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Automated tuning of an engine management unit for an automotive engine

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Abstract and Figures

Modern automotive engines are digitally controlled using an engine management unit (EMU) that is typically manually programmed using an engine dynamometer to obtain desired levels of power, emissions and effciency. Closed-loop control of an engine dynamometer and EMU, combined with an overall engine tuning algorithm, is used to automate the tuning of the engine map for a four-cylinder engine. The tuning algorithm determines the air-to-fuel ratio necessary for each region of engine speed and throttle position to obtain the desired performance, automatically moving to each operating region in the map. Preliminary automated tuning results produce power output curves comparable with those delivered using the original manufacturer tuned EMU. At lower engine speeds data filtering is required and results in power outputs slightly lower than the factory-tuned engine. At higher speeds small improvements in engine efciency, for equivalent performance, can be found. The research presented clearly demonstrates that engine tuning to a very high standard, equivalent to original equipment manufacturer engine performance, can he successfully automated, saving time and adding consistency to the engine tuning process.
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841
Automated tuning of an engine management unit for an
automotive engine
C Hardie, H Tait, S Craig, J G Chase*, B W Smith and G Harris
Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand
Abstract: Modern automotive engines are digitally controlled using an engine management unit
( EMU ) that is typically manually programmed using an eng ine dynamometer to obtain desired le vels
of power, emissions and eciency. Closed-loop control of an engine dynamometer and EMU, com-
bined with an overall engine tuning algorithm, is used to automate the tuning of the engine map for
a four-cylinder engine. The tuning algorithm determines the air-to-fuel ratio necessary for each region
of engine speed and throttle position to obtain the desired performance, automatically moving to
each operating region in the map. Preliminary automated tuning results produce power output curves
comparable with those delivered using the original manufacturer tuned EMU. At lower engine speeds
data  ltering is required and results in power outputs slightly lower than the factory-tuned engine.
At higher speeds small improvements in engine eciency, for equivalent performance, can be found.
The research presented clearly demonstrates that engine tuning to a very high standard, equivalent
to original equipment manufacturer engine performance, can he successfully automated, saving time
and adding consistency to the engine tuning process.
Keywords: control, automation, engine tuning, dynamometer, engine management, engine map
1 INTRODUCTION increased emissions of hydrocarbons and CO. Too little
fuel can result in engine damage such as burnt exhaust
valves. The amount of fuel supplied is controlled by the
Engine management units ( EMUs) are digital processors
EMU, which controls the frequency and pulse width of
that actively control fuel  ow and ignition timing to
the fuel injectors. At steady state, constant engine speed
ensure optimal engine operation and are employed in
the pulse width is calculated from a combination of three
most modern fuel injected engines. Engine tuning plays
inputs: ambient air temperature, the inlet manifold air
a vital part in ensuring that the EMU is programmed so
pressure ( MAP ) and user-de ned volumetric eciency
that the engine performs well under a variety of con-
correction factors ( VEC Fs).
ditions. The manufacturer-developed EMU parameters
A typical engine has a two-dimensional plane of
are typically developed to meet design compromises
steady state operating points with engine speed along
between performance, market and legislative speci ca-
the horizontal axis and throttle position or MAP along
tions, particularly with regard to emissions. After-
the vertical axis, as shown in Fig. 1. Each of these points
market EMUs are available to replace a damaged unit,
has diering requirements for fuel and ignition timing.
to achieve speci cations dierent to those used by the
Most EMUs divide this plane up into  nite rectangular
manufacturer, to enhance the operation of an engine
elements, commonly referred to as ‘zones’, that make up
intended for use both on land and in a marine environ-
an ‘engine map’ and where each zone has an associated
ment or to enable the tuning and enhanced performance
user-de ned VECF. The engine map acts as a look-up
of a modi ed engine.
table for operating parameters used by the EMU to con-
The air–fuel (A/F) ratio is important in the combus-
trol engine operation.
tion and tuning processes. If there is too much fuel, not
Currently, engine tuning is typically performed by a
all the fuel is burnt, causing high fuel consumption and
skilled technician who manually adjusts the operating
parameters for each zone of the engine map on a dyna-The MS was received on 3 January 2002 and was accepte d after revision
for pub lication on 6 Aug ust 2002. mometer or while driving. The engine is tuned to the
* Corresponding author: Departme nt of Mechanical Engineering, desired speci cation for each zone in which the engine
University of Canterbury, Private Bag 48 00, Christchurch, Ne w Zealand.
