STUDY ON TILLAGE RESISTANCE AND ENERGY CONSUMPTION OF A PLAIN STRAIGHT ROTARY BLADE FOR STRIP TILLAGE

ABSTRACT

The issue of reducing tillage resistance and lowering energy consumption has become increasingly relevant. Strip tillage has a positive impact on soil protection and energy consumption reduction. This study analysed the tillage resistance components of rotary blades and their relationship with operating parameters and developed a mathematical relationship between tillage resistance and energy consumption (power and fuel consumption). We summarised tillage resistance into three parts: air resistance, lateral rotational friction resistance (divided into horizontal and vertical resistance), and shear force. By theoretical analysis and coupled simulation tests 11 (DEM-CFD), we obtained an air resistance, lateral rotational friction, and shear force of 0.0883 N, 97.21 N, and 893.496 N, respectively, accounting for 0.01%, 9.81%, and 90.18% of tillage resistance. Meanwhile, we found that horizontal resistance decreased linearly with the increase of angular speed, which was the opposite of vertical resistance. Horizontal and vertical resistance increased linearly with the increase in contact area. Shear force increased significantly with angular speed. Fuel consumption in the field test and tillage resistance and power consumption in coupled simulation was formed to build a correspondence point, and a mathematical relationship between tillage resistance, torque, and power and fuel consumption was established.

tillage resistance; power consumption; fuel consumption; torque; DEM-CFD

INTRODUCTION

Strip tillage, the procedure of planting seed into narrow furrows and limiting soil inversion, is relatively new, having been evaluated for the first time in the early 1990s ( Celik et al., 2013 ). This operation mode confines tillage to a narrow strip where the crop will be planted ( Luna & Staben, 2002 ) and divides the cropping system into two distinct adjacent zones: tilled and untilled ( Lowry et al., 2021) . Within the crop row, tillage can provide a finer seedbed ( Licht & Al-Kaisi, 2005) , while the untilled zone between rows maintains no-tilled states. It combines the benefits of both conservation agriculture and conventional tillage. Compared to conventional tillage, strip tillage offers greater crop yields at reduced production costs and better soil erosion control ( Laufer & Koch, 2017) . The tilled zone enhances soil water evaporation and seedbed warming, while minimising total soil disturbance ( Licht & Al-Kaisi, 2005) . It offers a potential solution to late seed emergence due to cool and wet soil conditions associated with no tillage ( Turmel et al., 2015) . Strip tillage is preferable for proper seedbed preparation compared to direct drilling because it creases favourable conditions for seed germination; in comparison with full tillage, it reduces the working time and fuel and production costs, protects soil, and is ecologically benign ( Vaitauskienė et al., 2017) .

The improvement of operational efficiency has been a subject of considerable research. Operation efficiency can be improved by reducing tillage resistance and lowering energy consumption. The rotary blade is the core soil-engaging tool of the soil preparation machine for strip tillage ( Saimbhi et al., 2004 ). Tillage resistance, the most important indicator to assess the operational efficiency of tools for soil cultivation in plant production has been one of the crucial issues for rotary blades in the first two decades of the 21st century ( Ahmadi, 2018 ; Asl & Singh, 2009 ; Tong et al., 2015) . The main research results during this period include the proposed method of resistance reduction for contact parts and the investigation of the relationship between resistance and its affecting factors. Vibration resistance reduction ( Shahgoli et al., 2009, 20 , 2010 ), bionic resistance reduction ( Guan et al., 2022 ; Yang et al., 2018 ; Zhang et al., 2014) , layered resistance reduction ( Kasisira & du Plessis, 2006) , structural design resistance reduction ( Kichler et al., 2011) , surface coating resistance reduction ( Foley et al., 1984 ; Guan et al., 2021) , etc., and the relationship between indexes and factors under each method theory is constantly evolving. Reece (1965) was the first to suggest the general earth pressure model, which has since been widely used by almost all researchers attempting to predict soil cutting resistance. McKyes & Desir (1984) used the equilibrium mechanics technique to describe soil resistance as a function of the failure angle ¦Â, soil characteristics, and tool parameters. Zhang & Kushwaha (1995) considered soil cutting resistance to be dependent on the failure shape and pattern. The problems of identification of the working resistance of soil-engaging tools in all directions have been the subject of many studies. Kogut et al. (2016) investigated horizontal, longitudinal, and vertical components of working resistance of a compact disc harrow. In the analysis of the resistance mechanism of the rotary blade, the pressure and cutting force of the component cutting into the soil are the main objects of analysis, ignoring the resistance generated by other parts of the component. There is no perfect system of resistance for all parts of the soil-engaging components. In the rotary operation process, blade rotation and the surrounding air form friction, impact; blade lateral extrusion by the soil; blade and soil to form shear. These constitute the tillage resistance of the rotary blade. Therefore, the construction of a complete set of rotary blade tillage resistance theories will make the design and research of rotary blades more clear.

