Modeling and System-level Simulation of Force-balance MEMS ...

Sensors & Transducers
Volume 127, Issue 4,
April 2011
www.sensorsportal.com ISSN 1726-5479
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Sensors & Transducers Journal (ISSN 1726-5479) is a peer review international journal published monthly online by International Frequency Sensor Association (IFSA).
Available in electronic and on CD. Copyright © 2011 by International Frequency Sensor Association. All rights reserved.

Sensors & Transducers Journal
Contents
Volume 127
Issue 4
April 2011
www.sensorsportal.com ISSN 1726-5479
Research Articles
Going Fabless with MEMS
Bhaskar Choubey ............................................................................................................................... 1
Micromachined Polycrystalline Si Thermopiles in a T-shirt
Vladimir Leonov, Yvonne van Andel, Ziyang Wang, Ruud J. M. Vullers and Chris Van Hoof........... 15
Virtual Fabrication of Silicon Nitride Based Multifunctional MEMS Pressure Sensor
Mahesh Kumar Patankar.................................................................................................................... 27
General Development of a New Hall Effect Sensor
Vlassis N. Petoussis, Panos D. Dimitropoulos, George Stamoulis.................................................... 36
Inspection of Pipe Inner Surface using Advanced Pipe Crawler Robot with PVDF Sensor
based Rotating Probe
Vimal Agarwal, Harutoshi Ogai, Kentarou Nishijima and Bishakh Bhattacharya............................... 45
Ultrasonic System Approach to Obstacle Detection and Edge Detection
Yin Thu Win, Hla Thar Htun, Nitin Afzulpurkar, Chumnarn Punyasai ................................................ 56
Monitoring of Various Glucose Concentrations Based on Optical Spectroscopic
Reflectometry
Hariyadi Soetedjo ............................................................................................................................... 69
Studies of Gas Sensing Performance of Barium Zirconate (BaZrO 3 )
R. M. Chaudhari, V. B. Gaikwad, P. D. Hire, R. L. Patil,S. D. Shinde, N. U. Patil, G. H. Jain. .......... 76
Modeling and System-level Simulation of Force-balance MEMS Comb Accelerometers
Hao Chen, Limei Xu ........................................................................................................................... 88
Design and Fabrication of a Lab-on-a-chip for Point-of-care Diagnostics
Anne Balck, Monika Michalzik, Laila Al-Halabi, Stefan Dübel, and Stephanus Büttgenbach............ 102
Authors are encouraged to submit article in MS Word (doc) and Acrobat (pdf) formats by e-mail: editor@sensorsportal.com
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International Frequency Sensor Association (IFSA).

Sensors & Transducers Journal, Vol. 127, Issue 4, April 2011, pp. 88-101
Sensors & Transducers
ISSN 1726-5479
© 2011 by IFSA
http://www.sensorsportal.com
Modeling and System-level Simulation of Force-balance
MEMS Comb Accelerometers
Hao CHEN, Limei XU
Institute of Astronautics & Aeronautics
University of Electronic Science and Technology of China
Chengdu, Sichuan 611731, China
Tel.: 028-83205198
E-mail: scuch@uestc.edu.cn
Received: 10 April 2011 /Accepted: 22 April 2011 /Published: 30 April 2011
Abstract: This paper presents a quick system-level modeling and simulation of force-balance MEMS
comb accelerometers. The derivation of the system-level model including the sense element and
interface electronics is elaborated and the simulation results are obtained from COVENTOR and
MATLAB respectively. The force-balance MEMS comb accelerometer, with the size of 1920 µm
960 µm 50 µm, the static capacitance of 2.25 pF, and the inertial mass of 5.47 µg, can endure with
over load of 2000 g. Through the system-level simulation, the sensitivity is 100 mv/g, the full scale
range is 50
g, the nonlinear distortion is smaller than 0.5 % and the system bandwidth is 2.2 kHz.
Copyright © 2011 IFSA.
Keywords: Micro-accelerometer; System-level simulation; Closed-loop system; Differential
capacitive.