email: g.cha se@mech.canterbury.ac.nz is expected to be operated. This process is iterative and
D15501 © IMechE 2002 Proc Instn Mech Eng rs Vol 21 6 Part D: J A utomobile Engineering
842 C HARDIE, H TAIT, S CRAIG, J G CHASE, B W SMITH AND G HARRIS
Fig. 1 Structure of the engine map
time consuming, creating the potential for signi cant mation to enhance engine performance, rather than
automating EMU controller design. Engine tuning totime savings, additional repeatability and more accurate
results via automation. meet speci c performance criteria is typically performed
largely by hand via a combination of experience, scienceThe primary goal of this research is the automation
of the engine tuning process via engine tuning software and art. No references were found speci cally addressing
automation of the engine tuning process, although therethat communicates with both the dynamometer control-
ler and the EMU to create a closed-loop engine tuning is some prior research that generally references the
possibility of performing this task [5].system. The engine tuning algorithm that governs the
process is designed to optimize automatically the engine The following sections address the test system and
software developed to enable the automated tuning ofcontrol parameters for each operating zone, to achieve
performance in accordance with user-de ned speci ca- an EMU using an engine dynamometer and the basic
tuning algorithms developed. Subsequent sections testtions. In addition, the software ensures that potentially
damaging situations are detected and responds by plac- one of these tuning methods, compare the performance
obtained with that provided by the manufacturer’s EMUing the engine in a non-damaging state, sounding an
alarm and pausing the process until the problem can be and summarize the results and conclusions.
corrected. This second requirement ensures that the pro-
cess can be run largely unsupervised. Finally, the auto-
2 AUTOMATED ENGINE TUNING TEST
mation process, and the speci c software developed,
SYSTEM AND SOFTWARE
adds both speed and consistency to the engine tuning
process.
The after-market EMU employed is developed by The experimental automated engine tuning system is
tested on a 1992 Toyota 3S-GE engine from a ToyotaLink Electro-Systems of Christchurch, New Zealand.
This EMU along with the PCLink control and communi- MR2. This four-cylinder engine has two overhead cam-
shafts, displaces 1998 cm3and generates manufacturer-cation software is used to control the engine. A servo-
controlled Froude-Consine hydraulic dynamometer is listed peak outputs of 121 kW at 6800 r/min and
191 N m at 4800 r/min. Load is applied to the engine viaemployed for the tuning process. The automated tuning
algorithm comprises software designed to interface with, a servo-controlled Froude-Consine hydraulic dyna-
mometer that is controlled by a Test Automationand control, these two units for the end purpose of
tuning the Link EMU parameters for every usable zone TA2000 controller interfaced with a PC-based data
acquisition system utilizing an Advantech PCL-818 ana-of engine map.
Engine tuning is a well-known a rt documented in a log ue-to-digital converter ( ADC ) card. The test bed is
set up so that either the original Toyota EMU or thevariety of texts on the topic of internal combustion
engine performance [ 1]. Prior research in the area of Link EMU can control the engine. The dynamometer
and Link EMU are independently controlled via a PCautomated engine tuning is scarce with most research in
the area of automated engine tuning focusing on mod- program to close the loop on the engine tuning process.
Speci cally, the engine dynamometer and controllerifying speci c engine functions, such as spark ignition,
to enhance performance while the vehicle is in operation set and deliver values for engine speed, torque and
throttle position. The Link EMU can deliver values for[2,3]. Other works focus on systems to adaptively elim-
inate undesirable operating conditions or eects such as engine speed, throttle position, engine temperature, air
temperature, the injector duty cycle, ignition advance,knock [4]. All of these eorts focus on applying auto-
D15501 © IMechE 2002Proc Instn Mech Engrs Vol 216 Part D: J A utomobile Engineering
843AUTOMATED TUNING OF AN ENGINE MANAGEMENT UNIT
the oxygen sensor and the entire engine map. Where map. Once a tuning algorithm is run on the engine, per-
formance data are extracted for analysis and compari-there is overlap, such as engine speed, the control algor-
ithm uses these values to determine when transients have son. The power output, fuel consumption and eciency
curves are compared to evaluate the performance of thestabilized, as both units will report the same value.