Energy, as power and fuel consumption, is proportional to tillage resistance under cultivation. Soil tillage resistance is too large and will inevitably lead to high energy consumption, affecting the cost of agricultural production, intensifying the loss of machinery, and reducing operational efficiency. Thus, energy consumption has become an important indicator to evaluate the merits of tillage tools. Therefore, carrying out research on energy consumption in agricultural production is an effective means to promote the high quality and efficient development of agricultural mechanisation and has important practical value and significance for sustainable agricultural development. Part of the energy consumption is used to overcome tillage resistance. Numerous studies have measured the draught, power requirement, and fuel consumption of tillage equipment ( Al-Janobi, 2000 ; Sahu & Raheman, 2006 ; Serrano et al., 2003, 20 , 2007 ). Predicting tractor fuel consumption may result in more prudent tractor management choices. Ahmadi (2017) constructed rotational power prediction equations based on the classical laws of mechanics with an average error of 16% and 5% compared to the results of Asl & Singh (2009) and Chertkiattipol & Niyamapa (2010) , respectively. Matin et al. (2015) analysed conventional, half-width, and straight-edge rotary blades at different rotational speeds for torque, power, and energy consumption characteristics at different rotational speeds, pointing out that peak torque occurs further back in phase as the rotational speed increases. In summary, most of the existing literature is based on theoretical predictions of energy consumption or studies of the effects of different parameters on energy consumption. A mathematical relationship model between tillage resistance, power, and fuel consumption has not been established to provide a basis for the study of resistance and energy consumption reduction.

The discrete element approach has made significant strides in the area of soil cultivation in recent years, and discrete element simulation modelling has been used to investigate the interaction between soil and equipment ( Azimi-Nejadian et al., 2022 ; Li et al., 2014 ; Mak & Chen, 2015 ). Computational fluid dynamics (CFD) has also become a popular and highly valued engineering technology among agricultural researchers for simulating fluid flow, describing flow fields, and identifying fluid phase mechanisms for sustainable development (Lee et al., 2022; Teitel et al., 2022 ; Zhao et al., 2012) . To describe detailed dynamic information, including particle velocity, instantaneous forces acting on each particle, airflow, and interactions between gas and solid phases, discrete element method and computational fluid dynamics (DEM-CFD) techniques have been coupled ( Chen et al., 2022 ; Kong et al., 2022 ; Sakai & Koshizuka, 2009) . In this study, the purpose of forming a flow field by simulating the high-speed rotation of blades in the EDEM can be achieved by the DEM-CFD coupling method. In this way, the airflow can be considered in the discrete element simulation to make the simulation results more realistic.

Of the two types of blades applied in strip rototillers, plain straight blades are more compatible with conservation tillage to reduce soil disturbance than bent blades that cause excessive soil loss in the furrow zone ( Matin et al., 2021 ). The plain straight blade, which has only a lengthwise section ( Matin et al., 2014 ), has been adopted by several researchers ( Matin et al., 2015 , 2016 ) to replace traditional blades because, under certain circumstances, this blade causes less soil disturbance and educes fuel consumption. This study analysed the composition of tillage resistance and its relationship with operating parameters, and established a mathematical relationship model between tillage resistance, torque, and fuel consumption to provide a corresponding reference for the study of resistance and consumption reduction of driving rotary blades.

MATERIAL AND METHODS

Test scheme of tillage resistance

A plain straight rotary blade used for strip tillage was evaluated in this study, as shown in Fig. 1a . Based on the field operation conditions of the plain straight rotary blade, the causes of its tillage resistance were meticulously divided and studied; its force state is shown in Fig. 1b . Tillage resistance of the rotary blade was generated by three parts: air resistance, lateral angular friction resistance (divided into lateral horizontal resistance and vertical resistance), and shear force.

