=Paper=
{{Paper
|id=Vol-2387/20190141
|storemode=property
|title=Selecting a Rational Operation Mode of Mobile Power Unit Using Measuring and Control Complex
|pdfUrl=https://ceur-ws.org/Vol-2387/20190141.pdf
|volume=Vol-2387
|authors=Mykhailo Shuliak,Dmytro Klets,Yevhen Kalinin,Anton Kholodov
|dblpUrl=https://dblp.org/rec/conf/icteri/ShuliakKKK19
}}
==Selecting a Rational Operation Mode of Mobile Power Unit Using Measuring and Control Complex==
https://ceur-ws.org/Vol-2387/20190141.pdf
Selecting a Rational Operation Mode of Mobile Power
Unit Using Measuring and Control Complex
Mykhailo Shuliak1, Dmytro Klets2, Yevhen Kalinin1, Anton Kholodov2
1Kharkiv Petro Vasylenko National Technical University of Agriculture,44 Alchevskykh Str.,
Kharkiv, Ukraine
2Kharkiv National Automobile and Highway University, 25 Yaroslava Mudrogo Str., Kharkiv,
Ukraine
m.l.shulyak@gmail.com, d.m.klets@gmail.com
Abstract. Research goals and objectives: to increase efficiency and safety of
Mobile Power Unit operation mode using Information and Communication
Technology and Measuring and Control Complex.
Results of the research: The proposed algorithm made it possible to remove the
worst mode, namely the overload mode, almost at the initial stage of analysis,
and the nominal one dominates 1.5 times over the under load mode, both in
volume and in terms of the ellipsoid nucleus specific weight. This suggests that
the application of this algorithm is not inferior to the precision of the classical
analysis method. The methodology for selecting a rational operation mode has
been experimentally confirmed and can be used to rationally control the Mobile
Power Unit in the operation region.
Keywords: operation mode, mobile power unit, measuring and control com-
plex.
1 Introduction
The term mobile power unit (MPU) is adopted in connection with the use in the
transport industry of a large number of technical means for special purposes. For
MPU, it is typical to perform several operations, thereby changing the concept of their
classification as compared to vehicles. During MPU operation, there arise dynamic
loads, which destabilize the motion mode and cause oscillation of accelerations in a
three-dimensional space. Such fluctuations lead to higher energy consumption, reduce
the quality of the work performed and produce a detrimental effect on the operator.
Recently, in the area of mobile power unit (MPU) operation control, a clear trend
in using information systems used to track stochastic changes in dynamic parameters
is evidenced. One of the most promising ways is the use of systems that enable to
track the changes in the acceleration of the MPU during routine operation and give
recommendations as for the operation mode. In order to accurately determine the
dynamic parameters it is not sufficient to use in-built onboard systems, since the ap-
propriate algorithms were not embedded into their design parameters. Therefore, in
order to solve the problem in question, it is possible to additionally install the required
components of monitoring systems with embedded software, or to develop new soft-
ware for the on-board systems in use.
The purpose of the paper is to increase efficiency and safety of Mobile Power
Unit operation mode using ICT and Measuring and Control Complex.
The paper is organized as follows: part 2 describes related works on MPU; part 3
demonstrates parametric ellipsoid of the MPU operation; part 4 considers the system
algorithm; part 5 describes the Measuring and Control Complex development; part 6
describes the on-road experiment; the last part concludes.
2 Related Work
In work [1] it is proposed to present a vector of complete MPU acceleration in the
inertial coordinate system, using a hodograph (fig. 1).
Fig. 1. Partial fragment of steady MPU motion, characterized by a hodograph.
The hodograph of the vector of full acceleration shows the sequence of changes in the
value and position of vectors. When analyzing the fragment of stable running it can be
argued that the constructed vectors determine the region of MPU operation, where an
increase in the volume of the latter characterizes the growth in energy costs. Analysis
of the methods of the operation region approximation has revealed that it is most ac-
curately described by the surface of the second order (ellipsoid).
In work [2] an energy approach to estimating the dynamics and fuel economy of
cars that makes it possible to determine the interrelation between the consumption of
energy and the kinetic energy of the car is developed. Based on the obtained coeffi-
cients, it is possible to rank energy losses, as well as identify the ways to reduce them.