The automation of the engine tuning process is tested tuning algorithm.
achieved via speci c software written to communicate
with and control independently both the engine dyna-
3 ENGINE TUNING ALGORITHMS
mometer and the Link EMU. An overall tuning algor-
ithm steps through each zone in the engine map and
tunes the EMU parameters for each zone according to Optimum engine performance is typically obtained at a
user speci cations. User speci cations that set the tar- constant air–fuel ratio (l) and the most desirable settings
get(s) for the tuning process in each zone are set prior for emissions are obtained when lis valued around 1.0
to tuning using a graphica l user interfa ce ( GUI ). A [1,6]. Small reductions of lcan optimize power output
dierent GUI is used to provide the user with real-time but may lead to sizeable increases in emissions. Similarly,
information about the engine operation, displaying par- values of lslightly greater than 1.0 tend to increase
ameters such as desired engine speed, actual engine eciency, up to a point, as the engine runs leaner.
speed, torque, power, fuel  owrate and ignition advance. Ignition timing was initially tuned in the base map and
The software is developed using Borland C++ not considered in this tuning process. Since changes to
Builder version 4.0. The overall closed-loop system this variable are easily added as a second step, it was
architecture and communication links created are illus- not considered until an understanding of the eect of
trated in Fig. 2, where the broken line encloses the automation on tuning lwas performed.
software communication links created to close the loop Several algorithms for engine tuning to meet speci ed
on the tuning process. Figures 3 and 4 show the status performance requirements can be developed, imple-
window and tuning set-up window for the user interface. mented and tested using performance speci cations
The speci c software structure consists of three pri- developed by any method. Two basic approaches tune
mary C++ classes. Two classes handle commands for for either maximum torque or a speci c target stoichio-
the EMU and dynamometer. A third class of low-level metric lsensor reading (air–fuel ratio), enabling tuning
control functions enables closed-loop engine tuning, for performance or economy, as desired.
facilitating control of the separate dynamometer and There are two primary steps for each of the automated
EMU systems by a single global entity on the PC. More tuning algorithms:
speci cally, these functions enable ‘get’ and ‘set’ com- 1. Tune the master fuel setting.
mands for quantities including fuel, master level, throttle 2. Tune the fuel setting for each of the zones that can
position, torque, power, ignition advance, lsensor, be tested.
knock sensor, temperature, dynamometer engine speed,
EMU sensed engine speed and the active zone. Further The master fuel setting is a global multiplier for every
fuel setting in the engine map. The higher the mastercommands and functions are used to determine whether
the system is running, whether engine speed has stabil- fuel value, the higher the fuel input for every zone. This
value is tuned to move every zone in the engine mapized in a zone and communication of these values to and
from the global tuning function. collectively to a region close to the desired performance.
Once the master fuel value is set, the engine map is  neIn order to allow the engine to start and run, the Link
EMU is programmed prior to installation with a basic tuned by individually tuning each zone. The master fuel
is automatically set by the automated tuning softwarefuel and ignition con guration, referred to as the base
while running the engine at approximately 50 per cent
of maximum engine speed and 50 per cent throttle,
before speci c automated tuning of each zone. Hence,
the tuning algorithms all have two essential steps, an
initial approximation using the master fuel setting and
speci c tuning of each operating zone in the engine map.
The engine is commanded to operate in the centre of
the zone, for each zone tuned. Since each zone in the
Link EMU is 500 r/min wide and 30°of throttle position
high, the engine is operated from 250 r/min at 15°
throttle in 500 r/min and 30°steps. Note that these steps
are  xed by the Link EMU; however, zone size in general
is a trade-obetween engine map size and complexity,
and the resolution required. It is important to note that
Fig. 2 Automated engine tuning system architecture not all zones are ‘reachable’ in that the engine does not
D15501 © IMechE 2002 Proc Instn Mech Eng rs Vol 21 6 Part D: J A utomobile Engineering
844 C HARDIE, H TAIT, S CRAIG, J G CHASE, B W SMITH AND G HARRIS
Fig. 3 Automated engine tuning status window
Fig. 4 Automated engine tuning set-up window
operate at 250 or 1 0 000 r/min, for example. The auto- In the tuning process the engine is  rst incremented
in speed over the entire row for a given throttle position.mated system tunes the engine for each zone that is
reachable by automatically moving on when steady state Each row is followed by incrementing and repeating the
process for subsequent throttle positions. The additionoperation cannot be achieved in a given zone.
D15501 © IMechE 2002Proc Instn Mech Engrs Vol 216 Part D: J A utomobile Engineering
845AUTOMATED TUNING OF AN ENGINE MANAGEMENT UNIT
of a 15 s pause at idle before the throttle angle is Overall, this tuning algorithm employs simple control
systems to tune each operating zone of the engine mapincreased allows time for engine cooling to prevent
overheating as the cooling system employed for these automatically to match a desired lvalue. This algorithm
provides a solid base for further development andtests was not adequate for high speed operating con-
ditions. A larger cooling system would have alleviated enables automated tuning. The control algorithm is equ-
ally eective if tuning for dierent target lvalues inthis condition and eliminated the need for a pause.