FIGURE 1
The plain straight rotary blade used in this research institute.

Friction and impact were formed by blade rotation and air; the blade was laterally squeezed by soil; shearing was produced by the cutting of the blade against the soil. The friction and impact between the air and the blade were defined as air resistance ( f ₁). The lateral extrusion of the blade was defined as the lateral pressure ( X ). The resistance formed by the lateral pressure was defined as the horizontal resistance ( Y ) and the vertical resistance ( Z ), both of which constituted the lateral rotational friction resistance of the plain straight rotary operation. The shear of the blade edge was defined as the shear force ( F_t ), and these three parts constitute the tillage resistance of the rotary blade.

Air resistance

The air resistance was mainly the interaction with the air during the high-speed rotation of the rotary blade. During operation, air resistance was calculated as follows ( Kravchenko et al., 2019 ):

$f_1=\frac{1}{2}C\rho S{v}^2$ (1)

where:

f₁ is air resistance, N;

C is air resistance coefficient, C =0.3;

ρ is air density, kg^.m^-3, ρ =1.293 kg^.m^-3;

S is windward area of the object, mm²,

v is the relative velocity of an object to air, m^.s^-1.

Therefore, air resistance was jointly influenced by the air resistance coefficient, air density, relative velocity, and target area. Combined with the blade size, the target area S was 5436 mm2. The relative velocity v between the object and air was the average linear velocity of blade rotation. The relative velocity of [ eq. (2) ] is given by:

$v=\omega R$ (2)

where:

ω is the angular speed of the rotary blade at the high output shaft position of tractor;

ω =75.36 rad^.s^-1 (i.e., tractor high-grade output shaft knife roller speed, 720 rpm),

R is the average radius, R =165 mm.

Therefore, the relative velocity of an object to air v was 12.4344 m^.s^-1, and the result was that the air resistance of the rotary blade was 0.0815 N.

Lateral rotational friction

During the soil cutting operation, the movement of the blade was idealised as a planar movement (with the tractor's translation accompanied by rotation around the rotor); therefore, the resulting lateral rotational friction was different from the planar sliding friction in the current study. The main operating parameters associated with the planar motion of the rotating blade were the rotational angular speed of the blade and the contact area with the soil and straw. To ensure the stability of the test environment, discrete element software EDEM 2018^TM was used to carry out the simulation test.

In the simulation test, to investigate the relationship between the lateral rotational friction and the angular speed of the blade in plane motion, the angular speed was simulated by setting the kinetic parameters of the blade. The contact area was changed by enlarging the blade model and shrinking the soil and straw models to achieve a change in contact area. To make the model in the experimental investigation more stable, this part of the soil and straw model was simplified to a soil bin model, requiring the moving parts to be able to achieve rotation and translation; thus, the blade model was idealised as an enlarged disc model, as shown in Fig. 2a .

FIGURE 2
Simulation model of tillage resistance in each part of the rotary blade.

The disc (500 mm in diameter) and soil bins of different cross-sectional area sizes were established. To avoid the disc model from moving without detaching from the soil bins, the soil bins were reduced in size and established with Y (horizontal) x Z (vertical) x X (lateral) of 60 x 60 x 60, 100 x 100 x 60, 120 x 120 x 60, and 150 x 150 x 60 mm³. The cross-sectional area of the soil bin was smaller than the area of the disc), so that when the disc model moved, the soil bin model was located on the side of the disc model.

The disc forward speed was set to 0.56 m^.s^-1. The disc angular speed was et to 56.52 and 75.36 rad^.s^-1 (tractor low-grade output shaft knife roller speed), as well as 0, 28, and 84 rad^.s^-1 (equal spacing single-factor probe). The starting position of each movement of the disc did not cause the soil to break away from the disc model. Each group of tests was repeated three times, and the average value was used for the evaluation criteria. The points with large differences were excluded.

The pressure in the X -axis and Y -axis directions was extracted in the post-processing module to obtain lateral pressure and horizontal resistance, respectively. Since the vertical resistance of the blade was in opposite directions during soil entry and exit, the vertical resistance of the disc in model exploration consisted of the resistance generated by the blade cutting into soil and leaving soil (separated by the centre line, rotating clockwise, and moving to the right), as shown in Fig. 3 , but the vertical resistance was mainly determined by the entry resistance because the disc was less extruded from the lateral soil particles during the exit process. The blade operation process involved both incoming and outgoing blades, and the overall incoming and outgoing resistance was obtained by extracting the resistance in the Z-axis direction in the post-processing module and summing them in reverse order.