1. Introduction
Now, micro-machined sensors are widely used in many different aspects of inertial navigation system
as well as the center of the vibration examination system for their small size, low cost and low power
consumption. Especially, micro-machined accelerometers have been more and more popular since the
safety requirement for automobiles has tightened, such like seat belts and air-bag systems. This leads
to a high demand for low-cost and small-size accelerometers capable of sensing up to 50 g (where 1 g
is the acceleration due to earth gravitational force). Thus, integrated capacitive accelerometers that
meet the requirements are well received [1-4]. There are many different types of micro-machined
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Sensors & Transducers Journal, Vol. 127, Issue 4, April 2011, pp. 88-101
accelerometers, such as piezoresistive, piezoelectric, and capacitive accelerometer. But, most
accelerometers use the capacitive-based mechanism because of its structural simplicity, high accuracy,
low temperature sensitivity, low noise performance, good DC response, and compatibility with CMOS
readout electronics. Capacitive accelerometers are typically implemented as a differential capacitance,
using the linear relationship between the capacitance change and the acceleration [5]. Moreover, forcebalance
MEMS accelerometers based on capacitive mechanism can improve the system stability and
widen the measurement range using a closed loop structure [6].
As MEMS technology continues to grow, to design and simulate MEMS device is becoming an
interesting and important research issue. FEA/BEA is a commonly used numerical simulation method
in MEMS simulation; firstly this method meshes the entity model and produces the system matrix, and
then solves the system matrix to get simulation result. In order to analyze the interaction between
mechanical and electrostatic field, we must carry out the iterative calculation on both mechanical and
electrostatic field until the results of these two fields are consistent [8 - 10], but using this method will
cost too much time and have a poor convergence performance as the author indicated in [10], so it’s
often restricted in practical application. To solve the problem of force-balance MEMS comb
accelerometers, three widely used methods have been proposed: signal flow method; multi-emulator
coupling analysis method; unified modeling method.
The signal flow method emphasizes using general principles of perspective to simulate the system
behavior, such as simplifying the spring-mass-damper system and RLC oscillation circuit to a secondorder
system. The disadvantage of the above method is that it can’t directly reflect some local
characteristics of the device (like motion parameters etc.) and structure parameters (like dimension
parameters etc.), it is very difficult to use this method to research the impact of these local
characteristics and structure parameters on system performance.
Multi-emulator coupling analysis method uses the coupling of different special emulators including
fields of circuit, machinery and fluid to achieve the overall behavior’s simulation of MEMS [11, 12], it
has high accuracy and also can take the device’s local characteristics into account, but this method has
some disadvantages: non-unified abstract levels in coupled fields; poor convergence performance;
relatively long computing time.
The unified modeling method uses the same modeling approach and language (such as VHDL-AMS
etc.) to model and describe the whole system, hence one can simulate the entire system just by a single
simulator. The models of functional structure components constituting the system can be obtained on
the basis on numerical analysis, and they can be inserted into the system-level simulation model [13].
The models based on numerical analysis have high accuracy, suit for functional structure components
in different shape and can realize the top-down verification in MEMS design [14, 15], but the models
must be recalculated after changes in geometry dimension or topology of the functional structure
components, resulting in long design circle, and can’t meet the requirement of rapid design.
In order to realize rapid design of MEMS comb accelerometer and analyze the system-level behaviors
of it, on one hand, we use professional MEMS design software to simulate and optimize the sensor
part of MEMS comb accelerometers; on the other hand, we use numerical analysis to establish the
system-level model of force-balance accelerometers including interface circuit. This mixed rapid
modeling method has the following advantages: reflecting the impact of these local characteristics and
structure parameters on system performance comparing to signal flow method; less computing time
comparing to multi-emulator coupling analysis method; short design circle comparing to unified
modeling method.
This paper proposes a quick design method on system-level simulation of MEMS comb
accelerometers. Section II describes the derivation of the system-level model including the sense
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Sensors & Transducers Journal, Vol. 127, Issue 4, April 2011, pp. 88-101
element and interface electronics. Simulation results are obtained from COVENTOR and MATLAB in
Section III. The conclusions are reported in Section IV.
