Sic Mosfet Converter Matlab

Analysis and Development of SiC MOSFET Boost Converter as

A.Bharathi Sankar 1, Dr.R.Seyezhai 2

Abstract: Renewable energy source such as photovoltaic (PV) cell generates power from the sun light by converting solar power to electrical power with no moving parts and less maintenance. A single photovoltaic cell produces voltage of low level. In order to boost up the voltage, a DC-DC boost converter is used. In order to use this DC-DC converter for high voltage and high frequency applications, Silicon Carbide (SiC) device is most preferred because of larger current carrying capability, higher voltage blocking capability, high operating temperature and less static and dynamic losses than the traditional silicon (Si) power switches. In the proposed work, the static and dynamic characteristics of SiC MOSFET for different temperatures are observed. A SiC MOSFET based boost converter is investigated which is powered by PV source. This DC - DC converter is controlled using a Pulse-Width Method (PWM) and the duty cycle d is calculated for tracking the maximum power point using incremental conductance algorithm of the PV systems implemented in FPGA. Simulation studies are carried out in MATLAB/SIMULINK.A prototype of the SiC converter is built and the results are verified experimentally. The performance parameters of the proposed converter such as output voltage ripple input current ripple and losses are computed and it is compared with the classical silicon (Si) MOSFET converter.

Keywords: Photovoltaic panel, Maximum power point tracking control, Silicon carbide, Incremental Conductance, Pulse Width Modulation, Field Programmable Gate Array.

1. Introduction:

For several decades, silicon (Si) has been the primary semiconductor choice for power electronic devices. However, Si is quickly approaching its limits in power conversion. Wide band gap (WBG) semiconductors offer improved efficiency, reduced size and lower system cost. Of the various types of WBG semiconductors, silicon carbide (SiC) have proven to be the most promising technologies, with several devices already being available commercially . SiC has shown tremendous high temperature capability, as well as aptitude for high voltage applications. Furthermore, the cost of SiC devices has decreased within the last decade, and the performance has proven superior to that of conventional Si based devices. Some of the potential application areas for these devices include: transportation electrification and renewable energy. SiC devices have been explored for replacement of Si IGBTs in photovoltaic inverters in order to improve efficiency. Further, the fast switching speed of these devices allows for high frequency operation thereby resulting in the reduction of the passive components, which decreases the total size, weight and cost of the system .

The advantages of SiC have been investigated in this paper by developing a DC-DC boost converter using SiC MOSFET for PV applications. The characteristics of SiC MOSFET are analyzed and its performance is compared with the classical Si MOSFET. SiC based boost converter results in reduced input current and voltage ripple by implementing the PWM control using FPGA. Further, to get maximum power from PV, incremental conductance algorithm is employed and implemented using FPGA. Hardware setup of the proposed DC-DC converter is developed and the results are verified experimentally.

2. Description Of Sic Mosfet

SiC MOSFETs being unipolar devices typically experience faster switching than an IGBT. As a result, extensive work on the characterization of SiC MOSFETs and comparison of their dynamic performance with Si IGBTs has been carried out. . A common structure for SiC MOSFETs is the double-diffused or DMOSFET which is shown in Figure 1, that allows for fast switching speed and high durability. Upon the application of a positive gate bias, an inversion layer is produced at the surface of the p- well region underneath the gate electrode.

This inversion layer provides a path for the flow of current from the drain to the source. This structure includes an intrinsic body diode, and allows operation both in the first and third quadrants. Current flows through the body diode when the MOSFET gate is off, and a positive drain bias exceeding approximately 0.7 V is applied. If instead a positive gate voltage is applied, and the drain is negatively biased, then the channel will conduct with current flowing from the source to the drain, resulting in third quadrant operation .

