Failure Rate Calculation Method for High
Voltage Semiconductor Devices under Space
Radiation Environments
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Erdenebaatar Dashdondog
高耐圧パワー半導体素子の宇宙放射線環境下故障率の計算手法に関する研究
平成29年度
17104甲工第445号
http://hdl.handle.net/10228/00006913

Academic year 2017 DISSERTATION

Failure Rate Calculation Method forHigh Voltage Semiconductor Devices under Space
Radiation Environments
Erdenebaatar Dashdondog

A dissertation submitted for in partial fulfilment of the requirements
for the degree of Doctor of Philosophy in Engineering
Copyright © 2017 by Erdenebaatar Dashdondog
Department of Electrical Engineering and Electronics,
Graduate School of Engineering,
Kyushu Institute of Technology,
Kitakyushu, Fukuoka, Japani|

Acknowledgement ........................................................................................................... iv
Abstract ............................................................................................................................ vi
1.INTRODUCTION ..........................................................................................................1
1.1.

Satellite and Space industry ........................................................................... 1

1.2.

High Power for Satellite Power System ......................................................... 2

1.3.

Electrical Power Subsystem ........................................................................... 4

2.POWER SEMICONDUCTOR DEVICES .....................................................................6
2.1.

IGBT and MOSFET ....................................................................................... 7

2.2.

PiN Diode....................................................................................................... 8

3.COSMIC RAY INDUCED FAILURE AND ITS MECHANISM ON DEVICES ........93.1.1.

Flux, Cross Section ............................................................................... 11

3.1.2.

Proton flux at earth environment .......................................................... 14

3.2.

Mechanism and failure in Devices ............................................................... 16

3.2.1.

Proton-Silicon interaction ..................................................................... 17

3.2.2.

Semiconductor devices failure due to cosmic ray ................................ 21

4.PROPOSED METHOD TO CALCULATION OF FAILURE RATE ........................29
4.1.

Proton flux data for formula ........................................................................ 31

4.2.

Energy deposition probability function ....................................................... 35

4.3.

T-CAD simulation to obtain charge generation in device ........................... 42

4.3.1.

T-CAD simulation for charge generation function ............................... 44

5.RESULTS .....................................................................................................................55

5.1.

Probability Function fitting result ................................................................ 55

5.2.

T-CAD simulation result.............................................................................. 57

5.3.

Proton flux functions fitting results ............................................................. 72

5.4.

Cross section calculation result .................................................................... 75

5.5.

Failure rate calculation result ....................................................................... 76

ii |

6.

CONCLUSION....................................................................................................80

7.

LIST OF FIGURES .............................................................................................81

8.

LIST OF TABLES ...............................................................................................85

9.

BIBLIOGRAPHY................................................................................................86

10.

ACRONYMS .......................................................................................................89

11.

PUBLICATION LIST .........................................................................................90

12.

ABOUT AUTHOR ..............................................................................................91

Dissertation Committee
Professor. Kazuhiro Toyoda
Professor. Mengu Cho
Professor. Kei-ichi Okuyama
Professor. Ichiro Omuraiii |Acknowledgement
First of all, I would like to say thank to my lovely parents for grown up and driven
me for this good life and opportunity to being individual human being. Thanks my little
sister for taking care of our parents during period of my study here in Japan.
I would like to deeply appreciate to my supervisor Professor Ichiro Omura. He hashelped and instructed to me for this research and achievement. Without his vise advices I
wouldn’t come here. His word made me to think about technology development of mycountry many time on many points. I believe that those points will become real results in
Mongolia. This is the biggest luck of my life to meet him as his student. There is wordthat “One day’s teacher is thousand days virtue”. His three years supervising to me willbe the all my life’s virtue.
Also I would like to say thank to my Professor Cho Mengu. I had participated forthree satellites projects, HORYU-4, BIRDS-1 and SPATIUM, as a member of ElectricPower System team under his leading. His generous treatment gives me lot of knowledge
and thinking about top level manager and great future of my life. I have learned a lot
from him.
I thanks for Professor Toyoda for his great guidance and helpful advice. I was
happy for to be his student in last semester of my study.
I would like to appreciate to Miyo Iwahori san for supported and helped me since
first day I came in Japan until today. Her help was huge for my private daily and campus
life in Japan. I was lucky to meet her during my study.
Also I would like to thank for assistant professor Masui Hirokazu and LASEINE
colleagues for the helping and advice Mongolian very first “Mazaalai” satellite of BIRDS
project.
I also deeply appreciate Harada Shohei san, Takahara Satoru san, Shiba Yuji san,Sudo Masaki san, Kenta Nakashima san for helping me lot for my research and daily life
at Kyutech. They have become my good friends.
I thank for all of my friends and SEIC students at Kyutech; T.Turtogtokh,
D.Amartuvshin, B.Battuvshin, U.Tuguldur, B.Bolortuya, S.Purevdorj, Dmytro Faizullin,
Sidi Ahmed Bendoukha, Rafael Rodriguez Leon and all other members of BIRDS-1,
HORYU-4 and SPATIUM projects. They had been making my life happy in Campus.
I would like to express my respect to Japanese helpful friendly people and Japanese
government. I studied here in Japan by scholarship from Japanese Government (MEXT)
through The United Nations Office for Outer Space Affairs’ PNST project. I have studiediv |at Kyushu Institute of Technology for last three years. These three years were turning
point of my life to better direction. I hope what I have learnt here leads to me to do lots ofthings for my country's future. I will continue my study and academic life back in
Mongolia. All of people above have deepest respect from me. Any of my success is also
theirs.

v|

Abstract
Space industry market and manufacturing have been increased for last decades.
Furthermore, this trend seems will being increased. In order to practically use large sizeof manned and unmanned spacecraft for space missions, the total power generation of thatwill soon reach to range of Megawatts. Consequence of power demand increasing leads tothe harness weight increasing of spacecraft in order to decrease power loss on harness.
Harness mass is approximately 8% of spacecraft dry mass. Relation between harness
mass and power demand of spacecraft was studied. For instance if the bus voltage
increase by 100V, then harness mass reduction would be 75% of initial mass. Hence it
seems that bus voltage increase will be the requirement for future space platforms. By
using high voltage in bus system of spacecraft, there is a risk to destruct that powerdevice due to the energetic particle penetration from the space. The well-known studies
have been studied this failure which basically named “single event burn out for powerdevices and other electronics. In order to mitigate that risk, evaluate reliability then failure
rate should be investigated against space radiation environment. The proton flux is the
majority of energetic particle flux at low earth orbit. Therefore this thesis initially
proposes and discusses method for space proton induced failure rate on high powerdevice. The proposed method could be developed to be able to calculate failure rate ofany power device under space radiation in various altitude. We selected low earth
condition as basic example study for this thesis. Besides, high energetic particles can be
the reason of power device failure in both terrestrial and space.
In Chapter 1 of this thesis, satellite and space industry development trend whichleads to the high power usage of next generation spacecraft was presented. Due to thattrend, there will be appeared several aspect of spacecraft especially on the electrical
power subsystem. The basic structure of electrical power subsystem was discussed as
well.
In Chapter 2 of this thesis, high voltage power semiconductor devices werebasically presented. The electrical power subsystem of spacecraft works at DC voltage. A
power management and distribution unit is the main part of energy controlling andconditioning in the electrical power system. The high voltage power devices are the main
component of that power management distribution unit. Therefore high power
semiconductor device will be the key component of the next generation spacecraft’s
electrical power system.
In Chapter 3 of this thesis, the cosmic ray induced failure and its mechanism werevi |presented. This chapter includes two sections. First is that understanding about cosmic
rays and its aspect in low earth orbit. Second is that semiconductor devices failure
mechanism which induced by energetic particles. Proton silicon nuclear interaction,
charge multiplication avalanche phenomena in the silicon device especially for powerdevices were explained as well.
In Chapter 4 of this thesis, proposed method to calculate failure rate that induced bycosmic ray was presented. The proposed method in this study is expressed as formula andconsists of three sections. First, T-CAD simulation, its result gives a threshold charge
value for the device destruction, at various applied voltages case, which is triggered byenergetic proton from space. The amount of threshold charge depends on applied voltage
for high power device. Second, there is a probability of charge generation in silicon due
to proton penetration. This probability function’s variation depends on the thickness ofdevice and incident energy of proton. This function was defined before at library. Third
consideration on this study is space proton flux data at low earth orbit which has been
provided by astrophysics studies, assumed energy range of proton flux is 1MeV to200GeV. Simulated device model was 3.3 kV PiN diode. At the end of this chapter
ionization particle model of T-CAD simulation were briefly discussed.
In chapter 5 of this thesis, calculated result by proposed was discussed. T-CAD
simulation result, Proton flux function fitting result, proton induced failure cross section
and failure rate calculation results were included this chapter. Shielding function obtained
from literature. As seeing result aluminum shielding could not be proper protection
against proton flux. Comparing results at FIT=1(one failure in 109hours) that typicallyused for power device’s allowed failure rate for commercial application, space
applications power semiconductor devices failure rate was higher than terrestrial failure
rate several magnitude. For instance in case of an application voltage of 3.3kV diodeshould be approximately 1.5kV for space application.
This thesis concluded in Chapter 6. Conclusion were basically that we establishedmethod that consists of Destruction charge values from T-cad simulation, proton flux dataand probability of energy deposition due to proton-silicon interaction from literature.
From the result we can see that failure rate is apparently higher than terrestrial region case(assumed terrestrial FIT=1). By using Single Event burnout cross section σ(𝑉), that we
obtained can be used for any proton flux of environment. PiN diode model can bechanged by any other power semiconductor devices. Proposed method can contribute to
mitigate failure for high power devices’ usage and predict space application’s MW rangevii |of power systems reliability in future.
In this study, T-CAD simulation electric field, that can affected by proton hitting
position in silicon, was fixed at highest field of position. Crystal degradation due to spaceradiation was not considered as well.

viii |

1. INTRODUCTION
Research Vision is to contribute for accounting of increase of high power devices’reliability in the future space applications.
Purpose of research is to develop failure rate calculation method for all kind of
power devices in various space environments.
Goal of thesis research is to demonstrate that proposed method can give derating
value and failure rate of the high voltage device at the low earth orbit environment.
This thesis discusses the universal calculation method for space proton induced
failure rate of a high power device. High energy particles can be the reason of powerdevice failure in both terrestrial and space. In order to know failure of power devices, TCAD simulation result gives a threshold charge value for the device destruction which is
triggered by energetic proton from space. The amount of threshold charge depends on theapplied voltage for high power devices. The probability of charge generation in silicon
due to proton penetration is considered as a study. This probability function variation lessdepends on the thickness of the device and strongly affected by the incident energy of
proton which studied before. Last consideration in this study is PiN diode model’s single
event upset cross section and failure rate, which was calculated by the proposed method
in Low earth orbit environment condition. Following subtitle talk about rationale andimportance of this study. The main application of this study is big space platforms infuture.
1.1. Satellite and Space industry
Space industry brings up to economic activities related to fabricating elements thattravel into Earth's orbit or beyond, bearing them to those regions, and linked services. The
three major sectors of the space industry are: satellite manufacturing, support groundequipment manufacturing, and the launch industry. The satellite manufacturing sector isframed of satellite and their subsystem makers. [1].
The space industry started to make grow after World War II, as rockets and thensatellites introduced into military armouries, and later establish civilian applications. It
holds back significant links to the governments. In particular, the launch industry features
a substantial government involvement, with some launch platforms (like the space
shuttle) being controlled by governments. In late years, however, private spacefaring is
becoming realistic, and even major government agencies, such as NASA and JAXA, havestarted relying on privately worked launch services. Some future developments of thespace industry that are progressively being regarded include new services such as space1|

tourism and deep space missions. The 2015 Space Report estimates that in 2014 total
global space activity was $330 Billion [2].

1.2. High Power for Satellite Power System
Space industry market and manufacturing have been increased for the last decades.
Furthermore, this trend seems will be increased as well [3]. In order to implement largescale space platforms, such as space station, big satellites, power generation will soon
reach to the level of Megawatt. Total power is gradually increasing as shown in the lasttwenty years its trend as we can see Fig. 1-1 [4].

Fig. 1-1 Total power increasing trend last twenty years

Consequence of power increasing in space platform is harness mass increases.
Relation between harness mass and power of satellite was studied as shown in Fig. 1-2 [5].
When the total power of spacecraft is increase, then power loss also will increase. There
are three feasible solutions to reduce power loss. First is to use short cable, second is to
use thicker cable and third is use of higher voltage. Most suitable solution to reduce
power loss is to use higher voltage for the Electrical Power System of satellite; other twosolutions make a mass increase for application which leads to the budget issue of spacetechnology. We can confirm it as that power loss during transmission is proportional tocable length over multiple of voltage square and cable cross section. The Eq. 1-1 shows
relation between power loss and applied voltage, if bus voltage increases then power loss
will be decreased.