Owing to a dynamometer controller fault, it was each zone.
dicult to operate the system eectively at very low
speeds. Hence, the tuning process was run for operating
zones ranging from 500 to 7000 r/min. The user can 3.2 Tuning for maximum torque output
restrict the operating range for engine speed to speci ed
Engine tuning for maximum torque provides a dierent
ranges as required. Note that if the engine reaches a zone
tuning approach focused on maximum power. As with
in which it cannot operate, indicated by being unable to
the prior algorithm this controller varies the amount of
attain the commanded speed at the given throttle pos-
fuel supplied to the engine and logs the resulting torque
ition, the system times out, automatically skips the zone
output, while leaving ignition advance unchanged from
and moves to the next row of throttle positions.
the base map for this study. For example, when the fuel
supply is increased, torque comes to a peak and then
drops o, and the upper limit for fuel supply can be
3.1 Tuning for target air–fuel ratio
determined for that zone. This limit makes fuel sampling
This tuning method uses the factory lsensor to monitor iterative, as the fuel value associated with the peak
the amount of oxygen present in the exhaust gases and torque value must be found by  rst passing over the
hence the air–fuel ratio. The goal is to tune the EMU peak and then locating it via a simple peak detection
for peak torque while holding a constant lvalue to a routine with a tolerance of 1 per cent, or approximately
small range around 1.0. The algorithm illustrated in 1.5 N m at peak torque.
Fig. 5 implements a simple proportional control system Simple data smoothing is also performed so that spuri-
on both the master fuel setting and each of the zone fuel ous samples do not signi cantly aect the results. The
settings to perform this task. The control gain, K,end results are passed back to the overall controller and
controls the rate at which the actual air–fuel ratio put into the engine map and the tuning algorithm is
approaches the speci ed level. incremented to the next zone where the process is
This simple linear proportional control system is repeated. The automated software controlling the pro-
extremely eective in terms of its settling time and the cess handles moving from zone to zone. These basic
steady state error. In testing, the most appropriate gain process steps are essentially the same as those for the
for this system was found to be 0.25; however, the system target lmethod.
can be easily modi ed to  nd the best value adaptively.
Any positive value less than 1.0 should lead to steady
convergence. The controller implemented has a slight 3.3 Data  ltering
non-linearity owing to a limiter placed on the change in
controller output, to limit the amount the fuel can be The Test Automation TA2000 unit employs a simple
controller to oer throttle position, constant speed andchanged in any given step of the algorithm. Figure 6
shows the basic steps taken in this tuning process. constant torque control modes. This controller should
normally control the dynamometer to within 10 r/min;During testing of this algorithm a tolerance of ±2 per
cent on the target lsensor measurement is employed. however, during the tests it only held engine speed to
within 30–60 r/min. The inability to hold engine speedHigher tolerances produce signi cant deviations from
the target performance and lower tolerances make con- tightly leads to sizeable speed  uctuations, particularly
at low speed; however, it also presents a worst-case testvergence dicult. Tolerances can be modi ed via the
user interface for any system hardware. situation for automated engine tuning.
Fig. 5 Block diagram for target lautomated tuning algorithm
D15501 © IMechE 2002 Proc Instn Mech Eng rs Vol 21 6 Part D: J A utomobile Engineering
846 C HARDIE, H TAIT, S CRAIG, J G CHASE, B W SMITH AND G HARRIS
Fig. 6 Basic process steps for target lcontroller
To address these issues, simple digital low pass  lters results. The automated engine tune experiences a slight
are applied to smooth large variations in the data stream. tapering oin power soon after the peak output, while
The dynamometer is sampled by the ADC at 3 kHz and the factory EMU retained peak power for a more
is set up to average the data in lots of 50–100 samples. extended period. The maximum power was between 110
To increase the smoothness further, a rolling average is and 115 kW for each map, approximately 7 per cent
performed using  ve  ltered samples at a time. This  l- lower than the manufacturer-listed value of 121 kW,
tering is applied to the engine torque, engine speed and perhaps owing to age and wear.
oxygen sensor outputs. This approach low pass  lters At lower engine speeds, variations of ±5 kW occur
the data ranging from 0 to 12–60 Hz, depending on the owing to speed control issues with the dynamometer.
