Hybrid Energy Storage Matlab

International Journal of Electrical and Computer Engineering (IJECE)

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Journal homepage: http://iaescore.com/journals/index.php/IJECE Matlab/simulink simulation of unified power quality conditioner-battery energy storage system supplied by

Pv-Wind Hybrid Using Fuzzy Logic Controller

Amirullah1, Ontoseno Penangsang2, Adi Soeprijanto3

Accepted Dec 2, 2018

This paper presents performance analysis of Unified Power Quality Conditioner-Battery Energy Storage (UPQC-BES) system supplied by Photovoltaic (PV)-Wind Hybrid connected to three phase three wire (3P3W) of 380 volt (L-L) and 50 hertz distribution system. The performance of supply system is compared with two renewable energy (RE) sources i.e. PV and Wind, respectively. Fuzzy Logic Controller (FLC) is implemented to maintain DC voltage across the capacitor under disturbance scenarios of source and load as well as to compare the results with Proportional Intergral (PI) controller.

There are six scenarios of disturbance i.e. (1) non-linear load (NL), (2) unbalance and nonlinear load (Unba-NL), (3) distortion supply and non-linear load (Dis-NL), (4) sag and non-linear load (Sag-NL), (5) swell and non-linear load (Swell-NL), and (6) interruption and non-linear load (Inter- NL). In disturbance scenario 1 to 5, implementation of FLC on UPQC-BES system supplied by three RE sources is able to obtain average THD of load voltage/source current slightly better than PI. Furthermore under scenario 6, FLC applied on UPQC-BES system supplied by three RE sources gives significantly better result of average THD of load voltage/source current than PI. This research is simulated using Matlab/Simulink.

Wind Turbine

Copyright © 2019Institute of Advanced Engineering and Science. All rights reserved.

Institut Teknologi Sepuluh Nopember (Its),

Kampus ITS Keputih, Sukolilo, Surabaya 60111, Indonesia. 1.

Introduction

PV and wind are the most RE distributed generations (DGs) because they are able to convert sunlight and wind into power. PV and solar are the potential DGs sources since it only need sunlight to generate electricity, where the resources are available in abundance, free and relatively clean. Indonesia has enormous energy potential from the sun because it lies on the equator. Almost all areas of Indonesia get sunlight about 10 to 12 hours per day, with an average intensity of irradiation of 4.5 kWh/m2 or equivalent to 112.000 GW.

The potential of wind energy in Indonesia generally has a speed between 4 to 5 m/s and classified as medium scale with potential capacity of 10 to 100 kW. The weakness of PV and wind turbine besides able to generate power, they also produces a number voltage and current harmonics resulted by presence of several types of PV and wind turbine devices and power converters as well as to increase a number of non-linear loads connected to the grid,so finally resulting in the decrease in power quality.

In order to overcome and improve power quality due to presence of non-linear loads and integration of PV and wind turbine to grid, UPQC is a proposed. UPQC serves to compensate for source voltage quality problemsi.e. sag, swell unbalance, flicker, harmonics, and load current quality problems i.e. harmonics,

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unbalance, reactive currents, and neutral current. B. Han et. al and Vinod Khadkikar have investigated UPQC as one part of active power filter consisting of shunt and series active filters connected in parallel and serves as superior controller to overcome a number of power quality problems simultaneously. Series component has been responsible for reducing a number of interference on source side i.e. voltage sag/swell, flicker, unbalanced voltage, and harmonics. Shunt component has been responsible for addressing a current quality problems i.e.

low power factor, load current harmonics, and unbalanced load. [1, 2]. UPQC based on RE has been investigated by some researchers. There are two methods used to overcome this problem i.e. using conventional and artificial intelligence. Shafiuzzaman K.K., et.al have proposed system includes a series inverter, shunt inverter, and a DG connected to a DC link through a rectifier using PI. The system was capable of increase source voltage quality i.e. sag and interruption and load current quality, as well as transfer of active power on/off grid mode . The influence of DG on UPQC performance in reducing sag under conditions of some phase to ground faults to using DSTATCOM has been implemented by Norshafinash S., et.al. The DG was effective enough to help UPQC to improve sag . It was connected in series with load resulting better sag mitigation compared to system without DG. Implementation of UPQC using UVTG method with PI to reduce sag, swell, voltage/current harmonics has been doneby S. N. Gohil, et.al. Simulation of voltage distortion was made by adding 5th and 7th harmonics at fundamental source voltage, resulting in a reduction of THD source current and THD load voltage .

