Development of a Crawler-Type Self-Propelled Machine with Trenching, Fertilizing, and Soil-Covering Components for Hilly Orchard
Jun Li,
No information about this author
Chaodong Mai,
No information about this author
Ye Zeng
No information about this author
et al.
Agriculture,
Journal Year:
2025,
Volume and Issue:
15(4), P. 430 - 430
Published: Feb. 19, 2025
In
response
to
the
issues
of
high
energy
consumption,
limited
functionality,
and
uneven
soil–fertilizer
mixing
in
mechanical
operations
for
trenching
fertilizing
hilly
orchards,
this
study
proposes
design
a
crawler-type
self-propelled
machine,
integrating
three
main
functions:
trenching,
fertilizing,
soil
covering.
The
key
components
device,
soil-covering
device
were
designed.
Three
simulation
models
(pre-plant,
mid-plant,
post-plant)
established
using
EDEM
discrete
element
software.
effects
under
each
mode
analyzed,
with
results
indicating
that
post-plant
better
meets
requirements
deep
organic
fertilizer
application.
Using
speed,
forward
bending
angle
knife
as
experimental
factors,
operating
power
consumption
uniformity
evaluation
indicators,
Box–Behnken
experiment
was
conducted
optimize
parameters
components.
A
regression
model
analyze
interaction
between
factors
indicators.
optimal
operational
parameter
combination
determined
follows:
speed
265.03
r/min,
0.40
m/s,
130°.
Under
these
parameters,
1.74
kW
77.15%,
respectively.
Orchard
verification
tests
on
machine
showed
relative
errors
field
simulations
7.40%
4.50%,
These
meet
agronomic
provides
valuable
references
application
related
technologies
orchard
operations.
Language: Английский
Design and Testing of Film Picking–Unloading Device of Tillage Residual Film Recycling Machine Based on DEM Parameter Calibration
Agronomy,
Journal Year:
2025,
Volume and Issue:
15(4), P. 955 - 955
Published: April 14, 2025
The
operating
parameters
and
effect
of
a
residual
film
recycling
device
can
be
predicted,
the
key
determined
based
on
DEM–MBD
coupling
simulation.
obtained
from
parameter
calibration
are
basis
This
study
calibrates
DEM
for
soil-touching
components
tillage
machine.
A
film-picking
model
elastic
tooth–soil–residual
interactions
was
established.
reliability
contact
verified
by
comparing
simulation
experimental
angle
repose
soil–soil
(43.6°
vs.
42.42°,
error
2.7%)
film–residual
(43°
43.7°,
1.6%)
using
funnel
bucket
methods.
film–soil
detachment
developed,
with
force
analysis
showing
an
8.1%
between
(0.34
N)
experiment
(0.37
N).
Additionally,
used
to
analyze
recovery
rate
under
teeth,
yielding
2%
(90%)
(92%).
provides
optimization
in
components.
Language: Английский
Effects of soil-tool interaction and mechanical pulverization of arable soils in tillage -a comprehensive review
Frankline Mwiti,
No information about this author
Ayub Njoroge Gitau,
No information about this author
Duncan Mbuge
No information about this author
et al.
SSRN Electronic Journal,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Jan. 1, 2024
Language: Английский
Optimization of Rotary Blade Wear and Tillage Resistance Based on DEM-MBD Coupling Model
Agriculture,
Journal Year:
2025,
Volume and Issue:
15(3), P. 328 - 328
Published: Feb. 2, 2025
To
solve
the
problems
of
high
tillage
resistance
and
rapid
wear
rotary
blade
during
tillage,
this
study
employed
a
coupled
algorithm
discrete
element
method
(DEM)
multi-body
dynamics
(MBD)
with
Hertz–Mindlin
JKR
particle
contact
theory
to
establish
blade–sandy
soil
model.
The
interaction
between
sandy
was
analyzed.
results
indicated
that
lateral
horizontal
resistances
reached
peak
values
near
maximum
tilling
depth,
whereas
vertical
its
earlier.
Blade
predominantly
occurred
on
side
cutting
edge,
bending
zone
sidelong
most
significant
observed
followed
by
edge
which
showed
similar
patterns.
reduce
resistance,
Box–Behnken
optimization
applied
optimize
blade’s
local
parameters.
optimal
parameters—the
height
tangent
end
face
51
mm,
radius
28
angle
116°—reduced
22.4%
12%.
A
disturbance
analysis
demonstrated
optimized
performs
better
in
terms
width
compared
unoptimized
blade.
achieves
effects
reduced
wear,
improves
lifespan
blade,
reducing
material
loss,
meeting
requirements
sustainable
agricultural
production.
Language: Английский
Simulation analysis of mechanical response and failure mechanisms of maize stubble-soil composite based on discrete element method and fiber bundle model
Chunxiang Zhuo,
No information about this author
Haiqing Tian,
No information about this author
Ziqing Xiao
No information about this author
et al.
Computers and Electronics in Agriculture,
Journal Year:
2025,
Volume and Issue:
236, P. 110452 - 110452
Published: May 8, 2025
Language: Английский
Fuzzy backstepping controller for agricultural tractor-trailer vehicles path tracking control with experimental validation
Frontiers in Plant Science,
Journal Year:
2024,
Volume and Issue:
15
Published: Dec. 17, 2024
Unmanned
driving
technology
for
agricultural
vehicles
is
pivotal
in
advancing
modern
agriculture
towards
precision,
intelligence,
and
sustainability.
Among
machinery,
autonomous
tractor-trailer
(ATTVs)
has
garnered
significant
attention
recent
years.
ATTVs
comprise
large
implements
connected
to
tractors
through
hitch
points
are
extensively
utilized
production.
The
primary
objective
of
current
research
focus
on
tractor-trailers
enable
the
tractor
follow
a
reference
path
while
adhering
constraints
imposed
by
trailer,
which
may
not
always
align
with
agronomic
requirements.
To
address
challenge
tracking
ATTVs,
this
paper
proposes
fuzzy
back-stepping
controller
based
kinematic
model
ATTVs.
Initially,
error
was
established
trailer
as
positioning
center
Frenet
coordinate
system
using
velocity
decomposition
method.
Then,
designed
algorithm
calculate
target
front
wheel
steering
angle
tractor.
gain
coefficient
adaptively
adjusted
algorithm.
Co-simulation
experiments
were
conducted
MATLAB/Simulink/CarSim
physical
platform,
respectively.
Simulation
results
indicated
that
proposed
reduced
trailer's
online
time
36.33%.
When
following
curved
path,
significantly
lower
than
Stanley
single
In
actual
experiments,
U-turn
average
absolute
value
lateral
65.27%
maximum
87.54%.
mean
(MAE)
values
heading
0.010
0.016,
respectively,
integral
(IAE)
1.989
2.916,
effectively
addresses
practical
challenges
ATTV
tracking.
By
prioritizing
performance
quality
efficiency
during
field
operations
enhanced.
reduction
errors
demonstrates
effectiveness
improving
accuracy
Language: Английский