"""
Suspension: Double Wishbone
===========================
This module provides functions to analyze and simulate the behavior of a double wishbone suspension system. The double wishbone suspension is a type of vehicle suspension design that uses two wishbone-shaped arms (or control arms) to locate the wheel. This type of suspension is widely used in various vehicles, from road cars to competition vehicles.
"""
###############################################################################
# Import necessary libraries
# --------------------------
import os
import numpy as np
###############################################################################
# Import from pymycar package
# ---------------------------
from pymycar.files import prepare_simulation, save_results_2_txt
from pymycar.Logger.library_versions import logger_suspension_kinematics
from pymycar.SuspensionKinematic.functions import solve, generate_wheel_center_heights
from pymycar.SuspensionKinematic.suspension_files import saved_defined_geometry # save_data
from pymycar.SuspensionKinematic.functions import get_wheel
[docs]
def double_whisbone_base(data, max_height_increase, max_height_decrease, height_step, save_to_txt=True, result_folder_name="results", path = None):
"""
Computes and solves the geometric constraints for a double wishbone suspension system.
The function generates different wheel center heights based on input constraints, then calculates
the residuals for a non-linear optimization problem to find the correct configuration of the
suspension system.
Parameters
----------
data : dict
A dictionary containing the initial measurements and reference points for the suspension system.
Expected keys include:
- 'wheel_center': The initial wheel center position.
- 'uca_outer': The outer UCA (Upper Control Arm) position.
- 'UCA_FRONT': The front reference point for the UCA.
- 'UCA_REAR': The rear reference point for the UCA.
- 'lca_outer': The outer LCA (Lower Control Arm) position.
- 'LCA_FRONT': The front reference point for the LCA.
- 'LCA_REAR': The rear reference point for the LCA.
- 'tierod_outer': The outer tierod position.
- 'TIEROD_INNER': The inner reference point for the tierod.
max_height_increase : float
Maximum increase in wheel center height for the analysis.
max_height_decrease : float
Maximum decrease in wheel center height for the analysis.
height_step : float
Step size for incrementing and decrementing the wheel center height.
save_to_txt : bool, optional
If True, the results will be saved to a text file. Default is True.
result_folder_name : str, optional
The name of the folder where results will be saved. Default is "results".
path : str, optional
The path where the results folder will be created. If None, the current working directory is used. Default is None.
Returns
-------
solution : dict
A dictionary with the optimized suspension parameters and their values:
- 'UCA_FRONT': The front UCA position.
- 'UCA_REAR': The rear UCA position.
- 'LCA_FRONT': The front LCA position.
- 'LCA_REAR': The rear LCA position.
- 'TIEROD_INNER': The inner tierod position.
- 'uca_outer': Optimized outer UCA positions.
- 'lca_outer': Optimized outer LCA positions.
- 'tierod_outer': Optimized outer tierod positions.
- 'wheel_center': Optimized wheel center positions.
- 'index_reference': Index reference for the wheel center heights.
Notes
-----
The function utilizes an optimization algorithm to solve for the configuration of the suspension
system that satisfies the geometric constraints. The geometric model assumes a double wishbone
suspension layout with specific reference points for each component.