2. Theoretical Principles of MEMS Comb Accelerometers
The MEMS comb accelerometer system consists of two main parts: the sense element and the interface
electronics. As shown in Fig. 1, the sense element comprises a proof mass suspended by two folded
beams on each end, differential sensing and feedback capacitances. Movable fingers are mounted on
the mass, and stator fingers are attached to substrate. The movable fingers and the stators establish
differential sensing capacitances that can be evaluated by a signal pick-off circuit. In the initial state,
there is no acceleration and the proof mass rests in the null position. The differential capacitances are
equal, and the output voltage is zero. If an external acceleration is applied on the proof mass in the x
direction, the balance breaks and position variation of the proof mass is sensed, causing relative
changes of differential capacitances ( C ). With proper interface electronics, C can be converted to
a voltage signal, which is proportional to the magnitude of the external acceleration. In order to
improve the system stability and widen the measurement range, we use a closed loop structure, and
this can be realized by applying the feedback voltage signal to the proof mass, which can pull back the
deflected proof mass to the null position.
Anchor
F EXT
Anchor
C a1
C b1
y
x
Proof Mass: M
Air Damping: B
Spring Constant: K
Movable fingers
Stator fingers
C a2
C b2
Anchor
X
Anchor
Fig. 1. Simplified model of the MEMS comb accelerometer.
2.1. Sense Element
The structure design of a MEMS comb accelerometer is shown in Fig. 2. Lateral accelerometers have
been developed using comb electrodes and differentially detecting parallel electrodes to obtain linear
output. The movable parts of this sense element consist of four U-shape folded beams, a proof mass
and some movable fingers. The fixed parts include four anchors and stator fingers. The proof mass is
connected to four anchors through four folded beams. The stator fingers and the movable fingers form
four capacitances, which are C a1 , C a2 , C b1 and C b2 respectively.
The specific structure parameters of the sense element are shown in Table 1.
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Sensors & Transducers Journal, Vol. 127, Issue 4, April 2011, pp. 88-101
Fig. 2. 3D model of the sense element.
Table 1. Structure parameters for the sense element.
Serial
number
1
2
3
4
5
6
Name
Length of
mass L
Width of
mass B
Length of
superposition
l fr
Length of
comb finger
l f
Width of
comb finger
w f
Length of
girder l b
Value
Serial
number
1880 7
200 8
270 9
300 10
5 11
300 12
Name
Width of girder
w b
Plate distance
1 d f1
Plate distance
2 d f2
Ratio of plate
distance η
Thickness of
accelerometer
h
Number of
comb fingers n
Value
6
4
40
10
50
50
Dynamic behavior of the sense element is governed by the Newton’s second law of motion:
2
d x dx
M B Kx F
2 ext
Ma
(1)
dt dt
The effective spring constant (K) of the sense element is expressed by [16]
K K K
(2)
mechanical
electrical
The mechanical and electrical stiffness of the structure are given by [17]
K
mechanical
3
2Eb h
(3)
l
3
b
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Sensors & Transducers Journal, Vol. 127, Issue 4, April 2011, pp. 88-101
K
electrical
1
V
2
2
DC
n
hl
d
f
2
1
,
(4)
where E is the Young’s modulus of silicon in the sense direction; b, h, l b are the width, height and
length of the U-shape folded beams, respectively; n is the total number of movable fingers; is the
dielectric constant; the initial distances between movable finger and fixed are shown as d 1 and d 2
(d 1

2.2. Interface Electronics
Sensors & Transducers Journal, Vol. 127, Issue 4, April 2011, pp. 88-101
n order to measure the capacitance change, it’s not only to apply the excitation signal on the sense
element, but also need to pick up signals from it for subsequent conditioning circuit’s processing. The
excitation signal can be either a voltage or current signal, and also are the picked signals. When using
the current signal as the excitation signal, the magnitude of the current signal through the sense
element is determined by the admittance of the excitation node, which means it’s related to the
magnitude of the parasitic capacitance. Hence, it’s better to use the voltage signal as the excitation
signal. If the picked signals are voltage signal, it’s also affected by the parasitic capacitance, so it’s
more often used to pick up current signals from the sense element. To sum up, it’s a suitable way to use
a voltage signal to excite the sense element and pick up current signals from it.
Based on the above reasons, we build the interface electronics in Fig. 3. The capacitances changes
( C1, C2
) can be converted into two voltage signals at the input terminals of the high pass filter.
The signals are filtered and then sent to the differential operational amplifier, and the output of the
differential operational amplifier is demodulated, amplified, and then filtered by a low pass filter. The
output of the low pass filter is the output signal of circuit, which we can use a PID controller to
improve the dynamic characteristics of the whole system. Proportional to the output signal, the
feedback voltage is continuously applied to the proof mass, and then the deflected is pulled back to the
original position.