UPQC supplied by PV panels using boost converter, PI, MPPT P and O, and p-q theory has been proposed by Yahia Bouzelata at.al . The system was capable of compensate reactive power and reduce source current/load voltage harmonics, but did not discuss migitation of sag and interuption caused by PV penetration. Power quality enhancement of sag and source voltage harmonics on grid using UPQC supplied by PV array connected to DC link using PI compared with FLC has been done by Ramalengswara Rao, et.al.

Combination of UPQC and PV using FLC can improve source voltage THD better than PI . Amirullah et.al have researched a method for balancing current and line voltage, as a result of DGs of a single phase PV generator unit in randomly installed at homes through on a three phase four wire 220 kV and 50 Hz distribution line using BES and three of single phase bidirectional inverter. Both devices was capable of reduce unbalanced line current/voltage, but both of them were also capable of increase current/voltage harmonics on PCC bus .

Power quality migitation of UPQC on microgrid supplied by PV and wind turbine has been implemented by K S Srikanth et. al. It resulted that PI and FLC was able to improve power quality and reduce distortion in output power . The UPQC-wind turbine to provide active power to overcome low sag and interruption voltage to grid has been investigated by H.Toodeji, et.al. The model was used VSC as a rectifier on generator output and controlled so that maximum power desired can be generated by different speed wind turbines using PI . The UPQC-wind turbine connected to UPQC DC link was implemented by M. Hosseinpour, et al.

The proposed combination using PI was capable of compensate swell, interruption voltage, and reactive power both on on/off grid . R.Bhavani, et, al have researched on UPQC controlled by FLC to improve power quality in a DFIG wind turbine connected grid. FLC can improve power quality i.e. sag voltage and load current harmonics better than PI . Power quality enhancement on wind turbine and BES with PI connected grid on PCC bus using UPQC has been implemented by S.RajeshRajan, et al. BES was installed to maintain and stabilize active power supply under different wind speed .

This research will analyze UPQC-BES performance supplied by PV-wind hybrid connected to 3P3W of 380 volt (L-L) and 50 hertz distribution system.The performance of supply system is compared with two RE sources i.e. PV and Wind, respectively. BES serves to store excess energy produced by three RE sources and distribute it to load if necessary, to prevent interruption voltage, and to adjust charging and discharging of energy in battery. BES is also expected to store excess power produced by three RE combinations and use it as backup power. FLC is proposed and compared with PI to control variable of DC voltage and DC reference voltage input to generate reference current source in current hysteresis controller on shunt active filter.

DC voltage controller in shunt active filter and series active filter is used to migitate power quality of load voltage and source current.Performance of two controllers are used to determine load voltage, source current, describes proposed method, model of UPQC-BES system supplied by three RE sources i.e. PV, wind, and PV-wind hybrid, simulation parameters, PV and PMSG wind turbine model, series and shunt active filter, as well as application of PI and FLC method for proposed model. Section 3 shows results and analysis about performance of THD analysis on the proposed model of three RE sources connected to DC link of UPQC-BES system using PI and FLC. In this section, six disturbance scenarios are presented and the results are verified with Matlab/Simulink. Finally, this paper in concluded in Section 4.



Matlab/simulink simulation of unified power quality conditioner-battery energy storage… (Amirullah)

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2.