exact  ltering employed. Hence, interactions with dyna- When the dynamometer cannot hold the speed tightly,
mometer dynamics in the 30 Hz range are possible small changes in fuel input result in larger variations in
although no indications were noted as the implemented l, presenting a more dicult control problem. At higher
 ltering keeps data bandwidth under 30 Hz. speeds, the ltuning procedure resulted in equivalent or
slightly greater power output values. Overall, the auto-
mated engine tune using constant lresults in very similar
4 TESTING, RESULTS AND DISCUSSION torque and power performance to that of the OEM
EMU. The OEM EMU is probably tuned for l=1.0,
except at high speeds where fuelling may be increased to
The user interface code was modi ed so that, each time
something approaching l=0.9 to improve top end per-
the status screen is updated, the information displayed
formance. In contrast, the automated ltune method
is also logged to a  le. It was not possible to obtain the
tunes this value to be within ±2 per cent of l=1.0 for
same level of information from the OEM EMU as from
all zones. However, the torque and power results are
the Link EMU, making some comparisons dicult. To
very similar to the OEM graphs and it is possible, with
illustrate and prove the concept of automated engine
some added complexity, to tune each zone for a dierent
tuning, the engine is tuned for a constant lvalue using
target lvalue to mimic, more exactly, the basic OEM
the Link EMU, and the resulting performance compared
tuning process.
with the OEM EMU for torque and power.
The torque surfaces in Fig. 9 show the relatively  at
Figures 7 and 8 show the resulting performance for
torque curve associated with this engine for both the
the Toyota EMU and the automated engine tune respect-
automated engine tune and manufacturer’s EMU test
ively. These  gures show the engine map in the hori-
results. Maximum torque output was approximately
zontal plane with power on the vertical axis. The
180 N m at 5500 r/min for the OEM map using the exact
maximum power for this l-tuned engine map is consist-
data, with the automatically tuned results within 2 per
ently achieved around 6750 r/min, matching the manu-
facturer’s listed speci cations and OEM EMU test cent of this value. The region of the torque curve where
D15501 © IMechE 2002Proc Instn Mech Engrs Vol 216 Part D: J A utomobile Engineering
847AUTOMATED TUNING OF AN ENGINE MANAGEMENT UNIT
Fig. 7 OEM EMU power output ( kW )
Fig. 8 Automated engine tuned for constant lLink EMU power ou tput ( kW )
automated engine tuning achieved the smoothest result of this 1992 engine. The overall result is that the auto-
mated engine tuning concept is very close, at a  rst trial,was in the top half of the engine speed range around the
maximum torque values, where the dynamometer holds to the OEM tune in terms of peak torque, meeting the
aims of this project and proving the basic concept.the engine speed more tightly. This result is due to the
dynamometer controller delivering steady motion with As expected, the manufacturer’s EMU is programmed
to achieve a high level of performance from the engine.tight speed control more rapidly at higher speeds. At
lower engine speeds the impact of variation in speed The automated engine tune results in essentially equival-
ent performance to the manufacturer-listed speci ca-control, as a percentage of the total, and the size of the
engine map zones are evident in the less smooth result tions. Greater engine speed resolution of the engine map
at lower engine speeds and throttle settings would limitfor the automated engine tune. The peak torque values
for both cases are approximately 11 N m lower than the some of the roughness of the automatically tuned torque
response. The current engine map is de ned in 500 r/minlisted speci cation, probably as a result of age and wear
D15501 © IMechE 2002 Proc Instn Mech Eng rs Vol 21 6 Part D: J A utomobile Engineering
848 C HARDIE, H TAIT, S CRAIG, J G CHASE, B W SMITH AND G HARRIS
Fig. 9 OEM torque output ( N m, left ) and automated constant ltuned EMU torque output (N m right)
increments and steps of this size at engine speeds around resulting performance of a high standard is illustrated.
1500 r/min represent signi cant changes in engine Automation eliminates the requirement for full-time
operating condition. However, greater engine speed reso- oversight by skilled technicians and engineers. While the
lution of the engine map would enable a smoother auto- tuning routines developed are simple, results from auto-
matically tuned result. Greater engine speed resolution mated tuning of the Link EMU have reached a standard
would also enable a potentially smoother, more optimal approaching that of the factory EMU for a much lower
map to be obtained for this region and a potentially investment of time. Power and torque output data illus-
better overall result. trate how the engine map can be tuned from a very
The automated target lalgorithm required approxi- rough base map to a polished result that enables smooth
mately 30 min to complete. During this time, the centre operation over the entire engine operating range. Power
of each Link EMU engine map zone was tuned for all and torque results for the automated engine tune are
zones in the 500–7000 r/min range and in the 0°90°reasonably similar to those obtained from the original
throttle range, where the  rst zone would be tuned at manufacturer EMU with some roughness at lower
750 r/min and 15°. Of all 48 operating zones available engine speeds. The entire tune took approximately
in this region of the engine map, only 36 were attainable 30 min to deliver results and faster times could be
by the test engine and the rest represented operating achieved with better dynamometer controller settings.
conditions that the engine could not reach (e.g. These times are signi cantly faster than comparable
6750 r/min and 15°throttle). Here again, higher reso- hand-controlled tests at the same facility illustrating
lution in the engine map may provide better results and the potentially large time saving available through
greater  exibility, particularly at lower engine speeds. automating these tests.