2|

𝛥𝑃
𝑃

=

𝜌𝐼 2
𝑉𝐼

=

𝜌𝐼
𝑉

=

𝜌𝑃
𝑉

2

=

σ𝑙𝑃
𝑠𝑉

2

Eq. 1-1 Relation between Power loss and applied Voltage

PL : Load power consumption
Ρ : Cable resistanceσ : Cable electrical resistivityl : Cable length
S : Cross-sectional area
P=VI : Generated power
ΔP=ρI2 : Cable loss
Hence power of spacecraft leads to use of high voltage system by relation of Eq. 1-2.
On the other hand if power usage reaches to MW range then applied voltage should bereached KV range.
𝑉 ∝ √𝑃Eq. 1-2 Relation between Bus voltage and Total Power

Fig. 1-2 Relation between harness mass and power of satellite

3|The main idea of research is based on needs of high power demand on future space
applications. It calls for high voltage generation and transmission since minimize theenergy loss during power transmission and the cable mass. High voltage usage can be themitigation of harness mass increase. Satellite electric power system size (power level) is
verbalized by payload characteristics. Typical power levels and mass of today’s satellites
range between 100 and 1000W and 250 kg or less for small satellites, between1 and10
kW and on the order of 1000–5000 kg for conventional large satellites. However, due topresent lessening space budgets, mission developers are pushing strongly toward cheaper,small-satellite designs capable of launch on smaller, cheaper, and more easily deployedvehicles [5].

1.3. Electrical Power Subsystem
A spacecraft Electrical Power Subsystem (Electrical Power System) is one of thebus system compounds, which takes responsible for power generation and control, energy
storage, and power distribution. Fig.1-3 shows the functional block diagram of ElectricalPower Subsystem. The basic typical functions of Electrical Power Subsystem can belisted as below [6]:• Supply continuous power to the loads during the mission lifetime.
• Control and distribute electrical power to the spacecraft.
• Fulfil the loads average and peak power requirements.
• Provide regulated voltage bus to the loads.
• Protect the spacecraft against any failures within Electrical Power Subsystem.

Fig. 1-3 The functional block diagram of Electrical Power Subsystem

In the space missions, power requirements, mass, cost and lifetime are the key
parameters of Electrical Power Subsystem. Historically, power requirements of spacecraft4|

started from several watts. In future, this will reach several kilowatts to megawatts as forbig satellites and space platforms such as international space station. The previous data ofdifferent Spacecraft shows that, the Electrical Power Subsystem mass is 20-30% of the all
mass of spacecraft ( [6], [7]). Mission cost estimation and model which mentioned in [6],the Electrical Power Subsystem total cost can be estimated as ~23% of the total spacecraft
bus cost. The designed Electrical Power Subsystem lifetime depends on the required
mission lifetime and environment. The estimated lifetime is in the range of few hours tomore than 10 years as big space platforms.
Researchers and designers are trying to find out way to optimize Electrical Power
Subsystem performance, by minimizing mass, volume and cost.The Electrical Power
Subsystem is typically has two main architectures of the connection between its
compounding parts, Direct Energy Transfer and Peak Power Tracking. Direct Energy
Transfer architecture is less complex in the design; the power generated will be
distributed directly to applications. Development of space technology makes ElectricalPower System design challenges for future small and big spacecraft are similar in somebehaviour. In the case of small satellites, the purpose is to increase Electrical Power
System total power for reducing total satellite weight and volume to make it that increase
payload capability and use of smaller, cheaper launch vehicles. In the case of big
spacecraft, the important challenge is to increase Electrical Power System total power toenable enough power supply when maintaining acceptable spacecraft mass and volume tomake it possible to use of existing launchers. Fig. 1-4 shows an illustration for basicarchitecture of Electrical Power System, which comply with both basic designs.

Fig. 1-4 Basic architecture of Electrical Power System

It is shows that the exceeding generated electric power than the load using will be
stored in the energy storage element, on the contrary, in case of high consumption, the5|power will be flown to the load from power generator and energy storage element such asbattery. In the usual application, this aspect is main function of Power management anddistribution unit. This energy flowing controller Power management and distribution unit
is consisted of power devices as a key components such as PiN diode, IGBT and
MOSFET etc. Power management and distribution unit of electrical power system ofspacecraft was conceptually developed since 1990’s [8]. Basic idea of this concept is to
reduce mass and volume as much as possible due to the reason as we mentioned before.
In order to execute this idea to reality, basic components of power management anddistribution unit such as semiconductor power devices are should work in high power
range. In the next subchapter we will briefly talk about semiconductor power devices.

2. POWER SEMICONDUCTOR DEVICES
As before mentioned main part of Electrical Power System of spacecraft is PowerManagement Distribution. Main components of this part are Power Semiconductor
Devices such as Power diodes, Thyristors, MOSFET and IGBT. What are semiconductor
power devices? This is a semiconductor device used as a switch or rectifier in powerelectronics; power management distribution unit is an example which includes power
converters and rectifiers. Such a device is also called a power device or, when used in an
integrated circuit, a power IC. Basic one of possible classification of Power
Semiconductor Devices is shown in Fig. 2-1. It consists of two parts. First is two terminal
devices which includes diodes and its operation depends only applied power on its
terminals. Those terminals are called anode and cathode. Second are three terminal
devices which depend on applied power on terminals and also controlling signal on
driven terminal. Also there are four terminal power devices developed recently.

Fig. 2-1 Basic classification of Power Semiconductor Devices

Nowadays, power devices usage is everywhere in technology. These are the6|components which are for control energy flowing through any equipment. The main
application of power devices are home applications, motor drives and low voltage
inverters, converters so on in low voltage range, electric vehicle, electric train, renewableenergy specially for wind turbine drive and even for space platforms such ascommunication satellite in a high voltage range [9]. In this dissertation, high voltage
device will be the main focus. In the next subchapters we will discuss about MOSFET,
IGBT and Power diodes whereas these are the main components of power managementand distribution unit. In the component level, designing challenge to reduce volume andmass still exists, but in space application reliability is highest priority especially for big
space platforms. [8]2.1. IGBT and MOSFET
The metal–oxide–semiconductor field-effect transistor (MOSFET) and insulatedgate bipolar transistor (IGBT) are a three-terminal power semiconductor device primarily
used as an electronic switch which, as these were developed, came to combine highefficiency and fast switching. These two types of transistor can basically represent threeterminals of power devices. In the Fig. 2-2 shows that comparison of those two types ofdevices internal structure.

Fig. 2-2 IGBT and MOSFET internal structure comparison a) MOSFET b) IGBTThe IGBT has better performance than MOSFET at high switching frequency range.

7|But at low switching frequency range, the MOSFET has the less power loss and lower
operating junction temperature [10]. There is operational performance limitation on
MOSFET, between specified voltage rate and on-state resistance as said “Silicon limit”.
By using different material than silicon such as Silicon-Carbide, the limitation range may
increase. However Silicon material will be the majority material of manufacturing of
power devices due to the manufacturing and material costs even though there are lots ofresearches have been done by companies and institutes. This is a reason that we focusedon Silicon material in this study.
On the other hand IGBT has a low operational power loss even at higher
operational voltage. Due to this reason various applications, in the range of 1 kHz to 100
kHz frequency, 1kVA to 10MVA power and voltage of 600V - 4.5kV, will use suitable
one of silicon IGBT, Silicon Carbide MOSFET [9]. This range of power is actually ourtarget rated power of space platforms.

2.2. PiN DiodeA PiN diode is a diode with a wide, un-doped intrinsic region between p-n
semiconductor regions. This wide intrinsic region is a main difference PiN diode fromordinary PN diodes. The p-type and n-type regions are usually highly due to its purposeof ohmic contacts. The Fig. 2-3 shows that the basic internal structure of PiN diode. The
PiN diode is suitable for attenuators, fast switches, photo detectors, and high voltage
power electronics applications.

Fig. 2-3 Basic PiN diode internal structure

The PIN diode consists of three layers of semiconductor material as we mentioned
before. The typical P and N regions and between them is a layer of intrinsic material
which has a very low concentration of doping. It could be one of N-type or P-type, butwith a concentration of the order of 13^13 cm^-3 which makes it a resistivity of the orderof one kilo ohm cm. The high-frequency resistance is inversely proportional to the DC8|bias current through the diode. The PIN diode acts as a variable resistor. This highfrequency resistance may vary for big interval. The thickness of the intrinsic layer isgenerally from 10 to 300 micrometres. The P and N-type regions are heavily doped.
There are two ways in which the PIN diode can be manufactured. First one is tofabricate it in a planar structure, and other one is to make it as mesa structure. The planar
structure fabrication is that an epitaxial film is grown onto the substrate material and theP+ region is made by one of the diffusion or ion implantation. The mesa structure ismethod that layers grown onto the substrate. These layers have the impurity incorporated.
In this way it is possible to control the thickness of the layers and the level of impurity
more accurately and a very thin intrinsic layer is possible to manufacture as required. The
advantage of the mesa structure is that it provides a reduced level of fringing capacitanceand inductance.

3. COSMIC RAY INDUCED FAILURE AND ITS MECHANISM ON DEVICES
The well-known studies have been shown that the cosmic ray penetration insemiconductor device is the failure which basically named “single event upset” (SEU)[11]. The failure induces by space proton is the one of problem; however we can generatehigh voltage in space. As studies shown, high power device failure due to space particles
occurs in both space and terrestrial [12] [13] [14].
The reliability of high power device for space application have to be evaluatedsomehow, in order to mitigate issues of its. In space most of failures of electronic devices
are occurred due to the single event upsets through cosmic rays. In the next subchapters,cosmic ray and failure mechanisms will be explained.
Cosmic Ray
There is still not certain scientific description for terms of cosmic ray. Sometimes it
is named Space radiation. As known, cosmic rays come from outer space was discoveredin 1913. Customary, cosmic ray is energetic particles that composed of protons, electrons,
and fully ionized nuclei, which come from outer space. Nowadays, cosmic rays basicallydivide to four sections [15]:Primary Cosmic rays: It consists of Galactic particles which enter to Solar systemand some of them to earth. It called Galactic Cosmic Rays
Solar Cosmic rays: It is originated by phenomena on the Sun which called solar
wind.
Secondary cosmic rays: When cosmic rays enter to the earth atmosphere, it

9|becomes shower of secondary particles due to its hitting with atmosphere molecules.
Terrestrial cosmic rays: Particles which comes to the earth surface. More than 99%
of particles are non-primary cosmic rays particles. Most of them third to seventh
generation cascade of initial particles.
However, we will focus on space radiation environment. In the near-Earthenvironment first and second classification of particles are basically discussed. In
additionally there are trapped particles in the near-Earth environment.
There is a continuous flux of Galactic Cosmic Ray ions. Although the flux is low, a
few particles per area of cm2 and per time of s-1, Galactic Cosmic Rays include energetic
heavy ions which can deposit significant amounts of energy in sensitive materials and it
may cause problems to spacecraft’s electronics and manned missions in space [16].
Second huge source of Cosmic ray is the Sun. It has eleven years of periodical
activation cycle as shown in Fig. 3-1. As for solar particles, the Earth’s magnetic fieldacts a varying degree of geomagnetic shielding for near Earth environment.

Fig. 3-1Cosmic Ray flux at Terrestrial altitudes [15]A number of significant events related to solar cycles may have been reason forseveral spacecraft operational anomalies. Thus, radiation protection is significant issue
for big space platforms operations, for deep space missions such as to Mars, or for a

10 |landing on the Moon. For these several reasons, considerable importance has been
appeared in last decades concerning the prediction data of solar proton fluencies [16].

3.1.1. Flux, Cross Section
In term of Flux, to calculate proton caused error which basically called single event
error, is important understanding. Current density should be considered as well. “Integralsof the product of flux with corresponding cross sections yield the number of interactionsof interest per cubic centimeter or per gram of material. Particle-material interactions, as
opposed to particle-particle interactions, are of overwhelming interest. The latterinteractions occur, such as high energy gamma reactions that produce an electron andpositron” as mentioned in [17]. However, they have negligible bearing this dissertation.
Particles have movement of omnidirectional. Particle flux at position r in sphericalcoordinates is shown in Fig. 3-2.