Figure 1: Sic Mosfet Structure

SiC power MOSFET is also capable of supporting high positive drain voltages. Furthermore, due to its greater critical electric field for breakdown, the doping concentrations in the drift region of SiC MOSFETs can be increased, thereby resulting in a lower drift resistance for a given blocking voltage. This relationship is shown by the following equation for the ideal on-state resistance Ron-ideal

………… (1)

Where BV is the breakdown voltage, εs is the dielectric constant of the semiconductor, µ n is the mobility of the drift region, and Ec is the critical electric field for breakdown. Moreover, SiC also features a higher saturation drift velocity, allowing for faster switching, and thus is suitable for high frequency applications.

3. Characterization Of Sic Mosfet

SiC MOSFET is modeled in MATLAB and the static and dynamic characteristics are simulated by extracting the parameters from the data sheet for various temperatures.

3.1. Output Characteristics

Figure 2 shows the Simulink model for output characteristics for the SiC MOSFET. Output characteristic shows the variation of the drain current with respect to the drain source voltage at 25 °C and 150°C temperature as shown in figure 3 & 4. The output characteristics are Drain current ID versus Drain-source voltage VDS measured under different gate voltage VGS from 10 V to 22 V. It is found the results that the SiC MOSFET goes into saturation at prolonged period thereby pinch off point is increased.

Figure 2: Simulink model of SiC MOSFET Static characteristics.

Vg = 22 V

Figure 3: Output characteristics of SiC MOSFET at 25 C

Vg = 22 V

Figure 4: Output characteristics of SiC MOSFET at 150 C

3.2. Transfer Characteristics

Figure 5 shows the variation of the drain current with respect to the gate source voltage for various temperatures. From the figure it is clear that at high temperature, the threshold voltage of the device and transconductance increases.

3.3 On-State Resistance Rds(On)

The on-state resistance RDS(ON) is a critical parameter to the device since it determines the conduction power dissipation. The power D-MOSFET structure with its eight internal resistance components between the drain and source electrodes when the device at turned-on state. The total on-state resistance is the sum of the eight resistances,

Which Can Be Expressed As Rds(On) = Rcs + Rn

+ + RCH + RA + RJFET + RD + RSUB + RCD. Where RCS is source contact resistance, RN+ is the source resistance, RCH is channel resistance, RA is accumulation resistance, RJFET is JFET resistance, RD is drift region resistance, RSUB is the substrate resistance and RCD is the drain contact resistance. There are several different definitions for the RDS(ON), it to be the maximum slope of the output curve at a given turn-on gate voltage. This definition gives the minimum possible RDS(ON) for a given VGS, which resulting in RDS(ON) = 0.129 Ω at VGS = 20 V in our case. In this work, RDS(ON) can be read directly from the output characteristic curves.

The RDS characteristic of Si and SiC MOSFET is shown in figure 5 respectively for various temperatures. It is clear that the variation of on state resistance is in milliohms for the entire range of temperature for SiC compared to Si.

3.3 Switching Characteristics Curve

Figure 6 shows the Simulink model for dynamic characteristics for the SiC MOSFET. Switching characteristics for SiC MOSFET is shown in figure 7 and it provides the information of the SiC MOSFET under transient and saturation region and its corresponding dynamic parameters Turn on time(ton)=35ns, Turn off time (toff)=76ns, Fall time (tf)=36ns & Rise time (tr)=22ns is shown in fig 7a & 7b.Experimental setup Switching characteristics for SiC MOSFET is shown in figure 7c.

Figure 6: Simulink model of SiC MOSFET Dynamic characteristics.

Vds,Id (Volts,Amps)

Figure .7a Switching characteristics Ton state for SiC MOSFET

Vds,Id (Volts,Amps)

Figure .7b Switching characteristics Toff state for SiC MOSFET Figure .7c Experimental setup Switching characteristics for SiC MOSFET

3.4.Thermal Analysis For Sic Mosfet

As the power density and switching frequency increases, thermal analysis of power electronics system becomes imperative. The analysis provides valuable information on the semiconductor rating, long term reliability and efficient heat sink design have been reported in the literature for thermal analysis of SiC MOSFET. The aim of this work is to build a comprehensive thermal model for the SiC MOSFET modules. It is used in boost converter in order to predict the dynamic junction temperature rise under real operating conditions. The thermal model is developed in two steps, first step the losses are calculated and then the junction temperature is estimated. The real- time simulation environment dictates the requirement for the models for easy implementation on the software platform. The parameter of the thermal network is extracted from the junction to case and case to ambient dynamic thermal impedance curves. An equivalent RC network model is built to platform the thermal analysis as shown in Figure 8. It is shown in Figure 9 that the SiC MOSFET junction temperature and case temperature is about 400°C and 340°C respectively.