.. code-block::
#
# ///
# \-/
# UCA_REAR*
# /
# /
# ----------- /
# | | /
# | | *----------*UCA_FRONT
# | | uca_outer /⁻\
# | | ///
# | |
# | wheel center
# | * | tierod_outer
# | | *--------------------*TIEROD_INNER
# | |
# | |
# | | lca_outer
# | | *------------*LCA_REAR
# ----------- \ /⁻\
# \ ///
# \
# *LCA_FRONT
# /⁻\
# ///
+-----------------+--------------------------+--------+
| Points Name | Description | Type |
+=================+==========================+========+
| wheel center | Center of the Wheel | mobile |
+-----------------+--------------------------+--------+
| UCA FRONT | Upper Control Arm Front | fixed |
+-----------------+--------------------------+--------+
| UCA REAR | Upper Control Arm Rear | fixed |
+-----------------+--------------------------+--------+
| uca outer | Upper Control Arm Outer | mobile |
+-----------------+--------------------------+--------+
| LCA FRONT | Lower Control Arm Front | fixed |
+-----------------+--------------------------+--------+
| LCA REAR | Lower Control Arm Rear | fixed |
+-----------------+--------------------------+--------+
| lca outer | Lower Control Arm Outer | mobile |
+-----------------+--------------------------+--------+
| TIEROD INNER | Inner Tie Rod | fixed |
+-----------------+--------------------------+--------+
| tierod outer | Outer Tie Rod | mobile |
+-----------------+--------------------------+--------+
"""
if path is None:
path = os.getcwd()
prepare_simulation(path, result_folder_name)
logger_suspension_kinematics(data, max_height_increase, max_height_decrease, height_step, save_to_txt, result_folder_name, path)
wheel, index = generate_wheel_center_heights(
data["wheel_center"], max_height_increase, max_height_decrease, height_step)
def get_L():
L = np.array([
data["uca_outer"] - data["UCA_FRONT"],
data["uca_outer"] - data["UCA_REAR"],
data["lca_outer"] - data["LCA_FRONT"],
data["lca_outer"] - data["LCA_REAR"],
data["tierod_outer"] - data["TIEROD_INNER"],
data["tierod_outer"] - data["uca_outer"],
data["tierod_outer"] - data["lca_outer"],
data["lca_outer"] - data["uca_outer"],
data["wheel_center"] - data["uca_outer"],
data["wheel_center"] - data["lca_outer"],
data["wheel_center"] - data["tierod_outer"],
])
return L
L_squared = np.linalg.norm(get_L(), axis=1)**2
def jacobian(x, _):
J = np.zeros([len(x), len(x)])
# EQ0 (1)
J[0, 0] = 2 * (x[0] - data["UCA_FRONT"][0])
J[0, 1] = 2 * (x[1] - data["UCA_FRONT"][1])
J[0, 2] = 2 * (x[2] - data["UCA_FRONT"][2])
# EQ1 (1)
J[1, 0] = 2 * (x[0] - data["UCA_REAR"][0])
J[1, 1] = 2 * (x[1] - data["UCA_REAR"][1])
J[1, 2] = 2 * (x[2] - data["UCA_REAR"][2])
# EQ2 (2)
J[2, 3] = 2 * (x[3] - data["LCA_FRONT"][0])
J[2, 4] = 2 * (x[4] - data["LCA_FRONT"][1])
J[2, 5] = 2 * (x[5] - data["LCA_FRONT"][2])
# EQ3 (2)
J[3, 3] = 2 * (x[3] - data["LCA_REAR"][0])
J[3, 4] = 2 * (x[4] - data["LCA_REAR"][1])
J[3, 5] = 2 * (x[5] - data["LCA_REAR"][2])
# EQ4 (3)
J[4, 6] = 2 * (x[6] - data["TIEROD_INNER"][0])
J[4, 7] = 2 * (x[7] - data["TIEROD_INNER"][1])
J[4, 8] = 2 * (x[8] - data["TIEROD_INNER"][2])
# EQ5 (3 1)
J[5, 0] = 2 * (x[0] - x[6])
J[5, 1] = 2 * (x[1] - x[7])
J[5, 2] = 2 * (x[2] - x[8])
J[5, 6] = -2 * (x[0] - x[6])
J[5, 7] = -2 * (x[1] - x[7])
J[5, 8] = -2 * (x[2] - x[8])
# EQ6 (3, 2)
J[6, 3] = 2 * (x[3] - x[6])
J[6, 4] = 2 * (x[4] - x[7])
J[6, 5] = 2 * (x[5] - x[8])
J[6, 6] = -2 * (x[3] - x[6])
J[6, 7] = -2 * (x[4] - x[7])
J[6, 8] = -2 * (x[5] - x[8])
# EQ7 (2, 1)
J[7, 0] = 2 * (x[0] - x[3])
J[7, 1] = 2 * (x[1] - x[4])
J[7, 2] = 2 * (x[2] - x[5])
J[7, 3] = -2 * (x[0] - x[3])
J[7, 4] = -2 * (x[1] - x[4])
J[7, 5] = -2 * (x[2] - x[5])
# EQ8 (4, 1)
J[8, 0] = 2 * (x[0] - x[9])
J[8, 1] = 2 * (x[1] - x[10])
J[8, 2] = 2 * (x[2] - x[11])
J[8, 9] = -2 * (x[0] - x[9])
J[8, 10] = -2 * (x[1] - x[10])
J[8, 11] = -2 * (x[2] - x[11])
# EQ9 (4, 2)
J[9, 3] = 2 * (x[3] - x[9])