2.1. Proposed Method

Figure 1 shows proposed model in this research. The RE sources based DGs used i.e. PV, Wind Turbine, and PV-Wind Turbine Hybrid connected to 3P3W distribution system with 380 volt (L-L) and 50 Hz frequency, through UPQC-BES system. PV array produce power under fixed temperature and radiation as well as connect to UPQC-DC link through a DC/DC boost converter. The maximum power point tracking (MPPT) method with Pertub and Observer (P and O) algorithms helps PV produce maximum power and generate output voltage, as the input voltage for DC/DC boost converter. The converter serves to adjust duty-cycle value and output voltage of PV as its input voltage to produce an output voltage corresponding to UPQC DC link voltage.

Wind turbine type used is a permanent magnetic synchronous generator (PMSG) with variable speed and fixed voltage which generating power and is connected to UPQC DC link circuit through AC/DC bridge rectifier. The rectifier helps to change AC PSMG stator output voltage to DC voltage through LC circuit that serves to filter and smooth it before connected to UPQC-DC link.BES connected to the UPQC-DC link circuit serves as energy storage and is expected to overcome interruption voltage and overall help UPQC performance to improve voltage and current quality on source and load bus. Simulation parameters proposed in this study is shown in Appendix Section. Power quality analysis is performed on PV, Wind, PV-Wind Hybrid respectively, connected to 3P3W system through UPQC DC-link (on-grid) using BES circuit. Single phase circuit breakers (CBs) are used to connect and disconnect PV, Wind, and Hybrid PV-Wind respectively with UPQC DC-link.

There are six disturbance scenarios i.e. (1) NL, (2) Unba-NL, (3) Dis-NL, (4) Sag-NL, (5) Swell-NL, and (6) Inter-NL. In scenario 1, the model is connected a non-linear load with RL and LL of 60 Ohm and 0.15 mH respectively. In scenario 2, the model is connected to non-linear load and during 0.3 s since t=0.2 s to t=0.5 s connected to unbalance three phase load with R1, R2, R3 as 6 Ohm, 12 Ohm, 24 Ohm respectively, and value of C1, C2, C3 as 2200 μF. In scenario 3, the model is connected to non-linear load and source voltage generating 5th and 7th harmonic components with individual harmonic distortion values of 5% and 2% respectively.

In scenario 4, the model is connected to non-linear load and source experiences a sag voltage disturbance of 50% for 0.3 s between t=0.2 s to t=0.5 s. In scenario 5, the model is connected to a non-linear load and source experiences a swell voltage disturbance of 50% for 0.3 s between t=0.2 s to t=0.5 s. In scenario 6, the model is connected to non-linear load and source experiences an interruption voltage interference of 100% for 0.3 s between t=0.2 s to t=0.5 s. FLC is used as a DC voltage control in a shunt active filter to improve the power quality of the load voltage and current source and compare it with PI controller. Each disturbance scenario uses a PI controller and FLC so that the total of 12 disturbances. The result analysis of research was carried out i.e.

(1) voltage and current on source or poin common coupling (PCC) bus, (2) voltage and current on load bus, (3) harmonic voltage and harmonic current on source bus and (4) harmonic voltage and harmonic current on load bus. The final phase is to compare performance of UPQC-BES system on-grid supplied by PV, Wind, PV-Wind Hybrid respectively using two controllers to improve power quality of load voltage and source current under six disturbance conditions.

Upqc-Bes System

Figure 1. Proposed model of UPQC-BES system supplied by PV, Wind, and PV-Wind Hybrid

2.2. Photovoltaic Model

Figure 2 shows the equivalent circuit and V-I characteristic of a solar panel. A solar panel is composed of several PV cells that have series, parallel, or series-parallel external connections .

(B)

Figure 2. Equivalent circuit and V-I characteristic of solar panel The V-I characteristic of a solar panel is showed in (1):

(1)

where IPV is the photovoltaic current, Io is saturated reverse current, ‘a’ is the ideal diode constant, Vt=NSKTq-1 is the thermal voltage, NS is the number of series cells, q is the electron charge, K is the Boltzmann constant, T is the temperature of p–n junction, RS and RP are series and parallel equivalent resistance of the solar panels. IPV has a linear relation with light intensity and also varies with temperature variations.