Fig. 3-2 Particle flux at position r in spherical coordinates

11 |If we define n(r) by mathematical expression as it is a particle density. It can be
expressed that as shown in Eq. 3-1. At around r, particles with Omni directionally
travelling velocity is 𝑣𝛀, for 𝑑Ω, velocity becomes 𝑣.
2𝜋𝑛(𝐫) = ∫ 𝑛(𝑟, 𝛀)𝑑Ω = ∫𝜋

𝑑𝜙 ∫ 𝑛(𝐫, 𝛀)𝑠𝑖𝑛𝜃𝑑𝜃00

Eq. 3-1 Particle density

Where:
r – Radius position vector
Ω – Directional unit vector
Here we should mention about cross section which is the important term forparticles physics. Basically, an interaction cross section is written as letter σ. When theparticle with 𝑣 of velocity travels in the medium for 1 second, it interacts with themedium and that makes cylindrical shape as shown in Fig 3-3. This interacted shape’s
length is defined by velocity of particle and here is the σ as cross sectional area ofinteraction. We can consider that particle interacts with every single atom in thatcylindrical volume. Here, N is the number of atoms per cubic centimetre in thatcylindrical volume (particles/cm3). Hence, 𝑁𝜎𝑣 will be the number of interactions by an
incident particle per one second in the path volume.

Fig. 3-3 Interacts with the medium and that makes cylindrical shape

12 |On the other hand 𝑁 = 𝜌𝑁0 /𝑀 or 𝜌𝑁0 /𝐴 , here 𝜌 is material density and 𝑁0 is
Avogadro’s number. A is materials mass number when targets are nuclei; M is themolecular weight when targets are atoms or molecules. Yields in Eq. 3-2 are defined as
number of interactions per cubic centimetre which occur at r, characterized bycorresponding cross section.
𝑁𝜎𝑣𝑛(𝒓) =𝑛(𝐫)𝑣 𝜙(𝐫)=𝜆𝜆Eq. 3-2 Interactions at r

If there is needs to define interaction computing, probability of interaction should
be considered as well. This probability is defined by terms of Cross section. As shown in
Fig. 3-4. It can be simply explained by this manner which shown in figure. Particles beam
(Intensity of I particles/cm2) is normally incidence on the A area of thin slab which has ∆xof thickness. The material type of slab can be any which includes molecules or nuclei etc.
Those interacting area with beam normal incidence is assumed circular. All of target
should be normal to the beam which defined as 𝜎(cm2).

Fig. 3-4 Particles beam on the thin target material.

If we consider that beam is the function of I(x) along to the x direction. Slabbecomes attenuator. Total number of targets per cubic centimeter is N. Total number oftargets in the slab is 𝐴∆𝑥𝑁. Here A is the slab area, ∆𝑥 is the thickness of the slap andmultiple of these are the total volume of the slab. From here total target area becomes𝐴∆𝑥𝑁𝜎 . Attenuation defined by ratio of total target area and slap area. Thus beam
intensity difference just after slab becomes that as Eq. 3-3. [17]13 |𝐼(𝑥 + ∆𝑥) = 𝐼(𝑥) − 𝐼(𝑥)

𝐴∆𝑥𝑁𝜎
𝐴

Eq. 3-3 Beam intensity difference after and before slap

From here we can derive 𝜆 which is called the mean free path as shown in Eq. 3-4.
It means 𝜆 is mean distance between two collisions by particle and material atom.
1=𝜆𝑁𝜎
Eq. 3-4 Mean free path

Here are dimensions that 𝐴(cm2 ), 𝑁(cm−3 ), 𝜎(cm2 ), 𝜆(cm) , 𝑁𝜎(cm−1 ) . Even
though 𝜎 is the interaction probability per centimeter square area, unit is cm2. Cross
section can be varied that depends on what kind of method considered for collision. For
example mechanical collision electromagnetic collision or quantum collisions aredifferent. In our calculation, proton flux is the main particles, for this reason
electromagnetic collision is considered.

3.1.2. Proton flux at earth environment
90% of those cosmic rays consist of protons in low Earth orbit (below an altitude of
2000km) [15]. For that reason this study assumed proton flux as a main consideration.
(Neutron flux is dominated in terrestrial; in spite of space proton flux is higher than otherspace particles [18]). Further Protons of Cosmic rays will be called Proton flux in thisdissertation.
Proton flux in near earth environment majorly consists of solar protons and trapped
protons. The Earth's trapped particle radiation belts were discovered at the beginning of
the space technological development and were immediately noticed as considerable
problems to space missions. Consequently, NASA has developed several models whichenable to predict population of trapped protons and other particles, such as model AP-8
and AE-8 since 1970. But results say that reality of trapped particles modeling is muchcomplex than expected. Nowadays many models developed, however they are still
limited in spatial or temporal coverage. Therefore dynamic and complete model is stillrequired to be developed for trapped radiation belt of near earth environment.
The motions of charged particles entering the magnetosphere from the solar windand undergoing acceleration, or resulting from the decay of neutrons produced by cosmic
ray interactions with the neutral atmosphere, are dominated by the magnetic field ofmagnetosphere. The motion of these energetic charged particles consists of threecomponents as shown in Fig. 3-5 [16]:14 |Gyration about magnetic field lines;
Movement of the gyration centre up and down magnetic field lines;
Slow longitudinal drift of the guiding centre path around the earth, westward forions and eastward for electrons.

Fig. 3-5 The motion of energetic charged particles in magnetosphere [16]The result of trajectories lies on toroidal surfaces, called drift shells, centered on thecenter of Earth's dipole. Particles limited to a drift shell can remain there for long times,
up to several years for protons at altitudes of thousands kilometers, hence the term iscalled "trapped particles". The population of charged particles stably trapped by the
Earth's magnetic field consists mainly of protons with energies between 100 keV andseveral hundred MeV.
A Solar protons are generated when protons emitted by the Sun during a solar flareaccompanied by a coronal mass ejection it become very high energies of particles. Afterthat Protons are guided by the deep space magnetic field lines as shown in Fig. 3-6.

15 |

Fig. 3-6 Solar energetic protons emitted by the Sun and guided by magnetic field line [19]Energetic proton flux can be reason of electrical charging of spacecraft to amountthat can damage spacecraft components. This charging aspect is critical at high voltage
application on spacecraft, especially for High voltage solar panel application. Earth islargely protected by its magnetic field, or magnetosphere. However, the closer a
spacecraft near to the Polar Regions, these are been exposure higher radiation than otherregions. In further subchapter, damage and failure which caused by proton will be
discussed.

3.2. Mechanism and failure in Devices
One of the most difficult problems facing electronics of space application is that
effect of charged particles. When these particles pass through a material, it loses its
energy by ionizing volume material, generating electron-hole pairs along the path of theparticle. The interaction of electrons, protons, and heavy ions with electronic devices
leads to two different types of problems as shown in Fig. 3-7. The first one is total dosedegradation, which the cumulative effect of many particles is passing through anelectronic device cause parameter degradation and functional failure, and it will not be
discussed here. Another one problem, single particles passing through electronic device
may cause several of effects, generally known as single event errors or phenomena (SEP)
[20].

16 |

Fig. 3-7 Classification of Space radiation effects in electronics

The single event errors are classified in hard errors and soft errors. Hard errors are
non-recoverable errors which named destructive error. Soft errors may be recovered by areset, a power cycle or simply a rewrite of the information which named non-destructive
error.
Single event errors due to protons are a significant problem in the electronic
circuitry of earth-orbiting spacecraft. A nuclear reaction initiated by a proton can produce
sufficient ionization for a single event error.

3.2.1. Proton-Silicon interaction
In this section basic physics understanding about proton induced failure phenomena
in silicon will be briefly described. The cause of failure is proton flux. Why only proton
flux was considered here is described in chapter 3.1.1. When an energetic proton
penetrates silicon, several types of interactions may happen. For example, protons canscatter from the Silicon atoms as type of elastic, inelastic scattering can be happened,
which can then recoil, or they can ionize the atom by hitting molecules, leading to thegeneration of charge inside material. The nuclear interaction makes a mechanism due to17 |an energetic ionizing particle or non-ionizing neutron can deposit a large amount ofenergy in to the device material that has tiny dimensions. Ionizing is usually made bysecondary recoiled heavy ions track. But these interactions inside silicon by energetic
proton have some probability for those interactions occurrence. The incident protoninteracts with the nuclei of the material then heavy particles and scattered protons are
generated after this collision. As a result, scattered heavy particles transfer amount ofenergy to the Silicon. On the other hand, it can be said proton deposits energy to thesilicon. Most of the energy deposition takes the form of ionization loss along the way ofthe charged secondary recoils coming out from the affected atoms or molecules and along
the path of the recoiling residual nuclear fragment that as shown in Fig. 3-8. Generated
charge due to that ionization is the reason of single event errors which mentioned
previously. Basically those ionizing process generates extra charge inside semiconductor
device which nearly proportional to the deposited energy by high energetic proton. Pair
generation energy depends on the medium band gap energy. The energy 𝑊 required tocreate an h-e pair in a semiconductor by a charged mass particle traversing the medium
depends on the band gap energy Eg of the material and hence, although only slightly, on
the temperature. The measurements of this quantity show a nearly linear dependence on
the band gap energy, and the linear fit to the data obtained for different materials gives asshown in Eq. 3-5.
𝑊(𝐸𝑔 ) = 1.76 𝑒𝑉 + 𝐸𝑔 ∗ 1.84𝑒𝑉
Eq. 3-5 Required energy to generate one hole-electron pair

The probability of proton-induced failures and the dependence of cross section on
proton energy can be investigated both experimentally and theoretically.

Fig. 3-8 Ionization made by secondary recoils due to proton induced nuclear reaction.

18 |To measure this energy transfer from proton to silicon we use some terms ofunderstanding. These are terms of linear energy transfer (LET) and stopping power.
These are almost same meaning; the stopping power includes meaning of LET. The basic
𝑀𝑒𝑉

unit for linear energy transfer and stopping power is same as (𝑚−1 𝑜𝑟

𝑀𝑒𝑉 𝑐𝑚2𝑚𝑔). As before

mentioned that particles loss its energy by nuclear, electrical material and density caused
retracting when these penetrate to the material. In this study, we interest ionization
phenomena inside silicon by proton induced.
Firstly, linear energy transfer is the average energy deposition of the particle perunit track length; it means how much energy deposits to the material and it purely
generates hole-electron pairs in the unit length of the material. Linear energy transfer isthe positive quantity and basically it represents energy which makes ionization in thematerial. Linear Energy Transfer which is expressed by Eq. 3-6.

𝐿∆ =

𝑑𝐸∆
𝑑𝑥

Eq. 3-6 Linear Energy Transfer

This 𝐿∆ and yield of energy deposition with distance travelled depends on thematerial properties. Here 𝐸∆ is the energy of particle and 𝑥 is the distance travelled.
Basically, Linear Energy transfer is varied depending on incident particles’ kinetic energy.
Linear Energy transfer of material depends on the atomic density (atomic number so on)
as well as incident particles’ energy. In other words, Linear Energy transfer is describedby terms of atomic density thickness, rather than geometrical size of the length. In our
calculation, for defining of the heavy ion model ionization in the T-CAD is used term ofLinear Energy Transfer.
The term of stopping power is wider understanding than LET and that represents
total energy loss of the particle per unit length path in the volume material by both elastic
and inelastic collisions (another names are linear stopping power and mass stopping
power). Here, linear stopping power also includes term of LET in the some case. Other
words, term of stopping power includes two compounds terms which are nuclear andelectronic stopping power. The stopping power represents total energy loss of energetic
particle when it penetrates to the materials. The 𝑠𝑠𝑝 can be described as the total quantityof stopping power, which described in Eq. 3-7 and Eq. 3-8. Here 𝜌 is the density of the

19 |material and 𝜌𝑥 is the density-thickness.
𝑆𝑙 = −𝑑𝐸
𝑑𝑥

Eq. 3-7 Linear stopping power

𝑆𝑚 = −

𝑑𝐸
1 𝑑𝐸 𝑆𝑙=−=𝑑(𝜌𝑥)𝜌 𝑑𝑥 𝜌

Eq. 3-8 mass stopping power

Then the total energy losses of energetic particles rates 𝑆𝑡 can be defined sum of allinteractions results. Basically LET and stopping power are identical unless energetic
secondary particles may escape the material. LET is considered for the electromagnetic
interaction in the material which means almost all energy transfer makes ionization.
Charged particles such as proton can give energy to the atom even though it just passes
closely. Stopping power consists of several interaction influences for its total value ismostly in the range of keV to few MeV as shown in Fig. 3-9 [21]. In our calculation
proton flux energy range is up to 200 GeV corresponding literature data.