At Canterbury, an equivalent manual test, tuning These automated results are achieved through the
50–100 zones for greater resolution, would take approxi- development of independent software interfaces between
mately 4 h. A very experienced technician could tune the a PC an engine dynamometer and an after-market EMU.
equivalent 36 zones in as short a time as 1 h with a well- Further software encapsulates a global tuning algorithm
known engine. Given better dynamometer controller using closed-loop feedback to command the system to
tuning to hold engine speed to a far tighter tolerance, desired states and to tune the engine map. A graphical
the engine tuning tests presented here would take user interface enables user input of tuning speci cations
approximately 8–10 min, and an equivalent 50 100 zone for the entire map, each individual zone or larger regions
test would take approximately 25–35 min. The increased of the engine map. There are also a variety of safety
speed of the automated tune would result directly from shut-os and automatic restarts included to minimize
the ability to  nd and hold the steady state engine speed the need for human intervention.
required, far more quickly than with the controller In summary, automated torque and target lengine
tuned. In either case, automation of this process oers tuning procedures are developed and the ltune is tested.
signi cant time savings. The system has the  exibility to allow for further
advancement in automated engine tuning. Areas where
further work will have signi cant impact include the
5 CONCLUSIONS development of more sophisticated tuning algorithms
that include emissions control, thermal eciency,
ignition timing and exhaust systems. Other areas ofThe development of a closed-loop, automated engine
future research include tuning for dynamic conditionstuning system is demonstrated and the potential to pro-
duce consistent results, signi cant time savings and such as acceleration, expansion to include fuel usage
D15501 © IMechE 2002Proc Instn Mech Engrs Vol 216 Part D: J A utomobile Engineering
849AUTOMATED TUNING OF AN ENGINE MANAGEMENT UNIT
of spark ignition automotive engines. IEEE Mag., 1990,
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Automotive Electronics, London, 12 –15 October 1987.
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2 Scotson, P. G. and Wellstead, P. E. Self-tuning optimization
D15501 © IMechE 2002 Proc Instn Mech Eng rs Vol 21 6 Part D: J A utomobile Engineering
... Using classic M(n) function description method [1], we have problems with modern engines torque characteristics. Characteristics are not monotonic – resonant phenomena are noticeable in intake and exhaust manifolds [5]. The increase of description polynomial order doesn’t give better results [3], so we decided to use a classic method for torque function description and we were trying to describe consisted deflections using .urje ...
... It is impossible to formalize summarized M(ln(n) curve, using second or third order polynomials, so we returned to the method offered in the work [3] – to divide the whole coefficient b variation interval into three zones: working, intermediate and engine braking. Analyzing braking characteristics [5,6], we noticed, that the use of the analogy method for their description is completely answering the purpose, and summarized characteristic can be designed making elementary shifts in logarithmic coordinates without vertical correction. That’s why we pay more attention to regime formalization analysis. ...
... hicle. Besides, the extra equipment is necessary for engine load security in high revs zone, when coefficient β becomes less than 0,3 [2,5]. Positions of intake manifold valve were chosen insomuch, that the analogy method could be used, e.i. ...
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The original data for the evaluation of vehicle motion dynamics is external characteristic of its engine, which consists of three parameters: torque, power and specific fuel consumption. It is very important to have the dependences of these characteristics on revs for various engine load cases, creating a vehicle model under real motion conditions. Load cases are defined by a load coefficient. Car-makers usually don’t declare full engine external characteristics, which overtake all load coefficient variation interval. The purpose of this article is to research, how to get full description of engine torque function without its full data. The analogy method, which is used in polymers and composites mechanics, was employed for the description of a torque function. The method is based on the creation of summarized characteristic, making horizontal and vertical shifts of torque dependences. From the curve it is possible to get a proper characteristic at a chosen load coefficient.
... Using classic M(n) function description method [1], we have problems with modern engines torque characteristics. Characteristics are not monotonic resonant phenomena are noticeable in intake and exhaust manifolds [5]. The increase of description polynomial order doesnt give better results [3], so we decided to use a classic method for torque function description and we were trying to describe consisted deflections using .urje ...
... It is impossible to formalize summarized M(ln(n) curve, using second or third order polynomials, so we returned to the method offered in the work [3] to divide the whole coefficient b variation interval into three zones: working, intermediate and engine braking. Analyzing braking characteristics [5,6], we noticed, that the use of the analogy method for their description is completely answering the purpose, and summarized characteristic can be designed making elementary shifts in logarithmic coordinates without vertical correction. Thats why we pay more attention to regime formalization analysis. ...
