Optimal design of Magneto-Rheological damper comparing different configura-tions by finite element...

Journal of Mechanical Science and Technology 28 (9) (2014) 3667~3677

www.springerlink.com/content/1738-494x DOI 10.1007/s12206-014-0828-5

Optimal design of Magneto-Rheological damper comparing different configurations

by finite element analysis† Mohammad Meftahul Ferdaus1, Muhammad Mahbubur Rashid1,*, Muhammad Hasibul Hasan3

and Mohammed Ataur Rahman2 1Department of Mechatronics Engineering, International Islamic University Malaysia, 50728, Kuala Lumpur, Malaysia

2Department of Mechanical Engineering, International Islamic University Malaysia, 50728, Kuala Lumpur, Malaysia 3Department of Materials & Manufacturing Engineering, International Islamic University Malaysia, 50728, Kuala Lumpur, Malaysia

(Manuscript Received March 17, 2014; Revised May 15, 2014; Accepted May 26, 2014)

----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

Abstract Magnetorheological (MR) damper is one of the most advanced applications of semi active damper in controlling vibration. Due to its

continuous controllability in both on and off state its practice is increasing day by day in the vehicle suspension system. MR damper’s damping force can be controlled by changing the viscosity of its internal magnetorheological fluids (MRF). But still there are some prob-lems with this damper such as MR fluid’s sedimentation, optimal design configuration considering all components of the damper. In this paper both 2-D Axisymmetric and 3-D model of MR Damper is built and finite element analysis is done for design optimization. Differ-ent configurations of MR damper piston, MR fluid gap, air gap and Dampers housing are simulated for comparing the Dampers perform-ance variation. From the analytical results it is observed that among different configurations single coil MR damper with linear plastic air gap, top and bottom chamfered piston end and medium MR fluid gap shows better performance than other configurations by maintaining the same input current and piston velocity. Further an experimental analysis is performed by using RD-8041-1 MR Damper. These re-sults are compared with the optimized MR Damper’s simulation results, which are clearly validating the simulated results.

Keywords: Magnetorheological damper; Axisymmetric; Optimal; Finite element; ANSYS ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- 1. Introduction

Magnetorheological dampers are known as smart devices due to their controllability in both on and off states. Last few years they have been investigated widely due to their huge advantages such as high viscosity control range, comparatively low cost, low power consumption and quick response, small size etc. They are becoming demandable in the automotive industry especially for improving driving conditions, and thereby increasing driver’s safety. Generally the MR damper consists of cylinder, piston, coil or solenoid as electromagnets and fluid. MR Damper’s piston and cylinder is made by soft magnetic materials so that their magnetic induction saturation would be high with small hysteresis loop area. As fluids these dampers don’t use traditional oil, instead they use magneto-rheological (MR) fluid. MR fluid is also known as smart fluid as they can change their rheological behavior according to the applied magnetic field [1-3]. Some desirable characteristics of MR fluids are low viscosity without applied magnetic field, high yielding stress, improved sedimentation stability, quick

response time etc. After applying magnetic field the fluid changes its viscosity very quickly as the fluid become magnet-ized. The magnetic particles suspended in the fluid align them-selves like chain which restricts the movement of the fluid. The yield stress of the fluid also increased and the maximum yield stress is about 100 kPa within a very short time. It seems that this liquid becomes semi-solid very quickly, which results an infinitely variable, controllable damper capable of large damp-ing forces. Due to these high advantages MR fluid dampers have a huge application predominantly in automotive industry including off-road vehicles. These dampers are being used in vehicle suspension system. BMW, General Motors and some other company and several military vehicles started using MR damper based suspension system. Its application is now not only restricted in vehicle suspension, it is also used in naval gun controlling [4], field of artillery, landing gear [5-7], pros-thetic limbs [8-10], optical polishing, washing machines [11], seismic vibration control of different civil structures [12-14] etc.

MR dampers huge advantages attract researchers from the first. Already much advancement has been accomplished by many researchers. Seiyed Hamid Zareh, Meisam Abbasi, Hadi Mahdavi and Kambiz Ghaemi Osgouie [15] developed a Neu-ral Network based Semi-Active controller using MR damper.

