ARL-TR-8034 ● JUN 2017

US Army Research Laboratory

Optimization of In-Cylinder Pressure Filter for 

Engine Research

by Kenneth S Kim, Michael T Szedlmayer, Kurt M Kruger, and 

Chol-Bum M Kweon

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Destroy this report when it is no longer needed. Do not return it to the originator.
ARL-TR-8034 ● JUN 2017

US Army Research Laboratory

Optimization of In-Cylinder Pressure Filter for 

Engine Research

by Kenneth S Kim, Michael T Szedlmayer, Kurt M Kruger, and 

Chol-Bum M Kweon

Vehicle Technology Directorate, ARL

Approved for public release; distribution is unlimited.
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June 2017

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June 2016–December 2016

4. TITLE AND SUBTITLE

Optimization of In-Cylinder Pressure Filter for Engine Research

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6. AUTHOR(S)

Kenneth S Kim, Michael T Szedlmayer, Kurt M Kruger, and Chol-Bum M 

Kweon

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US Army Research Laboratory

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Aberdeen Proving Ground, MD 21005-5066

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ARL-TR-8034

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13. SUPPLEMENTARY NOTES

14. ABSTRACT

Proper filtering of an engine’s in-cylinder pressure is very important for analyzing combustion events. The objective of this 

study was to investigate and determine the optimal filter and its parameters for removing signal noise while retaining incylinder pressure characteristics of interest, for both normal and abnormal combustion events. A 4-cylinder direct-injection 

aviation diesel engine was instrumented to acquire in-cylinder pressure with a range of combustion events. Simple smoothing 

filters showed limited performance for an abnormal combustion event, resulting in biased in-cylinder pressure near start-ofcombustion. The Savitzky-Golay filter, one of the simple smoothing filters, determined filtered in-cylinder pressure with high 

accuracy near start-of-combustion but underperformed in removing signal noise after start-of-combustion. Various linear 

continuous-time filters with frequency stop-band have advantages over simple smoothing filters in removing signal noise with 

magnitude response as a function of frequency. A number of linear continuous-time filters with different phase-response 

characteristics were investigated, and the optimal filter response and parameters were determined to effectively filter incylinder pressure of an aviation diesel engine. The Chebyshev filter with 5th-order polynomial and 0.001%-allowed ripples 

showed the best results in matching the raw signal near start-of-combustion and minimizing oscillations after start-ofcombustion.

15. SUBJECT TERMS

engine, pressure, filter, combustion, analysis

16. SECURITY CLASSIFICATION OF:

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Kenneth S Kim

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iii

Contents

List of Figures iv

1. Introduction 1

2. Experimental Setup 2

3. Filtering Approaches 2

3.1 Simple Filters 3

3.2 Linear Continuous-Time Filter 5

3.2.1 Filter Comparison 5

3.2.2 Filter Optimization 7

4. Results and Discussion 9

4.1 Filtered In-Cylinder Pressure 9

4.2 Heat-Release-Rate Results using the New Filter 11

5. Conclusions and Recommendations 13

5.1 Conclusions 13

5.2 Recommendations 14

6. References 15

Appendix A. Engine Bench Specifications 17

Appendix B. Sensor Calibrations 27

List of Symbols, Abbreviations, and Acronyms 31

Distribution List 32
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iv

List of Figures

Fig. 1 In-cylinder pressure comparison at different combustion events......... 1

Fig. 2 Engine test bench .................................................................................. 2

Fig. 3 Comparison of simple in-cylinder filters.............................................. 4

Fig. 4 Biased heat-release rate using Savitzky-Golay filter............................ 4

Fig. 5 Linear continuous-time filter order and phase response 

characteristics........................................................................................ 5

Fig. 6 Comparison of linear continuous-time filters....................................... 6

Fig. 7 Magnitude response of linear time-continuous filters .......................... 8

Fig. 8 Magnitude response of linear time-continuous filters at a small field 

of view .................................................................................................. 9

Fig. 9 Raw and filtered in-cylinder pressure near combustion event............ 10

Fig. 10 Raw and filtered in-cylinder pressure near SOC ................................ 11

Fig. 11 Heat-release-rate calculation using different linear continuous-time 

filters................................................................................................... 12

Fig. 12 Heat-release-rate calculation, including high-frequency pressure 

oscillation during combustion, using different filters......................... 13

Fig. A-1 Kistler in-cylinder pressure sensor specification ................................ 18