Io is dependent on temperature variations. The values of Ipv and Io are calculated as following (2) and (3):

(3)

In which IPV,n, ISC,n and VOC,n are photovoltaic current, short circuit current and open circuit voltage in standard conditions (Tn=25 C and Gn=1000 Wm-2) respectively. KI is the coefficient of short circuit current to temperature, ∆T=T-Tn is the temperature deviation from standard temperature, G is the light intensity and KVis the ratio coefficient of open circuit voltage to temperature. Open circuit voltage, short circuit current and voltage-current corresponding to the maximum power are three important points of I-V characteristic of solar panel. These points are changed by variations of atmospheric conditions. By using (4) and (5) which are derived from PV model equations, short circuit current and open circuit voltage can be calculated in different atmospheric conditions.

2.3. Pmsg Wind Turbine

Wind turbine is one of part of an integrated system, which can be divided into two types i.e. fixed and variable speed wind turbines. In fixed speed type, rotating speed of turbine is fixed and hence, frequency of generated voltage remains constant, so it can be directly connected to the network. In this case, maximum power can not always be extracted by wind. On the other hand, on variable speed, turbine can rotate at different speeds, so maximum power can be generated in each wind speed by MPPT method . The advantage of

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using a PMSG over a synchronous generator and DFIG machine because it has high efficiency and reliability. Due to the elimination of rotor external excitation, machine size, and cost also decreases, making PMSG to be more controlled easily with feedback control system. PMSG has become an attractive solution on wind generation systems with variable speed wind turbine applications . Figure 3 and 4 shows model of PMSG wind turbine and wind turbin power characteristic curve.

Figure 4. Wind Turbin Power Characteristic Curve

The output power of wind turbine can be expressed using (6), (7), and (8) .

(8)

Where λ is the speed-tip ratio, Vwindis wind speed, R is blade radius, ωr is rotor speed (rad/sec), ρ is the air density, CP is the power coefficient, PM is the output mechanical power, and TM is output torque of wind turbine. The CP coefficient is dependent on the pitch angle value, at which rotor blade can rotate along axis and tip- speed ratio λ expressed in (9).

1.2 Pu

Max. power at base wind speed (5 m/s) and beta = 0 deg

Turbine Output Power (Pu)

Turbine Power Characteristics (Pitch angle beta = 2 deg)

(9)

Where β is a pitch angle blade. In a fixed pitch type, the value of β is set to a fixed value.

2.4. Control Of Series Active Filter

The main function of series active filter is as a sensitive load protection against a number of voltage interference at PCC bus. The control strategy algorithm of the source and load voltage in series active filter circuit is shown in Figure 5. It extracts the unit vector templates from the distorted input supply. Furthermore, the templates are expected to be ideal sinusoidal signal with unity amplitude. The distorted supply voltages are measured and divided by peak amplitude of fundamental input voltage Vm give in (10) .

(10)

A three phase locked loop (PLL) is used in order to generate a sinusoidal unit vector templates with a phase lagging by the use of sinus function. The reference load voltage signal is determined by multiplying the unit vector templates with the peak amplitude of the fundamental input voltage Vm. The load reference voltage (VLa*, VLb*, Vc*) is then compared against to sensed load voltage (VLa, VLb, VLc) by a pulse width modulation (PWM) controller used to generate the desired trigger signal on series active filter.

Voltage Magnitude

Figure 5. Control strategy of series active filter

2.5. Control Of Shunt Active Filter

The main function of shunt active filter is mitigation of power quality problems on the load side. The control methodology in shunt active filter is that the absorbed current from the PCC bus is a balanced positive sequence current including unbalanced sag voltage conditions in the PCC bus or unbalanced conditions or non- linear loads. In order to obtain satisfactory compensation caesed by disturbance due to non-linear load, many algorithms have been used in the literature. This research used instantaneous reactive power theory method "p- q theory". The voltages and currents in Cartesian abc coordinates can be transformed to Cartesian αβ coordinates as expressed in (11) and (12) .