*Corresponding author. Tel.: +60 361964493, Fax.: +60 361964433 E-mail address: [email protected]

† Recommended by Associate Editor Seong Beom Lee © KSME & Springer 2014

3668 M. M. Ferdaus et al. / Journal of Mechanical Science and Technology 28 (9) (2014) 3667~3677

They also constructed the inverse neural network to analyze the inverse dynamics of the MR damper. Atabak Sarrafan, Seiyed Hamid Zareh, Amir Ali Akbar Khayyat and Abolghas-sem Zabihollah [16] describes a neuro-fuzzy control strategy for an offshore steel jacket platform where the MR damper is used to produce wave induced forces. Young-Won Yun, Hyung-Sub Bae, Myeong-Kwan Park [17] tested the possibil-ity of using MR Damper in controlling the blank holding force in drawing press. Kyoung Kwan Ahn [18] describes a self tuned fuzzy based MR damper modeling. In their modeling there is no need to calculate the time for model parameter generating. Yasrebi, Ghazavi and Mashhadi [19] presented an analytical and experimental modeling of Magneto-rheological Damper. Their finite element analysis is done by using ANSYS Software. ANSYS simulation results are compared with Dampers experimental results. In their analysis only the magnetic field effect on MR fluid that flows in the annular gap between cylinder and piston head is modeled. M.S.A. Khan, A. Suresh and N.S. Ramaiah [20] analyzed different 2-D Axi-symmetric MR models by finite element method using ANSYS Software. In their design optimization they consid-ered only piston design variation for analyzing the vibration controlling force. H. Zhang, C. Liao, W. Chen, S. Huang [21] has discussed MR Dampers Magnetic Design method; they also analyzed magnetic saturation by ANSYS. Mohammad Meftahul Ferdaus et al. [22] designed a self-sensing and self powered MR Damper where they showed Damper’s perform-ance evaluation with new sedimentally improved MR fluids. Z. Chao, F. Tyan, S. Tu, and W. S. Jeng [23] have done finite element analysis of a 2-D axisymmetric MR Damper. Ex-perimentally they analyzed Lord Corporation MR Damper RD-1005-3. Walid H. El-Aouar [24] has also analyzed 2-D axisymmetric MR Damper model. In his finite element analy-sis based model he has shown comparison between different dampers model for getting the maximum force. Q. H. Nguyen, S. B. Choi and K. S. Kim [25] also described a finite element analysis based MR damper design optimization. For optimiza-tion they have used only one model and considered force, control energy and time constant.

This paper described the optimal design of MR damper. For accuracy the finite element (FE) analysis is done by ANSYS software. Many models with different configuration have been built for optimization. The variations of models are according to different piston shape, different piston area, and different MR fluid gap. By considering all these input parameters mag-netic field strength and damping force has observed as output for getting the optimized design configuration. Experimental analysis has accomplished by using MR Damper, current con-troller and Universal Testing Machine. The analytical results have compared with experimental for validation.

2. Theoretical analysis for optimized damper’s design

MR damper is semi-active damper consists of damper hous-ing, piston shaft, inner and outer piston, piston guide, floating

piston, MR fluid and gas chamber. Inside the damper housing piston guides contain the outer piston. Inner piston is sur-rounded by the outer piston, but there’s a small gap between them for flowing MR fluids. The coil is housed inside the inner piston in such a way so that coil’s induced magnetic flux can be flow through the MR fluid. This magnetic field changes the MR fluid’s viscosity, as a result changes the force to move the piston through the MR fluids. As the current value increases, induced magnetic field strength increases, causes more force to move the piston. The combination of this inner and outer pistons, piston housing and coil form a MR valve structure. Structure of a cylindrical MR damper is pre-sented in Fig. 1.

From the structure it is seen that this MR valve divides the damper into two chambers, they are lower and upper chamber, fully filled with the MR fluid. As the piston moves, the MR fluid flows from upper to lower chamber or vice-versa through the MR fluid gap of MR valve. The remaining parts of the damper are floating piston and a pressurized gas cham-ber which is also known as accumulator as it provides a space for MR fluid to occupy in time of piston shaft insertion. It also provides a pressure offset so that the pressure in the low-pressure side of the MR valve does not create cavitation in the MR fluid, which may occur in case of pressure reduction be-low the MR fluid’s vapor pressure. Axisymmetric model for finite element analysis by ANSYS is actually based on the damper’s model described above.

In design optimization MR damper’s dynamic range is a very important factor. The dynamic range (D) is defined as the ratio between the total damper output force (F) and the uncon-trollable force (Fuc) where uncontrollable forces include the fluid viscosity force (Fη) and the friction force (Ff) [27]. The dynamic range can be expressed as:

fuc

uc

uc FFF

FFF

FFD

++=

+==

h

tt 1.

