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Given the importance of comfort and safety in various driving circumstances, the suspension system emerges as the most crucial component. Two different suspension systems, passive (PSS) and semi-active (SASS), are compared for effectiveness in this research. MATLAB/Simulink is used for simulation, employing a representative two-degree-of-freedom car model to evaluate and compare the performance results of these systems. The differential equations of motion for the two systems are modeled and simulated using software, which illuminates how they would behave under the same parameters and circumstances. Additionally, a Magnetorheological damper (MR) model with a ¼ vehicle system is used to evaluate its behavior on various types of roads, including those with steps, bumps, and random inputs. This study utilizes the Bingham plastic model to compare the simulation results of SASS and PSS systems. After comparing the numerical and graphical results from the two systems, it is observed that SASSs with controllers perform better than PSSs in terms of suspension adjustment and response time. The SASS is superior to the PSS in suppressing oscillations by 55.12%, 77.47%, and 86.78% for step input, bump, and random inputs, respectively. Additionally, the SASS is faster in eliminating oscillations compared to the PSS by 54% and 51.7% for step input and bump inputs, respectively.
Rocznik
Tom
Strony
1--16
Opis fizyczny
Bibliogr. 24 poz., rys., tab., wykr.
Twórcy
autor
- Department of Mechanical Engineering, College of Engineering, University of Baghdad, IRAQ
autor
- Department of Mechanical Engineering, College of Engineering, University of Baghdad, IRAQ,
Bibliografia
- [1] Al-Ashtari W. (2023): Fuzzy logic control of active suspension system equipped with a hydraulic actuator.– Int. J.Appl. Mech. Eng., vol.28, No.3, pp.13-27, doi: 10.59441/ijame/172895.
- [2] Al-Araji H.M.H., Al-Zughaibi A.I.H. and Hussein E.Q. (2023): Testing two types of magneto-rheological (MR) dampermodels with quarter car suspension system response.– Int. J. Tech. Phys. Probl. Eng., vol.15, No.1, pp.52-61.
- [3] Wu J., Yang D., Cao W., Sun J., Wang Y. and Cao W.Z. (2023): Simulation study of semi-active suspension fuzzyadaptive PID control system.– J. Phys. Conf. Ser., vol.2501, No.1, doi: 10.1088/1742-6596/2501/1/012040.
- [4] Bhise A.R., Desai R.G., Yerrawar M.R.N., Mitra A.C. and Arakerimath D.R.R. (2016): Comparison between passiveand semi-active suspension system using Matlab/Simulink.– IOSR J. Mech. Civ. Eng., vol.13, No.04, pp.01-06, doi:10.9790/1684-1304010106.
- [5] Kumar S., Medhavi A., Kumar R., and Mall P.K. (2022): Modeling, analysis and PID controller implementation onsuspension system for quarter vehicle model.– Journal of Mechanical Engineering and Sciences, vol.16, No.2.,pp.8905-8916, doi: 10.15282/jmes.16.2.2022.08.0704.
- [6] Sinjari S. (2023): Comparing Optimization Algorithms for Parameter Identification of Sigmoid Experimental Studyon The Behaviour of a Magnetorheological (MR) Damper and Evaluation of Numerical Models.– Electronic Thesesand Dissertations, University of Windsor, https://scholar.uwindsor.ca/etd/9309.
- [7] Silva D.M.D., Avila S., Morais M.V.G. and Cavallini A.A. Jr (2023): Comparing optimization algorithms forparameter identiication of sigmoid model for MR damper comparing optimization algorithms for parameteridentification of sigmoid model for MR damper.– No.6, doi: 10.21203/rs.3.rs-2898815/v1.
- [8] Sassi S., Sassi A., Cherif K. and Tarlochan F. (2018): Magnetorheological damper with external excitation for moreefficient control of vehicles dynamics.– J. Intell. Mater. Syst. Struct., vol.29, No.14, pp.2919-2932, doi:10.1177/1045389X18781038.
- [9] Braz-Cesar M.T. and Barros R.C. (2010): Semi-active vibration control of buildings using MR dampers : numericaland experimental verification.– 14th Eur. Conf. Earthq. Eng., p.829.
