Vfd Variable Frequency Drive Matlab

Harmonic content analysis of a soft starting variable

Youngstown, Oh, Usa

Abstract—As the demands for electric vehicles, electric air- crafts, unmanned aircraft systems, and other motor-driven sys- tems increase, high-performance motor drives employing variable frequency control with higher efficiency a nd r eliability are becoming increasingly important parts of the ever-changing tech- nological landscape. This study proposes a Field Programmable Gate Array (FPGA)-based variable frequency soft-starting motor drive for a three-phase induction motor. Variable frequency drive is realized by employing Direct Digital Synthesis (DDS) technique. Gradually increasing the modulation index during the startup enables the soft start of the induction motor to limit the inrush current and controlling the soft-start period enables the reduction of the peak in-rush current. Digilent Arty A7- 35T Artix-7 FPGA Development board is used to realize the proposed motor drive. The performance of three different Pulse Width Modulation (PWM) techniques—Sinusoidal PWM, Third Harmonic Injected PWM, and Space Vector PWM are analyzed and compared. The proposed architectures require only a small fraction of the FPGA’s resources. The inverter output voltage and the load currents are analyzed for the harmonic contents using MATLAB. In the experimental realization, a four-pole squirrel cage delta- connected induction motor is utilized with a switching frequency of 4 kHz. The current and voltage characteristics of the induction motor are studied under different operating conditions to study harmonic contents and the effect of changing soft-start duration. The findings demonstrate a low-cost, flexible control of the induction motor with improved harmonic performance.

Figure: System Model & Simulation Flow for Vfd Variable Frequency Drive Matlab

I. Introduction

Field Programmable Gate Arrays’ (FPGA) usage in power electronics have been explored since the late 1990s . As the demand for higher frequency switching, along with lower conduction losses grew, FPGA’s highly parallel processing prowess attracted the interest of researchers and power elec- tronic engineers. FPGA’s reconfigurable nature along with higher throughput, in addition to the moderate power con- sumption, has made it a lucrative alternative to ASICs and microcontrollers for prototyping and testing new algorithms in the field of power electronics . Likewise, multiple cores of FPGA can be used to control multiple motor control systems parallelly. Three-phase induction motors are ubiquitous in industrial application because of their simple, low cost and rugged construction . Self-starting capabilities and absence of brushes like in brushed DC motor lends to easier main- tenance and longevity of the induction motors. Despite these benefits, induction motors have difficult control schemes for speed control. Advancements in the fields of motor drives with self-starters and variable frequency drives have eased the speed control for three phase induction motors. FPGA’s high computational prowess can be harnessed for better and precise speed control of the three-phase induction motor.

Figure: System Model & Simulation Flow for Vfd Variable Frequency Drive Matlab

This research paper is structured as follows: Section II briefly discusses about the PWM techniques implemented in this study, Section III elaborates on the FPGA architecture of the variable frequency PWM generators, and Section IV presents the findings from the experimental observations.

Figure: System Model & Simulation Flow for Vfd Variable Frequency Drive Matlab

Ii. Pulse Width Modulations (Pwm) Techniques

In comparison to the conventional Voltage Source Inverter (VSI) like square wave inverters, which only allow the fre- quency control of the output voltage, PWM techniques offer versatile control of the amplitude and frequency of the output voltage along with control of harmonic content present in the output voltage . PWM techniques are preferred for the DC- AC converters especially in three-phase applications because they can reduce the harmonics and switching losses .

Sinusoidal PWM (SPWM), Third Harmonic Injection (THI-

Spwm) And Space-Vector Pwm (Svpwm) Are Commonly

employed PWM inverter techniques. These PWM techniques can be modified depending upon the requirement of the three- phase loads to focus on different areas of power conversion.

C

Navarro et. al. have focused on high resolution output from SPWM. PWM modified to achieve high switching frequency was discussed by Lakka et. al . SPWM has been modified to PD-SPWM with a goal to reduce harmonic content and increase output voltage. Sarker et. al propose a high definition SPWM (HD-SPWM) technique that aimed at suppressing inverter output harmonics . Carrier based PWM, where a carrier waveform of high frequency is compared against a reference waveform, is a widely implemented technique.

Sinusoidal PWM, THI-SPWM along with carrier-based equiv- alence of Space Vector PWM are briefly discussed in this section.

A. Sinusoidal Pwm (Spwm)

In the SPWM technique, a sinusoidal waveform, called the reference signal vr, of the desired output frequency, fr, is compared against a carrier waveform vc with a switching frequency, fs, to determine the switching states of the gates driving the inverter output. The output voltage delivered to the motor phases is determined by modulation index (m) which

Is Given As:

Fig. 2. Modification of SPWM to THI-SPWM by addition of third harmonic content.

C. Space Vector Pwm (Svpwm)

Implementation of conventional Space Vector PWM re- quires a complex algorithm; however, the traditional SPWM method can be modified to generate gating pulses identical to the those produced by conventional SVPWM . The mod- ified modulating waveform is obtained by adding a common

(4)

and, the peak value of the magnitude of the output voltage is

(2)

where, Vdc is the DC link voltage. Fig. 1. Comparison of sine wave and saw-tooth wave to produce switching signals.

B. Third Harmonic Injected Sinusoidal PWM (THI-SPWM) Conventional SPWM can be modified according to (3) by adding a third harmonic component to obtain the modulating signal for THI-SPWM as shown in Fig. 2.

1

vmax and vmin are the maximum and minimum values of the three phases of the sine (va, vb, vc) at any given angle and

(5)

Fig. 3. Modification of SPWM to SVPWM by addition of common mode voltage. SVPWM reduces the harmonic contents present in the voltage and current output waveform .

Iii. Fpga Architecture

Fig. 4 depicts a simplified block diagram of the proposed SPWM generator architecture. It consists of a 100 MHz clock,

6

a sine Look-Up table of size 3600 elements, and saw-tooth waveform implemented using an up-counter, and a comparator. Third harmonic injection using (3) results in better utiliza- tion of the DC bus along with reduced harmonic content in the output voltage .

In addition, it has a variable frequency output block that gen- erates 5-100 Hz sine output and a variable modulation index based soft-starting block that controls the soft-startup duration.

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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