(1)

From Fig. 2, the fluid flux (q) in the direction of x-axis can

be represented by Eq. (2) as follows:

[ ] )(2

)(12

1121

32

31 hhhuhvhhh

dxdpq c

xo -+++-+-=

h. (2)

Fig. 1. MR damper configuration [26].

M. M. Ferdaus et al. / Journal of Mechanical Science and Technology 28 (9) (2014) 3667~3677 3669

The flow velocity ( cxu ) in the plug flow region is given by

following Eq. (3):

[ ]22 )(

21 hh

dxdpu c

x --=h

(3)

where from Fig. 2, 2 1 ,h R R= - 1 1 1 ,h r R= - 2 2 1 ,h r R= -

1 2 ;2m

R RR += 1 2 1 2, , ,R R r r are shown in Fig. 2. Rm is the

average radius of R1 and R2. The controllable force Ft represents the force due to the

field-induced yield stressτy [29] and can be written as

ymm

ymp

mp

hLhRR

hhRvhRv

F tp

thh

t)(

8.0)(12))((12

07.2 2

-÷÷ø

öççè

æ

+-

-+= . (4)

In designing the MR damper the dynamic range should be

as large as possible to maximize the effectiveness of the damper. To get the desired dynamic range shear force (Fτ) should be larger as it can be seen from Eq. (1). From Eq. (4) it is seen that Fτ has a proportional relational with yield stress (τy). By taking three dependent variables A, B and C Eqs. (2) and (4) can be simplified as

y

yyy

y BAAC

CCBAAF

tt

tttt +

+=÷÷ø

öççè

æ

++= 07.207.2

. (5)

In Eq. (5), 12 ( ),p mA v R hh= - 20.8 ,B h=

( ) .m mR R h LCh

p -=

The condition to get the maximum yield stress (τy-max) is

0)(

)()(07.2 2 =

+

-++=

y

yy

y BABACACBA

CddF

ttt

tt (6)

and this leads to

007.314.407.2 222 =++ CAABCCB yy tt . (7) The solution of Eq. (7) is

BAjy )6950480468.01( ±-=t (8)

where BAjy )6950480468.01( +-=t provides the maximum

yield stress and BAjy )6950480468.01( --=t provides the

minimum yield stress [30]. So the maximum and minimum shear force can be pre-

sented by Eq. (9) as follows:

CBAjF )28.807.1( ±-=t . (9)

Now, the viscous force can be written as

BAC

hRR

Fm

m

-= 4.0h . (10)

From Eqs. (1), (9) and (10) the maximum dynamic range

[31] can be written as

(11)

Dynamic range is proportional to shear force and a function

of gap dimension [32]. Gap size (h) is inversely proportional to the controllable force. So small gap size will increase the controllable force range, but when h is less than 0.5 mm, the viscous force (Fη) much faster than controllable force ( Ft ). This results a reduction in dynamic range. Again when the gap size rises, both Ft and Fη fall. Hence, it is very important to find out an optimal gap size which maximizes the dynamic range. The dynamic range not only reduces MR damper size but also improves damper performances.

This gap size optimization is analyzed and verified by finite element method with the help of ANSYS software. Necessity for design optimization of MR damper can be understood by some practical application such as for vehicle suspension de-sign, ride comfort and suspension travel are two performance indexes to be considered. High damping force is required to reduce the suspension travel, whereas low damping force is expected for improving ride comfort. Thus an optimal damper design is required. That’s why Not only the air gap size, but also the piston shape and area are also analyzed by FEA for getting the optimal model.

3. Modeling of MR damper using finite element

method

In MR damper the magnetic field is produced by an elec-tromagnet. Here in the ANSYS simulation model wound coil is considered as electromagnet and magnetic field provided by this wound coil is necessary to energize the MR fluid. By varying the current through the electrical coil the magnetic flux density can be varied and the MR fluid is energized ac-cordingly. In this Model there is a thin rectangular area among the engine, MR fluid gap and the electric coil, which is called as plastic linear gap. In this model the magnetic flux leakage

Fig. 2. Stress and velocity profiles in the annular duct [28].