(12)

The computation of the real power (p) and imaginary power (q) is showed in (13). The real power and imaginary are measured instantaneously power and in matrix it is form is given as.The presence of oscillating and average components in instantaneous power is presented in (14) .

Where P

= direct component of real power, p~ = fluctuating component of real power, q

= Direct

component of imaginary power, q~ = fluctuating component of imaginary power. The total imaginary power (q) and the fluctuating component of real power are selected as power references and current references and are utilized through the use of (15) for compensating harmonic and reactive power .

P

, is obtained from voltage regulator and is utilized as average real power. It can also be specified as the instantaneous active power which corresponds to the resistive loss and switching loss of the UPQC. The error obtained on comparing the actual DC-link capacitor voltage with the reference value is processed in FLC, engaged by voltage control loop as it minimizes the steady state error of the voltage across

Ci

) as required to meet the power demand of load are shown in (15). These currents are represented in α-β coordinates. The phase current is required to acquire using (16) for compensation. These source phase currents (

) Are Represented In A-B-C Axis Obtained

from the compensating current in the α-β coordinates presented in (16) . Figure 6 shows a control of shunt active filter.

Figure 6. Control Strategy Of Shunt Active Filter

The proposed model of UPQC-BES system supplied by three RE sources is shown in Figure 1. From the figure, we can see that PV is connected to the DC link through a DC-DC boost converter circuit. The PV partially distributes power to the load and the remains is transfered to three phase grid. The load consists of non linear and unbalanced load. The non-linear load is a diode rectifier circuit with the RL load type, while the unbalanced load is a three phase RC load with different R value on each phase. In order to economically efficient, PV must always work in MPP condition. In this research, MPPT method used is P and O algorithm. The model is also applied for UPQC-BES system which is supplied by wind and PV-wind hybrid respectively. In order to operate properly, UPQC-BES system device must have a minimum DC link voltage (Vdc). The value of common DC link voltage depends on the nstantaneous energy avialable to UPQC is defined

(17)

where m is modulation index and VLL is the AC grid line voltage of UPQC. Considering that modulation index as 1 and for line to line grid voltage (VLL=380 volt), the Vdc is obtained 620, 54 volt and selected as 650 volt.

The input of shunt active filter showed in Figure 5 is DC voltage (Vdc) and reference DC voltage

Is As One Of Input Variable To Generate The

reference source current (Isa*, Isb*, and Isc*). The reference source current output is then compared to source current (Isa, Isb, and Isc) by the current hysteresis control to generate trigger signal in IGBT circuit of shunt active filter. In this research, FLC as DC voltage control algorithm on shunt active filter is proposed and compared with PI controller. The FLC is capable of reduce oscilation and generate quick convergence calculation during disturbances. This method is also used to overcome the weakness of PI controller in determining proportional gain (Kp) and integral gain constant (Ki) which still use trial and error method.

P

as the input variable to result the reference source current on current hysteresis controller to generate trigger signal on the IGBT shunt active filter of UPQC using PI controller (Kp=0.2 and Ki=1.5). By using the same procedure,

P

is also determined by using FLC. The FLC has been widely used in recent industrial process because it has heuristic, simpler, more effective and has multi rule based variables in both linear and non-linear system variations. The main components of FLC are fuzzification, decision making (rulebase, database, reason mechanism) and defuzzification in Figure 7. The output membership function is generated using inference blocks and the basic rules of FLC as shown in Table 1.