Fig. A-2 Kistler fuel line pressure and temperature sensor/amplifier 

specification ........................................................................................ 19

Fig. A-3 Kistler fuel line pressure and temperature sensor/amplifier 

specification ........................................................................................ 20

Fig. A-4 Kistler optical encoder specification................................................... 21

Fig. A-5 Glow-plug specification...................................................................... 22

Fig. A-6 Kistler glow-plug adapter for Mercedes OM642 engine .................... 23

Fig. A-7 Kistler glow-plug adapter for Mercedes OM642 engine .................... 24

Fig. A-8 Re-Sol fuel, bench specification ......................................................... 26

Fig. A-9 Closed-loop cooling column specification.......................................... 26

Fig. B-1 In-cylinder-pressure sensor calibrations............................................. 28

Fig. B-2 Static-pressure sensor calibrations...................................................... 29

Fig. B-3 Thermocouple calibrations.................................................................. 30
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1

1. Introduction

In-cylinder pressure data recorded during an internal combustion engine 

experiment is one of the most effective measurements to provide detailed 

information for combustion analysis. However, the use of raw in-cylinder pressure 

data is limited due to signal noise, and it is difficult to remove this noise while 

retaining characteristics of interest. A number of filters have been developed in the 

field of signal processing to remove unwanted noises and suppress interfering

signals. There has been limited transition of these filters into the engine research 

community, where they perform well for normal engine operation. Either a simple 

moving-average-based filter or band-pass filter would remove signal noises for a 

normal engine combustion event that shows a gradual increase and decrease of 

in-cylinder pressure, shown as a red solid line in Fig. 1. However, when an 

abnormal combustion event occurs, the simple filters perform poorly near the 

transition point. Figure 1 shows an example of an extremely high-pressure rise 

cycle in a compression-ignition engine, shown as a black solid line, which cannot 

be filtered properly using simple filtering approaches. 

Fig. 1 In-cylinder pressure comparison at different combustion events

The objective of this study was to determine the optimal filter and relevant filter 

parameters that 1) remove signal noise recorded in a raw data and 2) maintain 

characteristics of in-cylinder pressure without any filter bias for both normal and 

abnormal combustion.

-50 -25 0 25 50

CAD [°aTDC]

0

2000

4000

6000

8000

10000

12000

14000

In-cylinder pressure [kPa]
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2

2. Experimental Setup

A 4-cylinder, turbocharged direct-injection aviation diesel engine was instrumented 

to acquire in-cylinder pressure data. Figure 2 shows the engine test bench. On the 

test stand, the engine is connected to an AC dynamometer that can operate up to 

250 hp, with a maximum torque of 580 Nm and a maximum speed of 30,000 rpm. 

Engine crank angle was measured with a Kistler encoder (model no. 2614C11) with 

a resolution of 0.5° crank angle. In-cylinder pressure sensors were installed in the 

place of the glow plugs using off-the-shelf Kistler glow plug adapters (model no.

6544Q10). Detailed information on the glow plug and the glow plug adapter is 

shown in Appendix A. The calibrations of the major sensors can be found in 

Appendix B.

Fig. 2 Engine test bench

3. Filtering Approaches

This section discusses characteristics of differing filter types, limitation in filtering 

an erratic in-cylinder pressure, and optimal filter parameter design for engine 

research.
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3

3.1 Simple Filters

A number of filters have been developed and recommended to fulfill different 

requirements of the analysis of engine experimental data. Simple smoothing filters 

such as a moving-average or median filter, are commonly used to reduce short-term 

fluctuations and highlight the long-term trend of the signal. The unweighted 

moving-average filter uses the simplest convolution operation and can serve as a 

low-pass filter. More-complex smoothing with a weighted moving-average can be 

achieved by using the Savitzky-Golay convolution coefficients, which are based on 

a least-squares fit of subsets of adjacent data points with a low-degree polynomial. 

An engine test condition that showed high-pressure rise rate and high-frequency 

pressure oscillation was selected to demonstrate the capabilities and limitations of 

these simple filters. Two different data spans (5 and 10 points) were used for a 

moving-average filter, and 3rd-order polynomials were used for 1-D median filter. 

