Optimization of nonlinear quarter car suspension–seat–driver model

Nagarkar, Mahesh; Patil, G. J. Vikhe; Patil, Rahul N. Zaware

doi:10.1016/j.jare.2016.04.003

Cited by 60 publications

(40 citation statements)

References 25 publications

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“…Through many years of investigation and practice, the quarter-car suspension nonlinear model is suitable for the research on the ride comfort control [27]. In this paper, the ride comfort controller of the hydro-pneumatic suspension is built based on the quarter-car model, which makes it easy to compute.…”

Section: Ride Comfort Controlmentioning

confidence: 99%

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Sliding Mode Switch Control of Adjustable Hydro-Pneumatic Suspension based on Parallel Adaptive Clonal Selection Algorithm

Zhou

Liu

et al. 2020

Applied Sciences

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The hydro-pneumatic suspension, as a widely used suspension for heavy vehicles, has been taken seriously by researchers for a long time because it is crucial in terms of handling stability, riding comfort, and driving safety of these vehicles. Most previous studies only discussed the control of ride comfort or vehicle handling stability of the suspension system separately. This article proposes a dynamic switch control strategy which can switch between ride comfort and handling stability controllers under different road surfaces and driving conditions. The load transfer ratio (LTR) is selected as the switch performance index, and it is calculated through a six-degrees-of-freedom (6-DOF) model. The ride comfort and handling stability controller of the hydro-pneumatic suspension are designed based on the sliding mode control theory. The objective functions of parameters optimization of the sliding mode controller (SMC) are obtained by means of analytic hierarchy process (AHP), and then the controller's parameters are optimized by the parallel adaptive clonal selection algorithm (PACSA). The simulation results based on MATLAB/Simulink show that: (1) the PACSA performs better than a genetic algorithm in terms of the parameters optimization of the SMC; (2) the proposed switch control strategy can simultaneously improve the ride comfort and handling stability under several typical steering maneuvers and various road profiles compared with the conventional SMC-controlled suspension. thus reduce the rollover propensity. Awad, Magdy Naeem [5] designed a hydro-pneumatic energy harvesting suspension system based on a PID-PSO (particle swarm optimization) controller, which achieved the maximum riding comfort as the peak values of the acceleration.However, past research on adjustable hydro-pneumatic suspension mainly focused on the analysis of vehicles' ride comfort or handling stability under different operating conditions separately, because it is difficult to achieve optimality in both aspects of ride comfort and handling stability due to the conflicting relationship between them. Hence, it is urgent to concentrate on the dynamic switch control strategy between the vehicle's ride comfort and handling stability to meet different requirements of working conditions.As a powerful controller, the sliding mode controller (SMC) has a great use in control systems because of its good robustness to external disturbance and fast dynamic response. Pradhan, Subarni [6] applied a composite SMC for wind power extraction in a remotely located solar PV-wind hybrid system. Biricik, Samet [7] used an SMC three-phase dynamic voltage restorer with adaptive notch filter to protect sensitive loads. Farahmandrad, Maryam [8] designed a fuzzy SMC for a cooperative robotic system with uncertainty for handling an object. Abtahi, S. Mahdi [9] suppressed chaotic vibrations in a suspension system of vehicle dynamics based on the optimal SMC. Inspired by the previous studies mentioned above, an SMC is used to control the hydro-pneumatic suspension system...

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Section: Ride Comfort Controlmentioning

confidence: 99%

“…Select λ high-affinity antibodies from the antibody population R ⊗ to replace λ low-affinity antibodies in Y . The value of λ can be obtained from Equation (27).…”

Section: Optimization Process Of Pacsamentioning

confidence: 99%

Sliding Mode Switch Control of Adjustable Hydro-Pneumatic Suspension based on Parallel Adaptive Clonal Selection Algorithm

Zhou

Liu

et al. 2020

Applied Sciences

View full text Add to dashboard Cite

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“…In addition, the test car is equipped with wire potentiometer, accelerometer, GPS, speed, tire slip angle, gyroscope, rotating wheel sensor that connected to the data acquisition system that has been installed with DEWESoft Software to collect and monitor the data. To check the performance on varying speed ranging from 20 to 120 km/h [10]. The gear shifting for the experiment need to follow the maximum speed of each gear ( Table 1).…”

Section: Design Of Experimentsmentioning

confidence: 99%

Investigation of passenger car using Macpherson strut for suspension system pt.1: Vehicle behaviour variation of time response

et al. 2016

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Abstract. It has been decade, researchers has been conducting researches on the topics concerning vehicle behavior. Suspension system, driving maneuver and road profile are the particular parameters in order to achieve the aim in vehicle behavior understanding. This paper combined these three criteria by means of using a passenger car equipped with MacPherson strut front suspension undergoes different driving behavior. The objective of this paper is to study the effect of passenger car equipped with MacPherson strut front suspension system vehicle behavior based on different driving maneuvers. For this study, Proton Persona Sedan 1.6 Manual Transmission Base Line was used to investigate the MacPherson strut suspension system. Data were collected using DEWESoft Software. As the velocity and direction varies with time, the vehicle response subjected to stationary excitation, while it varies with different velocity and different type of road. Acceleration, deceleration and bumpy test the suspension mechanism support the weight of the vehicle yet to cushion bumps and holes in the road. It can be concluded that the MacPherson strut suspension system has an effect on not only vehicle behavior but also comfort ride. These findings provide the following insights for future research in suspension vibration in order to optimize the performance of the MacPherson strut suspension system.

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“…Optimisation of nonlinear quarter car suspension-seatdriver model is carried out by Nagarkar 3 , et al, but the study considered only single DoF of vehicle. Stationary response of a military tracked vehicle was analysed by Ravishankar and Sujatha 4 .…”

Section: Introductionmentioning

confidence: 99%

“…is given as follows. In the original biodynamic model proposed by Nagarkar 3 , et al, four separate masses make the human body. One set of spring and damper connects the set of two body parts.…”

Section: Introductionmentioning

confidence: 99%

Comfort Level Refinement of Military Tracked Vehicle Crew through Optimal Control Study

2018

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Military tracked vehicle and crew are modelled together in this paper as integrated man-machine lumped parameter model, by integrating the simplified 5 degrees of freedom (DoF) tracked vehicle model, including seat and 4 DoF human bio-dynamic model, thus resulting in a 9 DoF simplified vehicle-occupant model. Then the natural frequency of major mass segment namely the chassis mass is obtained through simulation study, for a known road input. The value obtained is compared with that of an earlier research work, for validation of said man-machine model. Then focusing our study locally at crew seat location, parameters of crew seat suspension for ride comfort are optimised using the optimal digital state space controller designed for this purpose by implementing it in a 2 DoF occupant -seat suspension model and its Simulink model constructed. Simulation results illustrate the attainment of the goal by meeting the controller design requirements.

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Optimization of nonlinear quarter car suspension–seat–driver model

Abstract: Graphical abstract

Cited by 60 publications

References 25 publications

Sliding Mode Switch Control of Adjustable Hydro-Pneumatic Suspension based on Parallel Adaptive Clonal Selection Algorithm

Sliding Mode Switch Control of Adjustable Hydro-Pneumatic Suspension based on Parallel Adaptive Clonal Selection Algorithm

Investigation of passenger car using Macpherson strut for suspension system pt.1: Vehicle behaviour variation of time response

Comfort Level Refinement of Military Tracked Vehicle Crew through Optimal Control Study

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