Z

The fuzzy rule algorithm collects a number of fuzzy control rules in a particular order. This rule is used to control the system to meet the desired performance requirements and they are designed from a number of intelligent system control knowledge. The fuzzy inference of FLC using Mamdani method related to max-min composition. The fuzzy inference system in FLC consists of three parts: rule base, database, and reasoning mechanism . The FLC method is performed by determining input variables Vdc (Vdc-error) and delta Vdc (ΔVdc-error), seven linguistic fuzzy sets, operation fuzzy block system (fuzzyfication, fuzzy rule base and defuzzification), Vdc-error and ΔVdc-error during fuzzification process, fuzzy rule base table, crisp value to

P

is one of input variable to obtain compensating currents

Ci

) in (16). During fuzzification process, a number of input variables are calculated and converted into linguistic variables based on a subset called membership function. The error Vdc (Vdc-error) and delta error Vdc (ΔVdc-error) are proposed input variable system and output variable is

. To Translate These Variables, Each

input and output variable is designed using seven membership functions: Negative Big (NB), Negative Medium (NM), Negative Small (NS), Zero (Z), Positive Small (PS), Positive Medium (PM) and Positive Big (PB). The membership functions of crisp input and output are presented with triangular and trapezoidal membership functions. The value of Vdc-error range from -650 to 650, ΔVdc-error from -650 to 650, and

P

from -100 to 100. The input and output MFs are shown in Figure 8.

Deployment In Out-Of-Position Situations

D. Bendjaballah1, A. Bouchoucha1, M. L. Sahli1,2* and J-C. Gelin2

Abstract

Side-impact collisions represent the second greatest cause of fatality in motor vehicle accidents. Side-impact airbags have been installed in recent model year vehicle due to its effectiveness in reducing passengers’ injuries and fatality rates. In meeting these requirements, simulations of folding and deploying airbags are very useful and are widely used. The paper presents a simulation method for the deploying airbags using three materials in different working conditions. Finite element analysis is primarily used to evaluate this concept. In these simulations, the gas flow is described by the conservation laws of mass, momentum, and energy. The numerical results indicate that the FE method in this paper is capable of capturing airbag deploying process accurately.

Keywords: Airbag simulations, Out-of-position, Crash, Modeling, Out-of-position

Background

The passive safety of cars has become a very high prior- ity issue for the automotive industry. Today, there are not only one or two airbags in a car; certain models have ten times more than that. With the increasing usage of airbags, the number of accidents where the airbag itself can cause an injury to the occupant also increases

(Augenstein Et Al. 2003; Gabauer And Gabler 2010;

Audrey et al. 2011). As is well known, safety belts are also now devices designed to provide protection to the users of vehicles during crash events, minimizing the loads necessary to adapt their movement to the move- ment of the car (Freesmeier and Butler 1999; Schmitt et al. 1997). In general, the seat belt is designed to restrain the occupant in the vehicle and prevent the

Occupant From Having Harsh Contacts With Interior

surfaces of the vehicles. The airbag acts to cushion any impact with vehicle structure and has positive internal pressure, which can exert distributed restraining forces over the head and face. As a safety component of auto- mobile, an airbag decreases occupants’ injury likelihood effectively in case of an accident (Ruff et al. 2007). These safety elements can reduce the death rates on the roads, and its protection effects have been widely approved (Crandall et al. 2001; Teru and Ishikawa 2003). With computational tools such as finite element methods designed for dynamic contact problems, crashworthiness simulations can now be used with reliable accuracy to evaluate occupant protection in various collision condi- tions with safety metric/parameters such as acceleration, head injury criteria, intrusion distance, intrusion vel- ocity, and neck forces (neck injury risk or whiplash).

Thus, new types of airbag products are being developed to handle different collision scenarios.

Become Standard Equipment On Most New Passenger

vehicles (Braver and Kyrychenko 2004; Teng et al. 2007; Yoganandan et al. 2007). The airbag cushion is com- posed of a woven fabric which is rapidly inflated during a car crash. The airbag dissipates the passenger’s kinetic energy thereby reducing injury through biaxial stretching of the fabric bag and escaping gas through vents. There- fore, the performance of the airbag is greatly influenced by the mechanical properties of the fabric. Generally, air bags are designed to deploy in a crash that is equivalent to a vehicle crashing into a solid wall at 8 to 14 mph.

Air bags most often deploy when a vehicle collides with another vehicle or with a solid object like a tree. There are various types of airbags: frontal, side-impact, and curtain airbags. In general, the passenger side airbags are usually larger than the driver airbags (see Fig. 1).