The built-in Matlab function sgolayfilt with a second-order polynomial and a frame 

length of 7 was used for a Savitzky-Golay filter. Figure 3 shows a comparison of 

all 4 filters against the original pressure data set. It is readily apparent that the 

Savitzky-Golay and the median filters exhibit excellent agreement with the 

in-cylinder pressure trace during compression stroke up until the start-ofcombustion (SOC) around 4° aTDC (after top dead center). On the other hand, the 

moving-average filters showed deviations shortly before the initial pressure rise 

with higher-filtered pressure values. This is due to calculated average pressure in 

the window spreading the influence of the rapid pressure rise. As expected, a larger 

deviation was shown with the larger 10-point data span than the 5-point span. 

During the high-frequency pressure oscillation after the SOC, it is clear that the 

high-frequency signal noise was not effectively reduced or removed for any of the 

simple filters tested in Fig. 3. The median filter provided the worst performance 

among the tested filters, at some points even yielding the same value as the raw 

signal during the pressure oscillations after SOC. The Savitzky-Golay filter also 

showed relatively high oscillation compared with the moving-average filters. A 

tradeoff between accuracy near SOC and during pressure oscillations after SOC 

was found when simple filters were used. Figure 4 presents calculated heat-release 

and accumulative heat-release rates using the in-cylinder pressure signal filtered by 

Savitzky-Golay polynomials.
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4

Fig. 3 Comparison of simple in-cylinder filters

Fig. 4 Biased heat-release rate using Savitzky-Golay filter

-5 0 5 10 15 20

CAD [°aTDC]

6000

7000

8000

9000

10000

11000

12000

13000

In-cylinder pressure [kPa]

raw

Savitzky-Golay

moving avg., 10pts

moving avg., 5pts

1-D, median

-20 0 20 40 60

CAD [°aTDC]

-50

0

50

100

150

200

250

300

Heat release rate [J/cad]

0

0.25

0.5

0.75

1

Accumulative heat release [-]
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5

Heat release rate was calculated using the first law of thermodynamics, as seen in 

Eq. 1, where γ is the time and temperature-dependent specific heat ratio, V is timedependent combustion chamber volume, P is time-dependent in-cylinder 

combustion chamber pressure, and Q is energy added to the combustion chamber.

1

dddd

dddd = γγγγ−1

PP dddd

dddd + 1γγ−1

VV dddd

dddd . (1)

As shown in Eq. 2, γ was determined from a first-order polynomial equation, where 

T is the mean in-cylinder temperature obtained from the equation of state.

2

γγ = 1.392 − 7.35 × 10−5 × TT . (2)

Equation 1 shows hat the calculated rate of heat release is a strong function of both 

the pressure itself and the time derivative of the pressure data. The Savitzky-Golay 

filter removes noise effectively prior to the initial pressure rise, as seen in the 

calculated heat-release rate, which is close to zero. Additionally, the SOC can be 

determined with the least uncertainty using this set of filtered in-cylinder pressure 

data. However, the inefficiency of the Savitzky-Golay filter during the pressure 

oscillation phase is transferred to the heat-release calculation, and the oscillations 

in calculated heat-release rate can be seen in Fig. 4. During the oscillation, negative 

values of the heat-release rates are seen, which is not physically possible and mostly 

due to filter bias.

3.2 Linear Continuous-Time Filter

3.2.1 Filter Comparison

Various linear continuous-time filters, which operate in the frequency domain, were 

investigated to compare filter response characteristics and noise reduction 

performance. Figure 5 illustrates the basic characteristics of the filters with regard 

to filter order and phase response.

3 No single filter performs perfectly for all 

possible experimental setups; therefore, a filter should be selected with care to 

efficiently filter the raw signal. In this report, Butterworth, Chebyshev, and elliptic 

filters, which are the most widely used linear continuous-time filters, are compared.

Fig. 5 Linear continuous-time filter order and phase response characteristics3

Bessel

Butterworth

Chebyshev

Elliptic

smaller order, or 

narrower transition

more linear phase 

over the passband
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6

Figure 6 presents the magnitude response of the Butterworth, Chebyshev Type 1 

and 2, and elliptic filters with respect to a signal frequency. The Butterworth is a 

well-known and widely used filter that is often referred to as a maximally flat 

magnitude filter. It was designed not only to remove certain frequencies, but also 

to maintain a uniform sensitivity for the frequencies of interest. To allow a uniform 

sensitivity for both passband and stopband without any ripples, the Butterworth 

filter shows the slowest roll-off of the signal magnitude decrease and widest 

frequency range compared with the other filters shown in Fig. 6. A 4th-order 

polynomial was used for the Butterworth filter, and the slope of the filter can be 

adjusted by changing the order of polynomial. Higher order will make the 

Butterworth filter sharper at the cutoff frequency; however, the magnitude response 

value of any order will be the same at the cutoff frequency, approximately at 0.7.