Fig. 3-9 Stopping power of the proton variation respects to the incident energy up to 100 MeV [21]20 |Then we should consider high energy range of proton flux affect rather than keVenergy of range of proton flux. When the high energy range of proton penetrates to thematerial, electromagnetic stopping power will be dominated as shown in Fig. 3-10 [22].
Here we can see the 𝑠𝑠𝑝 is majorly compound by electronic stopping power. Thus we used
LET for our calculation and considering worst case, all energy were assumed to generatehole-electron pairs.

Fig. 3-10 Stopping power type corresponding to energy of incident particles [22]3.2.2. Semiconductor devices failure due to cosmic ray
3.2.2.1. Integrated circuits failure by cosmic ray
Huge amount of hole-electron pairs are generated due to this ionization loss. If sucha nuclear event happens within or near the sensitive part of electronic elements such aslarge scal integrated circuits and power devices. The large scale integrated memory
device and sufficient charge is generated, the result can switch logic state of the memory
bit. The change of information stored at some location in memory has physical damage
which cannot be seen by observer, to the device is usually caused by single event soft
error. Energetic protons have been shown to induce soft errors in a number of Large Scale
Integrated dynamic and static RAM devices, the trend of development of electronic
components goes towards to usage of smaller, faster and more sensitive detectors in any
field of application. Small size of modern devices minimized to improve power

21 |consumption and processing speed; a single particle can have a critical effect and evencause non-recoverable damage to an electronic device. As a consequence, these devices
are more sensitive to radiation effects than older components. It makes needs tounderstand and protect for spacecraft systems against space proton effects. In traditional
space applications, larger components were used. For this reason single particles could
only affect a limited volume of the device, hence only cumulative damage occurred frommultiple particle affect could lead to malfunction of the devices as shown in Fig. 3-11
[23].

Fig. 3-11 Single event errors for low voltage electronics [23]3.2.2.2. Power devices failure by cosmic ray
Power devices for instance IGBTs, MOSFETs, and diodes in space application athigh altitude and sea level systems are incompetent to wrecker single event burnout due
to energetic particles. Single Event Burnout was initially observed in power MOSFETs,
and the error was related to the regenerative feedback mechanism when energetic
particles hit the device. Charge carrier multiplication process was the main reason of the
failure. After that single event burn out in bipolar transistors, observed this is similar to
failure mechanism of power MOSFETs. Recent studies have been related to accountingof Single Event Burn out in power transistors. Subsequently, power diode incompetent toSingle Event Burnout was started to study. The Single Event Burnout mechanism issomehow similar to the other power devices. In this study, we discuss the Single Event

22 |Burn out conditions in power diodes (PiN diode). Basic structure of power devices are
similar that consists of P-N junction and semiconductor materials as shown in Fig 3-12.
However we will briefly mention about power transistors failure as well in further.

Fig. 3-12 Structural similarity of power devices

When high energetic particle hits power transistor, hole-electron pair will be
generated along its track. And these charges will be flow both direction by electric field;
current is flown.
When the charge flows to ground via the body, the voltage drop in the bodyresistance may turn on the parasitic bipolar transistor that is an integral part of double
diffused MOS (DMOS) power transistors. If this current flows from positive to ground,
there will be voltage drop inside transistor, and it will turn on parasitic bipolar transistor
automatically. That parasitic bipolar transistor or thyristor is typically inside powertransistors as shown in Fig.3-13 and Fig.3-14 [24]. If the applied voltage is continuously
applied to the device quickly, at that time high currents and high voltages make second
breakdown of the parasitic bipolar transistor or thyristor and can result in burnout of thedevice.

23 |Fig. 3-13 A schematic representation of a power MOSFET transistor and a parasitic bipolar structure [24]Here:Power MOSFET body which hit by energetic particle
Energetic particles
Interaction of particle and materials atom
Secondary coils generates ionization which makes voltage drops
6- 7- parasitic bipolar transistor structure

24 |Fig. 3-14 A schematic representation of a parasitic thyristor in the IGBT components [24]As a result of the base push-out phenomenon the failure mechanism was describedbased on the current induced avalanche model. For IGBT, single event burnout study iskind of newly developed. As mentioned before in this study we will discuss about power
diode rather than other group of power devices such as power transistors and thyristors.
The reason for the single event error is often an internal gaining process forexample due to a parasitic transistor or thyristor for the power devices. A lot of recent
researches were observed that single event burnout can also be triggered by strong
avalanche charge carrier multiplication alone.
This phenomena was watched in high-voltage power devices and in large area
avalanche diodes, but has also been recognized for a long time in surface barrier detectors
as a non-destructive phenomenon. The event of avalanche multiplication is contingent thestart of event and its magnitude is exceedingly depending on the applied voltage to thepower device. The power diodes failure is very low probabilistically occurred in theterrestrial area. Basically natural background of charged particles flux is not so high in theterrestrial area which can destroy power devices. However, still it has catastrophic

25 |possibility to destroy systems. But this failure rate is quite higher in the spaceenvironment as we mentioned before. It should be considered worst case ever ofapplication systems every time. In order to investigate failure rate of power diode which
triggered by avalanche phenomena, several experiments have been done by researchers.
For well understanding about this phenomenon, let us take an example of power diodesingle event burn out process. The power device simulations have the disadvantage thatthe multiplication phenomenon is only triggered by nuclear reactions with the silicon
atoms [13]. As shown in Fig. 3-15 diode has generated charge which flow through along
to electric field distribution.

Fig. 3-15 PiN diode structure respect to electric field

Actual generated charge by energetic particle inside diode is not sufficient to makedestruction. But there is a phenomenon which called avalanche charge carrier
multiplication. This phenomenon explained in existing studies which tested 1700V power
diode under exposure of energetic particle flux and result was that as shown in Fig. 3-16[25]. Here yellow colored part represents direct ionized charges by energetic particle, andpink colored part represents multiplied charge under avalanche phenomenon. At thevoltage of 1060V, power was destructed. Hence we can see that avalanched failure rate ismuch less than break down voltage of the power diode. In detail, other study shows thatavalanched charge carrier respect to temporal and spatial evaluations as shown in Fig. 317 [12].

26 |Fig. 3-16 Generated charge and multiplied charge histogram respect to the voltage [25]27 |Fig. 3-17 Electric field and Current density variation respect spatial and temporal distribution. [12](Model 4k Diode, Nbase=450 µm, Applied voltage 1800V, LET=1.2 MeV/µm, Ion: C12 17MeV.)

28 |4. PROPOSED METHOD TO CALCULATION OF FAILURE RATE
In our study, we proposed that failure rate calculation of power devices’ main
formula which based on Single Event burnout cross section and Space proton flux
function. Difference from single event burn out cross section of small power
semiconductor devices, the Single event burnout cross section for high voltage power
semiconductor changes that depending on applied voltage for device itself. Basicbackground information was given in previous chapters.
The cross section is calculated by two functions, one is the threshold charge todestruction Qdest(V) obtained by T-CAD simulation as shown in Eq. 4-1 and charge
generation probability function ΦEp (Q) which was found from literature. By convoluting
proton flux function with the Single Event burnout cross section function, the main failure
rate calculation formula was derived as shown in Eq. 4-2.
𝑄𝑚𝑎𝑥

𝜎(𝑉) = A ∗ ∫𝑄𝑑𝑒𝑠𝑡 (𝑉)𝛷𝐸300
(𝑄) 𝜕𝑄𝑝

Eq. 4-1 Cross section respect to applied voltage for the power device
𝐸𝑝𝑚𝑎𝑥

𝐹𝑅 = ∫

𝐸𝑝𝑚𝑖𝑛

𝑄𝑚𝑎𝑥

𝐴∗∫
𝑄𝑑𝑒𝑠𝑡 (𝑉)(𝑄) 𝜕𝑄 ∗ 𝐹(𝐸𝑝 )𝜕𝐸𝑝𝛷𝐸300
𝑝

Eq. 4-2 Failure rate calculation formula which proposed as new

Here:
FR - failure rate of device [s-1]A - Device area [m2]Ep - Incident energy of proton [MeV]
Ep max -Maximum incident energy of Proton [MeV]
Ep min - Minimum incident energy of Proton [MeV]
Q -Generated charge inside silicon by deposited energy [C]Qmax - Maximum generated charge inside of silicon by deposited energy [C]
Qdest(V) -Threshold charge which can generate avalanche phenomena inside silicon
due to deposited energy from proton [C]ΦEp300(Q) - Probability function of charge generation according to incident energy
[C-1]

29 |

F (Ep) - Space proton flux funtion, which consists three sections by energy range at
Low Earth Orbit [MeV-1s-1m-2]

σ(𝑉)- Single Event Upset Cross section [m2]
In order to establish our proposed formula, three sections were considered. First, TCAD device simulation, 3.3kV PiN diode was chosen for device model. Hence,
destruction charge value, which is generated by deposited energy of space proton, wasobtained from simulation. Second, Space proton flux data according to energy range in
Low Earth Orbit (LEO), was obtained from SPENVIS web based software from
European Space Agency, Alpha Magnetic Spectrometer (AMS) [18]and PAMELA data
[26]. Third, probability functions of energy deposition in device because consequently
silicon-proton reaction and SEU cross section were studied before [27] [28] [29] [30],from here, probability functions of energy deposition corresponding to device’s applied
voltages were calculated. Last result was defined as SEU cross section and failure rate
respect to the applied voltage for 3.3 kV PiN diode. Details will be explained in next
section as shown in Fig. 4-1.

𝑬𝒑

𝑭𝒂𝒊𝒍𝒖𝒓𝒆 𝑹𝒂𝒕𝒆 = ∫𝑬𝒑Power Devices Physics
Based on T-CAD(SYNOPSIS)SIMULATION

𝒎𝒂𝒙

𝒎𝒊𝒏

𝑸
𝒎𝒂𝒙

𝑨∗∫

𝑸𝒅𝒆𝒔𝒕(𝑽)

Nuclear Physics
Based on Study of
LITERATURES

𝜱𝟑𝟎𝟎
𝑬𝒑 (𝑸)𝝏𝑸 ∗ 𝑭(𝑬𝒑 )𝝏𝑬𝒑

Astro Physics
Based on SPENVISSIMULATION
Data of
LITERATURES

Fig. 4-1 Compounds of the Failure rate Formula30 |4.1. Proton flux data for formula
As mentioned before, majority of cosmic ray consists of proton in Low Earth Orbit[9]. Trapped proton flux, solar proton flux, and cosmic proton flux compound total space
proton flux at Low Earth Orbit basically in range of up to energy of GeV. In thiscalculation, range was 1MeV-200GeV as shown Fig. 4-2. Proton flux data resources andits features is shown in Table 4-1.

Fig. 4-2 Proton flux range at this calculation
Table 4-1Proton flux data resources and its features

Source of data

1. SPENVIS

2. PAMELA

3. AMS

Methods

Simulation

On orbit

On orbitExperiment

Experiment

ProtonProtonProtonEnergy range

1-400MeV

1GeV-20GeV

20GeV-200GeV

Altitudes~700km~610km~400kmConsidered
Particles

However proton flux density is not uniformly dispersed along the Low earth orbit,in the main formula, total space proton flux written as fitted function F(Ep) which doesn’t
depend on orbital position. In calculation, shield material hasn’t been considered in thissection. But further for development of this research, shielding materials and hardening

31 |will be discussed. To find out precise data is still complicated and near consideration was
taken in this study.
Entire energy range of considered proton flux divided three sections that wascovered from 1Mev up to 200GeV. First 1MeV-400MeV proton flux data, which
considered at 700 km altitude and its fitted function were taken from SPENVIS [16], here
mission period assumed 2018-2019, that could clarify sun activation. SPENVIS is the
web based software was developed by European Space Agency and is widely used space
application studies. This web site has several models for predict cosmic ray distribution in
the along to earth outer space. Basically space proton flux in the earth orbit consists ofthree kinds of resources. First one is Galactic proton flux that comes from deep space ispredicted by CREME-96 Sol. Min (1977) model. Second one is solar proton flux that has
two models which are CREME-96 (worst week) and ESP-PSYCHIC worst case event.
Third one is the trapped proton flux that has a model AP-8 max. After combining thesethree of resources data, as shown in Fig. 4-3, majority of space proton is came from thesun. Fitted function in this section is considered by that total flux data for proton flux
until 400MeV.