- [10] Pepe G., Roveri N. and Carcaterra A. (2019): Experimenting sensors network for innovative optimal control of carsuspensions.– Sensors (Switzerland), vol.19, No.14, pp.14-17, doi: 10.3390/s19143062.
- [11] Kang B.H., Jo B.H., Kim B.G., Hwang J.H. and Choi S.B. (2023): Linear and nonlinear models for drop simulationof an aircraft landing gear system with MR dampers.– Actuators, vol.12, No.7, doi: 10.3390/act12070287.
- [12] Ochoa-Diaz C., Rocha T.S., Oliveria L.L. and Paredes M.E. (2014): An above-knee prosthesis withmagnetorheological variable-damping.– Proc. IEEE RAS EMBS Int. Conf. Biomed. Robot. Biomechatronics, No.8,pp.108-113, doi: 10.1109/biorob.2014.6913761.
- [13] Abdul Aziz M., Muhtasim S. and Ahammed R. (2022): State-of-the-art recent developments of largemagnetorheological (MR) dampers.– Korean Society of Rheology, Australian Society of Rheology, vol.34, No.2,doi: 10.1007/s13367-022-00021-2.
- [14] Zhang Y., Guo J., Yang J. and Li X. (2023): Recent structural developments and applications of magnetorheologicaldampers (MRD): a review.– Magnetochemistry, vol.9, No.4, doi: 10.3390/magnetochemistry9040090.
- [15] Elderrat H.I. (2013): Research Towards the Design of a Novel Smart Fluid Damper Using a McKibben Actuator.–Submitted for the degree of Master of Philosophy, University of Sheffield, p.65.
- [16] Kim B.G., Yoon D.S., Kim G.W., Choi S.B., Tan A.S., and Sattel T. (2020): Design of a novel magnetorheologicaldamper adaptable to low and high stroke velocity of vehicle suspension system.– Appl. Sci., vol.10, No.16, doi:10.3390/app10165586.
- [17] Zhang S., Shi W., and Chen Z. (2021): Modeling and parameter identification of MR damper considering excitationcharacteristics and current.– Shock Vib., vol.2021, No.3, doi: 10.1155/2021/6691650.
- [18] Yang G., Spencer B.F., Carlson J.D. and Sain M.K. (2002): Large-scale MR fluid dampers: modeling and dynamicperformance considerations.– Eng. Struct., vol.24, No.3, pp.309-323, doi: 10.1016/S0141-0296(01)00097-9.
- [19] Wang D.H. and Liao W.H. (2011): Magnetorheological fluid dampers: a review of parametric modelling.– SmartMater. Struct., vol.20, No.2, doi: 10.1088/0964-1726/20/2/023001.
- [20] Spencer Jr B.F., Dyke S.J., Sain M.K. and Carlson J.D. (1996): Phenomenological model of a magnetorheologicaldamper.– J. Eng. Mech., vol.230-238, No.123, pp.1-23, doi: 10.1061/(ASCE)0733-9399(1997)123.
- [21] Jamil M., Zafar S., and Gilani S.O. (2018): Designing PID controller based semi-active suspension system usingMATLAB simulink.– Lect. Notes Inst. Comput. Sci. Soc. Telecommun. Eng. LNICST, vol.224, No.7, pp.282-295,doi: 10.1007/978-3-319-94180-6_27.
- [22] Riazi B. (2021): Design and Investigation of a Semi-Active Suspension System in Automotive Applications. –Electronic Theses and Dissertations, University of Windsor, https://scholar.uwindsor.ca/etd/8683.
- [23] Eshkabilov S. (2016): Modeling and simulation of non-linear and hysteresis behavior of magneto-rheologicaldampers in the example of quarter-car model.– Engineering Mathematics, vol.1, No.1, pp.19-38, doi:10.11648/j.engmath.20160101.12.
- [24] Ismaili N. (2019): Performance analysis of passive, semi-active and active-controlled suspension systems usingMATLAB / SIMULINK.– Journal of Applied Sciences-Sut, vol.5, No.9, pp.94-105.
Typ dokumentu
Bibliografia
Identyfikator YADDA
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