Fig. 6 Comparison of linear continuous-time filters

The Chebyshev filter is known as the best approximation to the ideal step response 

with steeper roll-off at the cutoff frequency by allowing oscillations in the 

passband. Type 1 has ripples in the passband, while Type 2 has ripples in the 

stopband. The elliptic filter has ripples in both passband and stopband with the 

steepest roll-off of all the filters. Figure 6 shows the filter magnitude response of a 

4th-order Chebyshev Type 1 with a 0.5-dB ripple in passband and a Type 2 with a 

20-dB ripple in stopband and an elliptic filter with the same order and ripple factor. 

The elliptic filter showed the steepest magnitude response at the cutoff frequency; 

10 -1 10 0 10 1

Frequency [rad/sec]

0

0.2

0.4

0.6

0.8

1

Magnitude response [-]

Butterworth

Chebyshev I

Chebyshev II

Elliptic
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7

however, ripples in the both stopband and passband can cause bias. As the ripples 

in the passband approaches zero, the elliptic filter becomes a Type 1 Chebyshev 

filter, and reduced ripples in the stopband becomes similar to the Type 2 filter. A 

Butterworth filter is the extreme case of a Chebyshev filter without any oscillations 

over the whole bandwidth. 

3.2.2 Filter Optimization

For the purpose of combustion analysis, a stable low-pass-filtered in-cylinder 

pressure is very critical. To determine as accurately as possible the metrics of an 

erratic combustion event (e.g., pressure rise rate and knock intensity), the leastbiased bandpass-filtered data are required. To avoid filter bias and over-filtering 

issues, flat magnitude responses at low frequency (passband) are preferred;

therefore, Butterworth and Chebyshev Type 1 filters with ripples at the passband 

were compared with different parameters.

Figure 7 shows magnitude responses of filters with different cutoff frequencies, 

order of polynomials, and ripple allowances. The Butterworth filters were 

compared with 2 different cutoff frequencies, 4 and 5 kHz. A normalized cutoff 

frequency of 4 kHz (0.1852 π×rad/sample) is marked in the figure to visually 

confirm filter response at the cutoff frequency. Figure 7 shows that the magnitude 

response of the Butterworth filters with a 4-kHz cutoff frequency starts decreasing 

at the normalized frequency of 0.14 π×rad/sample, which is equivalent to a 3-kHz 

in-frequency domain. Even with a 5-kHz cutoff frequency, the Butterworth filter 

showed a magnitude response of 0.96 [-] at the normalized frequency due to the 

slow roll-off characteristics. The Butterworth filter has an advantage of maximum 

flat magnitude response; however, as a tradeoff, the filter showed less sensitivity 

responding to the desired cutoff frequency. 
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8

Fig. 7 Magnitude response of linear time-continuous filters

The magnitude response of the Chebyshev Type 1 filter with a different order of 

polynomials, and therefore acceptable levels of oscillation, are presented in Fig. 7. 

Compared with the Butterworth filters, the Chebyshev filters showed relatively 

faster roll-off between passband and stopband. As the level of acceptable oscillation 

increased, magnitude response decreased slowly, or the same level of magnitude 

was achieved at higher normalized frequency. The higher-order polynomial showed 

slightly steeper magnitude response. Every tested Chebyshev filter showed an 

initial decrease of the magnitude response very close to the targeted cutoff 

frequency. 

Figure 8 presents the magnitude response of different filters discussed in Fig. 7 with 

a smaller field of view at the passband. Ripples allowed in the passband for 

Chebyshev filters are clearly shown. The amount of allowed oscillation is shown in 

decibels and not with the absolute value of magnitude. For any orders of polynomial 

and allowed ripples, the Chebyshev filter showed good response of decreased 

magnitude at the targeted cutoff frequency. When compared with different 

magnitudes of acceptable oscillation at the same order of polynomials, the location 

of the ripples were the same with only differences in the amplitude of the ripples. 