Fig. 4-3 Radiation sources data from SPENVIS (Differential flux (𝐸𝑝)) [16]32 |Second 1GeV-20GeV proton flux data, which measured at around altitude of 350610km were taken from PAMELA data source as shown in Fig. 4-4 [26]. PAMELA is thespacecraft mission payload for study about possible exotic cosmic ray source and its
propagation reasons; mission time was 2006-2008. Proton is top set of data. Helium isthe bottom set of data. All but one of the previous measurements comes from balloonborne experiments. Previous data up to few hundred billion electron volts per nucleon
were collected by magnetic spectrometer experiments, whereas higher-energy data comefrom calorimetric measurements. PAMELA data cover the energy range 1 GeV to 1.2
TeV (1 to 600 GeV per nucleon for He). The fluxes are expressed in terms of kinetic
energy per nucleon, converted from the rigidity measured in the tracker and neglecting
any contribution from less abundant deuterium (d/p ≃ 1%) (where d is deuterium) and3He (3He/4He ≃ 10%). Therefore, pure proton and 4He samples are assumed. Error bars
are statistical and indicate 1 SD; the gray shaded areas represent the estimated systematic
uncertainty. E is kinetic energy per nucleon. (as explained in [26]).

Fig. 4-4 Proton and helium absolute fluxes measured by PAMELA above 1 GeV per nucleon, comparedwith a few of the previous measurements [26].

33 |From PAMELA data we have chosen proton flux until 20GeV and make amathematical function for it through fitting data graph. However PAMELA data covers
up to 1TeV energy of flux measurement, based on consideration of the influence of solar
modulation, upper range of data from here is 20GeV in the beginning of the study.
At last 20GeV-200GeV proton flux data, which measured at altitude ofInternational space station around 400 km and its fitted function were taken from AMS
data source as shown in Fig. 4-5 [18]. AMS is a general purpose high energy particle
physics detector in space. The permanent magnet, the silicon tracker, four planes of timeof flight (TOF) scintillation counters, and the array of anticoincidence counters (ACCs),
transition radiation detector (TRD), a ring imaging Cerenkov detector (RICH), and anelectromagnetic calorimeter (ECAL) were the tools and equipment which used in thismeasurement. An accurate measurement of the electron and positron energy E and of theshower shape has been made by three-dimensional imaging capability of the 17 radiation
length ECAL. The proton flux’s precise measurement in primary cosmic rays isestablished based on 300 million of events. It has been covered with the rigidity(momentum/charge) from 1 GV to 1.8 TV. Due to our initial calculation capability, we
have chosen upper limit of total proton flux by 200 GeV. Then from 20GeV to 200GeV
energy range of proton flux data in Low earth Orbit was taken from AMS, correspondingaround 400km altitude and its fitted function derived as well.

Fig. 4-5 The AMS measured proton flux as a function of kinetic energy E K as multiplied by E2.7K comparedwith recent measurements [18]34 |These three set of data were used to fitting functions for calculation when early
study. After that some our paper used PAMELA and STE-QUEST space missions’ proton
flux data [26] [31].

4.2. Energy deposition probability function
This section purpose is to derive probability function of charge generation

ΦEp300(Q) with depending energetic proton flux as shown in Fig. 4-6 .

Fig. 4-6 Probability function of charge generation ΦEp300(Q) by energetic proton.

We assumed that, deposited energies form protons to the silicon completely
generate electron-hole pairs. On the other hand amount of generated charge linearly
depends of deposited energy. Pair generation energy depends on the medium band gap
energy. The energy W(Eg) required to create an e-h pair in a semiconductor by a charged
mass particle traversing the medium depends on the band gap energy Eg of the material
and hence, although only slightly, on the temperature. The measurements of this quantity
show a nearly linear dependence on the band gap energy, and the linear fit to the dataobtained for different materials gives Eq. 4-3.
𝑊(𝐸𝑔) = 1.76 eV + 1.84𝐸𝑔 eV
Eq. 4-3 Required energy to generate a hole-electron pair in the silicon

The mean energy 𝑊(𝐸𝑔) to create an electron-hole pair has been calculated andmeasuredinexperiments

including high energy charged

particles.

The

mean

energy 𝑊(𝐸𝑔) required to create an e-h pair in silicon is 𝑊(𝐸𝑔)≈ 3.68 eV. The paircharge is e=1.6*10-19 coulomb [32]. Hence coefficient α=2.33×1013MeV/C, which shows
relation between deposited energy and generated charge has been found.
In order to define proton cross section, literature study was used [27] [28]. In this35 |that referenced paper, the modelling of proton single event phenomena cross-sections
versus proton kinetic energies is based on the fact that secondary recoils induced byproton Silicon nuclear reactions are mainly responsible for the devices destruction. The
proton energy loss in matter is too low (several keV/pm) to generate Single Event burnout
directly. The secondary recoil energies, ranging from several keV to several MeV, arecomparable to the energies lost by primary heavy ions crossing the devices. The
referenced model, developed to define proton cross section in silicon, assumes that thesemiconductor element will react similarly as long as the amount of energy Ed is provided
by a proton Silicon nuclear reaction or by an energetic heavy ion.
Basic idea of referenced paper is that proton cross section can be defined by heavy
ion cross section which developed before in several studies. Using this study result, we
can obtain proton energy deposition probability function 𝛷𝑥,𝐸𝑝 (𝐸𝑑 ). The heavy ion LET
corresponds to exact energy deposition to the device Ed (here Ed = LET x device sensitive
thickness). When the sensitivity of a component is well characterized as a function ofincident heavy ion LET which depends on heavy ion cross section, the device's sensitivity
can be expressed versus Ed(σIL(Ed). Convoluting the probability function of Ed from thesecondary recoils x, Ep (Ed) with the heavy ion cross-section curve σIL(Ed)calculated for
one incident proton energy Ep gives the proton single event error cross section of thedevice at Ep as shown in Eq. 4-4, Fig. 4-7.

Fig. 4-7 Φx,Ep(Ed) and σ(Ed) : the hatched area hides the part of Φx,Ep(Ed) which is not taken into account in
the convolution

36 |

Ep

σp (Ep ) = ∫ σIL (Ed )Φx,Ep (Ed ) dEd
Es

Eq. 4-4 Proton single event effect cross section of the device at Ep

The existing study defined probability function of energy deposition based on
HETC calculation as shown in Eq. 4-5 [27] [28] [29] [30].
x

x

x

x

ΦEx p (Ed ) = 10a1 (Ep )Ed +a0 (Ep ) +10b1 (Ep)Ed +b0(Ep )ΦE𝑥𝑝 (Ed ) = Φ1 (Ed )+Φ2 (Ed )Eq. 4-5 Probability function of energy deposition based on HETC calculation

Here:
Ed - Deposited energy [MeV]x - Sensitive thickness [µm]

Φ1 - Probability function for low energy deposition [MeV-1]
Φ2 - Probability function for high energy deposition [MeV-1]
b1 - Parameter according to high energy depositionb0 - Parameter according to probability
Basically, we can say that energy deposition function consists of two decreasing
exponential functions and Φ1 correspond to Ed < 2 MeV energy of particles, Φ2correspond to higher energy of particles [27]. In our calculation Φ2 is important, and then
Φ1 omitted. Then we can have Eq. 4-6. If we define compound and shape of energy
deposition probability by proton flux and silicon interactions, we can make 𝛷𝑥,𝐸𝑝 (𝐸𝑑 ).
xx

ΦEx p (Ed ) = 10b1 (Ep)Ed +b0(Ep )Eq. 4-6 Probability function of energy deposition from proton flux to silicon material

That neglecting is related to the method of evaluating deposited energy. Secondary
protons were neglected in the total result for the all nuclear reaction cases. Their
withdrawn energy after collision usually does not exceed 6 MeV that could be consideredmean value. HETC is not appropriated to simulate intermediate and low proton energies
such as less than 70 MeV.
As before mentioned Φ1(Ed) represents the probability to deposit tiny amounts ofenergy less than 2MeV, while, Φ2(Ed) represents the more practical assumable amounts.

37 |Parameters al, a0, b1, b0 provided by developed model in referenced paper depends
strongly on the incident proton energies Ep (MeV) and on the silicon thickness x (µm). In
order to prove that energy deposition probability function existence, this bidirectionalparameter dependence is shown Fig. 4-8 for b1, which represents the change of the slope
corresponding high amounts of deposited energies. For insteance Fig. 4-7 shows that
deposited energy spectrum at 6 µm thickness of silicon case, which represent energy
deposition probability variate by incident energy.

Eq. 4-7 Modeling of experimental 𝚽𝐄𝐱𝐩 (𝐄𝐝 ) for various proton energies in 6 pm Si layer

Fig. 4-8 Parametrization of bl (Ep,x) [28]38 |Fig. 4-9 Energy deposition probability function at various thickness of silicon under 200MeV energy of
proton flux

Fig. 4-9 shows that same incident energy of proton flux gives different energy tosilicon even though thickness of silicon is constant. These aspects proves bidirectional
dependence of silicon’s energy absorption function Φ2 which defined by two parameters.
In order to define Φ2, we need to Figure out b1 and b0. Parameters depend on
sensitive thickness of silicon and incident energy of particles. Our model defined device
thickness as around 350µm and on the other hand generally device thickness is around
300µm therefore sensitive thickness has been fixed on 300µm. Parameters b1 and b2
found from the paper as well [27].
Parameter b1 at 19µm sensitive thickness defined at the paper [28]. By combining
these data as shown in Table 4-2, fitted functions for b1 and b0 were obtained as shown in
Fig. 4-10, Fig. 4-11.

39 |Table 4-2 Fitting of b1 and b0

Incidentb1
b1
b0
Fitted Fitted
Energy(19um) (300um) (300um) b1
b0
(MeV)
100

-0.107-0.077 -4.481

120-0.105-0.076 -4.480

140-0.102-0.073 -4.477

160

-0.1

-0.072 -4.476

180-0.097-0.070 -4.474

200-0.095220-0.094-0.068 -4.472

240-0.092-0.066 -4.470

260

-0.09

-0.065 -4.469

280

-0.09

-0.065 -4.469

300

-0.09

-0.065 -4.469-0.068-4.472 -0.068 -4.472

Fig. 4-10 Fitted b1 (at 300 µm Si).

40 |

Fig. 4-11 Fitted b0 (at 300 µm Si).

Hence probability function of energy deposition ΦEp300(Ed) has been defined at
300µm thickness as shown in Eq. 4-8. Here probability function defined by depositedenergy, last purpose is to define probability function by generated charge. We used α
coefficient for transition under the relation, ΦEp300(Ed) to ΦEp300 (Q) as using expressionΦEp300(Ed) = ΦEp300 (α×Q). Probability function which defined by generated charge has
been found as shown in Eq. 4-9.
xx(Ed ) = 10b1 (Ep )Ed +b0 (Ep)ΦE300
p
Eq. 4-8 probability function of energy deposition ΦEp300(Ed)Ed = αQgxx(αQ) = 10b1 (Ep )αQg+b0 (Ep)ΦE300
p
Eq. 4-9 Probability function which defined by generated charge

Using above relation we made transition from probability function of depositedenergy ΦEp300(Ed) to probability function of generated charge ΦEp300 (Q), and forsimplicity we used same notation ΦEp300 for both functions.

41 |4.3. T-CAD simulation to obtain charge generation in device
When high energetic particles penetrate a semiconductor device, they deposit theirenergy by the generation of hole–electron pairs. These charges can perturb the normal
operation of the device. This chapter describes the models for T-CAD simulation to get
critical charge which could lead to avalanche multiplication phenomenon. In chapter
3.2.2.2 we discussed about avalanche phenomena effect on the power diode. The
deposited energy generates amount of charge that could be trigger of destruction whichcaused by avalanche phenomena as shown in Fig. 4-12.

Fig. 4-12 Burnout Condition based on avalanche phenomena

Particles penetrate into the device and deposit energy, that generated charge bydeposited energy expressed Q. Single Event Burnout failure occurs when the generated
charge Q exceed to a certain amount of charge, which causes avalanche phenomenon. We
named it by threshold charge to destruction Qdest(VDC).

42 |Fig. 4-13Function of threshold charge to destruction Qdest(VDC) respect to the applied voltage

Main purpose of this T-CAD simulation is to estimate function of threshold charge
to destruction Qdest(VDC) respect to the applied voltage as shown in Fig. 4-13. Expectedcurve divides three zones which are illustrated safe zone, avalanche zone, burnout zone.
Qdest(VDC) function defined by border line between safe zone and avalanche which
depends on applied voltage. This was the expectation of result of simulation.
Combination of charge and voltage need to be defined. Each point requires transient
TCAD simulation for Avalanche phenomenon. More than 100 points needed to be
simulated in order to mitigate problem of simulation time. To do that we selected PiN
diode for simulation model for simplification of device structure and reduction of mesh
number. PiN diode can represent other power devices as internal structure. Homogenous
structure of diode makes it to be able to perform Cylindrical Simulations (Quasi-3D)
instead of ordinary 3D simulation for reduction of simulation time as well.