out of engine or housing perimeter is considered near about zero and so saturation of any material does not occur. This permits a single iteration linear analysis of the model. This assumption makes the model small and analysis simple. In this model the non-magnetic air gap is considered to make possi-ble the quadrilateral mesh analysis. This quadrilateral mesh permits for a uniform thickness of the air gap next to the en-gine and the calculation of virtual work force is accomplished here. In MR damper DC current is supplied to the excitation coil. In this ANSYS MR damper model, the DC current is applied in the form of current density i.e. current in the coil area. In ANSYS, the current density is calculated as follows:

ANIJS = . (12)

In Eq. (1), N is the number of turns, I is the current, A is the

coil area and JS is the current density. The assumption of no leakage at the model perimeter means that the flux will be acting parallel to this surface. As a confirmation of this as-sumption the Flux Parallel boundary condition is enforcedly placed around the model where an iron circuit contains the flux. In postprocessing, Maxwell stress tensor and a virtual work calculation is used to summarize the forces for the en-gine, MR fluid and the damper housing. The computation of terminal parameters such as coil inductance is accomplished by the final postprocessing operation.

2-D Axisymmetric and a 3-D model of MR Damper are built in ANSYS 14.5 for getting optimized design. Static magnetic analysis is done by 2-D axisymmetric model as shown in Fig. 3. First step of this analysis is to create the phys-ics environment by selecting magnetic nodal option from preferences of ANSYS main menu. Then element addition process has accomplished. PLANE 13 has chosen as element. This element has quad 4 nodes. PLANE13 has a 2-D magnetic, thermal, electrical and piezoelectric field capability with cou-pling limitations between fields. Then the MR Damper’s 2D axisymmetric model has been created as shown in Fig. 3.

In Fig. 3 five different areas represents five different mate-rials of the model. Here the red color indicating inner piston or Engine area (A3). The pink is the linear plastic air gap. The sky blue is the coil area, the water blue is the combination of

outer piston and damper housing as both of them are made of same material.

3.1 Different simulation models with respect to inner piston

shape’s variation

For design optimization at first five different models having different piston shapes are designed, where number of sole-noid or coil stage is one. Model properties are can be summa-rized as below

Model 1: Number of coil stage: 1; Inner Piston shape: All plain ended; MR Fluid: MRF-132DG from Lord Corporation, housing dimension: 3.25×17.5 mm and area code: A1; MR fluid flow gap dimension: 0.5×17.5 mm and area code: A2; engine dimension: 11.25×17.5 mm and area code: A3; coil dimension: 2.5×7.5 mm and area code: A4.

Model 2: number of coil stage: 1; inner piston shape: top and bottom fillet ended; MR fluid: MRF-132DG from Lord Corporation, Housing dimension: 3.25×17.5 mm and Area code: A1; MR fluid flow gap dimension: 0.5×17.5 mm and area code: A2; engine dimension: 11.25×17.5 mm and area code: A3; coil dimension: 2.5×7.5 mm and area code: A4.

Model 3: number of coil stage: 1; inner piston shape: top and bottom chamfered ended; MR fluid: MRF-132DG from Lord Corporation, housing dimension: 3.25×17.5 mm and area code: A1; MR fluid flow gap dimension: 0.5×17.5 mm and area code: A2; engine dimension: 11.25×17.5 mm and area code: A3; coil dimension: 2.5×7.5 mm and area code: A4.

Model 4: number of coil stage: 1; inner piston shape: All fil-let ended; MR Fluid: MRF-132DG from Lord Corporation, housing dimension: 3.25×17.5 mm and area code: A1; MR fluid flow gap dimension: 0.5×17.5 mm and Area code: A2; angine dimension: 11.25×17.5 mm and area code: A3; coil dimension: 2.5×7.5 mm and area code: A4.

Model 5: number of coil stage: 1; inner piston shape: all

Fig. 3. MR Damper’s 2-D axisymmetric model.

(a) Model 1 (b) Model 2 (c) Model 3

(d) Model 4 (e) Model 5 Fig. 4. 2D axisymmetric view of different MR damper’s simulation model.


chamfered ended; MR fluid: MRF-132DG from Lord Corpo-ration, housing dimension: 3.25×17.5 mm and area code: A1; MR fluid flow gap dimension: 0.5×17.5 mm and area code: A2; engine dimension: 11.25×17.5 mm and area code: A3; coil dimension: 2.5×7.5 mm and area code: A4.

All these models are shown in Fig. 4. Fig. 4 represents different models of MR damper for single

coil and different piston shapes developed by ANSYS. From this directory using rectangular by dimensions all the above models are drawn.