FIGURE 3
Vertical resistance schematic.

Shear force

The shear force determines the operational effectiveness of the rotary blade. To avoid the influence of the resistance generated by other parts on the test results and the requirement to control the stability of the test environment, this part was implemented in the discrete element software. A single plain straight rotary blade model was established, and the blade and the adjustable holding flange were established as an assembly (blade edge and blade face were set as two parts), and only the resistance of the blade edge part was extracted, i.e., the shear force. The simulation model is shown in Fig. 2b , and the simulation parameters were the same as the soil parameter, as shown in Table 1 . The shear force of the blade edge in the x-axis direction was extracted in the post-processing module, and blade resistance was extracted to obtain the shear force and the tillage resistance of the individual blade operation process.

TABLE 1
Basic parameters of simulation model.

Parameter	Value
Tillage depth (mm)	80
Density of soil particel (kg.m-3)	2150
Density of 65Mn steel (kg.m-3)	0.3
Poisson¡¯s ratio of the soil particles	0.41
Poisson¡¯s ratio of 65Mn steel	0.3
Shear modulus of soil particels (MPa)	1.24x106
Shear modulus of 65Mn steel (MPa)	7.9x104
Coefficient of restitution betweeen soil and soil	0.6
Coefficient of rolling friction betweeen soil and soil	0.2
Coefficient of static friction betweeen soil and soil	0.3
Coefficient of restitution betweeen soil and 65Mn steel	0.6
Coefficient of rolling friction betweeen soil and 65Mn steel	0.05
Coefficient of static friction betweeen soil and 65Mn steel	0.6
Normal stiffness per unit area (N.m-1)	3.4x108
Shear stiffness per unit area (N.m-1)	1.5x108
Critical Normal stress (Pa)	200,000
Critical Shear stress (Pa)	68,000
Bonded disk radius (mm)	3.5

Tillage resistance

According to the actual field operation of the driven rotary blade, the blade assembly model was assembled as the rotary blade model in Fig. 2c , and the airflow-soil-blade coupling field with discrete elements and finite elements was established, and the operating parameters were consistent with the normal operation in the field, with a forward speed of 0.56 m^.s^-1 and an angular speed of 75.36 rad^.s^-1. The motion mode was set as rotation accompanied by translation, and the total motion time was 1 s. The air resistance, lateral rotational friction, and shear force data were extracted in the post-processing module of EDEM 2018^TM.

Energy consumption

Based on the coupled simulation test in section Tillage resistance , the dynamic tillage resistance and torque f rotary blade operation were extracted, and the results were output in the Analyst module of EDEM 2018^TM. The corresponding power consumption was calculated and output. The obtained data were imported into Matlab 2014a, and the mathematical relationship models of tillage resistance, torque, and power consumption were established.

The fuel consumption of rotary blade operation could not be obtained in the simulation test. To obtain fuel consumption, the field test was conducted at the research farm (44° 04' - 46° 40'N and 125° 42' - 130° 10'E ) of Northeast Agricultural University located in Heilongjiang Province of north-eastern China with an area of 0.4 hm² from November 3-6, 2020. This region has a typical temperate continental monsoon climate and shows the continental climate with a short hot period during summer and a long cold period during winter. The mean annual precipitation is 569.1 mm, and more than 60% of the precipitation occurs from June to September. The average annual potential evapotranspiration is 1009 mm (1971-2000) and markedly exceeds the annual precipitation. Soil in the northeast is typically black soil (Typic Hapludoll, USDA, 1993) with a clay loam texture containing 36.0% sand, 24.5% silt, and 39.5% clay ( Zhang et al., 2015) . The distance between two adjacent ridges was 650 mm. The average moisture content of soil was 20.4%.