0 0.1 0.2 0.3 0.4 0.5

Normalized Frequency ( rad/sample)

0

0.2

0.4

0.6

0.8

1

Magnitude

Magnitude Response

Butter,5th,4k

Butter,5th,5k

Cheby,5th,0.1%

Cheby,5th,0.01%

Cheby,5th,0.001%

Cheby,6th,0.01%

4kHz cutoff frequency
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9

A higher order of polynomial at the same allowed ripples shows a slightly steeper 

magnitude response around the targeted cutoff frequency. In the passband 

frequency range, the 6th-order polynomial showed one more ripple than the 5thorder polynomial, which resulted in less than unity of the magnitude response at 

the lowest frequency range. Odd numbers of polynomial orders are preferred for 

the optimized Chebyshev filter parameters, with magnitude response close to unity 

at the lowest frequency. 

Fig. 8 Magnitude response of linear time-continuous filters at a small field of view

4. Results and Discussion

Linear time-continuous filters discussed in the previous section were applied to 

in-cylinder pressure data to compare filter performances. 

4.1 Filtered In-Cylinder Pressure

Figure 9 presents raw and filtered in-cylinder pressure signals at a long ignition 

delay condition to evaluate filter performance. A Butterworth filter with a 5th-order 

polynomial using a 4-kHz cutoff frequency and a Savitzky-Golay filter with 

second-order polynomial using a frame length of 7 were used as low-pass filters to 

calculate filtered in-cylinder pressure traces. As discussed in the previous section, 

0 0.05 0.1 0.15 0.2 0.25

Normalized Frequency ( rad/sample)

0.98

0.985

0.99

0.995

1

1.005

Magnitude

Magnitude Response

Butter,5th,4k

Butter,5th,5k

Cheby,5th,0.1%

Cheby,5th,0.01%

Cheby,5th,0.001%

Cheby,6th,0.01%

percent 

ripple

4kHz cutoff frequency
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10

only a 5th-order polynomial was used for Chebyshev filter. The filtered 

in-cylinder pressure using the Savitzky-Golay filter and the Chebyshev with 

0.001%-allowed ripples showed good agreement with the raw in-cylinder pressure 

data around SOC timing (from top dead center [TDC] to 3° aTDC), while pressure 

oscillation are observed after the initial pressure rise (after 5° aTDC). Other filters, 

including the Butterworth and the Chebyshev with a larger amplitude of ripples 

allowed, showed deviations at SOC timing and less oscillations after the initial 

pressure rise. 

Fig. 9 Raw and filtered in-cylinder pressure near combustion event

Figure 10 presents the same data as seen in Fig. 9 but at a smaller field of view to 

focus filtered in-cylinder pressure data at SOC timing. Over-filtered in-cylinder 

pressure as pressure fluctuations ahead of SOC were shown with the Butterworth 

and Chebyshev filters. The Butterworth filter showed the highest deviations, about 

150 kPa, compared with the raw data at a few crank-angle degrees ahead of SOC 

timing. Any biases at SOC timing will significantly impact determining SOC and 

initial heat-release results. The Chebyshev filter with 0.001%-allowed ripples 

showed reasonable deviations with a less than 50-kPa difference around SOC 

timing.

0 5 10

CAD [°aTDC]

6000

7000

8000

9000

10000

11000

12000

13000

In-cylinder pressure [kPa]

raw

Cheby,0.1%

Cheby,0.01%

Cheby,0.001%

Butter

Sgolay
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11

Fig. 10 Raw and filtered in-cylinder pressure near SOC

4.2 Heat-Release-Rate Results using the New Filter

Figure 11 presents calculated heat-release-rate results using different linear 

continuous-time filters. Results calculated using the Savitzky-Golay-filtered 

in-cylinder pressure data clearly showed the timing of an initial combustion event, 

while other filters showed fluctuations before SOC. These fluctuations are not 

physically possible and are purely due to over-filtering bias in the in-cylinder 

pressure trace. The Chebyshev filter with 0.001%-allowed ripples showed fewer 

fluctuations than other filters, and the value of the peak heat-release rate was 

reasonably well-matched with the Savitzky-Golay filter. After the initial premixed 

combustion, a reasonable trace of heat-release rate with less oscillation and no 

negative values were shown with the Chebyshev and Butterworth filters. The 

Butterworth filter showed the least fluctuation of all the filters; however, 

in-cylinder pressure data and heat-release-rate calculation at SOC could be 

significantly biased due to over-filtering.