In work [3] the laws of change in the vehicle acceleration time at the existing step
transmission, when implementing the total traction force, boundary for the drive
wheels adhesion to the road, and during implementation of the proposed rational law
for acceleration control are established.
The vehicle detection process plays the key role in determining the success of in-
telligent transport management system solutions [4]. The risk of this forecast, predict-
ed by the neural network, is "very low", we can definitely trust the forecast, and the
risk is calculated by the equation of the neuroregression "low", which indicates that
we can trust the forecast, but with caution and further monitoring [5].
In work [6] it is analyzed the four-wheel independent steering vehicle dynamic
characteristics and the influence of linear quadratic regulator control parameters on
control performance, a linear quadratic regulator control parameter adjustment strate-
gy based on vehicle steering state is proposed to achieve the adaptive adjustment of
linear quadratic regulator control parameters. In work [7] it is declared the essential
novelty that distinguishes a new MPU from the standard tractors through the usage of
complex multipurpose operations. The implementation of automatic weighing sys-
tems [8] will affect both the improvement of road safety and indirectly limit the num-
ber of road users moving by overloaded vehicles.
3 Parametric Ellipsoid of the MPU Operation
To calculate the resulting volume, we’ll specify the ellipsoid (fig. 2) equation [1]:
x M 2
y M y
2
z M 2
1,
a M
x z
(1)
a x max
M x
2
y max y
2
a z max
M z
2
where а is the maximum value of projections of the vector of full acceleration on
i max
the axis of the applicator, in terms of the mean square deviation of the sam-
ple а 3 , M is the mathematical expectation for the corresponding axis.
i max i i
Fig. 2. Parametric ellipsoid of the MPU operation
By studying the properties of the finite character structures, such as the deterministic
signal obtained experimentally, as well as the infinite structures of technological op-
eration, which involve the discontinuity of processes in them or the separation of
constituent elements, it is opportune to apply the elements of the theory of sets.
The range of operation, approximated by the ellipsoid, is given by the set of ends
of the radius of the vector of full acceleration established from the center of mass of
the MPU Фа а1 , a 2 , a3 ...a n .
The potency of this set is limited by the time of the experiment conducted t and the
frequency of the measuring complex survey t , М N t t .
The scope of minimum deviations of acceleration is a subset of the set Ф – a
T Ф :
op t a
T a Ф a sgn 0,5,
opt n a n
(2)
The set To p t is the nucleus of the ellipsoid, and its specific gravity is the criterion for
assessing the operation mode. It is possible to determine it on the basis of statistical
processing:
n
p , t
(3)
N
T
where n is the number of acceleration values belonging to the set a n To p t .
t
Since the spherical form of the nucleus with a center at the origin of coordinates is
regarded as an ideal case being approached, the nucleus can change its position in the
middle of the ellipsoid during statistical processing. Analysis of the nucleus position
will make it possible to determine which direction the maximum energy losses are
due to, as well as identify the methods for reducing them.
One should determine the areas where the displacement of the nucleus can be ad-
mitted. The value of projections on the axis of ordinates is determined by the nature
of technological operation: the forces causing the deviation in direction; the frequency
of the path of motion adjustment; application of variable-mass machines, etc. In the
absence of the possibility to eliminate the displacement of the nucleus, this is allowed
for a particular technological operation and the given MPU in comparative studies.
The greatest impact on the value of the acceleration projection on the axis of the
applicate has the relief of the agricultural background, both macro and micro inequali-
ties have a stochastic character due to the given displacement of the nucleus for this
axis is allowed, however, the magnitude is not greater than М . z
Any displacement of the nucleus relative to the origin of coordinates along the ab-
scissa will give a constant increase or decrease in velocity, which will characterize the
mode of motion as a transient one, so the displacement along the axis of abscissa is
not allowed.
4 Algorithm
Based on the presented method of analysis, it is possible to find a rational mode of the
MPU operation, which with other factors being equal will be characterized by less
energy losses and improved quality of the technological operation implementation.