J[9, 4] = 2 * (x[4] - x[10])
J[9, 5] = 2 * (x[5] - x[11])
J[9, 9] = -2 * (x[3] - x[9])
J[9, 10] = -2 * (x[4] - x[10])
J[9, 11] = -2 * (x[5] - x[11])
# EQ10 (4, 3)
J[10, 6] = 2 * (x[6] - x[9])
J[10, 7] = 2 * (x[7] - x[10])
J[10, 8] = 2 * (x[8] - x[11])
J[10, 9] = -2 * (x[6] - x[9])
J[10, 10] = -2 * (x[7] - x[10])
J[10, 11] = -2 * (x[8] - x[11])
# EQ11
J[11, 11] = -1
return J
def residual(vars, wheel_center_z):
uca_outer, lca_outer, tierod_outer, wheel_center = vars[
0:3], vars[3:6], vars[6:9], vars[9:12]
diff = np.array([
uca_outer - data["UCA_FRONT"],
uca_outer - data["UCA_REAR"],
lca_outer - data["LCA_FRONT"],
lca_outer - data["LCA_REAR"],
tierod_outer - data["TIEROD_INNER"],
tierod_outer - uca_outer,
tierod_outer - lca_outer,
lca_outer - uca_outer,
wheel_center - uca_outer,
wheel_center - lca_outer,
wheel_center - tierod_outer,
])
F = np.linalg.norm(diff, axis=1)**2 - L_squared
return np.append(F, np.array([-wheel_center[2] + wheel_center_z]))
initial_guess = [data["uca_outer"],
data["lca_outer"],
data["tierod_outer"],
data["wheel_center"]]
solution_save = solve(wheel, index, initial_guess, residual, jacobian=jacobian)
solution = {
"UCA_FRONT": data["UCA_FRONT"],
"UCA_REAR": data["UCA_REAR"],
"LCA_FRONT": data["LCA_FRONT"],
"LCA_REAR": data["LCA_REAR"],
"TIEROD_INNER": data["TIEROD_INNER"],
"uca_outer": solution_save[:, 0:3],
"lca_outer": solution_save[:, 3:6],
"tierod_outer": solution_save[:, 6:9],
"wheel_center": solution_save[:, 9:12],
"index_reference": index
}
wheel_variables = get_wheel(solution)
if save_to_txt:
saved_defined_geometry(data, os.path.join(result_folder_name, "input_geometry.suspgeo"))
save_results_2_txt(wheel_variables, os.path.join(result_folder_name, "wheel_variables.suspvar"))
return solution, wheel_variables
[docs]
def double_whisbone_configuration_1(data, max_height_increase, max_height_decrease, height_step, save_to_txt=True, result_folder_name="results", path=None):
"""
Computes and solves the geometric constraints for a double wishbone suspension system.
The function generates different wheel center heights based on input constraints, then calculates
the residuals for a non-linear optimization problem to find the correct configuration of the
suspension system.
Parameters
----------
Data : dict
A dictionary containing the initial measurements and reference points for the suspension system.
Expected keys include:
- 'wheel_center': The initial wheel center position.
- 'uca_outer': The outer UCA (Upper Control Arm) position.
- 'UCA_FRONT': The front reference point for the UCA.
- 'UCA_REAR': The rear reference point for the UCA.
- 'lca_outer': The outer LCA (Lower Control Arm) position.
- 'LCA_FRONT': The front reference point for the LCA.
- 'LCA_REAR': The rear reference point for the LCA.
- 'tierod_outer': The outer tierod position.
- 'TIEROD_INNER': The inner reference point for the tierod.
max_height_increase : float
Maximum increase in wheel center height for the analysis.
max_height_decrease : float
Maximum decrease in wheel center height for the analysis.
height_step : float
Step size for incrementing and decrementing the wheel center height.
save_to_txt : bool, optional
If True, the results will be saved to a text file. Default is True.
Returns
-------
solution : dict
A dictionary with the optimized suspension parameters and their values:
- 'UCA_FRONT': The front UCA position.
- 'UCA_REAR': The rear UCA position.
- 'LCA_FRONT': The front LCA position.
- 'LCA_REAR': The rear LCA position.
- 'TIEROD_INNER': The inner tierod position.
- 'uca_outer': Optimized outer UCA positions.
- 'lca_outer': Optimized outer LCA positions.
- 'tierod_outer': Optimized outer tierod positions.
- 'wheel_center': Optimized wheel center positions.
- 'index_reference': Index reference for the wheel center heights.