3.2 Different simulation models with respect to inner piston area and MR fluid gap area variation

After changing the piston shape, the inner piston or engine area for all the models from Model 1 to Model 5 has been decreased by 25%. So all the dimensions of these new models will be same as the previous models, but the only changes in these models’ dimension is the new engine dimension and that is 8.44×17.5 mm. These new models are from Model 6 to Model 10 and they are similar with the model 1 to Model 5, respectively. Now again the MR fluid gap dimension has been changed i.e. increased by 20% with respect to the dimensions of the model 1 to model 5 and these new models are from Model 11 to Model 15. The MR fluid gap revised dimension is 0.6×17.5 mm.

3.3 Model meshing and solution

After building model and assigning element and materials attributes, the next step is meshing of the model. Meshing is an important part of the computer aided engineering simula-tion and finite element simulation process. Any finite element solution’s speed, accuracy and convergence etc. are influenced by mesh. Moreover, the time of meshing a model is often a major portion of the total time of executing the solution for getting results. So, the better and faster solution greatly de-pends upon more automated and better meshing tools. Here in ANSYS 14.5 version the meshing is very accurate and ana-lyzes the models quickly. In ANSYS mesh tool option the first step is to set areas from element attributes. This step is known as material properties specification step. Here, different areas are picked for their corresponding material number. Then it is important to specify meshing size control in air gap and finally meshing of the model using mesh tool. After meshing all the five models, the mesh plotted results with different materials are shown in Fig. 5. Actually there are six materials in the model, but in Fig. 5 only five numbers are displaying i.e. from 1 to 5. As outer piston and damper housing are made of same materials so one colored area represents them both and only one number is used.

After completing the meshing process the boundary condi-tions and loads are applied to the 2-D axisymmetric model. In this section the excitation current is applied to the coil.

The next step is the solution using solver. In ANSYS soft-

ware there are different kinds of solver such as Sparse solver, Frontal solver, Jacobi Conjugate Gradient (JCG) solver, In-complete Cholesky Conjugate Gradient (ICCG) solver, Pre-conditioned Conjugate Gradient (PCG) solver. Different solver has different kinds of advantages. The Frontal Solver which is a direct elimination solver works better when robust-ness is required in case of nonlinear analysis or when memory is limited. The frontal solver does not assemble the complete global matrix. Instead, ANSYS performs the assembly and solution steps simultaneously as the solver processes each element. Sparse Direct Solver is direct elimination solver too. In occasion of nonlinear analysis when robustness and solu-tion speed both are required in that situation Sparse Direct Solver works better. In case of linear analysis if iterative solvers are slow to converge especially for ill-conditioned matrices, such as ill shaped elements in such events Sparse Direct Solver also works better. Preconditioned Conjugate Gradient (PCG) Solver is not direct elimination solver but an iterative solver. Sometimes solution speed is crucial such as in linear analysis of large models. In such situation PGG works better. So they are well-suited for large models with solid elements. Incomplete Cholesky Conjugate Gradient (ICCG) Solver is an iterative solver. In some multiphysics applications solution speed is crucial. In such application ICCG Solver perform quickly whereas those application models are harder to converge in other iterative solvers. Jacobi Conjugate Gradi-ent (JCG) Solver is also an iterative solver. In some single field problems for example thermal, magnetics, acoustics or multiphysics problems the solution speed is very important. In such situation JCG solver performs better than the other solver. It is seen from the above explanation that Jacobi Conjugate Gradient (JCG) solver is best suited for MR Damper’s 2-D axisymmetric model. After solution from the General Posture option of the ANSYS software all the results are compared for getting the optimized MR damper’s model.

(a) (b) (c)

(d) (e) Fig. 5. Finite element mesh analysis of different damper’s models.


4. ANSYS finite element simulation result compari-son for the optimal damper design

Different MR dampers models have been analyzed for dif-ferent current. According to their magnetic field strength be-fore and after magnetic saturation, damping force value, re-sponse time model 2 that means piston with top and bottom chamfered ends Dampers shows the optimal results. One of the result comparisons of magnetic induction for different current among the models are shown in Table 1.

From Table 1 and Fig. 6 it is clear that among the all the models according to their B values, model 2 shows the maxi-mum B value for different current. B has a proportional rela-tion with the damping force and that model provided the maximum damping force and so is the optimal damper model.

