Conduction Loss Calculation Matlab

Losses In Cascaded H-Bridge Multilevel Inverters

Abstract-Nowadays, voltage source multilevel inverters are being used extensively in industry due to its many advantages ,compared to conventional two level inverters, such as higher output voltage at low switching frequency, low voltage stress(dv/dt) , lower total harmonic distortion (THD), less electro-magnetic interference (EMI), smaller output filter and higher fundamental output. However, the evaluation of multilevel inverter losses is much more complicated compared to two level inverters. This paper proposes an on-line model for precise calculation of conduction and switching losses for cascaded h-bridge multilevel inverter. The model is simple and efficient and gives clear process of loss calculation. A single- phase 7-level cascaded h-bridge with IGBT’s as switching devices has been used as a case study of the proposed model. The

Harmonic

elimination in which the switching angles were determined using the Genetic Algorithm (GA). MATLAB-SIMULINK is used for the modelling and simulation.

Figure: System Model & Simulation Flow for Conduction Loss Calculation Matlab

Index Terms—Cascaded H-Bridge Multilevel Inverter (CHB- MLI), Conduction Losses, Switching Losses, Selective Harmonic Elimination (SHE).

Figure: System Model & Simulation Flow for Conduction Loss Calculation Matlab

Introduction

In the last decade, the use of multilevel inverters has been grown numerously in most of the industrial power applications. It is hard to connect one power semiconductor switch directly in utility applications that requires medium voltage and high power level. Hence, the concept of multilevel inverters came as an alternative to conventional inverters in such applications. The multilevel inverters became very attractive as they produce low harmonic component at low switching frequency. In addition, they result in lower losses, lower blocking voltage of switching devices, and low electromagnetic interference (EMI) .

Figure: System Model & Simulation Flow for Conduction Loss Calculation Matlab

There are basically three main commercial topologies of multilevel voltage-source inverters well placed in industry which are: cascaded H-bridge (CHB-MLI), neutral-point clamped (NPC-MLI) and flying capacitor (FC-MLI).

Among these topologies, the CHB-MLI is very widely used in industry for high power applications. It is used in high voltage and high power levels and it requires small number of devices, consequently, it has a reliable modular structure compared to the NPC-MLI and FC-MLI.

For Power System Planning And Multilevel Inverter

design, accurate calculation of inverter power loss is of great importance to evaluate system efficiency, reliability and system operating cost. The design engineer should calculate the inverter losses precisely. In fact, loss evaluation in multilevel inverter is not an easy task and much more challenging compared to conventional two level inverters.

This is mainly because that the current differ in each power switch in the inverter. This paper focuses on a precise modelling of switching and conduction losses in CHB-MLI.

Different methods were suggested in literatures to calculate the power loss in multilevel inverters. Some of these methods are based on online calculation from the simulated circuit and

Some Are Based On Deep Mathematical Analysis And

evaluation. In , each IGBT was modelled by characteristic curves using curve fitting exponential equations as a function of load current. In , a general scheme for calculating switching and conduction losses of power semiconductors in numerical circuits has been proposed. The model can be used online on the circuit simulation. Switching functions have been used in to model the inverter losses for three phase nine level cascaded h-bridge inverter in which the load was assumed to be mixed RL load and the modulation index was 0.85. All the previous papers used online modelling for calculating the losses by applying curve fitting to characterize the IGBT based on the datasheet. On the other hand, in ,

And , The Losses Of Multilevel Inverter Have Been

calculated based on mathematical model in which the voltage across the switch as modelled by a threshold voltage and a series resistance.

This Paper Implement A Model For Calculating

conduction and switching losses in CHB-MLI based on the method applied in with little modification to be applied for multilevel inverters. A very clear and efficient procedure is to be explained in details which should serve as a guide in loss evaluation for multilevel inverters. The proposed modelling will be based on online simulation in which the inverter losses are calculated precisely with much less computational efforts.