A single test rotor, as shown in Fig. 2c , was fitted with twelve blades ( Fig. 1a ). A double row rotary tillage implement fitted with two rotor assemblies were pulled by a Benye 454 Tractor (Ningbo Benye Tractor & Automobile Manufacturing Co., Ltd.). The test measurements were power consumption and fuel consumption. The power consumption was measured using a power sensor, which was installed behind the engine output shaft. The fuel consumption was measured by a fuel consumption measuring instrument, which was installed between the tank and the bottom of the injection pump. The sensors and fuel consumption measuring instrument were connected to the GPS-10A motor vehicle multi-function tester, which was installed on the tractor. The forward travel and angular speed of the rotor were constant at 0.56 m^.s^-1 and 75.36 rad^.s^-1 (equivalent to the rotation speed of the high-grade output shaft of the tractor), respectively. During operation, the tractor's power consumption and fuel consumption were monitored by the motor vehicle multifunction tester. Each test area was divided into a test area of 10 m and a preparation area of 5 m. The machine entered the test area after reaching a smooth speed in the test preparation area, and each test was repeated three times, with the average value as the evaluation standard for each test. The results of power consumption and fuel consumption were the average values of the 10 m operation process. The data output for the steady state of the whole tractor operation process, and the data corresponding to the coupled simulation time step, was selected in the steady state for collation. Power consumption in the field test was compared with that in the coupled simulation test to further verify the reliability of the coupled simulation model and to establish a mathematical relationship between tillage resistance and torque in the coupled simulation test and fuel consumption in the field test.

Simulation model development and parameters

The contact model is an essential basis of the discrete element method, which in essence is the result of contact mechanics elastoplastic analysis of granular solids under quasi-static conditions. The analytical calculation of the contact model directly determines the magnitude of the forces and moments applied to the particles, which in turn determines the trajectory of the particles during the est. To improve the accuracy of the simulation results, different contact types must be established for different simulation objects.

To describe the cohesion of agricultural soils, in addition to the Hertz-Mindlin (no slip) contact model between soil particles ( Aleshin & Van Den Abeele, 2009 ; de Billy & Cohen Tenoudji, 2021 ; Wang et al., 2020) , considering the strong cohesion properties between loam and the mutual bonding between soils, the Hertz-Mindlin with Bonding contact model was added ( Shaikh et al., 2021 ; Su et al., 2020 ; Wang et al., 2019) . Virtual soil bin models were created using clay loam particles with an 8-mm radius (selected based on available computation time), and soil particles were randomly generated and settled to reach an equilibrium state in the soil bin.

A three-dimensional model of the rotary blade (with a density of 7865 kg^.m^-3) was established in Catia V5 software and then imported into the ICEM software for dynamic meshing, and the dynamic meshed rotary blade was imported into the EDEM 2018^TM software to establish the interaction model of the coupling field. The parameters to be determined for the soil-blade interaction model are shown in Table 1 .

While exploring tillage resistance, the soil-blade model was imported into the Fluent 17.0 module to establish the interaction between the blade and air. The working condition was turbulent, and the RNG k-ε turbulent flow energy dissipation rate model was used ( Ahn et al., 2018 ; Dai et al., 2022 ; Huo et al., 2022 ; Tiwary et al., 2022 ).

RESULTS AND DISCUSSION

Tilage resistance

Lateral rotational friction

The pressure in the X -axis directioin is extracted in the post-processing module, and the collated results are shown in Fig. 4 . Based on the simulation results, the lateral pressure of the disc model showed a linear decreasing trend with the increase of angular speed during operation. The fitting equation is shown in [ eq. (3) ]. The larger the angular speed, the stronger the dynamic effect of the material around the disc model, which dispersed the pressure effect of the material on the part.

FIGURE 4
Lateral pressure simulation test results.

The lateral pressure showed an increasing trend with the increase in the contact area. The fitting equation is shown in [ eq. (4) ]. As the contact area increased, the number of materials in contact increased.

$X=-1.1078\omega +95.251$ (3)

$X=0.0122A-90.608$ (4)

where:

X is the lateral pressure (N),

A is the contact area (mm²).

The resistance in the Y -axis direction is extracted in the post-processing module, and the collated results are shown in Fig. 5 . Based on the simulation results, the horizontal resistance generated by lateral extrusion of the disc model in the operation process showed a linear decreasing trend with the increase in the angular speed. The fitting equation is shown in [ eq. (5) ]. The larger the angular speed, the weaker the friction between the lateral material and the disc model (changed the friction coefficient), making this situation consistent with the previous literature ( Hu et al., 2014 ).

FIGURE 5
Horizontal resistance simulation test results.