C 1
U drive
C 2
Fig. 3. The schematic diagram of interface electronics in a force-balance MEMS comb accelerometer.
The voltage signals coming out of the high pass amplifier can be expressed as:
C
U () t - Acos( t)
(11)
1
1 0
CCA
C
U () t - Acos( w t)
(12)
2
2 0
CCA
where C CA is the magnitude of feedback capacitance in charge amplifier; U drive is the excitation signal,
which frequency is w 0 and amplitude is A.
The differential operational amplifier can translate the two voltage signals (U 1 and U 2 ) into one voltage
signal, which is U pos . It can be expressed as:
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Sensors & Transducers Journal, Vol. 127, Issue 4, April 2011, pp. 88-101
C C C
U
pos
K Acos( w t) K Acos( w t)
(13)
C
1 2
1 0 1 0
CCA
CA
The synchronous demodulator is composed of the multiplier and low pass filter, which can demodulate
the dc flow signal related to the acceleration signal. The output signal of the multiplier can be
expressed as:
KA C
U U Acos( w t) [1 cos(2 w t)]
(14)
mult
pos
2
1
0 0
2 CCA
In order to filter out the high frequency signal in it, we select the second voltage-controlled voltage
type low pass filter, which amplitude-frequency characteristics is closer to the ideal low pass filter and
has some gain amplification. The output signal of this low pass filter is:
1
2 C
Uout
K1Alp
A
2 C
CA
(15)
where A lp is the amplification of the low pass filter. In general, the greater open-loop gain of the
system, the higher the accuracy of it, but the system is prone to oscillation when the gain is very large.
Hence, it’s very important to have an appropriate gain of the system, and usually we use the amplitudefrequency
characteristics of the system to determine it. If open-loop gain amplification of the system is
K 2 , we can express the feedback voltage as:
1
2 C
U
fb
K2K1Alp
A
2
C
CA
(16)
3. System-level Simulation of the Force-balance MEMS Comb Accelerometer
Section II describes the derivation of the system-level model including sensor part and interface
electronics, and we use professional MEMS design software COVENTOR to model, simulate and
optimize the sensor element. After that we use numerical analysis software MATLAB to establish and
simulate the system-level model of force-balance accelerometers including interface circuit.
The design way of our quick system-level modeling and simulation method is shown in Fig. 4. In the
beginning, we have an initial design for a MEMS comb accelerometer, including the sensor part’s
structural parameters and the interface electronics; after that, we use COVENTOR to establish the
architect model of the sensor part according to its parameters. We can get the macro model’s
parameters from the architect model, and also can analyze the parameters’ influence on the macro
model; Using the macro model from the COVENTOR and the transfer functions of interface
electronics we can build the system-level model of the MEMS comb accelerometer in MATLAB, and
get the performance parameters of it; Finally, if the performance parameters cannot meet the
requirements, we can change the parameters in the architect model until we get the performance
parameters that meet the requirement.
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Sensors & Transducers Journal, Vol. 127, Issue 4, April 2011, pp. 88-101
Fig. 4. The quick system-level modeling and simulation method in MEMS comb accelerometers.
3.1. Simulation of the Sense Element
We build the architect model of the sense element in COVENTOR, which is shown in Fig. 5. Using
this architect model we can easily simulate the sense element, if some parameters of the sense element
change, we can easily analyze the parameters’ influences on the sense element, unlike CAE traditional
way that we need to reestablish the three-dimensional model and analyze it in finite element analysis
software. Architect model can quickly model and analyze the sense element, and also doesn’t lose
accuracy.
Fig. 5. The architect model of a MEMS comb accelerometer in COVENTOR.
According the known, the sense element of MEMS comb accelerometer was a mass-spring system, the
vibration was occurred on the condition of acceleration. So the significant limitation of accelerometer
sensor was the narrow range for frequency response, whose main factors were the resonant frequency.
We did the modal analysis of the sense element in COVENTOR, and the modal results are shown in
Fig. 6. The first mode is lateral vibration in the sense direction x, which is preferable for stable device
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operation, and the modal frequency is 7.72 kHz; the second mode is lateral vibration in the direction z,
which modal frequency is 32.06 kHz; the third mode is torsional vibration in the direction z, which
modal frequency is 70 kHz; the fourth mode is torsional vibration in the direction y, which modal
frequency is 72.75 kHz. The result of theoretical analysis was about 7.1 kHz, and the error was below
10 % compared with the data of simulation, which was in the range of error for engineering.