The initial question to be answered is the allowable range of changes in the param-
eters responsible for the efficiency of the technological operation (hereinafter the
initial conditions).
It is possible to implement the required speed of the MPU by engaging several
transmission gears given the possibility of using partial speed modes of engine opera-
tion. The selection of a rational mode according to the classical methods in this case is
reduced to the definition of the minimum fuel consumption and the maximum engine
load. Based on the proposed method of analysis of the MPU functioning it is possible
to determine a rational mode, avoiding the loss of quality over a shorter period of
time.
To implement the method in question, one must follow the analysis algorithm
(fig. 3). Let’s assume that the operation of the MPU is allowed in different k modes
according to the initial conditions. First, the valid displacement area of the real nucle-
us is selected for all modes, providing the minimum distance from the normal
one T ' o p t To p t .
Fig. 3. Algorithm for selecting the operation mode, based on the analysis of the area of MPU
operation
To speed up the analysis, the ones that do not match this area for the rest are then
eliminated. We build an ellipsoid of functioning and select the modes with the lowest
volume volE min . After obtaining the modes with the lowest volumes, it is nec-
k
essary to determine those in which the distribution a Ф is subject to the following
n a
condition:
a T ' a P ,
n o pt n
(4)
The mode with the highest specific gravity p is the most appropriate for the analyzed
T
series. It should be noted that if several modes have been identified, the share of the
latter equals to p p p . The mode with a minimal shift of the actual nucleus is
T1 T 2 Ti
given the selection priority.
The proposed algorithm will enable to significantly accelerate the analysis of ex-
perimental data and select the mode most closely related to the rational one, taking
into account both the elements of the classical traction method and the dynamic char-
acteristics of the MPU. Taking into account the additional energy losses and ways for
their reduction, new perspectives for improving the efficiency of MPU application in
carrying out transport operations are created.
5 Measuring and Control Complex Development
Implementation of the given algorithm requires the development of measuring and
control complex. To achieve the goal set, one needs to accomplish the following
tasks:
the elements of the complex should provide comprehensive information for the
study of functional stability generalized parameters;
the measurement and control complex is supposed to provide reliable information
for further analysis, which requires systems duplication;
the number of elements of the complex must be substantiated and tend to the min-
imum necessary;
the software for monitoring, filtering and analyzing the experimental data obtained
is to consume the minimum of allocated resources (a constituent element required
for applying a complex with low computing power systems);
the installation and calibration of the measuring elements of the complex in ques-
tion should not take up more than 30 minutes;
when selecting a warehouse for storing the measuring equipment it is necessary to
use such equipment, which application for scientific purposes leaves no doubt in
the world experience;
synchronization of the experimental data flow obtained through various elements
of the complex.
The proposed complex (fig. 4) should ensure the implementation of the control al-
gorithm through the use of high-sensitive sensors and related software. One of the
most daunting problems to be solved is the synthesis of measuring sensors, which
work relies on the application of fundamentally dissimilar physical effects (induction,
electromagnetic oscillations, and radio waves).
Fig. 4. Diagnostic complex of monitoring the dynamic parameters of mobile energy resources
An individual noise spectrum is inherent for each of these sensors, so when applying
the software, it is required to use filtration algorithms that enable to eliminate this
shortcoming.
The world experience proves that one of the best options for solving this problem
is the use of duplicate monitoring systems. When choosing duplication systems, one
should remember that the use of a large number of measuring equipment will compli-
cate the conduct of experiments and reduce the effectiveness of the latter; therefore, it
is required to apply the necessary minimum of devices. When selecting the devices,
one needs to be guided by the following rule: at least two duplicate systems should be
applied while determining the generalized parameters (acceleration, speed, hitch-
ing)of functional stability. For instance, to determine the acceleration, in addition to
the accelerometer, one should apply either a radar or a lidar.
Application of such a principle of kitting the measuring and control complex will
make it possible, subject to the appropriate filtering of the data received, to adjust the
operating modes of the MPU, based on the control algorithm.