This model’s magnetic flux lines, magnetic flux vector sum, 2-D axisymmetric nodal solution is shown in Fig. 7.

Further, in Fig. 7 ANSYS contour plot and vector plot solu-tion are illustrated. Fig. 7(b) represents magnetic flux lines after saturation that why a very few flux lines through the MR fluids. And Fig. 7(a) represents before saturation flux lines, as huge number of flux lines through MR fluids. Similarly in Fig. 7(c) the red color through the MR fluid represents high flux density, where in Fig. 7(d) green color represents low flux

density. From Fig. 7, the flux lines and density strength can be easily understood by the corresponding maximum and mini-mum value.

FEA nodal solution of the optimized 2-D and 3-D axisym-metric MR damper’s model before and after saturation are shown in Fig. 8.

In addition, a color variation is seen which is actually due to the magnetic field strength variation. The magnetic induction Fig. 8(b) values for all the colors are also displayed in Fig. 8. From those values it is obvious that red color represents maximum magnetic field strength and blue color represents minimum.

5. Experimental setup and result comparison for

damper’s characterization and optimization

MR damper has been observed experimentally with the help of Universal Testing Machine (UTM). Experimentally it has

Table 1. Magnetic induction comparison among different models at different models at different current.

Current, (A)

B for Model

1

B for Model

2

B for Model

3

B for Model

4

B for Model

5

B for Model

6

B for Model

7

B for Model

8

0.1A 0.2569 0.2670 0.2581 0.25613 0.2560 0.2441 0.2562 0.2458

0.2A 0.2877 0.3620 0.29865 0.2763 0.32088 0.2748 0.2967 0.2863

0.3A 0.4156 0.4692 0.4222 0.3965 0.4642 0.4027 0.4204 0.4099

0.4A 0.5339 0.6001 0.5371 0.5078 0.5941 0.5210 0.5352 0.5248

0.5A 0.6200 0.6862 0.6146 0.59275 0.6833 0.6071 0.6127 0.6023

0.6A 0.6756 0.7444 0.6594 0.6408 0.7412 0.6627 0.6575 0.6471

0.7A 0.7302 0.7987 0.7028 0.68682 0.7983 0.7173 0.7009 0.6904

0.8A 0.7842 0.8553 0.7456 0.7323 0.8525 0.7713960.7437 0.7333

0.9A 0.8385 0.912 0.7881 0.7777 0.9059 0.8279 0.7862 0.7758

1A 0.8918 0.9679 0.8304 0.8230 0.9291 0.8789 0.8285 0.8180

B for

Model 9 B for

Model 10 B for

Model 11 B for

Model 12 B for

Model 13 B for

Model 14 B for

Model 15

0.2550 0.2558 0.2442 0.2647 0.2490 0.2560 0.2527

0.2752 0.3207 0.2750 0.359 0.2895 0.2762 0.3176

0.3954 0.4641 0.4028 0.4668 0.4131 0.3964 0.4610

0.5066 0.5940 0.5211 0.5978 0.5280 0.5076 0.5909

0.5916 0.6832 0.6073 0.6838 0.6055 0.5926 0.6801

0.6397 0.7411 0.6628 0.7421 0.6503 0.6407 0.7380

0.6856 0.7982 0.7175 0.7964 0.6937 0.6867 0.7951

0.7312 0.8524 0.7715 0.8529 0.7365 0.7322 0.8493

0.7766 0.9058 0.8280 0.9096 0.7790 0.7776 0.9027

0.8219 0.9290 0.8791 0.9321 0.8213 0.8229 0.9259

Different MR Damper Model

Fig. 6. Magnetic induction comparison for MR damper models when the current varies from 0.1A to 1A.

(a) (b)

(c) (d) Fig. 7. Magnetic flux lines and flux density of Model 2 (a) and (c) before saturation; and (b) and (d) after saturation.


been analyzed by changing different parameters for charac-terization of the damper. For optimization the optimized damper model’s simulated results have been compared with those experimental results for validation.

5.1 Experimental setup

The experimental setup consists of MR damper, the current controller, and a Universal Testing Machine (UTM) as dis-played in Fig. 9.