Notes
-----
The function utilizes an optimization algorithm to solve for the configuration of the suspension
system that satisfies the geometric constraints. The geometric model assumes a double wishbone
suspension layout with specific reference points for each component.
.. code-block::
#
# ///
# \-/
# UCA_REAR*
# /
# /
# ----------- /
# | | /
# | | *----------*UCA_FRONT
# | | uca_outer /⁻\
# | | ///
# | | * U_SPRING_MOUNT
# | wheel center /
# | * | tierod_outer .
# | | *-------------/------*TIEROD_INNER
# | | .
# | | /
# | | lca_outer .
# | | *-----------/-*LCA_REAR
# | | \ . /⁻\
# ----------- \ / ///
# \ .
# \ * l_spring_mount
# \
# *LCA_FRONT
# /⁻\
# ///
+-----------------+--------------------------+--------+
| Points Name | Description | Type |
+=================+==========================+========+
| wheel center | Center of the Wheel | mobile |
+-----------------+--------------------------+--------+
| UCA FRONT | Upper Control Arm Front | fixed |
+-----------------+--------------------------+--------+
| UCA REAR | Upper Control Arm Rear | fixed |
+-----------------+--------------------------+--------+
| uca outer | Upper Control Arm Outer | mobile |
+-----------------+--------------------------+--------+
| LCA FRONT | Lower Control Arm Front | fixed |
+-----------------+--------------------------+--------+
| LCA REAR | Lower Control Arm Rear | fixed |
+-----------------+--------------------------+--------+
| lca outer | Lower Control Arm Outer | mobile |
+-----------------+--------------------------+--------+
| TIEROD INNER | Inner Tie Rod | fixed |
+-----------------+--------------------------+--------+
| tierod outer | Outer Tie Rod | mobile |
+-----------------+--------------------------+--------+
| Spring/Damper | Supensión Superior | mobile |
| Upper Mount | | |
+-----------------+--------------------------+--------+
| Spring/Damper | Supensión Inferior | mobile |
| Lower Mount | | |
+-----------------+--------------------------+--------+
"""
if path is None:
path = os.getcwd()
prepare_simulation(path, result_folder_name)
logger_suspension_kinematics(data, max_height_increase, max_height_decrease, height_step, save_to_txt, result_folder_name, path)
wheel, index = generate_wheel_center_heights(
data["wheel_center"], max_height_increase, max_height_decrease, height_step)
def get_L():
L = np.array([
data["uca_outer"] - data["UCA_FRONT"],
data["uca_outer"] - data["UCA_REAR"],
data["lca_outer"] - data["LCA_FRONT"],
data["lca_outer"] - data["LCA_REAR"],
data["tierod_outer"] - data["TIEROD_INNER"],
data["tierod_outer"] - data["uca_outer"],
data["tierod_outer"] - data["lca_outer"],
data["lca_outer"] - data["uca_outer"],
data["wheel_center"] - data["uca_outer"],
data["wheel_center"] - data["lca_outer"],
data["wheel_center"] - data["tierod_outer"],
data["l_spring_mount"] - data["LCA_FRONT"],
data["l_spring_mount"] - data["LCA_REAR"],
data["l_spring_mount"] - data["lca_outer"],
])
return L
L_squared = np.linalg.norm(get_L(), axis=1)**2
def residual(vars, wheel_center_z):
uca_outer, lca_outer, tierod_outer, wheel_center, l_spring_mount = vars[
0:3], vars[3:6], vars[6:9], vars[9:12], vars[12:15]
diff = np.array([
uca_outer - data["UCA_FRONT"],
uca_outer - data["UCA_REAR"],
lca_outer - data["LCA_FRONT"],
lca_outer - data["LCA_REAR"],
tierod_outer - data["TIEROD_INNER"],
tierod_outer - uca_outer,
tierod_outer - lca_outer,
lca_outer - uca_outer,
wheel_center - uca_outer,
wheel_center - lca_outer,
wheel_center - tierod_outer,
l_spring_mount - data["LCA_FRONT"],
l_spring_mount - data["LCA_REAR"],
l_spring_mount - lca_outer,
])
F = np.linalg.norm(diff, axis=1)**2 - L_squared
return np.append(F, np.array([wheel_center[2] - wheel_center_z]))
initial_guess = [data["uca_outer"],
data["lca_outer"],
data["tierod_outer"],
data["wheel_center"],
data["l_spring_mount"]]
solution_save = solve(wheel, index, initial_guess, residual, jacobian=None)
solution = {
"UCA_FRONT": data["UCA_FRONT"],
"UCA_REAR": data["UCA_REAR"],
"LCA_FRONT": data["LCA_FRONT"],
"LCA_REAR": data["LCA_REAR"],
"TIEROD_INNER": data["TIEROD_INNER"],
"U_SPRING_MOUNT": data["U_SPRING_MOUNT"],
"uca_outer": solution_save[:, 0:3],
"lca_outer": solution_save[:, 3:6],
"tierod_outer": solution_save[:, 6:9],
"wheel_center": solution_save[:, 9:12],
"l_spring_mount": solution_save[:, 12:15],
"index_reference": index
}
wheel_variables = get_wheel(solution)
if save_to_txt:
saved_defined_geometry(data, os.path.join(result_folder_name, "input_geometry.suspgeo"))
save_results_2_txt(wheel_variables, os.path.join(result_folder_name, "wheel_variables.suspvar"))
return solution, wheel_variables
[docs]
def double_whisbone_configuration_2(data, max_height_increase, max_height_decrease, height_step, save_to_txt=True, result_folder_name="results", path=None):
"""
Computes and solves the geometric constraints for a double wishbone suspension system.