43 |4.3.1. T-CAD simulation for charge generation function
In Combination of charge and voltage need to be defined Each point require transient
TCAD simulation for Avalanche More than 100 points needed to be simulated Problem
of simulation time
In order to evaluate generated charge Q by energetic particle we used ionization
particle model of T-CAD software. This model gives destruction function by generated
charge inside semiconductor devices. When a particle penetrates a device structure, itloses energy and creates a trail of electron–hole pairs along its track. These additional
electrons and holes cause the avalanche phenomena which leads to single event burnout.
However, our study target is proton; it can make heavy ion as secondary recoils by hitting
the Silicon atom with some probability. This probability function discussed in previous
chapter. There may have misunderstood that seems like heavy ion relates to calculation
formula. The calculation formula doesn’t relate to the heavy ion. Heavy ion model has
been used only for prediction of destruction charge generation value which leads toavalanche charge multiplication phenomenon. For modelling ionization particle in TCAD important factors are:

The energy and type of the particle.



The angle of penetration of the particle.



The relation between the lost energy and linear energy transfer (LET) and thenumber of pairs created.

The generation rate by the ionization particle is in most cases practiced in transient
simulations. The number of hole–electron pairs generated before the initial time of thetransient is added to the carrier densities at the beginning of the simulation.

44 |Fig. 4-14 Track of ionization particle penetration a semiconductor material; it is defined by a length and thetransverse spatial influence is assumed to be symmetric about the track axis`
A simple model for the heavy ion impinging process is shown in Fig 4-14. The
generation rate caused by the heavy ion is computed by Eq. 4-10:
𝐺(𝑙, 𝑤, 𝑡) = 𝐺𝐿𝐸𝑇 (𝑙)𝑅(𝑤, 𝑙)𝑇(𝑡)
Eq. 4-10 The generation rate

If l lmax (lmax is the length of the track), and by 𝐺(𝑙, 𝑤, 𝑡) = 0:
If l lmax Rwand Ttare functions describing the spatial and temporalvariations of the generation rate. 𝐺𝐿𝐸𝑇 (𝑙)is the linear energy transfer generation density
and its unit is pairs/cm3.
Tt is defined as a Gaussian function as show in Eq. 4-11:

2 ∙ exp (− (𝑇(𝑡) =𝑡 − 𝑡0 2))𝑠ℎ𝑖 √2√2 ∙ 𝑠ℎ𝑖 √𝜋 (1 + erf (𝑡0))
𝑠ℎ𝑖 √2

Eq. 4-11 Gaussian function

45 |Where the moment of the ionization particle penetration and 𝑠ℎ𝑖 is the characteristic
value of the Gaussian.
In the T-CAD simulation, 3.3 kV PiN diode model was chosen as energetic particle
penetrated devices; because simple structure of PiN diode can basically represent othersemiconductor power devices, as P-N junction structure and biasing. The transient
simulation was performed on default value of most characteristics of model. We analysed
Qdest(VDC) with 3.3-kV PiN diode in T-CAD simulation. A cylindrical structure with a
400 μm radius was used. Fig 4-15 and Fig 4-16 show that simulated diode model andmeshing method of it. The structure consists of highly doped N-layer and P-layer, andlightly doped 350 μm N-base between these highly doped layers. Position of the energetic
particle penetration is the centre axis of the cylindrical structure, and it is 10 μm deep
from the boundary between P-layer and N-base toward N-base that path includes
generated charge Q. The radial distribution of the generated charge was determined by aGaussian distribution with a characteristics length of 0.02 μm.

Fig. 4-15 Simulated diode model in TCAD

46 |

Fig. 4-16 Meshing method of simulated diode mode in TCAD

Fig. 4-17 Charge deposited 3.3 kV PiN diode model in T-CAD simulation.

As shown in Fig. 4-17, reverse biased diode, the charge generation as a function of
applied voltage for different particle energy. When the generated charge Q becomeslarger than certain amount, then avalanche phenomenon starts. The value of generated
charge Q that triggers avalanche phenomenon starting was determined as the thresholdcharge to destruction Qdest(VDC), which has a function of the applied voltages. We
obtained values of threshold charge to destruction Qdest(VDC) from three kinds of energyof particle cases (10 MeV, 50 MeV and 100 MeV).
The Fig. 4-18 shows Reverse bias Characteristics of 3.3kV PiN diode model for TCAD simulation.

47 |Fig. 4-18 Reverse bias Characteristics of 3.3kV PiN diode model for T-CAD simulation.

Purpose of simulation is to obtain destruction charge value prediction, which can bereason of SEU in device. When charged particles penetrate to the silicon, it generates
amount electron-hole pairs, which can be trigger of avalanche phenomena in powerdevice. It also strongly depends on applied voltage [12]. However heavy ion model wereused for this simulation, it can gives properly destruction charge value function. Because
avalanche phenomena can be occur as long as charge generates by any charged particles
inside silicon. No matter ionization particle is either heavy ion or proton.
Defined PiN diode model with injected ionization particle is shown in Fig. 4-19 –Fig. 4-22. This is simultaneously with initial charge injected moment cases appearance.
Initial charge injection distribution is respected by Gaussian distribution. The length of
initial injected charge is chosen 10 µm. However in the reality ionization track can reachup to 350 um. It is assumed as diode thickness. We can see here that charge injection’s
starting point is almost in top boundary line of the diode. This boundary is corresponded
to highest electric field region along to the diode body.

48 |Fig. 4-19 Main model appearance of cylindrical model of PiN diode simulation on T-CAD

Fig. 4-20 Total length of ionization particle track is 10µm starting position is just below P-layer.

49 |Fig. 4-21 The radial distribution of excess charge was not uniform it was expressed as a Gaussian
distribution. Center of ionization particle injection is highest charge concentrated place.

Fig. 4-22 Characteristic length represent about 63% reduced distance at Expanded width view

In order to have sufficient values to make function of destruction charge, we did
several different input of simulations. Among them we have chosen 10 MeV, 50 MeV
and 100 MeV energy of heavy injection simulation. Table 4-3 shows main input
parameters of ionization particle model.
Table 4-3 Main input parameters of ionization particle model

E (MeV)1050
100

LET (pairs/cm3)
2.16x1020
1.08 x1021
2.16 x1021

Q(C)4.35 x10-13
2.18 x10-12
4.35 x10-1250 |Here LET represents the possible charge generation amount which means that how
much charge can be generated by deposited energy from ionization particle. Calculation
was made through Eq. 4-12 and Eq. 4-13.
∞

(

𝑟2

𝑄 = 𝑞 ∫ 𝐿𝐸𝑇 ∙ 𝑒 𝑤𝑡)

∙ 2 𝜋ℎ𝑟 𝑑𝑟

0

Eq. 4-12 Charge generation calculation equation

𝐸 = 𝛼𝑄Eq. 4-13 Deposited energy conversion to generated chargeHere:q – Elementary charge [1.6x10-19 C]
r – Radius of ion track [cm]h – Length of ion track [10x10-4cm]
wt – characteristic width of track [2x10-6cm]
E – Incident energy of ion
Hence, LET was calculated by Eq. 4-14

𝐿𝐸𝑇 =

𝑄
𝑞 ∙ 𝜋ℎ ∙ 𝑤𝑡 2

Eq. 4-14 LET calculation formula for ionization particle model of T-CAD simulation.

After simulation values of charge generations by diverse energy of ionization
particle case were obtained from simulation as described result section of this dissertation.
Generated charge should obtained by integrating generated charges values from cathodecurrent curves which shown in Fig. 4-23. Here we can see that current curve area,
generated charge, relatively increased by applied voltage. Depending on initial injectedcharge, curve area is defined. At the same time it also depends on applied voltage. In thiscertain example, burn out occurred when applied voltage reaches 4kV. The main target tofind out is the threshold charge value which can be trigger of single event burnout.
Basically this phenomena duration is from several hundred picoseconds to several
decades of nanoseconds.

51 |Fig. 4-23 Current waveform through PiN diode after charge depositing to inside the device.

The current generated by avalanched charge has aspects that either continues or
stoppable. There is threshold charge value for destruction. Hence we can say that burnout
condition is depends on how much charge generated by deposited energy inside of thesilicon devices. Burnout condition and charge relation is illustrated in Fig. 4-24.

Fig. 4-24 Burnout condition and charge relation

52 |The values of generated charge and applied voltage depending should be obtained
from T-CAD transient simulation and then charge generation as a function of applied
voltage for different LET by ionization particle in 3.3kV PiN diode should be predicted
and it is shown in Fig. 4-25.

Fig. 4-25 Prediction of charge generation as a function of applied voltage for different LET by ionization
particle in 3.3kV PiN diodeOn this plotted prediction for destruction charge, 102 points simulation has beenmade. Green circles represent safe zone of generated charge and applied voltage. Whendeposited energy increases then generated charge will be increase. As we can see here,
generated charge suddenly increases along applied voltage. That means avalanche
phenomena occurred there. In this case that certain amount of basic charge at bending
point of graph becomes destruction charges. Along the bending points of several curves,
several points can be obtained. Those points depend on the applied voltage can be thefunction of the destruction charge which is shown in the Fig. 4-24 as blue dashed line.

53 |Fig. 4-26 Generated charge versus applied voltage simulations [33]From here we can gather destruction charge values which can be trigger ofavalanche phenomena. Based on these results, fitting function for destruction charge andapplied voltage dependence were built. Value of this function written as Qdest(V) in main
formula. It should be fitted the literature result for instance Fig. 4-26 [33]. From theprediction and existing data, we can see that charge multiplication immediately increased
when voltage reaches certain values. In this case, charge value of base line of the curve isassumed for the destruction charge value on that corresponded voltage value. For
example, on Fig. 21, charge value assumed 10-11 C, when voltage is corresponded toapproximately 2.6kV. As this methodology, destruction charge function of applied
voltage can be obtained from TCAD simulation. Result will be shown in the next chapter
5.

54 |

5. RESULTS
Basically result consists of five sections. First result is probability function fitting
result. Second is T-CAD simulation result which was purposed to evaluate charge
generation inside device by ionization particle injection. Third result is the fitted proton
flux function. Fourth result is the Cross section calculation depended on applied voltage
based on formula calculation. Fifth one is failure rate calculated by proposed formula.
Using these results we can have conclusion for this particular study.

5.1. Probability Function fitting result
From the literature, that says high energetic proton and neutron’s energy depositionis almost same [34]. At the 300 um silicon case, energy deposition of 20 MeV, 50MeV
and 100MeV of flux is shown in the literature as well. Fig. 5-1 shows that plot energy
deposition which generated charge inside silicon. Here we can see that from after
300MeV of particle energy deposition saturates

Fig. 5-1 Probability function for deposited charge ΦEp(Qd) for 106 particles.

55 |Then from the plot we can fit the b1 and b0 parameters as shown in Fig. 5-2. Afterthat by fitting dots to continue curve, we can have mathematical expression for theparameters and charge generation function. The expressions are shown in the Eq. 5-1 andEq. 5-2.

Fig. 5-2 Fitted b1 and b0 parameters𝑏1 (300, 𝐸𝑝 ) =−100

1.8 − 0.063(𝐸𝑝 + 15)

Eq. 5-1Fitted function for b1 parameter at 300 um thickness of silicon case𝑏0 (300, 𝐸𝑝 ) =200

1.38 − 4.2(𝐸𝑝 + 20)

Eq. 5-2 Fitted function for b1 parameter at 300 um thickness of silicon case

56 |

−100

(𝑄) = 10(𝐸𝑝 +15)𝛷𝐸300𝑝

1.8 −0.063+

200(𝐸𝑝 +20)

1.38 −4.2

Eq. 5-3 Charge generation probability function which depends on incident energy of the proton

5.2. T-CAD simulation result
In the T-CAD simulation, as before mentioned, 3.3 kV of PiN diode model wasused for ionization particle injection simulation. The Electron current density distribution
was shown in from Fig. 5-3 to Fig. 5-6 after 250ps 100MeV of ionization particle
injection when applied voltage was varied. Here we can see that, electron density andamount proportionally increases to the applied voltage. If high voltage applies, morecharge carrier is generated. Electron density is higher in the near region to place where
ionization particle injected. In our simulation, worst sensitive region, upper side of thediode, was selected to ionization particle injection place. In the electric field simulation,
it was observed that ionization particle injection place is at the highest electric fieldregion. It makes to easy simulate worst condition of the operation of diode.