-4 -3 -2 -1 0 1 2

CAD [°aTDC]

6000

6500

7000

7500

8000

In-cylinder pressure [kPa]

raw

Cheby,0.1%

Cheby,0.01%

Cheby,0.001%

Butter

Sgolay
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12

Fig. 11 Heat-release-rate calculation using different linear continuous-time filters

Figure 12 presents calculated heat-release rate that includes high-frequency 

pressure oscillation during combustion. The pressure oscillations that were 

captured by the Savitzky-Golay filter were shown as high-frequency oscillations in 

the heat-release calculation. With the use of any linear continuous-time filters 

investigated in this report, the nonphysical heat-release-rate oscillations were 

reduced. A clearer separation between premixed and mixing-controlled combustion 

can be achieved with either Chebyshev or Butterworth filters.

-20 -10 0 10 20 30 40 50

CAD [°aTDC]

-50

0

50

100

150

200

250

300

Heat release rate [J/cad]

Sgolay

Cheby,0.01%

Cheby,0.001%

Butter
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13

Fig. 12 Heat-release-rate calculation, including high-frequency pressure oscillation during 

combustion, using different filters

5. Conclusions and Recommendations

The in-cylinder pressure data from engine research requires proper filtering for 

combustion analysis, especially with the existence of erratic combustion events. 

The objective of this research was to investigate linear continuous-time filter 

characteristics and their performance filtering engine in-cylinder pressure data to 

remove noise in the raw data without causing any filter bias. To achieve this goal, 

a number of filters were tested, and the Chebyshev Type 1 filter with optimal 

parameters was determined to be an optimal filter for analysis of an aviation diesel 

engine in-cylinder data. 

5.1 Conclusions

A relatively simple filter, based on a moving-average calculation, cannot 

sufficiently remove signal noise in the raw data. Linear continuous-time filters were 

compared to determine the optimal parameters that filters engine in-cylinder data 

for both normal and erratic combustion with minimal filter biases. The Butterworth 

filter provides stable filtered signal with its maximally flat magnitude response but

-20 0 20 40 60 80

CAD [°aTDC]

-40

-20

0

20

40

60

80

100

Heat release rate [J/cad]

Sgolay

Cheby,0.01%

Cheby,0.001%

Butter

mixing-controlled

pre-mixed
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14

under-performs with sudden pressure increase. Filter response to a cutoff frequency 

was low due to a slow roll-off characteristic of the Butterworth filter. The 

Chebyshev filter showed a good response of decreased magnitude response at the 

targeted cutoff frequency for any order of polynomials and allowed ripples. The 

Chebyshev Type 1 filter with 5th-order polynomial and 0.001%-allowed ripples 

showed good agreement with experimental data near SOC timing and significantly 

lower signal oscillations than the Savitzky-Golay filter. 

5.2 Recommendations

From the investigation of linear continuous-time filters’ characteristics and 

performance, it was found that the filter should be selected with care to ensure noise 

removal and maintaining the accuracy of in-cylinder pressure trace. The following 

recommendations are made for potential future use of in-cylinder filters:

• The Butterworth filter calculates filtered pressure with reasonable accuracy 

for normal combustion. In the case of an erratic combustion, the 

Butterworth filter resulted biases, especially at the start of combustion with 

a high-pressure rise.

• The Chebyshev Type 1 filter performed well, filtering both normal and 

erratic combustion in-cylinder pressure data. An odd-number polynomial 

order is suggested to ensure flat response at the lowest frequency range. 

• An energy spectral density analysis of the engine system is required to 

determine the natural frequency of the engine block to effectively remove 

unwanted frequency ranges.
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15

6. References

1. Heywood JB. Internal combustion engine fundamentals. New York (NY): 

McGraw-Hill; 1988.

2. Gatowski J, Balles E, Chun K, Nelson F, Ekchian J, Heywood J. Heat release 

analysis of engine pressure data. Warrendale (PA): Society of Automotive 

Engineeers; 1984. SAE Technical Paper No.: 841359. 