Horizontal resistance with the increase in contact area showed an increasing trend. The fitting equation is shown in [ eq. (6) ]. As the contact area increased, the number of materials in contact increased, and the adhesion force between the material and the disc model became greater.

$Y=-1.1078\omega +95.251$ (5)

where:

Y denotes the horizontal resistance (N).

From the results of vertical resistance can be obtained, shown as Fig. 6 . The vertical resistance generated by the lateral extrusion of the disc model in the operation process with the increase in speed was a linear increasing trend. The fitting equation is shown in [ eq. (7) ]. The greater the angular speed, the stronger the friction between the lateral material and the disc model (which changed the friction coefficient); in this situation, vertical resistance with the increase in contact area showed an increasing trend. The fitting equation is shown in [ eq. (8) ]. As the contact area increased, the number of materials in contact increased, and the greater the adhesion between the material and the driving soil contact parts.

FIGURE 6
Simulation test results of vertical resistance.

$Y=0.0013A+0.7685$ (6)

where:

Z is the vertical resistance (N).

Shear force and tillage resistance

In this model, the average shear force of the cutting edge was 50.88 N at an angular speed of 56.52 rad^.s^-1 of the rotary blade, which was lower than 67.96 N at an angular speed of 75.36 rad^.s^-1, as shown in Fig. 7a . Therefore, increasing the angular speed increased the shear force because the impact between the cutting edge and soil particles was enhanced by increasing the angular speed. When the angular speed was 56.52 rad^.s^-1, the average tillage resistance of the rotary blade was 59.46 N, and the shear force accounted for 85.57% of the tillage resistance of the rotary blade. When the angular speed was 75.36 rad^.s^-1, the average tillage resistance of the rotary blade was 78.24 N, as shown in Fig. 7b . The shear force accounted for 86.86% of the tillage resistance; therefore, shear force was the main resistance during the operation of the rotary blade.

FIGURE 7
Simulation test results of shear force and tillage resistance.

From Fig. 7c , tillage resistance was 990.795 N. When the rotational angular speed of the blade was 75.36 rad^.s^-1, air resistance was 0.0883 N, accounting for 0.01% of tillage resistance, which was 7.7% different from the calculation results in section Air resistance . The lateral rotational friction was 97.21 N, accounting for 9.81% of tillage resistance, which was different from the sliding friction. The shear force was 893.496 N, accounting for 90.18% of tillage resistance, which was the main portion of tillage resistance and determined the operating effect of the rotary blade. Therefore, the shape and movement form of the rotary blade edge can be studied to reduce the shear force to reduce the tillage resistance.

Energy consumption

The tillage resistance, torque result output, and power consumption results of the rotary blade operation process in the coupled simulation test were shown in Fig. 8 .

FIGURE 8
Coupling simulation results.

The simulation data of the cut and the left soil bin of the coupled simulation test were excluded, and the output results of the stable operation section of the rotary blade were selected for analysis. The simulation results showed ( Fig. 8a and Fig. 8b ) that the tillage resistance of plain straight rotary blades in the stable phase was stable in the range of 1100-1500 N, and its torque was stable in the range of 210-285 N¡¤m. The power consumption of the blade in the coupled simulation test was output, and the results are shown in Fig. 8c . The power consumption calculation results showed that the power consumption was in the range of 15.8-24 kW during the stable phase.

Based on the coupled simulation test data, the spatial surface model of tillage resistance, torque, and power consumption was formed, as shown in Fig. 9 . Travel speed v and rotation speed n were 0.56 m^.s¹ and 720 rpm, respectively. The model showed that tillage resistance and torque jointly affected power consumption. Power consumption increased with the increase of tillage resistance and torque. The theoretical relationship between power consumption and tillage resistance and torque was as follows:

FIGURE 9
Model of tillage resistance and torque on power consumption.

$Z=1.19\omega +29.151$ (7)

where:

P is the power consumption of plain straight rotary blades, kW;

F is the tillage resistance of plain straight rotary blades, N,

M is the torque of plain straight rotary blades, N^.m.

Fig. 9 shows the theoretical relationship surface, which was a good fit. Only some data points were affected by the coupled simulation environment that was not in the theoretical range, but the overall fit was good. Therefore, the coupled simulation model represented the relationship between tillage resistance, torque, and power consumption more accurately.