2600V

Fig. 5-3 Electron current density distribution after 250ps 100MeV of ionization particle injection whenapplied voltage was 2600V

57 |2200V

Fig. 5-4 Electron current density distribution after 250ps 100MeV of heavy ion injection when applied
voltage was 2200V

1800V

Fig. 5-5 Electron current density distribution after 250ps 100MeV of ionization particle injection whenapplied voltage was 1800V

58 |1400V

Fig. 5-6 Electron current density distribution after 250ps 100MeV of ionization particle injection whenapplied voltage was 1400V

After electron density distribution evaluating, Electric filed changes were analyzed
under case of 1000V, 2000V and 3000V as shown in from Fig. 5-7 to Fig. 5-9. Here, time
moments steady state and after 0ps, 10ps, 20ps of 100MeV energy of ionization particle
injection. Red graph represent electric field at the moment of 0ps, green graph represent
electric field at the moment of 10 ps, dark blue graph represent electric field at the
moment of 20ps and bright blue graph represent electric field at the steady state. In orderto understand phenomena inside power device by time step, Table 5-1 to Table 5-4 showsthat electron current density dispersiing inside diode at the variation of voltages.

59 |Table 5-1Electron current density inside device after charge injection by time distribution at 1400V ofapplied voltage caseCaptured Time ofElectron current

Applied Volatage = 1400V

Densityt= 0 ps

t= 100 ps

t= 200 ps

60 |t= 250 ps

t= 270 ps

t= 280 ps

61 |Table 5-2 Electron current density inside device after charge injection by time distribution at 1800V ofapplied voltage caseCaptured Time ofElectron current

Applied Volatage = 1800V

Densityt= 0 ps

t= 100 ps

t= 200 ps

62 |t= 250 ps

t= 270 ps

t= 280 ps

63 |Table 5-3 Electron current density inside device after charge injection by time distribution at 2200V ofapplied voltage caseCaptured Time ofElectron current

Applied Volatage = 2200V

Densityt= 0 ps

t= 100 ps

t= 200 ps

64 |t= 250 ps

t= 270 ps

t= 280 ps

65 |Table 5-4 Electron current density inside device after charge injection by time distribution at 2600V ofapplied voltage caseCaptured Time ofElectron current

Applied Volatage = 2600V

Densityt= 0 ps

t= 100 ps

t= 200 ps

66 |t= 250 ps

t= 270 ps

t= 280 ps

67 |Fig. 5-7 Electric field changes on steady state and after 0ps, 10ps, 20ps of 100MeV energy of ionization
particle injection at 1000V of applied voltage caseFig. 5-8 Electric field changes on steady state and after 0ps, 10ps, 20ps of 100MeV energy of ionization
particle injection at 2000V of applied voltage case

68 |

Fig. 5-9 Electric field changes on steady state and after 0ps, 10ps, 20ps of 100MeV energy of ionization
particle injection at 3000V of applied voltage case

Here we can see that electric field fluctuation is expanding along its direction.
Charge carriers move to along this electric field. At the case of higher applied voltage,
widest expanding occurs. The proportional relation between applied voltage and Electricfield fluctuating expansion happens due to the avalanche phenomena. The avalanche
Phenomena observed at generated charge plotting at energy of 100MeV case which isshown in Fig. 5-10 and it is shown in Fig. 5-11 as a logarithmic scaled.

Fig. 5-10 Generated charge inside diode at 1000V, 2000V, 3000V

69 |Fig. 5-11 Generated charge inside diode at 1000V, 2000V, 3000V

From here, we can have a generated charge values due to the 100 MeV, 50MeV and
10MeV energy of ionization particle injection. Integral of the graphs give total generated
charge Q. Then Charge generation as a function applied voltage obtained from T-CAD
transient simulation for different deposited charge in 3.3kV PiN diode as shown in Fig. 512.

Fig. 5-12 Charge generation as a function applied voltage obtained from T-CAD transient simulation fordifferent deposited charge in 3.3kV PiN diode.

70 |Hence, we can see that generated charge immediately increased at the certain point.
In this figure, value of deposited energy is for only related to simulation variation. Itmeans those energy values don’t related with particle type. In other word, T-CAD
simulation result gives relation between applied voltage dependence respects to thegenerated charge by any reason. Only important thing is amount of generated charge
inside device. If generated charge inside silicon exceeds from certain amount thenavalanche phenomena will be starts. This charge called destruction charge as we
mentioned before, which is depended on applied voltage to the device. From simulation
result as shown in Fig. 5-12, we can have three points to build curve for destruction
charge function. After building graph, it should be expanded by mathematical prediction,then from here we have got fitted function and its expression as show in Fig. 5-13 and Eq.
5- 4.

Fig. 5-13 Destruction charge values from penetrated space proton and its fitted function.

𝑄𝑑𝑒𝑠𝑡 (𝑉) = 7 ∗ 10−10 𝑒 −0.003𝑉
Eq. 5-4 Destruction charge function which depends on applied voltage to the device

71 |5.3. Proton flux functions fitting results

Proton flux data obtained Most of portion of cosmic ray is proton in Low Earth
Orbit. Entire energy range of considered proton flux divided three sections which are in
range of 1Mev-200GeV. Firstly, 1MeV-400MeV proton flux data corresponding to 700
km altitude was taken from SPENVIS that data’s fitted function is shown in Fig. 5-14,
and that accounted sun activation. SPENVIS is the web based software was developed by
European Space Agency and is widely used space application studies, here mission period
assumed 2018-2019. Second 1GeV-20GeV proton flux data, which measured at aroundaltitude of 350-610km were taken from PAMELA data’s fitted function is shown in Fig.
5-15. PAMELA is the spacecraft mission payload for study about possible exotic cosmic
ray source and its propagation reasons; mission time was 2006-2008. Proton is top set ofdata. Helium is the bottom set of data. Thirdly, 20GeV-200GeV proton flux data, whichmeasured at altitude of around 400km, were taken from AMS data’s fitted function shownin Fig. 5-16.

Fig. 5-14 1-400 MeV proton flux data at in LEO /SPENVIS around 700 km altitude/ and its fitted function

72 |Fig. 5-15 Fitted function has been taken from 1GeV-20GeV proton flux in LEO /PAMELA 350km-610km
altitude.

Fig. 5-16 20GeV-200GeV proton flux in LEO/AMS around 400km altitude/ and its fitted function.

73 |From these data fitted functions depending incident proton energy can be written in
low, medium and high range of energy levels as shown in Eqs. 5-5, 5-6 and 5-7. Shielding
effect was accounted during calculation.
𝐸𝑝𝐿𝑜𝑤 (𝐸𝑝 ) = 5 ∙ 108 ∙ (𝐸𝑝 )−2.196
Eq. 5-5 1-400 MeV proton flux data at in LEO

𝐸𝑝𝑀𝑒𝑑 (𝐸𝑝 ) = 9337.8 ∙ (𝐸𝑝 )−1.884
Eq. 5-6 Fitted function has been taken from 1GeV-20GeV proton flux in LEO /PAMELA

𝐻𝑖𝑔ℎ

𝐸𝑝

(𝐸𝑝 ) = 5 ∙ 107 ∙ (𝐸𝑝 )−2.796

Eq. 5-7 20GeV-200GeV proton flux in LEO/AMS

74 |5.4. Cross section calculation result
By combining data and calculating main formula, as shown in Eq. 5-8, last results
were obtained. Result is the 3.3 kV PiN diode’s Single Event burnout Cross Section
respect varying applied voltages, which can used for any proton flux of environment asshown in Fig. 5-17. This result seems similar to existing data on literature [35].
𝑄𝑚𝑎𝑥

𝜎(𝑉) = 𝐴 ∗ ∫𝑄𝑑𝑒𝑠𝑡(𝑉)

(𝑄)𝜕𝑄
𝛷𝐸300
𝑝

Eq. 5-8 Proton induced failure cross section depended on applied voltage

Fig. 5-17 SEU Cross section VS Incident energy of Proton dependence at various applied voltages(3.3kV PiN diode, Area=10-4 m2, 10MeV-20GeV).

75 |5.5. Failure rate calculation result
The voltage dependent failure rate prediction calculated by proposed formula, as
shown in Eq. 5-9, for 3.3 kV PiN diode in Low Earth Orbit condition is shown as below
as shown in Fig. 5-18, Fig. 5-19 and Fig. 5-20. In the Fig. 5-18, we can see that proton
flux energy affects to which range of applied voltage. Hence we can see that high failure
rate corresponds to higher energy of particle flux. Here it seems that experiment ofvoltage dependent failure rate against radiation is tough in terrestrial level.
𝐸𝑝𝑚𝑎𝑥

𝐹𝑅 = ∫

𝐸𝑝𝑚𝑖𝑛

𝑄𝑚𝑎𝑥

𝐴∗∫
𝑄𝑑𝑒𝑠𝑡(𝑉)(𝑄)𝜕𝑄 ∗ 𝐹(𝐸𝑝 )𝜕𝐸𝑝𝛷𝐸300
𝑝

Eq. 5-9 Proposed failure rate calculation formulaFig. 5-18 Failure rate VS Applied voltage in Low Earth Orbit (3.3kV PiN diode, Incident energy range
1MeV-200GeV).

76 |Fig. 5-19 The failure rate of 3.3-kV PiN diode calculated by our proposed calculation method at the sea
level and at satellite orbit level.

As before mentioned, majority of the particles compound energetic protons and its
percentage is around 90% in space. [15] Due to the Earth is protected by geomagnetic
field, the proton, which is an electric particle, is bent or confined in the geomagnetism.
From them, the protons that fall down to the Earth collide with molecules in atmosphereof the Earth and it makes neutron shower. For that reason, we calculated the failure ratewith terrestrial neutron flux at sea level and space proton flux in space.
Fig. 5-19 shows the terrestrial neutron flux and space proton flux induced failures.
The terrestrial neutron flux data is analytic model by M. S. Gordon, et al. [36]. Space
proton flux data have two kinds of data, which is difference altitude and proton energy.
One is a STE-QUEST mission data [37] and the other is PAMELA data [26]. We
approximated function of the two space proton flux data. At about 1 MeV - 500 MeV
space proton flux data, which measured at around altitude of 800 km - 2400 km and its
fitted function were taken from STE-QUEST mission data source. This result also wascompared with the terrestrial applications voltage dependent failure rate study [38].

77 |Fig. 5-20 The failure rate of 3.3-kV PiN diode calculated by our proposed calculation method at the sea
level and at satellite orbit level.

The failure rate of 3.3-kV PiN Diode was calculated by our proposed calculation
method at sea level and in space. As combining three kind of functions, we calculated
failure rate of 3.3 kV PiN diode at low earth environment condition was calculated and its
result shown in the Fig. 5-21. Here, two types of dotted lines represents failure rate of
3.3kV pin diode, corresponding to case of shielded and unshielded condition. Shielding
material is 0.1 in of Aluminum. Shielding function obtained from literature [39]. As
seeing this result aluminum shielding could not be proper protection against proton flux.
The red dashed line represents FIT=1(one failure in 109 hours) that typically used for
power device’s allowed failure rate for commercial application. In this case, as seeing theresult, application voltage of 3.3kV diode should be approximately 1.5kV for space
application. The blue line represents power devices failure rate at terrestrial. In space, thefailure rate can be expressed as one function, even with multiple flux of particles Flux(Ep).
The reason is that the failure rate is the sum of the failure rates for the each particle
energy. The failure rate depends strongly on flux of particles Flux(Ep) and thresholdcharge to destruction Qdest(VDC). Below about VDC = 2200V, the failure rate drops
suddenly, it is influenced by threshold charge to destruction Qdest(VDC). Threshold charge
to destruction Qdest(VDC) increases exponentially if applied voltage is decreased beyond
that point. Therefore, the failure rate is decreased at low applied voltage. From these78 |result, it is possible to ensure the reliability of high voltage devices in satellite electrical
power system. Also, we confirmed that there is no effect of aluminum shield because highenergy proton does not prevent to penetrate into devices.
In our result, since generated charge Q position is the most electric field, the failure
rate is considered to be high. In experience, charge generations positions were in various
points. Also, we obtained aluminium shielding space proton flux data at same condition,
too. Comparing results, space applications power semiconductor devices failure rate ishigher than terrestrial failure rate several magnitude. From one of the existing studies
about voltage dependent failure rate, it showed that 50V increase of change makes
approximately three magnitudes increasing of FIT.

79 |

6. CONCLUSION
We established method that consists of Destruction charge values from T-cad
simulation, proton flux data and probability of energy deposition due to proton-siliconinteraction from literature. From the result we can see that failure rate is apparently
higher than terrestrial region case (assumed terrestrial FIT=1). By using Single Eventburnout cross section σ(𝑉), that we obtained can be used for any proton flux ofenvironment. PiN diode model can be changed by any other power semiconductor
devices. The main formula which used for calculation compounds of three independentparts. Each part can be developed separately and it could be changed by otherenvironment other devices. That means the proposed method for high voltage powerdevices failure rate calculation is feasible to diversity of any other power devices at any
radiation environment. In further, using this flexible aspect of method, software
application will be developed for radiation induced failure rate calculation of powerdevices. Proposed method can contribute to mitigate failure for high power devices’usage and predict space application’s MW range of power systems reliability in future. In
this study, T-CAD simulation electric field, that can affected by proton hitting position insilicon, was fixed at highest field of position. Crystal degradation due to space radiation
was not considered as well.
Furthermore, in order to confirm calculation result by experiment, testing facilities
required. But in the reality, feasibility of the equipment of radiation source is limited tosimulate real space environment. Then cubesat class of satellite mission could be thesolution of the experimental result of this study as developing dedicated model for highpower devices radiation testing.