Theatsink

Figure .9: SiC MOSFET junction and case temperature Figure 10 shows the Simulink model for Thermal characteristics for the SiC MOSFET. Thermal characteristic shows the variation of the drain current with respect to the drain source voltage at 25 °C and 125°C temperature as shown in figure 11.The output characteristics are Drain current ID versus Drain-source voltage VDS measured under different gate voltage VGS from 10 V to 22 V. It is found the results that the SiC MOSFET goes into saturation at prolonged period thereby pinch off point is increased.

Figure 10: Simulink model of SiC MOSFET Thermal characteristics.

Figure .11 Thermal Characteristics For Sic Mosfet

Figure .11 Experimental setup temperature Vs switching frequency temperature Vs Drain current for SiC MOSFET for various duty cycle. Fig.11. Thermal pictures of the main components in the boost converter for different switching frequencies An infrared camera was used to investigate how the switching frequency affects the different components in the converter. For 100 kHz, 150 kHz and 175 kHz, temperatures of the diode, the SiC MOSFET and the inductor are shown in Fig.11. At a switching frequency of 150 kHz, the boost inductor has a temperature of 55 C. The heat sink, to which the SiC MOSFET is attached to, has a temperature of 68 C.Increasing the switching frequency to 175 kHz results in a high thermal stress in the SiC devices. The boost inductor has a temperature increases to 58 C. The case temperature of the SiC MOSFET increases to 75 C.

Experimental setup Thermal characteristic for SiC MOSFET is shown in figure 11.The SiC MOSFET junction temperature Vs switching frequency for various duty cycle and SiC MOSFET junction temperature Vs Drain current for various duty cycle.

4. Sic Mosfet Based Dc-Dc Converter

Choppers are static DC-DC converters for generating variable DC voltage source from a fixed DC voltage source. It is used to step up the input voltage to a required output voltage without the use of a transformer. The control strategy lies in the manipulation of the duty cycle of the switch which causes the voltage change. The circuit diagram of the designed SiC boost converter is shown in Figure.8.

Figure 8: Circuit Diagram Of Boost Converter

The function of boost converter can be divided into two modes, Mode 1 and Mode 2.

Figure 9: Boost Converter Operation Of Mode I

Mode 1 begins when MOSFET is switched on at time t=0. The input current rises and flows through inductor L and MOSFET are shown in Figure 9.

Figure 10: Boost Converter Operation Of Mode Ii

Mode 2 begins when MOSFET is switched off at time t=t1. The input current now flows through L, C, load, and diode Dm. The inductor current falls until the next cycle. The energy stored in inductor L flows through the load is shown in Figure 10.The waveforms of the voltages and currents for boost converter are shown in Figure 11.

Figure 11: The waveforms of the voltages and currents for boost converter. The voltage-current relation for the inductor L is:

When The Mosfet Is Switched:

and when the MOSFET is switched off the current is: Here VD is the voltage drop across the diode Dm, and VM is the voltage drop across the MOSFET.

, We Can Solve For Vout:

Neglecting the voltage drops across the diode and the switch The active switch in the boost converter is a SiC MOSFET (1200V, 40A). A fast recovery diode is used as the freewheeling diode. The functioning principle of the boost is to excite the switch (SiC MOSFET) transistor with a duty cycle D produced by the MPPT control and when the switch is closed the inductor L is loading during T(D) time, afterwards the switch is opened, the inductor supplies the load through the diode during (1-D)T. For a DC-DC boost converter, the input–output voltage relationship for continuous conduction mode and design equation of L & C

Is Given By:

Based on the design equations, the simulation parameters for SiC boost converter is shown in Table 2.

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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