Besançon, France

© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Bendjaballah et al. International Journal of Mechanical

Doi 10.1186/S40712-016-0070-2

Extensive studies have shown that the airbag deploy- ment in load cases consists of two occupant loading phases: a punch-out effect where the airbag bursts out of its container with the airbag and airbag module cover accelerating towards the occupant and a second loading phase during which the airbag is taking on its deployed shape and volume (membrane-loading effect). Bankdak et al. (2002) developed an experimental airbag test system to study airbag-occupant interactions during close proximity deployment. The results provided insight for simulating the effect of inflation energy and mass flow on target response. Bedard et al. (2002) found that while left-side (driver-side) impacts accounted for only 13.5% of all crashes, the fatality rate among these

Crashes Was 68.3% In Comparison To Front Impact

(48.3%), right-side impact (31.3%), and rear impact (38.4%). These studies underscore the importance of oc- cupant safety during side-impact collisions. In the last years, the current market requested to reduce the time and cost airbag development. In order to achieve this result, virtual simulations play an important role since they allow to minimize the number of experimental tests (Pei et al. 2013; Cao et al. 2014). Several simulation models of airbag were established (Wang et al. 2007). It is feasible to optimize the parameters of airbag deploy- ment using simulation technology. Experimental and numerical studies have quantified injury risks to close- proximity occupants from deploying side airbags. These studies have focused on the prevention of the most ad- verse effects of airbag deployment (Duma et al. 2003).

Other studies have proposed airbag characteristics to minimize particular biomechanical responses (Haland and Pipkorn 1996). In a more recent study, Marklund and Nilsson (2003) compared deformation patterns with experimental data as well as the computational costs associated with three different airbag deployment simu- lation methods; they concluded that the SPH method is relatively inexpensive and produces incremental deform- ation patterns that compare most closely to the experi- mental results. The process of inflation of an airbag is one of the determining factors in saving lives. The duration from the initial impact of the crash to the full inflation of an airbag is about 40 ms, and during this time, the airbag goes from being in a folded state to a fully inflated state, with a high internal pressure. After achieving this state, the airbag begins to deflate, thus providing a nice cushion for the body impacting it.

Ideally, the person in the crash should come into contact with the airbag at this time. In the present study, a large volume passenger side airbag model is developed to handle different collision scenarios. The main aim is evaluate the performance of deploying of passenger side airbag using finite element methods (FEM).

Materials

The tensile specimens were made in different airbags (P: Peugeot, R: Renault, and VW: Volkswagen) with a length of 200 mm long and a width of 40 mm. Table 1 shows the mechanical properties of the airbag.

Tensile Tests

To determine the mechanical properties of the material of airbag used in the test pieces, tensile tests were performed on Lloyd EZ20 universal testing machine in Constantine. These tests were conducted using rect- angular samples. The axial force and axial displacement acquired during a test are converted into stress and the strain in order to be used for the fabric material model.

The continuous recording of the stress-strain data was performed during both the load and unload phases. A minimum of five samples were made in order to check the repeatability of the measurements. All the data was collected by using a PC-based data acquisition system and analyzed by commercial software. The picture frame test device that is made for this study is shown in Fig. 2.

Fig. 1 a Frontal and side airbags. b Oblique view of facet occupant model in sitting posture following airbag deployment (Lim et al. 2014)

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Bendjaballah et al. International Journal of Mechanical and Materials Engineering (2017) 12:12

Page 2 Of 9

Figure 3 shows the stress-strain relationship of the airbag sample under axial tensile loads. The results are showing a linear increase in extension with the increas- ing stresses. This is an expected output and it confirms with the theoretical behavior of a sample subjected to tensile stress. The rupture strain values for different airbags (R/P/VW) were 0.322, 0.441, and 0.472, respect- ively. The measured elastic parameters (i.e., Young’s modulus E and initial yield strength) and Poisson’s ratio are summarized in Table 2. The tensile tests of the woven fabrics can show differences on mechanical prop- erties because woven fabrics can resist in-plane shear loads once the yarn lock-up angle has been reached. The differences of material property on material direction can affect the shape of fully deployed bag (see Fig. 3b).

