Bridgeless Pfc Matlab Simulink

International Journal of Power Electronics and Drive System (IJPEDS)

 1427

Journal homepage: http://iaescore.com/journals/index.php/IJPEDS Bridgeless PFC single ended primary inductance converter in

Continuous Current Mode

Nor Akmal Rai, Mohd Junaidi Abdul Aziz, Mohd Rodhi Sahid, Mohd Rodhi Sahid

Accepted Mar 23, 2019

This paper presents bridgeless single ended primary inductor (SEPIC) converter operated in continuous conduction mode (CCM). The converter used in the study offers a lesser conduction loss compared to the other bridgeless SEPIC converter. In order to regulate the required output current and output voltage with high efficiency while achieving high power factor correction (PFC) at the input side, average current mode control (ACMC) is applied. The model is simulated using MATLAB/Simulink and it is found that the converter and the proposed control strategy provide a promising result. The preliminary results obtained from the experimental test-rig shows a good agreement as in simulation. The theoretical analysis of the proposed controller is verified on an output 100V to 300W prototype.

Power Factor Correction (Pfc)

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

Universiti Teknologi Malaysia,

81310 Skudai, JohorMalaysia. 1.

Introduction

A nonlinear load such as a battery, electronic device, and generator produce high harmonic distortion to ac input supply. This leads to losses in the supply and low power factor in the electrical system. PFC improves the power factor of electronic circuit. PFC ensure both input voltage and current are in phase, which leads to high power factor and reduces harmonic in supply. Normally, a conventional PFC can be accomplished by using a full bridge diode rectifier and dc-dc converter. Even though bridge rectifier has the ability to produce dc output but its drawback which produce an absolute sinusoidal voltage with high ripple and current that are highly nonsinusoidal . A dc voltage produced by the rectifier is quite large and need to be regulated to a required value. Intended to this reason, a dc to dc converter are used to regulate an actual dc voltage with actual current waveform shape and low output ripple . Moreover, this technique enhanced to PFC with low harmonic distortion .

There are various of dc-dc converter topologies used in PFC circuit. SEPIC converter is popular due to its advantages over another dc to dc converter. This converter produces an output voltage that is less or more than the input voltage, but with no polarity reversal [1, 4]. However, SEPIC converter is a 4th order converter since it has 4 storage elements in converter make it seldom uses due to difficulty in design the controller . Nevertheless, this converter offers a surplus advantage compared to 2nd order converter where a lower input current ripple is possible to achieve [5, 6].

Literature studies state that a normal bridge SEPIC converter rectifier produces high conduction loss at input bridge diode hence reduces overall efficiency of the converter. This is due to a bridge rectifier consists of 4 diodes that produce high conduction loss during operation. It is possible to eliminate this high conduction loss with bridgeless converter. The efficiency of these converters is improved by removing the input bridge diode of the conventional bridge SEPIC converter. In the bridgeless converter number of

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elements conduct during each cycle are reduce as compare to the bridge rectifier. This significantly reduces losses in the circuit as reported in . The Bridgeless SEPIC converter offer reduction of cost, light, increases efficiency at the same time maintaining near unity power factor performance. It is possible for the converter to operate in CCM and discontinuous conduction mode (DCM) depends on its application.

In CCM, the inductor current is always positive while for DCM inductor current is characterized by current returning to zero during every period. DCM causes large voltage stress, consequently gives impact on electromagnetic interference (EMI) into line . Furthermore, at high power application, current stress and voltage stress in DCM become too large which affecting the efficiency of the converter [5, 15]. Hence, DCM normally used for low power application usually less than 200 W while CCM popularly used for medium and high power application . This is due to CCM has lower conducted noise, lower conduction losses in the semiconductors and inductor, and lower inductor core loss [8, 18]. Additionally, it has low output voltage ripple. However, the design of CCM controller is more complex as compared to DCM. DCM has properties of self PFC since its capability to give higher power factor by the nature of their topologies [19, 20]. Hence, DCM has simple control and can achieve PFC by using simple control system. CCM required complex control system and required closed loop control to achieve PFC.