Basically, there are four types of losses in multilevel inverters which are: Conduction loss, Switching loss, OFF-state loss and Gate loss. The OFF-state and Gate losses are very small and normally neglected. Hence, in this paper only conduction and switching losses are considered throughout the analysis.

As it is most widely used in medium voltage, high power applications, the CHB-MLI has been considered for the analysis with IGBT’s as power switching devices. First, Selective Harmonic Elimination (SHE) technique is to be performed to determine the switching angles which give minimum harmonic distortion. Genetic Algorithm (GA) optimization method is used for solving the system of transcendental equations. Then, simulation is conducted to evaluate the conduction and switching losses based on the proposed modelling. Curve fitting equations are implemented to model the power switch mathematically as per the datasheet.

While Diode-Clamped (Dc-Mli) And Flying Capacitor

(FC-MLI) are widely used for industrial medium voltage- high power applications when just low number of levels (typically three) is required, Cascaded H-Bridge inverters (CHB-MLI) are most suitable for high voltage-high power, HVDC utility applications. Mainly due its modular structure which can be extended for high number of levels with no much complexity. Furthermore, with CHB-MLI, higher power and voltage capability can be achieved at lowest number of required devices compared to DC-MLI and FC- MLI. The CHB-MLI uses series connection of single phase h- bridge inverters with separate dc sources. The main idea is that each bridge cell will generate three different voltages and the output waveform can be synthesized by the sum of the voltages generated by each cell. The separate dc sources might be solar panel PV cells or fuel cells.

In this paper, a 7 Level CHB-MLI has been chosen to be investigated. The circuit layout for single phase 7-Level CHB-MLI is shown in Figure (1). The switching devices have been selected to be of IGBT type FZ1500R33HL3, which has a blocking voltage capability of 3.3 kV, and a maximum forward current of 1500 A and its shown in Figure(2).

Datasheet for this type IGBT is given in . Typical applications of this IGBT are: Chopper Applications, Medium Voltage Converters, Motor Drives, Traction Drives, UPS Systems and Wind Turbines . Each cell is connected to a dc link supply of 100 V. Modulation index of (0.8) was used throughout the analysis. The inverter has been modelled in

Maltal-Simulink With Main Objective Of Precisely

calculating the conduction and switching losses of the inverter.

S12

Fig. 1. Single-phase 7-level cascaded h-bridge inverter circuit layout. 2.IGBT module FZ1500R33HL3 typical appearance .

Selective Harmonic Elimination (She)

To control the output of voltage waveform in multilevel inverters, different modulation techniques have been applied. These control techniques are classified mainly based on the switching frequency into low or high switching techniques.

Space Vector Control (Svc) And Selective Harmonic

Elimination (SHE) are low switching techniques in which the active power switch is commutated only one or two times within one cycle. On the other hand, various PWM are used for high switching techniques in which the power switch is switched many times within a cycle . In this analysis, SHE has been proposed for controlling the inverter as this technique has lower switching losses and less EMI because of its low switching . In addition, it can eliminate the dominant low order harmonic and hence minimize the size of the required filter at the inverter output.

SHE uses pre-defined switching angles to form the desired multilevel fundamental voltage and eliminate the predominant low order harmonics which results in minimizing the total harmonic distortion (THD). The switching angles are pre- calculated off-line and hence this is considered open loop control technique. Figure (3) shows the stepped-voltage waveform for 7-level CHB-MLI. It is clear that, there are 3 switching angles which can be pre-calculated in this case.

Fig. 3. Stepped-voltage waveform for 7-level inverter. Applying Fourier’s expansion, the stepped voltage wave form can be expressed in sum of sine and cosine periodic signals and a constant. The signal consists of odd and even harmonics. Due to the quarter symmetry of the waveform, the even harmonics and the dc constant are cancelled. Hence, only odd harmonics are considered. For balanced three phase systems all triplen harmonics are zero. Generally, The output



,,,…..  ∝ +  ∝ … . . + ∝ ! #$ (1) Where (S) is the number of H-bride cells of the inverter.