80 |7. LIST OF FIGURES
Fig. 1-1 Total power increasing trend last twenty years

2

Fig. 1-2 Relation between harness mass and power of satellite

3Fig. 1-3 The functional block diagram of Electrical Power Subsystem

4

Fig. 1-4 Basic architecture of Electrical Power System

5

Fig. 2-1 Basic classification of Power Semiconductor Devices

6

Fig. 2-2 IGBT and MOSFET internal structure comparison a) MOSFET b) IGBT

7

Fig. 2-3 Basic PiN diode internal structure

8

Fig. 3-1Cosmic Ray flux at Terrestrial altitudes [15]10Fig. 3-2 Particle flux at position r in spherical coordinates

11

Fig. 3-3 Interacts with the medium and that makes cylindrical shape

12

Fig. 3-4 Particles beam on the thin target material.

13

Fig. 3-5 The motion of energetic charged particles in magnetosphere [16]15

Fig. 3-6 Solar energetic protons emitted by the Sun and guided by magnetic field line [19]16
Fig. 3-7 Classification of Space radiation effects in electronics

17

Fig. 3-8 Ionization made by secondary recoils due to proton induced nuclear reaction. 18
Fig. 3-9 Stopping power of the proton variation respects to the incident energy up to 100
MeV [21]

20

Fig. 3-10 Stopping power type corresponding to energy of incident particles [22]21

Fig. 3-11 Single event errors for low voltage electronics [23]22

Fig. 3-12 Structural similarity of power devices

23

Fig. 3-13 A schematic representation of a power MOSFET transistor and a parasitic
bipolar structure [24]24

Fig. 3-14 A schematic representation of a parasitic thyristor in the IGBT components
[24]

25

Fig. 3-15 PiN diode structure respect to electric field

26

Fig. 3-16 Generated charge and multiplied charge histogram respect to the voltage [25] 27
Fig. 3-17 Electric field and Current density variation respect spatial and temporal
distribution. [12]28Fig. 4-1 Compounds of the Failure rate Formula

30

Fig. 4-2 Proton flux range at this calculation

31

Fig. 4-3 Radiation sources data from SPENVIS (Differential flux (𝐸𝑝)) [16]32

Fig. 4-4 Proton and helium absolute fluxes measured by PAMELA above 1 GeV per

81 |nucleon, compared with a few of the previous measurements [26].

33

Fig. 4-5 The AMS measured proton flux as a function of kinetic energy E K as multipliedby E2.7K compared with recent measurements [18]Fig. 4-6 Probability function of charge generation ΦEp34300(Q) by energetic proton.

35

Fig. 4-7 Φx,Ep(Ed) and σ(Ed) : the hatched area hides the part of Φx,Ep(Ed) which is nottaken into account in the convolution

36

Fig. 4-8 Parametrization of bl (Ep,x) [28]38

Fig. 4-9 Energy deposition probability function at various thickness of silicon under
200MeV energy of proton flux

39

Fig. 4-10 Fitted b1 (at 300 µm Si).

40

Fig. 4-11 Fitted b0 (at 300 µm Si).

41

Fig. 4-12 Burnout Condition based on avalanche phenomena

42

Fig. 4-13Function of threshold charge to destruction Qdest(VDC) respect to the applied
voltage

43

Fig. 4-14 Track of ionization particle penetration a semiconductor material; it is definedby a length and the transverse spatial influence is assumed to be symmetric about the
track axis

45

Fig. 4-15 Simulated diode model in TCAD

46

Fig. 4-16 Meshing method of simulated diode mode in TCAD

47

Fig. 4-17 Charge deposited 3.3 kV PiN diode model in T-CAD simulation.

47

Fig. 4-18 Reverse bias Characteristics of 3.3kV PiN diode model for T-CAD simulation.
48
Fig. 4-19 Main model appearance of cylindrical model of PiN diode simulation on TCAD

49

Fig. 4-20 Total length of ionization particle track is 10µm starting position is just below
P-layer.

49

Fig. 4-21 The radial distribution of excess charge was not uniform it was expressed as a
Gaussian distribution. Center of ionization particle injection is highest charge
concentrated place.

50

Fig. 4-22 Characteristic length represent about 63% reduced distance at Expanded width
view

50

Fig. 4-23 Current waveform through PiN diode after charge depositing to inside thedevice.

52

Fig. 4-24 Burnout condition and charge relation

52

82 |

Fig. 4-25 Prediction of charge generation as a function of applied voltage for different
LET by ionization particle in 3.3kV PiN diode53

Fig. 4-26 Generated charge versus applied voltage simulations [33]6

54

Fig. 5-1 Probability function for deposited charge ΦEp(Qd) for 10 particles.

55

Fig. 5-2 Fitted b1 and b0 parameters

56

Fig. 5-3 Electron current density distribution after 250ps 100MeV of ionization particle
injection when applied voltage was 2600V

57

Fig. 5-4 Electron current density distribution after 250ps 100MeV of heavy ion injection
when applied voltage was 2200V

58

Fig. 5-5 Electron current density distribution after 250ps 100MeV of ionization particle
injection when applied voltage was 1800V

58

Fig. 5-6 Electron current density distribution after 250ps 100MeV of ionization particle
injection when applied voltage was 1400V

59

Fig. 5-7 Electric field changes on steady state and after 0ps, 10ps, 20ps of 100MeV
energy of ionization particle injection at 1000V of applied voltage case

68

Fig. 5-8 Electric field changes on steady state and after 0ps, 10ps, 20ps of 100MeV
energy of ionization particle injection at 2000V of applied voltage case

68

Fig. 5-9 Electric field changes on steady state and after 0ps, 10ps, 20ps of 100MeV
energy of ionization particle injection at 3000V of applied voltage case

69

Fig. 5-10 Generated charge inside diode at 1000V, 2000V, 3000V

69

Fig. 5-11 Generated charge inside diode at 1000V, 2000V, 3000V

70

Fig. 5-12 Charge generation as a function applied voltage obtained from T-CAD transient
simulation for different deposited charge in 3.3kV PiN diode.

70

Fig. 5-13 Destruction charge values from penetrated space proton and its fitted function.
71
Fig. 5-14 1-400 MeV proton flux data at in LEO /SPENVIS around 700 km altitude/ andits fitted function

72

Fig. 5-15 Fitted function has been taken from 1GeV-20GeV proton flux in LEO/PAMELA 350km-610km altitude.

73

Fig. 5-16 20GeV-200GeV proton flux in LEO/AMS around 400km altitude/ and its fitted
function.

73

Fig. 5-17 SEU Cross section VS Incident energy of Proton dependence at various applied
voltages (3.3kV

PiN

diode,

Area=10-4

m2,

10MeV-20GeV).
75

83 |

Fig. 5-18 Failure rate VS Applied voltage in Low Earth Orbit (3.3kV PiN diode, Incident
energy range 1MeV-200GeV).

76

Fig. 5-19 The failure rate of 3.3-kV PiN diode calculated by our proposed calculation
method at the sea level and at satellite orbit level.

77

Fig. 5-20 The failure rate of 3.3-kV PiN diode calculated by our proposed calculation
method at the sea level and at satellite orbit level.

78

84 |

8. LIST OF TABLES
Table 4-1Proton flux data resources and its features

31

Table 4-2 Fitting of b1 and b0

40

Table 4-3 Main input parameters of ionization particle model

50

Table 5-1Electron current density inside device after charge injection by time distribution
at 1400V of applied voltage case60

Table 5-2 Electron current density inside device after charge injection by time distribution
at 1800V of applied voltage case

62

Table 5-3 Electron current density inside device after charge injection by time distribution
at 2200V of applied voltage case64

Table 5-4 Electron current density inside device after charge injection by time distribution
at 2600V of applied voltage case

66

85 |

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Soelkner, "Charge Carrier Avalanche Multiplication in High-Voltage Diodes
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86 |[14] A.M. Albadri et al, "Single event burnout in power diodes: Mechanisms andmodels," Microelectronics Reliability, vol. 46, no. 2-4, pp. 317-325, February–April
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[16] ESA. (1997-2016) SPENVIS. [Online]. https://www.spenvis.oma.be/models.php[17] Milton S. Ash George S Messenger, Single Event Phenomena.: Springer, 1997.
[18] M. Aguilar et al. (AMSCollaboration), "Precision Measurement of the Proton Flux inPrimary Cosmic Rays from Rigidity 1 GV to 1.8 TV with the Alpha Magnetic
Spectrometer on the International Space Station," PHYSICAL REVIEW LETTERS,
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[19] Marlon

Núñez.

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[21] M.J. Bochini et al, "Nuclear and Non-Ionizing Energy-Loss for Coulomb Scattered
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[36] P. Goldhagen, K. P. Rodbell, T. H. Zabel, H. H. K. Tang, J. M. Clem and P. Bailey,
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88 |[38] H. R. Zeller, "Cosmic ray induced failures in high power semiconductor devices,"
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[39] E. C. Smith, "Effects of Realistic Satellite Shielding on SEE Rates," IEEE
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May 2015.
10.

ACRONYMSCMOS = Complementary Metal Oxide Semiconductor
MOSFET= Metal Oxide Semiconductor Field Effect Transistor
IGBT= Insulated Gate Bipolar Transistor
LET = Linear Energy Transfer
SEU = Single-Event Upset
SOI = Silicon-On-Insulator
SRAM = Static Random Access Memory
EPS = Electrical Power System

89 |

11.

PUBLICATION LIST Screening Process And In-Orbit Performance Of Horyu-IV Battery Proceeding
The 35th Space Energy Symposium, 2016,3, Mohamed Yahia Edries,
Erdenebaatar Dashdondog, Ichiro Omura, Mengu Cho;
 Failure Rate Calculation Method For High Power Devices in Space Applications
at Low Earth Orbit, Microelectronics Reliability 64 pp. 502–506,20169,
Erdenebaatar Dashdondog, Shohei Harada, Yuji Shiba, Ichiro Omura; Formulation of Single Event Burnout Failure Rate for High Voltage Devices inSatellite Electrical Power System, Proceedings of ISPSD 29th,2017,6, Yuji Shiba,
Erdenebaatar Dashdondog, Masaki Sudo, Ichiro Omura; The Failure Rate Calculation Method for High Power Devices in Low Earth Orbit,
Proceedings of ISTS 31st, 2017,6, Erdenebaatar Dashdondog, Shohei Harada,
Yuji Shiba,Masaki Sudo, Ichiro Omura; Method for the synthesis of semiconductor structures n-InSb1-xBix-i-GaAs, nInSb1-xBix-i-GaAs/Te, looking for the manufacture of highly element hall.
“Physics”, 2011, National University of Mongolia; Golimensee Shilagardi,
Erdenebaatar Dashdondog
 Electrical properties of semiconductor structures n-InSb1-xBix-i-GaAs, and nInSb1-xBix-i-GaAs/Te. Published in “Physics”, 2011, National University ofMongolia; Golimensee Shilagardi, Erdenebaatar Dashdondog
 Features para magnetism samples of brown coal in their thermal degradation,“Physics” , 2012, National University of Mongolia; Golimensee Shilagardi,
Erdenebaatar Dashdondog
 Effect of neutron irradiation on para magnetism coals, “Physics” , 2012, National
University of Mongolia; Golimensee Shilagardi, Erdenebaatar Dashdondog

90 |

12.

ABOUT AUTHOR
Erdenebaatar Dashdondog was born in Erdenet city, Mongolia on June 30, 1987. Hereceived Bachelor degree in Physics and Electronics from the National University ofMongolia in 2009 and Master’s degree in Physics and Electronics from the National
University of Mongolia in 2011. He was electrical and electronics researcher and assistantteacher at National University of Mongolia until 2014. He has been a doctoral student in
Graduate School of Engineering, Kyushu Institute of Technology in Japan. During thattime he was member of engineering team of Mongolian first satellite project andparticipated to other two satellites projects, HORYU-4 and SPATIUM as ElectricalPower System engineer. His interest is power system, system engineering and to study forpossibility of developing countries space technology ownership and its indirect benefit totechnological field development of home country.
Email address: erdenebtr@gmail.com

91 |