The UTM is used to test and analyze the MR damper where input excitation is staircase step. UTM have different kinds of upper and lower head for different kinds of test. Compressor, grippers’ etc. different kinds of things can be attached with MR damper. It is difficult to attach the MR Damper with UTM by compressor or gripper due to piston’s round shape. As a solution two rectangular aluminum sheet have attached

with the top and bottom of the MR damper. Now, the Univer-sal Testing Machine’s upper and a lower gripper head can easily grasp the damper to create appropriate pressure. Upper end is the movable head that is operated by a hydraulic actua-tor which takes TRAPEZIUMX software generated signal from the computer attached with it. The lower head is con-nected with a load cell that helps to measure the applied force to the damper. A linear variable differential transformer (LVDT) sensor is integrated with the UTM. It helps to meas-ure the displacement of damper’s piston. During the experi-ment, a variable voltage was supplied from a DC voltage source to the current controller that provides the current exci-tation to the damper-coil. In this experiment for characterizing the MR damper different kinds of graphs has been generated such as force-displacement, force-time, and stress-strain, time displacement. The computer connected with the UTM export the required signal by using TRAPEZIUMX software of SHIMADZU. Stroke rate, stroke length and input currents are varied to characterize and evaluate the dampers performance. The simulation results are also compared with these experi-mental results to verify the optimal design. MR damper model used in experiment is RD-8041-1 from Lord Corporation. For controlling the current no commercial current controller is used because of their high price and long response time. A very simple current controller is designed using LM 317 volt-age regulator IC. This designed controller is very simple, cheap and also has a very quick response time. As input the current is varied from 0 to 1 Ampere.

Experimentally used MR damper has stroke length of total 74 mm. MR damper is connected to the UTM with the help of two rectangular aluminum support sheet. The upper sheet is coming inside the stroke area that’s why the total stroke can-not be used. Total Four different strokes are used and they are 10 mm, 20 mm, 30 mm and 40 mm, which is shown in Fig. 10.

Observing Fig. 10 carefully, it is seen that the 1st 10 mm stroke is after a certain distance which is due to the damper’s rectangular support.

5.2 Experimental and analytical result comparison

Experimentally damper’s force has been observed for dif-ferent stroke length such as 10 mm, 20 mm, 30 mm, 40 mm and stroke rate of 4 mm/min and 10 mm/min, when the cur-rent varies from 0.1 A to 1 A.

Fig. 11 shows force time curves for two different current i.e. 0.1A, 0.2A, when stroke rate was at 4 mm/min and stroke

(a) (b)

(c) (d) Fig. 8. FEA nodal solution of the optimized 2-D and 3-D axisymmetric model before magnetic saturation (a, c); and after magnetic saturation (b, d).

Fig. 9. Experimental setup of MR damper with universal testing ma-chine.

Fig. 10. MR damper’s different stroke lengths.


length was 10 mm. Here, in Fig. 11, the experimental results are compared with

simulation results of real MR damper model and optimized MR damper model. These results are for 10 mm stroke length and the piston velocity was maintained at 4 mm/min or 6.67×10-5 m/s. It is seen from Fig. 11 that for both current value, model 2 is providing the maximum force. Another ob-servation is that as the current is increasing the damping force is increasing. So in MR damper the current has a proportional relation with the provided damping force.

Fig. 12 shows force displacement curves for two different piston stroke rate i.e. 4 mm/min and 10 mm/min, when the current was 0.1 A as follows.

In Fig. 12 also the experimental result is compared with simulation result of real MR damper model and optimized MR damper model. These results are for 4 mm stroke length and the supply current was 0.1 A. For both stroke rate, the opti-mized model showing the best performance. As the stroke rate is increasing for the same stroke length the force value is in-creasing.

Fig. 13 shows force displacement curve for two different strokes where first stroke is 10 mm and second stroke is 40 mm, when the current was 0.1 A.

Here the curves are also a comparison among the experi-mental result and previously mentioned damper’s model. In this case the piston stroke rate was maintained at 4 mm/min

and the supply current was 0.1 A. Here, the optimal model also shows better performance compared to others. Here, also for the same stroke rate, as the stroke length is increasing the damping force is increasing.

Fig. 14 represents the force VS velocity curve comparison among experimental analysis, simulation analysis of real MR damper model and optimized MR damper model. Here, the velocity varies from -10 to 10 mm/min. From Fig. 14 it is clear that for any velocity optimized model is providing the

(a)

(b)

Fig. 11. MR damper’s force vs. time curve comparison among experi-mental and ANSYS simulation results at different current: (a) normal view; (b) zoomed view.