Fig. 6. Resonant modes of the sense element (by COVENTOR).
In order to scale the anti-shock ability of the sense element, we simulated the sense element with an
external acceleration of 2000 g in x, y, z direction. The result shows that the maximum stress is
47 MPa. Because the maximum stress of the silicon can hold is 7 GPa, so the sense element can endure
with over load of 2000 g.
From the above data we can have a conclusion that the first mode of the sense element is isolated with
the second, third and fourth mode. So we can see that the design of the sense element can meet the
basic requirements of the modal analysis.
Although the above analysis can meet the requirements of the modal analysis, it is necessary to be sure
that the sense element has good linearity in working range, which means we should be sure that the
applied load has linear relationship with the proof mass’s displacement. By using the architect model,
we can easily change the applied load for analysis. Therefore, we applied external acceleration from
0-40 g (1g=9.8 m 2 /s), the displacement of the proof mass is shown in Fig. 7. From Fig. 7 we can say
that the sense element has good linearity when the external acceleration is in the range of 40 g.
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Sensors & Transducers Journal, Vol. 127, Issue 4, April 2011, pp. 88-101
60 Displacement[nm] Acceleration(g)
50
40
30
20
10
0
0 5 10 15 20 25 30 35 40
Fig. 7. The relationship between external acceleration and the displacement of the proof mass.
From the dc analysis, we can get the initial capacitances C1 and C2 are 2.25 pF. Through applying
different external acceleration, we can get the capacitance change (C1-C2), the relationship between
them is shown in Fig. 8. From Fig. 8 we can see that when the external acceleration is in the range of
4g, the relationship is linear between them. But when the external acceleration is above 4 g, the
relationship is not linear. If the sense element is controlled by open-loop system, the work range of
MEMS comb accelerometer will be subject to the nonlinear effect of capacitor plates. So we use closeloop
system to sense and feedback the sense element, which the work range will not be affected by the
nonlinear effect of capacitor plates.
10
Capacitance Change [10 -2 pF]
8
6
4
2
Real relationship
Linear relationship
0
0 2 4 6 8 10
Acceleration [g]
Fig. 8. The relationship between external acceleration and the capacitance change.
Through the modal analysis, we found that the first mode is also the sense direction, which can
improve the sensitivity of the detection axis, and its second and high order modes are isolated with the
first mode, that can avoid cross-coupling; through the static analysis, we found that when the
acceleration is in the range of 40 g, the displacement of the proof mass has good linear relationship
with it.; finally, we analyzed the relationship between the capacitance change and the external
acceleration, and found the nonlinear effect of capacitor plates.
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Sensors & Transducers Journal, Vol. 127, Issue 4, April 2011, pp. 88-101
3.2. System-level Simulation of the Force-balance MEMS Comb Accelerometer
The above analysis of the sense element proved that the design structure and parameters are
appropriate, and from the architect model’s analysis we can get the macro model’s parameters of the
sense element: the mass is 5.47 µg; the damping is 2.1 mNm/s; the mechanical spring constant is
357.8 N/m; the initial capacitances (C1 and C2) are 2.25 pF. So we can use these parameters to derive
corresponding transfer function of the sense element. We also designed the electronic circuits in Fig. 3,
which are the charge amplifier, the high pass filter, the differential operation amplifier, the
synchronous demodulator, and the PID controller, and derived the transfer functions of them. Thus we
established the system-level model of the MEMS comb accelerometer using the transfer functions
according to the real parts in the numerical analysis software MATLAB, which is shown in Fig. 9.
a
Acceleration
Subtract1
Subtract
-K-
Gain
Gain1
1
x'
s
Integrator
1 x
s
Integrator1
x
-K-
Gain2
-K-
f(u)
x to c1
C1
Signal
Generator
f(u)
x to c
Product
-1.64E-3s 2
den(s)
Transfer Fcn
Delta C
f(u)
x to c2
C2
-10
-1
Gain4
Switch
Gain3
Subtract2
Demodulation V
Switch1
Signal
Generator1
Sign
-K-
Gain7
1
s
Integrator2
butter
-10
Analog
Filter Design
Gain5
-K-
du/dt
Subtract3
Vf
Gain8
Derivative
signal before PI
Gain6
-K-
Fig. 9. System-level model of the force-balance MEMS comb accelerometer system in MATLAB.