... hicle. Besides, the extra equipment is necessary for engine load security in high revs zone, when coefficient β becomes less than 0,3 [2,5]. Positions of intake manifold valve were chosen insomuch, that the analogy method could be used, e.i. ...
Article
Full-text available
The original data for the evaluation of vehicle motion dynamics is external characteristic of its engine, which consists of three parameters: torque, power and specific fuel consumption. It is very important to have the dependences of these characteristics on revs for various engine load cases, creating a vehicle model under real motion conditions. Load cases are defined by a load coefficient. Car‐makers usually don't declare full engine external characteristics, which overtake all load coefficient variation interval. The purpose of this article is to research, how to get full description of engine torque function without its full data. The analogy method, which is used in polymers and composites mechanics, was employed for the description of a torque function. The method is based on the creation of summarized characteristic, making horizontal and vertical shifts of torque dependences. From the curve it is possible to get a proper characteristic at a chosen load coefficient. First Published Online: 27 Oct 2010
... To achieve this, the engine management unit (EMU) automatically deactivates the operating cylinders. For example, during acceleration where the entire engine HP is required, all six cylinders in a V6 engine are employed to provide maximum amount of power; however, once the target cruising speed is reached and the load on the engine decreases, EMU deactivates three cylinders from the firing sequence (Hardie et al., 2002). Practically, it is proved that the VDE system can save up to a quarter of the gas used in normal operating mode of V6 and V8 vehicles (Jackson and Jones, 1976). ...
Article
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This study introduces the concept of smart materials, namely magnetorheological (MR) fluids, to the design of automotive engine isolation systems. Hydraulic bushings and mounts are widely used in the automobile industry to isolate the engine and chassis from each other. The simplicity and low cost associated with these types of bushing, in addition to their dual frequency response characteristics, are the main reasons for their industrial popularity. Recently with the introduction of variable displacement engines (VDE), the conventional bushings have reached their performance limits. A more versatile isolator is therefore required to handle the additional vibration and disturbances in VDE, associated with the change in the engine displacement whenever the automobile does not use its full displacement capacity for maintaining the desired speed. The realization is that the appropriate isolator should be half as stiff in the operating frequency range of the three cylinder mode of the engine. In addition, in the full cylinder mode the isolator must maintain the performance levels comparable to existing conventional products.
... For example, when accelerating all six cylinders in a V6 engine should be firing to provide the maximum amount of power; however, once the target cruising speed is met and the load on the engine decreases the engine management unit (EMU) may take any given 3 cylinders out of the firing sequence (Hardie et al., 2002). Jackson and Jones (1976) discovered over 25 years ago that this technique could save a quarter of the gas used in a V16 cylinder engine using 50% of the cylinders, also noting that they experience torsional vibrations when switching to 50% mode requiring a special torsional analysis. ...
Article
The purpose of this work is to design a semi-active magnetorheological (MR) hydraulic bushing. The semi-active bushing is intended to be used to isolate a cylinder deactivating engine. Cylinder deactivation causes high transient torsional loading in addition to changing the magnitude and mode of engine vibrations requiring an adaptive or controllable isolator. Practical and simple semi-active control strategies are inspired by investigating the optimization of linear and slightly cubic nonlinear single degree of freedom isolators. Experimental verification of the optimization technique, which minimizes the root mean square (RMS) of engine acceleration frequency response and RMS of the force transmitted frequency response, shows that this method can be implemented on real linear systems to isolate the engine from harmonic inputs. This optimization technique is also applied to tune selected model parameters of existing two degree of freedom hydraulic bushings. This thesis also details the development of a MR hydraulic bushing. The MR bushing design retrofits an existing bushing with a pressure driven flow mode valve on the inertia track. A new efficient valve design is selected and developed for the application. The MR hydraulic bushing is designed, mathematically modeled, and numerically simulated. The simulation results show that the MR bushing tends to increase the low frequency dynamic stiffness magnitude while simultaneously decreasing the phase. The next stage of the project is fabrication and testing of the semi-active bushing. The performance of the manufactured MR bushing is tested on a base excitation apparatus. Varying the current input to the MR valve was found to have a small effect on the response of the suspended mass. The results are in agreement with the effects demonstrated by the dynamic stiffness numerical simulation. "A thesis presented to the University of Waterloo in fulfillment of the thesis requirement for the degree of Master of Applied Science in Mechanical Engineering. Thesis (M.A.Sc.)--University of Waterloo, 2005. Includes bibliographical references (p. 120-125). Available in PDF format. System requirements: Internet connectivity and World Wide Web browser. Adobe Acrobat reader required to view and print files. Mode of access: World Wide Web.
