough terrains like mines or other planets.Therefore this research presents the method of real-time rollover prevention of UGVs making use of Adaptive control techniques based on Recursive least Squares (RLS) estimation of unknown parameters, in order to enable the UGVs to adapt to unknown hush terrains thereby increasing their reliability and survivability.The adaptation is achieved by using indirect adaptive control technique where the controller parameters are computed in real time based on the online estimation of the plant's (UGV) parameters (Rollover index and Roll Angle) and desired UGV's performance in order to appropriately adjust the UGV speed and suspension actuators to counter-act the vehicle rollover.A great challenge of indirect adaptive control system is online parameter identification, where in this case the RLS based estimator is used to estimate the vehicles rollover index and Roll Angle from lateral acceleration measurements and height of the centre of gravity of the UGV.RLS is suitable for online parameter identification due to its nature of updating parameter estimate at each sample time.The performance of the adaptive control algorithms and techniques is evaluated using Matlab Simulink ® system model with the UGV Model built using SimMechanics physical modelling platform and the whole system runs within Simulink environment to emulate real world application.The simulation results of the proposed adaptive control algorithm based on RLS estimation, show that the adaptive control algorithm does prevent or minimize the likely hood of vehicle rollover in real time

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Rollover Index for the Diagnosis of Tripped and Untripped Rollovers

Cited by 18 publications

References 16 publications

Dynamic Behavior of the Full-Car Model in the J-Turn Maneuver by Considering the Engine Gyroscopic Effects

Dynamic Behavior of the Full-Car Model in the J-Turn Maneuver by Considering the Engine Gyroscopic Effects

Unmanned ground vehicles: adaptive control system for real-time rollover prevention

Unmanned ground vehicles: adaptive control system for real-time rollover prevention

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