Current mode control typically work for converter operate in CCM. Among all current control mode, ACMC offers several advantages such as the ability to sense and control average inductor current while offering immunity to noise . In PFC application, another significant feature of ACMC near the zero crossing of the line voltage, the converter operates with the maximum duty cycle. As a result, the dead angle period which encounter in peak current mode control is greatly reduced [22, 23]. Most of PFC applications has been widely adopte AMMC as a control technique for CCM converters [24, 25].

Bridgeless SEPIC converter in focus at low power application operated in DCM using voltage control. This controller design is simple since all zero and pole are located at left hand plane make a tuning process easier. However, this controller provides high current and voltage stress for medium power application which cause some power loss to converter.

In this paper, CCM with ACMC applied to bridgeless SEPIC converter proposed in [9, 10] are studied. This paper is organized as follows. The bridgeless SEPIC converter detail circuit operation with average current controller are discussed in Section 2. The proposed circuit parameter, simulation result and preliminary result of hardware prototype are presents in Section 3. Finally, the conclusion is present in Section 4.

2.

2.1. Circuit Operation

Bridgeless SEPIC converter as proposed in [9, 10] as in Figure 1, are simulated in CCM with an average current mode controller. The circuit consist of three inductors, three capacitors, two diode and two MOSFET apart from a resistor as its load.

Figure 1. Bridgeless Sepic Circuit

This circuit has the same operation in both cycles, where each switch will only turn on in positive or negative half cycle. During the positive half cycle, only nine elements conduct which is L1, L2, S1, Ds2, C1, L3, D1, C3 and R as shown in Figure2. In negative half cycle L1, L2, S2, Ds1, C2, L3, D2, C3 and R are conduct as shown in Figure 3. This bridgeless SEPIC converter reduced number of component conduction during half cycle. At each half cycle of bridgeless SEPIC converters, it operates as basic dc-dc SEPIC converter.



Bridgeless PFC single ended primary inductance converter in continuous current mode (Nor Akmal Rai)

(B)

Figure 2. Operation of the bridgeless SEPIC converter in: (a) positive half cycle (b) negative half cycle Bridgeless SEPIC operate in CCM and it consists of two mode operation per cycle. For positive half cycle it is operated in mode 1 and mode 2 as shown in Figure 3. The waveform of voltage and current operation for bridgeless SEPIC converter are shown in Figure 4.

(B)

Figure 3. Positive half cycle operation in (a) mode 1 (b) mode 2 In mode 1, S1 and Ds2 are operate, current will flow through S1 and Ds2. L1 and L2 charge and are increase linearly to its peak depends on its duty cycle. In mode 2, S1 will turn off and D1 turn on, which allow current through it. Current across L1 decrease linearly due to discharging process through the C1, C3 and load. Since the circuit operation is symmetrical, the modes of operation for the negative half cycle are not shown here. Symmetrical feature of the converter in CCM is discussed in detail in [9, 10].

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In mode 1, S1 and Ds2 are operate, current will flow through S1 and Ds2. L1 and L2 charge and are increase linearly to its peak depends on its duty cycle

(4)

In mode 2, S1 will turn off and D1 turn on, which allow current through it. Current across L1 decrease linearly due to discharging process through the C1, C3 and load. Since the circuit operation is symmetrical, the modes of operation for the negative half cycle are similar as in positive cycle but in opposite direction.

2.2. Mathematical Model

In order to design the controller, it is mandatory to obtain the transfer function based on mathematical model to simplified controller tuning. Based on mode of operation of bridgeless SEPIC converter in CCM, the state space averaging modelling technique , are applied based on KCL and KVL of circuit during turn ON and turn OFF state as in equation (1-8).

B - Input Matrix

C - Matrix which connect output to the state variable

𝐵ௗ.𝑑ሚ- Duty Ratio Variation For Ccm

The average matrices for steady state and liner small signal state space equation of bridgeless SEPIC

𝟏ቃ

(11) and (12) consists of the ac perturbation. By using Laplace transformation in (11) and (12), yield a form of transfer function of bridgeless SEPIC converter.

(13)

Where 𝑰𝟒 is a unity matrix, based on expansion and solving of equation 13, the transfer function of inner loop

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)

0.150

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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