Theoretical Background

Numerical simulations of airbags use very complex and techniques such as an orthotropic model to identify the mechanical behaviors during the airbag inflation and the fluid mechanics (gas flow) to describe the inflator gas flow (pressure gradient) and improve the representation of the pressures within the airbag. To model the airbag as an orthotropic model, three material constants have to be provided. Assuming a plane stress condition, the

Ð1Þ

where σ is the normal stress and τ is the shear stress, the subscript refers to the principal material directions, i.e., the fill and warp directions. Also, ε and γ are the strain components. The material elastic constants Qij are

Ð2Þ

where E1 and E2 are the Young’s modulus in the fill and wrap directions and G12 is the shear modulus of the fabric material. νij is the Poisson ratio of the material.

The gas exerts a pressure load on the airbag causing it to expand. This expansion puts the airbag under tensile stress lowering the expansion rate. In this study, heat conduction and heat transfer is not taken into account.

Fig. 2 A photograph of Lloyd EZ20 universal testing Fig. 3 Stress versus strain using Lloyd EZ20 machine for a three different airbags at 0° and 90° and b VW airbag test specimens at

Different Angles

Table 2 Physical and mechanical properties of the airbag

Page 3 Of 9

In the deployment of an airbag, an inflator supplies high velocity gas into an airbag causing it to expand rapidly. The gas inside the airbag is assumed to be ideal, to be of constant entropy, and to satisfy the equation of state:

Ð3Þ

Here p, ρ, and e are respectively the pressure, density, and specific internal energy, and γ is the ratio of the heat capacities of the gas. The gas flow is described by the conservation laws for mass, momentum, and energy that

Ð4Þ

here, V is a volume, A is the boundary of this volume,

N Is The Normal Vector Along The Surface A, And U

denotes the velocity vector in the volume. Applying Bernoulli’s equation in the case of an ideal gas with

Ð5Þ

Here, the subscript ex denotes quantities at the throat of the tube. Furthermore u, p, and ρ denote the quan- tities inside that part of the tube that is supplying mass.

Materials And Boundary Conditions

The airbag system mainly consists of three parts: the airbag itself, the inflator unit, and the crash sensor or diagnostic unit. Thus, to study the behavior of the airbag using FE simulations, we need to have an FE model of the airbag in the folded position. A FE model of the airbag was used to simulate the test condition as shown in Fig. 5. LS-DYNA® material model FABRIC (MAT_34) is used to simulate the airbag material. It is a variation of the layered orthotropic material model. Additionally, in the LS-DYNA® material model, fabric leakage can be accounted for. However, for this CAB material, the leak- age is almost negligible and therefore no leakage is specified. The mechanical properties can be determined from the physical test. Typical material properties for airbag fabrics are taken as given in Chawla et al. (2004a) (Table 3). These properties are used to simulate inflation process of airbag (see Table 1). The car dashboard is modeled as the rectangular thin plate using a MAT_RI-

Gid Material, And The Degrees Of Freedom Are Con-

strained in all the directions. The similar properties of thermoplastic polymer are assigned for contact purposes. The porosity of the fabric is assumed zero. The nitro- gen gas is taken for inflating the airbag. Properties of nitrogen gas and initial bag conditions are shown in Table 4. The example on which we perform the study is a typical passenger side airbag. The geometric de- tails have been measured from a commercially avail- able airbag. The initial state of the airbag is a closed rectangular whose sides are to be finished to 482 × 635 mm2 and is shown in Fig. 4.

Table 3 Material properties of airbag and rigid plate used in FE

–

Table 4 Initial values used for FE simulation of the swelling of

3.33 × 10−4

Fig. 4 The initial airbag geometry in the form of a rectangular Bendjaballah et al. International Journal of Mechanical and Materials Engineering (2017) 12:12

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