The task set is solved due to the fact that the diagnostic complex used for monitor-
ing the dynamic parameters of traction vehicles includes measuring sensors, a data
collection and synchronization system, software for filtering and analysis of experi-
mental studies, which differs in that the measurement of the actual speed of motion
occurs with the use of a coherent radar performed through the agency of a homodyne
circuit, which design provides for the possibility of changing the angle of inclination
of the transmitting antenna, and for measuring the propulsion sensor rotation they use
a sensor based on the Hall effect that is simply mounted on any type of MPU due to a
unified mounting system based on neodymium magnets, in addition to the filters
mounted in the sensors proper, there is added a filtering system, programmed to the
appropriate sensitivity, according to the consumer’s requirements and advanced soft-
ware, enabling detailed comparison of the selected operating modes by the criterion of
energy saving in real time.
Establishing the actual speed of motion is performed using a specific range radar.
The corresponding frequencies are emitted by the use of the generator based on the
LPD 4 and the ferrite circulator 2 (FC), and the signal reflected from the resistive
surface is received by antenna 1 (A), then the Doppler frequency 5 (MAP) is ampli-
fied with the use of the mixer 3 (M), the processed signal falls into the registration
device of speed 7 (RDS). The radar has an autonomous power supply 6 (APS) suffi-
cient in capacity for conducting long-term experiments.
To investigate the power dynamic parameters, they use inertial acceleration sensors
30 (AS) that are located at arbitrary points of the MPU frame elements, provided that
at least two sensors are installed on each element. The obtained data are converted to
10 (C) and amplified by 11 (A) using the frequency generator 8 (FG) and the clock
generator 9 (CG). The amplified signal then goes to the low-pass filter 12 (MF)
mounted in the board and adjusted using the temperature compensator device 13
(TCD) for each of the main coordinate axes. The sensor exhibits the property of se-
lecting the sensitivity mode 28 (SM) and the recording device 14 (RD). The system of
self-testing and correction of sensor position 29 (LB-EEPROM) is provided for.
The wheel rotation is determined using the Hall sensor 27 (HS), fed by the power
from the autonomous source 24 (APS) through a double-current source 25 (DPS).
Controller 26 (CONT) controls the operation of the sensor, the received signal enters
the receiver-limiter 23 (R-L), then it is filtered from the available fluctuation errors 22
FFS and recoded in the recording device 21 (RDR) of the wheel rotation.
Further, processing and synchronization of experimental data is performed by spe-
cial software. Experimental data supplied by registration devices is synchronized at a
constant time and checked for compliance with 15 (SD). Next, in the block of external
filtration 16 (BEF), where filter kits are provided for each of the received signals, the
amplitude-frequency spectra necessary for further study are isolated. The processed
signals fall into the analytical-calculation block 17 (ACB) where the mathematical
apparatus carries out the statistical and spectral estimation and detects the inconsist-
encies of signals, in the presence of such ARB re-accesses the SD and conducts filter-
ing along with other settings. The analyzed experiment is stored in data bank 18 (DB)
on the hard disk. The visual representation of the parameters that the diagnostic com-
plex captures is carried out using the «Vehicle Dynamics v. 3.9.2 » program 20 (VD)
on the information display 19 (ID) of the laptop or tablet. The software of the com-
plex has the property of analyzing the obtained data, both directly during the research
in real time, and to reproduce the experiment in laboratory conditions, based on the
data supplied by registration devices.
The general view of the Vehicle Dynamics v. 3.9.2 software interface is shown in
Fig. 5.
Fig. 5. The software interface of the recording and control complex
The application of the functional parameter monitoring program allows to visually
analyze the selected modes and, if necessary, to adjust the initial data, or to make
conclusions regarding the aggregation of the MPU. The results of each experiment are
recorded into the data bank and stored for the purpose of obtaining a statistical data
sample, which will enable to provide recommendations for the MPU series.
Thus, the offered diagnostic complex of monitoring the dynamic parameters of
traction vehicles makes it possible to investigate the changes of the MPU operation
parameters with high precision, in real time, as well as select the rational functioning
modes.
6 Experiment
The experiment was carried out on a mobile power special purpose unit, namely
KrAZ 5233. The experiment methodology and the requirements for the installation of
measuring equipment are described in detail in work [1].