3. Orfanidis S. Lecture notes on elliptic filter design. New Brunswick (NJ): 

Department of Electrical and Computer Engineering, Rutgers University; 2006.
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16

INTENTIONALLY LEFT BLANK.
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17

Appendix A. Engine Bench Specifications
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18

Fig. A-1 Kistler in-cylinder pressure sensor specification

Model Number [] 6058A

Range [bar] 0 ... 250

Overload [bar] 300

Sensitivity [pC/bar] -17

Natural frequency, nominal [kHz] 160

Linearity [%FSO] 0.3

Acceleration sensitivity [bar/g] <0.0005

Operating temperature range [°C ] -50 ... 400

Sensitivity shift

200±50°C [%] ±0.5

23 ... 350°C [%] ±2

Short term drift (thermal shock) (at 1 500 

1/min, pmi = 9 bar)

|Δp| (Short therm drift) [bar] <0.5

|Δpmi| [%] <2

|Δpmax| [%] <1

Insulation resistance at 23 °C [Ohm] >10^13

Shock resistance [g] 2000

Capacitance, without cable [pF] 5

Weight with cable [gram] 30

Tightening torque [Nm] 1.2

Connector, ceramic insulator [] M3×0.35

Kistler In-cylinder Pressure Sensor
Approved for public release; distribution is unlimited.

19

Fig. A-2 Kistler fuel line pressure and temperature sensor/amplifier specification

Model Number [] 4067C3000 / 4618A2

Range [bar] 0 ... 3000

Overload [bar] 3500

Threshold [mbar] 200

Sensitivity (± 0.5 % at 25°C) [mV/bar] 5

Natural frequency (sensor) [kHz] >100

Rise time (5-95 %) [μs] <10

Output signal, pressure [V] 0 ... 10

Output signal, temperature [mV/K] 10

Output resistance [Ohm] 10

Supply (amplifier) [VDC] 18 ... 30

Zero setting (at 25°C, 1 bara) [mV] <±100

Linearity and hysteresis [% FSO ] <±1

Thermal shift (20 ... 120 °C) of 

Zero [% FSO ] <±2

Sensitivity [%] <±2

Operating temperature range

Sensor [°C ] 10 ... 120

Amplifier [°C ] 0 ... 70

Minimum/maximum temperature (sensor) [°C ] –40/140 

Acceleration sensitivity [mbar/g ]

Vibration resistance [g] 1000

Tightening torque [Nm] 15

Degree of protection [] IP 65

Service life (guideline) [cycles] >10^7

Kistler Fuel Line Pressure and Temperature Sensor / Amplifier
Approved for public release; distribution is unlimited.

20

Fig. A-3 Kistler fuel line pressure and temperature sensor/amplifier specification

Model Number [] 4045A5

Range [bar] 0 ... 5

Overload [bar] 12.5

Threshold [mbar] <2.5

Burst pressure [bar] 12.5

Sensitivity (± 0.5 % at 25°C) [mV/bar] 100

Natural frequency (sensor) [kHz] >30

Full scale output [mV/bar] 500

Constant current excitation [mA] <10

Calibration current [mA] 2 ... 5

Input/output impedance [kOhm] 3 (nominal)

Zero measured output [mV/bar] <±20

Linearity [%FSO] <±0.3

Hysteresis [%FSO] <0.1

Repeatability [%FSO] <0.2

Stability of sensitivity <0.2

Stability of zero [%FSO] <0.1

Thermal zero shift [%FSO] <±0.5

Thermal sensitivity shift [V] <±1

Operating temperature range [°C ] 20 ... 120

Minimum/maximum temperature [°C ] 0 / 140

Acceleration error [bar/g] <3×10^(-4)

Shock resistance [g] 1000

Volume change [mm3] <0.2

Insulation Resistance [megaOhm] >100

Material (head and diaphragm) [] 18/8 steel

Material (body with threads) [] Armco 17-4 PH

Tightening torque (with Delrin plastic 

gasket) [Nm] 3 ... 5

Socket for plug [] Fisher Type SE 103A054

Kistler Manifold Air Pressure Piezoresistive Sensor
Approved for public release; distribution is unlimited.

21

Fig. A-4 Kistler optical encoder specification

Model Number [] 2614C11

Crank angle signal [°] 720x0.5

Speed range [1/min] 0 ... 12 000

Temperature rang [°C] –40 ... 85

Mechanical Interface/Mounting diameter [mm] 60

(mounting compatibility to Type 2614B1)

Electrical connection cable with plug l = 2 m

Weight [g] 340

Control & Indication LED’s – Power

– Rotation cw/ccw

– Trigger

– Synchronization

Output signal to Indicating System – LVDS-Signal

– TTL-Signal

Power supply [VDC] 5 ... 30

Temperature range [°C] –30 ... 70

Dimensions [mm] 108x74x36

Weight [g] 290

Kistler Optical Encoder
Approved for public release; distribution is unlimited.