It is clear from Figure (3) that all switching angles are less than 90°, and are all in ascending order. In 7-level CHB-MLI

(2)

And it is possible to eliminate the 5th and 7th harmonic by solving the following system of non-linear equations where (mi) is the modulation index.

 ∝+  ∝+  ∝= 3*+ (3) 5 ∝+ 5 ∝+ 5 ∝= 0 (4) 7 ∝+ 7 ∝+ 7 ∝= 0 (5) Newton-Raphson iterative method has been applied to solve such system in practice. Key issue is that when the inverter level gets higher, it becomes more difficult to get to the solution. In addition, it requires good initial guessed values of the switching angles. In this paper, Genetic Algorithm (GA) has been applied to solve the system of transcendental equations . The objective function is to minimize the total harmonic distortion (THD) with the transcendental equations (3-5) are set to be minimization constraints. This should result eliminating the 5th and 7th harmonics. The optimum switching angles of the 7-level CHB-MLI under investigation at 0.8 modulation index are found to be 11.5° , 28.7° and 57.2° respectively using GA- toolbox in Matlab.

Power Loss Modelling

When operating power electronics devices that involve switching of semiconductor devices, there are mainly four types of power losses occur during this operation. These types are: 1) Conduction losses, 2) Switching losses, 3) OFF-state losses, and 4) Gate losses. The Off-state and Gate losses are very small and normally neglected. Hence, in this paper, only conduction and switching losses have been considered for the analysis.

Compared to two level inverters, the estimation of inverter losses is a complicated task for multilevel inverters. The usual conventional methods used to calculate the losses in two level inverters, are not suitable to be applied in the case of multilevel inverters. Main reason for this is that in multilevel inverters, each semiconductor devise has different current compared to other devices which implies different losses behavior for each one. This results from having different on-state ratio for each device for one leg during one period of output phase voltage. Furthermore, at higher number of levels, the switching frequency of each device is not the same which add more complexity to the estimation method.

In This Paper, A Simplified Model Is Proposed For

calculating the losses of CHB-MLI precisely. The proposed model uses the method applied in with little modifications. The operating temperature is assumed to be maximum at 150ᵒ. The model is based on on-line calculation in which

Matlab-Simulink Software Has Been Used For The

modelling. Mixed load of R=60 Ω and L=20 mH , has been considered for the analysis. The result compared to the case where the load is changing from purely resistive load gradually to purely inductive load. The purpose is to provide a comprehensive study of the inverter losses behavior at different load conditions.

A. Conduction Losses

For a semiconductor device, the losses which occur while the power device is on the on-state and conducting current, is defined to be the device conduction losses. In CHB-MLI, the conduction loss increases proportionally with the number of cascaded cells. At conduction, the power dissipation can be computed by multiplying the on-state saturation voltage by on-state current.

./01234+0 = |#3| .
0 (6) The absolute value is taken as the conducting current is always positive for the device. Most of the literatures usually are modelling the on-state voltage by inserting a voltage Vo, representing the voltage drop of the device called threshold voltage, and a resistor ron representing the current dependency in series with the ideal device. The main

Drawbacks Of This Modelling Approach Are :

1) Additional parameters to be added in series with the ideal switches, hence rebuilding the circuit partially.

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.

Figure: System Model & Simulation Flow for Ansys Airbag Injury Simulation

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).

Figure: System Model & Simulation Flow for Ansys Airbag Injury Simulation

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.

Figure: System Model & Simulation Flow for Ansys Airbag Injury Simulation

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).

Figure: System Model & Simulation Flow for Ansys Airbag Injury Simulation

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.

Figure: System Model & Simulation Flow for Ansys Airbag Injury Simulation

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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