To provide the experimental confirmation of the relationship between the scale of
fluctuations of full acceleration of the MPU as well as the mode of engine operation
of the latter, it is required to simulate the load in field conditions.
The load of the engine is specified at 55 – 60%, 85 – 95% and 105 – 115% of the
nominal value (the required towed load is selected using the classical traction charac-
teristics, and fixed with a strain gauge link). With stabilization of speed (achievement
of the steady state of motion) by making use of the registration complex the following
parameters are fixed: the components of the full acceleration vector, the actual speed
of motion, the engine rpm speed (to obtain the theoretical speed), fuel consumption,
traction load, the temperature of both the sensors and the environment, as well as the
pressure.
Upon completion of basic research, analysis of the experimental data is obtained
using the operating mode control algorithm. It is theoretically substantiated that the
rational mode of the MPU operation must correspond to the minimal dynamic losses
of the unit. That is, the control algorithm is to select the second series of experiments
as the best one from the energy saving position since the engine is loaded close to the
nominal value.
On the basis of statistical processing we construct an operation ellipsoid for the
modes analyzed in Fig. 6.
a) engine load b) engine overload c) nominal mode
Fig. 6. Ellipsoid of operation
The sequence proposed in the algorithm requires setting the permissible shift region
of the actual nucleus, the worst possible mode is the engine overload, the actual nu-
cleus of the latter is outside the permissible range. Next, we determine the vol (Ek)
volume of each of the ellipsoids: the mode of under loading vol (Ek) = 147,2
(Fig. 6, а), the overload mode vol (Ek) = 183,5 (Fig. 6 b), the nominal mode vol(Ek) =
97,76 (Fig. 6 c). That is, the control algorithm chose the nominal mode as being the
most appropriate one according to the two evaluation criteria: the volume of operation
ellipsoid for the nominal mode is 1.5 and 1.8 times smaller than the corresponding
ellipsoids of the under load and overload modes; the value of the specific weight of
the nucleus also confirms the nominal mode to be the best one of the series.
7 Conclusions and Outlook
The methodology for selecting a rational operation mode has been experimentally
confirmed and can be used to rationally control the MPU in the operation region.
The proposed algorithm made it possible to remove the worst mode, namely the
overload mode, almost at the initial stage of analysis, and the nominal one dominates
1.5 times over the under load mode, both in volume and in terms of the ellipsoid nu-
cleus specific weight. This suggests that the application of this algorithm is not inferi-
or to the precision of the classical analysis method.
References
1. Shulyak, M. Formation of functional tractors stability for transport works. Kharkiv Na-
tional Automobile and Highway University: Kharkiv, (2017).
2. Podrigalo, M. (2017). Creation of the energy approach for estimating automobile dynamics
and fuel efficiency. In: Eastern-European Journal of Enterprise Technologies, vol. 5/7 (89),
Kharkiv, pp. 58-64.
3. Podrigalo M. (2018). Synthesis of energyefficient acceleration control law of automobile.
Eastern-European Journal Of Enterprise Technologies, vol. 1/7(91), Kharkiv, pp. 62-70.
4. Markevicius, V (2016) Dynamic Vehicle Detection via the Use of Magnetic Field Sensors.
Sensors, 16 (1), 78.
5. Nemchenko D,Kobets V, Potravka L (2018) Neuro-Fuzzy Model of Development Fore-
casting and Effective Agrarian Sector Transformations of Ukraine. ICT in Education, Re-
search and Industrial Applications. Integration, Harmonization and Knowledge Transfer,
Kyiv, 16 p.
6. Linlin Gao (2015) Genetic algorithm–based varying parameter linear quadratic regulator
control for four-wheel independent steering vehicle. Advances in Mechanical Engineering,
Vol. 7 (11), 1–14.
7. Lipkovich, E. (2013) Principles of efficiency estimation technique of machine-process
units based on the fifth-generation mobile utilities. Don State Technical University; 13(7-
8), 106-116.
8. Sarnecki, R (2018) Traceable calibration of automatic weighing instruments operating in
dynamic mode. MATEC Web Conf. 182. doi:10.1051/matecconf/201818202005.