22

Fig. A-5 Glow-plug specification
Approved for public release; distribution is unlimited.

23

Fig. A-6 Kistler glow-plug adapter for Mercedes OM642 engine
Approved for public release; distribution is unlimited.

24

Fig. A-7 Kistler glow-plug adapter for Mercedes OM642 engine
Approved for public release; distribution is unlimited.

25

Fig. A-7 Kistler glow-plug adapter for Mercedes OM642 engine (continued)
Approved for public release; distribution is unlimited.

26

Fig. A-8 Re-Sol fuel, bench specification

Fig. A-9 Closed-loop cooling column specification

Model RS905C

Fuel Type JP-8, Jet fuels, diesel, synthetic JP-8, bio fuels

Flow Measurement Range 0.1 to 15g/s

Engine Supply Pressure 120 PSI

Pressure Control Stability +/- 0.75 PSI

Temperature Accuracy Better than +/- 0.5°C

Temperature Control Range 30°C to 50°C

Density Range 0.6 to 0.9 g/cc

Fuel Capacity Two 6 gallon reservoirs

Cooling Capacity 6 kW

Cooling water flow 4 gpm with 20 psi differential

Shop Air Supply Pressure Minimum 40 PSI

Power 120 VAC, Single-Phase, 4.8 FLA, 60 Hz

Re-Sol Fuel Bench

Category Description Unit Value

Model [] CLC-300 

Serial number [] 63844

Max power [hp] 300

Estimated weight [lbs] 600

Max inlet temp. [°F] 230

Max pressure [psi] 15

Max inlet temp [°F] 85

Pressure pange [psi] 30-65

Min flow / 100 hp [gpm] 7

Power requirement [VAC] 120

Max current [A] 15

System

Engine

Water

Power

PTI Closed-Loop Cooling System
Approved for public release; distribution is unlimited.

27

Appendix B. Sensor Calibrations
Approved for public release; distribution is unlimited.

28

Fig. B-1 In-cylinder-pressure sensor calibrations
Approved for public release; distribution is unlimited.

29

Fig. B-2 Static-pressure sensor calibrations
Approved for public release; distribution is unlimited.

30

Fig. B-3 Thermocouple calibrations

-200.0 193.0 586.0 979.0

1 1 1 Cyl 1 exh -198.3 193.9 586.7 979.4

2 1 2 Cyl 2 exh -198.3 193.9 586.7 979.4

3 1 3 Cyl 3 exh -198.3 193.9 586.7 979.4

4 1 4 Cyl 4 exh -198.3 193.9 586.7 979.4

5 1 5 Exh Mnfld -198.3 193.9 586.7 979.4

6 1 6 Oil -198.3 193.3 586.7 979.4

7 1 7 Exh Pipe -198.3 193.3 586.7 979.4

8 1 8 Intake Pipe -198.3 193.3 586.7 979.4

9 2 1 Intake Mnfld -198.3 193.3 586.7 979.4

10 2 2 Coolant Supply -198.3 193.3 586.7 979.4

11 2 3 Coolant Return -198.9 193.3 586.7 979.4

12 2 4 Exh Surge Tank -198.9 193.3 586.7 979.4

13 2 5 Ambient -198.3 193.3 586.7 979.4

14 2 6 Unused -198.3 193.3 586.7 979.4

15 2 7 Unused -198.3 193.3 586.7 979.4

16 2 8 Unused -198.3 193.3 586.7 979.4

Sourced Temperature on Calibrator [°C ]

Reading [°C ]

Ref PTI Module Thermocouple TC name
Approved for public release; distribution is unlimited.

31

List of Symbols, Abbreviations, and Acronyms

1-D 1-dimensional

AC alternating current

aTDC after top dead center

SOC start-of-combustion

TDC top dead center
Approved for public release; distribution is unlimited.

32

1 DEFENSE TECHNICAL

(PDF) INFORMATION CTR

DTIC OCA

2 DIRECTOR

(PDF) US ARMY RESEARCH LAB

RDRL CIO L

IMAL HRA MAIL & RECORDS

MGMT

1 GOVT PRINTG OFC

(PDF) A MALHOTRA

6 DIR USARL

(PDF) RDRL VT

K MORGAN

RDRL VTP

L BRAVO

C KWEON

M SZEDLMAYER

J TEMME

K KIM