Fig. 12. MR damper’s force vs. displacement curve comparison among experimental and ANSYS simulation results at different piston stroke rate normal view and zoomed view respectively.

Fig. 13. MR damper’s force vs. displacement curve comparison among experimental and ANSYS simulation results at different stroke length Normal view and (B) zoomed view.


maximum force. So it can be concluded that MR damper’s damping force

has a proportional relationship with the input current to the damper and damper’s stroke length and stroke velocity. In all cases the simulation results of the optimized model have var-ied for justification.

6. Conclusions

Magnetorheological fluid damper is an advanced semi ac-tive device. This study was about the design optimization of this advance device. Both simulation and experimental analy-sis has been accomplished for the optimization. Finite element simulation has been accomplished has been accomplished with ANSYS software version 14.5. Analytically different design configuration has been developed by changing damper’s different physical parameters such as piston shape, piston area, MR fluid gap width etc. Five models with five different piston shapes have been considered, for each model piston area, MR fluid gap width has changed. All these mod-els are simulated at different current from 0 to 1 ampere, dif-ferent piston velocity and at different stroke. Analyzing the entire simulation results optimal design configuration has found and that was MR damper ANSYS simulation Model 2. The optimized model simulation result has been compared with experimental results for different current, stroke length and stroke rate. After analyzing and comparing all the results it is clear that damper Model 2 shows the optimal result in all cases.

Acknowledgment

This work supported by the Ministry of Higher Education, (Fundamental Research Grant Scheme), Malaysia. The au-thors would like to thank the Department of Mechatronics Engineering, International Islamic University of Malaysia for giving the chance to use the different equipment of the vibra-tion and smart Materials laboratory.

Nomenclature------------------------------------------------------------------------

MR : Magneto-Rheological D : Dynamic range F : Damper total output force Fuc : Uncontrollable force Ff : Friction force Fη : Fluid viscosity force Fτ : Controllable force JGG : Jacobi conjugate gradient UTM : Universal testing machine A : Ampere

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Mohammad Meftahul Ferdaus re-ceived the B.Sc. (Eng.) degree in Elec-trical and Electronic engineering from Rajshahi University of Engineering and Technology, Rajshahi, Bangladesh in 2011. Now he is doing his masters in Mechatronics Engineering from Interna-tional Islamic University Malaysia. He

is working as a research assistant in Mechatronics Engineering Department, International Islamic University Malaysia. He has published some papers in Indexed Journals and conference proceedings. His research interests are active and semi-active vehicle suspension system, smart materials, Electric and Hy-brid Vehicles.


Muhammad Mahbubur Rashid (M’07) received the B.Sc. (Eng.) degree in electrical and electronic engineering from Bangladesh University of Engi-neering and Technology, Dhaka, Bang-ladesh, in 1992, and the M.Sc. and Ph.D. degrees in electrical engineering from the University of Malaya, Kuala Lum-

pur, Malaysia, in 2003 and 2007, respectively. Since 2007, he has been working as an Assistant Professor and Associate Professor in the Department of Mechatronics Engineering, International Islamic University Malaysia, Kuala Lumpur. He has published more than 80 papers in journals and conference proceedings. His research interests include advanced control system and simulation and nonlinear modeling, industrial automation, instrumentation, neural networks, artificial intelli-gence, power electronics, and renewable energy.

Muhammad Hasibul Hasan has over ten years of research, teaching and in-dustrial experience. He received his BEng (Hons) in Mechanical Engineer-ing, BUET, Bangladesh, MSc (Eng) in Mechanical Engineering, Wayne State University, USA, Ph.D. in Mechanical Engineering, University of Nevada Las

Vegas, USA. His current research interests are High tem-perature application of super alloys, ANN, Creep-Fatigue, Fracture Mechanics, Reactive scheduling, Value Engineering and Manufacturing Engineering.

Ataur Rahman, Ph.D. is a Professor in the Department of Mechanical Engi- neering, Faculty of Engineering, Interna-tional Islamic University Malaysia since 1996. His research interests are green transportation system: EV/HEV, hybrid engine, intelligent power train for hybrid and electrical vehicle, intelligent steering

system and traction control system, electromagnetic actuated CVT and intelligent air-cushion vehicle for swamp and peat terrain. He has worked in The University of Tokyo, Japan, as a Visiting Fellow on the development of integrated instrumen-tation systems for Autonomous Vehicles. He has published 100 Journal articles including 60 ISI listed journal from his research work.

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