The results of field tests are shown in Fig. 10 . The power consumption (range 14 to 30 kW) was less stable compared to the coupled simulation output (range 15.8 to 24 kW), which was due to more instability in the field and therefore resulted in higher fluctuations in the power consumption. The average power consumption of the rotary blade in the field test and the coupled simulation was 22.28 kW and 20.14 kW, respectively. Power consumption in the field test increased by 10.63% compared to the coupled simulation test, and there was a discrepancy between the two. However, the trend of power consumption in the coupled simulation and field test was basically the same ( Fig. 10a ), and this variability was within a reasonable range. Yu et al. (2009) and Zhao et al. (2017) also considered the approximate variability acceptable when studying the simulation test, so the coupled airflow¨Csoil¨Cblade simulation model established in this paper was reasonable and simulated rotary blade operation.

FIGURE 10
Energy consumption and fuel consumption results obtained through field test.

The results of fuel consumption in the field test are shown in Fig. 10b . Since the time interval in the coupled simulation test was 0.01 s, the accumulated time of fuel consumption in the field test needed to be timed and finally processed to the same 0.01 s as the time interval of the coupled simulation test (i.e., each data point was the oil consumption of a 0.01 s interval). The test results are basically consistent with those measured by Zhao et al. (2015) . The modeling of tillage resistance, torque, and fuel consumption was shown in Fig. 11 .

FIGURE 11
Three-dimensional model of torque, tillage resistance and fuel consumption.

The mathematical relationship between tillage resistance and torque on field fuel consumption in the coupled simulation test was as follows:

$Z=0.0027A+26.795$ (8)

where:

V is fuel consumption, mL;

p₁ is tillage resistance constant of 1.776x10^-6 N^.mL^-1 for 0.01 s rotary tillage operatice,

p₂ is torque constant of 7.88x10^-5 (N^.m) mL^-1 for 0.01 s rotary tillage operatice.

The fit was good, and most of the data points were around this surface. Therefore, this mathematical relationship can be used to represent the relationship between tillage resistance, the torque of rotary blades and the fuel consumption of the field test in the coupled airflow¨Csoil¨Cblade simulation test.

CONCLUSIONS

For the problem of tillage resistance during the operation of plain straight rotary blades, the tillage resistance of the rotary blade was divided into three parts: air resistance, lateral rotation friction resistance, and shear force in this paper.

(1) When the rotary blade was driven by the tractor's high-grade output shaft to rotate at high speed, the angular speed of the blade was 75.36 rad^.s^-1, and the air resistance was 0.0815 N. The coupling simulation output air resistance was 0.0883 N (7.7% difference from the theoretical calculation), and tillage resistance was 990.795 N. Air resistance accounted for 0.01% of tillage resistance. The horizontal resistance generated by lateral extrusion of the rotary blade during operation was linearly decreased with the increase of angular speed and linearly increased with the increase in contact area using discrete element simulation test. Vertical resistance tended to increase linearly with the increase in angular speed and increased linearly with the increase in contact area. The coupling simulation obtained a lateral rotational friction of 97.21 N, accounting for 9.81% of the tillage resistance. The greater the angular speed of the rotary blade, the greater the shear force. The coupling simulation obtained a shear force of 893.496 N, accounting for 90.18% of tillage resistance.

(2) The power consumption and fuel consumption of plain straight rotary tillage operations were tested in the field, and the power consumption ranged from 14 to 30 kW, with an average power consumption of 22.28 kW. Compared with the coupled simulation results, the power consumption increased by 10.63%. The 0.01 s unitisation process was performed on the output of fuel consumption, and the correspondence points were formed with the tillage resistance and power consumption in the coupled simulation, and the mathematical relationship model of tillage resistance, torque, and fuel consumption was established.

A thorough delineation of tillage resistance and energy consumption will provide theoretical support for the optimal design of rotary blades to reduce resistance and consumption. Meanwhile, the coupled simulation model was established to provide research ideas for the study of the resistance of soil-engaging components.

ACKNOWLEDGEMENTS

This work was financially supported by Technology Support Plan (Grant No.: 2020YFD1000903).

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Edited by

• Area Editor: Fábio Lúcio Santos

Publication Dates

• Publication in this collection
  26 June 2023
• Date of issue
  2023

History

• Received
  9 Aug 2022
• Accepted
  28 Mar 2023