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Front Assembly: Front Suspension Forks Configuration#
Import necessary libraries#
from pymycar.MotorCycleKinematic.front_assembly import forks_system
import numpy as np
Parameters Definition#
data = {
# --- Front assembly ---
"wheel_center_front": np.array([650.0, 0.0, -520.0]),
"STEERING_AXIS_BOTTOM": np.array([650.0, 0.0, -100.0]),
"STEERING_AXIS_TOP": np.array([570.0, 0.0, 250.0]),
"fork_right_upper": np.array([570.0, -110.0, 250.0]),
"fork_left_upper": np.array([570.0, 110.0, 250.0]),
"fork_right_bottom": np.array([650.0, -120.0, -520.0]),
"fork_left_bottom": np.array([650.0, 120.0, -520.0]),
# --- Rear assembly ---
"wheel_center_rear": np.array([-600.0, 0.0, -520.0]),
"SA_RIGHT": np.array([-100.0, -90.0, -300.0]),
"SA_LEFT": np.array([-100.0, 90.0, -300.0]),
"sa_right_outer": np.array([-600.0, -110.0, -520.0]),
"sa_left_outer": np.array([-600.0, 110.0, -520.0]),
"U_SPRING_MOUNT": np.array([-150.0, 0.0, 50.0]),
"l_spring_mount": np.array([-420.0, 0.0, -350.0]),
}
import pyvista as pv
from pymycar.Cad.MotorCycle.front_assembly import fork_front_suspension_steer
from pymycar.Cad.MotorCycle.frame import frame_cad_base
from pymycar.Cad.MotorCycle.wheel import motorcycle_wheel
wheel = motorcycle_wheel(data["wheel_center_front"], data["fork_right_bottom"], data["fork_left_bottom"], ringradius=200, crosssectionradius=80)
steer_axis, top_part_steer, U_form = fork_front_suspension_steer(data)
plotter = pv.Plotter()
plotter.add_mesh(wheel, color="black", opacity=1.0)
plotter.add_mesh(steer_axis, color="blue")
plotter.add_mesh(top_part_steer, color="red")
plotter.add_mesh(U_form, color="green")
# Add points to the plot
for name, coord in data.items():
plotter.add_mesh(pv.Sphere(radius=5, center=coord), color='red')
# Add text annotations
for name, coord in data.items():
plotter.add_point_labels([coord], [name], point_size=20, font_size=30, text_color='black', always_visible=True)
plotter.show()
# file_path = 'data.suspgeo'
# data = load_defined_geometry("double_whisbone_base/input_geometry.suspgeo")
Call the Solver#
drive_type = "mixed" # "steer", "bump" or "mixed"
solution, wheel_variables = forks_system(data,
max_height_increase=40,
max_height_decrease=40,
height_step=1.0,
drive_type=drive_type, # Passed dynamically
max_steer_increase=40,
max_steer_decrease=40,
steer_step=5.0,
max_bump_increase=40,
max_bump_decrease=40,
bump_step=5.0,
save_to_txt=True,
result_folder_name="bike",
path = None)
from pymycar.Cad.geometric_forms import cylinder_from_two_points
from pymycar.Cad.MotorCycle.wheel import motorcycle_wheel
last_meshes = []
def plot_frame(plotter, data, index=None, bump_index=None, steer_index=None):
global last_meshes
if drive_type == "mixed":
if bump_index is None or steer_index is None:
bump_index, steer_index = data["index_reference"]
wheel = motorcycle_wheel(data["wheel_center_front"][bump_index, steer_index], data["fork_right_bottom"][bump_index, steer_index], data["fork_left_bottom"][bump_index, steer_index], 200, 80)
# wheel = cylinder_from_two_points(
# data["wheel_center"][bump_index, steer_index],
# data["fork_right_bottom"][bump_index, steer_index],
# data["fork_left_bottom"][bump_index, steer_index],
# height=50,
# radius=200,
# )
steer_axis, bar, U_form = fork_front_suspension_steer(solution, (bump_index, steer_index))
else:
if index is None:
index = data["index_reference"]
# swingarm, wheel_center1 = swingarm_cad_base(data, index)
wheel = cylinder_from_two_points(data["wheel_center"][index], data["fork_right_bottom"][index], data["fork_left_bottom"][index], height=50, radius=200)
steer_axis, bar, U_form = fork_front_suspension_steer(solution, index)
# Remove the last meshes
for mesh in last_meshes:
plotter.remove_actor(mesh)
# Add new meshes
last_meshes = [
plotter.add_mesh(steer_axis, color="blue"),
plotter.add_mesh(bar, color="red"),
plotter.add_mesh(U_form, color="blue"),
plotter.add_mesh(wheel, color="black")
]
plotter = pv.Plotter()
def create_mesh_steer(value):
if drive_type == "mixed":
state["steer"] = np.abs(solution["steer_values"] - value).argmin()
plot_frame(plotter, solution, bump_index=state["bump"], steer_index=state["steer"])
else:
res = np.abs(solution["fork_right_upper"][:,0] - value).argmin()
plot_frame(plotter, solution, index=res)
def create_mesh_bump(value):
if drive_type == "mixed":
state["bump"] = np.abs(solution["bump_values"] - value).argmin()
plot_frame(plotter, solution, bump_index=state["bump"], steer_index=state["steer"])
else:
res = np.abs(solution["wheel_center"][:,2] - value).argmin()
plot_frame(plotter, solution, index=res)
state = {"bump": 0, "steer": 0}
if drive_type == "steer":
plotter.add_slider_widget(create_mesh_steer,
rng=[solution["fork_right_upper"][0, 0], solution["fork_right_upper"][-1, 0]],
value=solution["fork_right_upper"][solution["index_reference"]][0],
title='Steer / Jounce (fork_right_upper x)')
else:
if drive_type == "bump":
plotter.add_slider_widget(create_mesh_bump,
rng=[solution["wheel_center"][0, 2], solution["wheel_center"][-1, 2]],
value=solution["wheel_center"][solution["index_reference"]][2],
title='Bump (wheel_center z)')
else:
state["bump"], state["steer"] = solution["index_reference"]
plot_frame(plotter, solution, bump_index=state["bump"], steer_index=state["steer"])
plotter.add_slider_widget(
create_mesh_steer,
rng=[solution["steer_values"][0], solution["steer_values"][-1]],
value=solution["steer_values"][state["steer"]],
title='Steer (fork_right_upper x)'
)
plotter.add_slider_widget(
create_mesh_bump,
rng=[solution["bump_values"][0], solution["bump_values"][-1]],
value=solution["bump_values"][state["bump"]],
title='Bump (wheel_center z)',
pointa=(0.025, 0.15),
pointb=(0.31, 0.15)
)
plotter.show()
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/home/docs/checkouts/readthedocs.org/user_builds/pymycar/checkouts/latest/src/pymycar/MotorCycleKinematic/front_assembly.py:334: RuntimeWarning: The iteration is not making good progress, as measured by the
improvement from the last five Jacobian evaluations.
sol = fsolve(
/home/docs/checkouts/readthedocs.org/user_builds/pymycar/checkouts/latest/src/pymycar/MotorCycleKinematic/front_assembly.py:334: RuntimeWarning: The iteration is not making good progress, as measured by the
improvement from the last ten iterations.
sol = fsolve(
Total running time of the script: (0 minutes 5.885 seconds)