Conference Paper
This paper outlines the development of an active hydraulic bushing system for the Multi Displacement System (MDS) Engine isolation problems. The prior art research effort on engine mounts and bushings has so far focused on the improvement of the mount dynamic stiffness properties. The optimum dynamic stiffness and damping of the engine bushings is both frequency and amplitude dependent. While these systems are available commercially, they have many limitations, particularly for new vehicle models and new engine generations such as MDS engines. A suitable isolator for an MDS engine should be half as stiff in the operating frequency range of the engine (5-70 Hz) in MDS mode, while showing the same performance as conventional hydraulic bushings in normal engine operations. Passive hydraulic bushings are not capable of meeting the isolation requirements discussed for the MDS engines because they are not adjustable. There are different parameters which contribute to the dynamic stiffness response of a hydraulic bushing. Some of those parameters are defined by passive components such as rubber stiffness and damping. However, other parameters such as the pressure inside the bushing can be altered actively. The mathematical model of a conventional hydraulic bushing is given in this paper. The model suggests that the pressure inside the bushing has a significant role in the dynamic stiffness response of the bushing. As a result, an additional pumping chamber is introduced as a solution. The pump is utilized to adjust the pressure inside the bushing based on the engine excitation frequency. This pump can be driven by proper actuators which can produce pressure differences in the frequency range of interest. The mechanical and mathematical model of such a system is derived using a simplified linear model. This technique enables the engine mount to adjust to the dynamic stiffness characteristics by applying a feedback signal to the actuator. The feedback signal to the actuator is also obtained using the mathematical model for many required cases yet adjustable for others. The response of the system is discussed in frequency domains. The simulation results prove that the additional pumping chamber can effectively be used to control the stiffness of the conventional hydraulic bushings.
Article
In this paper a novel active compliance chamber is designed, which can be used to control the dynamic stiffness of a common hydraulic bushing. This chamber offers a simple and cost-effective solution for the variable displacement engine (VDE) isolation problem. A VDE system requires a soft bushing for the half cylinder mode and a regular one for normal engine operations. A magnetic actuator is used to produce mechanical pulses. The linearisation technique is used for simplifying the nonlinear equation of motion. Different current sources are used to feed the magnetic actuator. The pressure inside the chamber follows linearly the current input signal. The phase shift in various current inputs is used in the form of the transfer functions to create the required pressure response pattern in the frequency domain. Since the dynamic stiffness of a conventional hydraulic bushing is a direct function of the pressure inside it, the active compliance chamber can be used to alter the pressure and consequently produce the required dynamic stiffness response. As a result, it can address the engine vibration problem for VDE situation.
Conference Paper
Today's situation in this field is characterized by three distinct development phases: First, the analysis and design of functionality. This type of work is typically performed in the laboratory, i.e. on the desk. Second, the implementation of a prototype system, realized by (semi)automatic code generation and followed by a test with a “Lab-car” or in a real vehicle. The third and final step comprises the calibration and fine-tuning of algorithms and their parameters, commonly done in a real car. However, there are some flaws associated with this approach. There is no support for multiple interconnected electronic control units. Automatic generation of code of production quality is still a challenging task. And there is a large gap between the properties of a virtual car and the behavior of the real vehicle. The latter is one reason why nowadays the adjustment of calibration parameters still needs to be done manually. In the future, the picture outlined above will change remarkably. Function development tools will be able to generate efficient and reliable software code automatically. Vehicle models will mimic the characteristics of the real object to an extent we cannot imagine today. And automated test without manual interference will unprecedented degree of optimization and quality throughout a complex network of electronic control units. Almost the entire development process will be shifted to the desk with no need for costly, risky, and error-prone experiments with prototype engines or vehicles
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The use of self-tuning control concepts applied to the adaptive optimization of spark ignition angles of an automotive engine is described. In particular, it is shown how the concepts of self-adaptive control theory can be modified to allow their use in a continuous updating of the spark-angle map as a function of load and speed. Used in this manner, the self-tuner can account for in-service changes in engine characteristics, changes due to variations of ambient and operational conditions. In addition, self-adaptation allows the spark-controller algorithm to tune itself, so that the factory-generated spark map is precisely matched to the exact nature of each individual engine. The basic theory of self-tuning optimizers (also known as extremum controllers) is outlined, and their performance features are discussed with particular reference to their implementation in adaptive spark-timing systems. It is shown that the self-tuning extremum controller can be made robust even when the signal-to-noise ratio is less than one.< >
The Internal Combustion Engine in Theory and tronic systems Automation and Test in Europe
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Self-tuning optimization D15501 © IMechE
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