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Sensors & Transducers Journal, Vol. 127, Issue 4, April 2011, pp. 88-101
When the external step acceleration is 1 g, 2 g, 4 g, 6 g, 8 g, the displacement of the proof mass is
shown in Fig. 10-a. We can see that the displacement of the proof mass gradually increases firstly
because of the external acceleration, but the displacement starts to decrease after a very short time,
which is caused by the influences of feedback electrostatic force and the beam’s spring force. After
about 0.008 second, the displacements decrease to zero.
The according output voltage, which is also the feedback electrostatic voltage, is shown in Fig. 10-b.
When the external step acceleration is 1 g, after a very short vibration (about 0.003 second) the output
voltage can hold a stable value of 0.1 V; as is shown in Fig. 10-b, the stable value of the output voltage
has a good linear relationship with the external acceleration. From Fig. 10, we can get the sensitivity of
the MEMS comb accelerometer is 100 mV/g.
14
Displacement [nm]
Output Voltage(V)
1.2
12
10
8
6
4
8g
6g
4g
1.0
0.8
0.6
0.4
8g
6g
4g
2 2g
0.2 2g
1g
0
1g
0.000 0.002 0.004 0.006 0.008 0.010 0.0
Time[s] 0.000 0.002 0.004 0.006 0.008 0.010
Time(s)
(a)
(b)
Fig. 10. (a) the displacement response of the proof mass in 1 g step external acceleration Fig.10-b;
(b) the output voltage response of the accelerometer system in 1 g step external acceleration.
The relationship between the external acceleration and the final output voltage is shown in Fig. 11.
Because we defined the bias voltage of the MEMS comb accelerometer as 5 V, so the output voltage is
constrained to [-5 V, 5 V]. From Fig. 11, we can see that when the external acceleration is in the range
of [-50 g, 50 g], it can hold a very good linear relationship with the output voltage, and we can get the
range of the MEMS comb accelerometer is 50g , and the nonlinear distortion is smaller than 0.5 %. If
we want to extend the range of the MEMS comb accelerometer, we can reduce the feedback
coefficient of the output voltage, which will reduce the sensitivity; and if we want to increase the
sensitivity of the MEMS comb accelerometer, we need to enlarge the feedback coefficient of the
output voltage, but this will cause the loss the range that the MEMS comb accelerometer can measure.
So when we design the real electronic interfaces of the MEMS comb accelerometer, one resistance of
the differential operation amplifier can be designed as an adjustable resistance in order to adjust the
sensitivity and range of the accelerometer manually.
The amplitude-frequency response of the MEMS comb accelerometer is shown in Fig. 12. When we
load 20 acceleration signals on the MEMS comb accelerometer with the same amplitude but different
frequencies, the final output voltage changes as the frequency change. As is shown in Fig. 12, in the
low frequency scale (

Sensors & Transducers Journal, Vol. 127, Issue 4, April 2011, pp. 88-101
4
3
2
1
0
-1
-2
-3
-4
-5
-50 -40 -30 -20 -10 0 10 20 30 40 50
5 Output voltage[V] Acceleration[g]
Fig. 11. the relationship between the external acceleration and the output voltage.
Output Voltage(V)
0.32
0.30
0.28
0.26
0.24
0.22
0.20
0.18
0.16
0.14
0.12
0.10
1 10 100 1000 10000
Frequency[Hz]
Fig. 12. The amplitude-frequency response of the force-balance MEMS comb accelerometer system.
4. Conclusions
To aid system designers, the system-level modeling and simulation of force-balance MEMS comb
accelerometers is studied. A mathematical model, which involves both the sense element and interface
electronics, is developed and governing equations are derived. The sense element is designed and
simulated in COVENTOR. The modal analysis shows that the resonance frequency of the sense
element in detecting direction is 7.1 kHz; the static analysis shows that the sense element can endure
with over load of 2000 g, and the displacement of the proof mass has a very good linear relationship
with the external acceleration in the range of ±40 g. The whole accelerometer system is derived and
simulated in MATLAB. The results show that the force-balance MEMS comb accelerometer system’s
sensitivity is 100 mv/g, the full scale range is ±50 g, the nonlinear distortion is smaller than 0.5 % and
the system bandwidth is 2.2 kHz.
References
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