The function generates different wheel center heights based on input constraints, then calculates
the residuals for a non-linear optimization problem to find the correct configuration of the
suspension system.
Parameters
----------
data : dict
A dictionary containing the initial measurements and reference points for the suspension system.
Expected keys include:
- 'wheel_center': The initial wheel center position.
- 'uca_outer': The outer UCA (Upper Control Arm) position.
- 'UCA_FRONT': The front reference point for the UCA.
- 'UCA_REAR': The rear reference point for the UCA.
- 'lca_outer': The outer LCA (Lower Control Arm) position.
- 'LCA_FRONT': The front reference point for the LCA.
- 'LCA_REAR': The rear reference point for the LCA.
- 'tierod_outer': The outer tierod position.
- 'TIEROD_INNER': The inner reference point for the tierod.
- 'push_rod_outer': The outer push rod position.
- 'push_rod_inner': The inner push rod position.
- 'ROCKER_PIVOT': The rocker pivot position.
- 'ROCKER_PIVOT_AXIS': The rocker pivot axis position.
- 'l_spring_mount': The lower spring mount position.
- 'U_SPRING_MOUNT': The upper spring mount position.
max_height_increase : float
Maximum increase in wheel center height for the analysis.
max_height_decrease : float
Maximum decrease in wheel center height for the analysis.
height_step : float
Step size for incrementing and decrementing the wheel center height.
save_to_txt : bool, optional
If True, the results will be saved to a text file. Default is True.
result_folder_name : str, optional
The name of the folder where results will be saved. Default is "results".
path : str, optional
The path where the results folder will be created. If None, the current working directory is used. Default is None.
Returns
-------
solution : dict
A dictionary with the optimized suspension parameters and their values:
- 'UCA_FRONT': The front UCA position.
- 'UCA_REAR': The rear UCA position.
- 'LCA_FRONT': The front LCA position.
- 'LCA_REAR': The rear LCA position.
- 'TIEROD_INNER': The inner tierod position.
- 'uca_outer': Optimized outer UCA positions.
- 'lca_outer': Optimized outer LCA positions.
- 'tierod_outer': Optimized outer tierod positions.
- 'wheel_center': Optimized wheel center positions.
- 'push_rod_outer': Optimized outer push rod positions.
- 'push_rod_inner': Optimized inner push rod positions.
- 'l_spring_mount': Optimized lower spring mount positions.
- 'index_reference': Index reference for the wheel center heights.
Notes
-----
The function utilizes an optimization algorithm to solve for the configuration of the suspension
system that satisfies the geometric constraints. The geometric model assumes a double wishbone
suspension layout with specific reference points for each component.
.. code-block::
# l_spring_mount
# *-\/\/\/\/\/\/\/\/\/\/\--* U_SPRING_MOUNT
# /// /| /⁻\
# \-/ pushrod inner* | *ROCKER PIVOT AXIS ///
# uca_rear* / \| /
# / / *ROCKER PIVOT
# / / /⁻\
# ----------- / pushrod outer* ///
# | | /
# | | *----------*uca_front
# | | uca_outer /⁻\
# | | ///
# | |
# | wheel center
# | * | tierod_outer
# | | *--------------------*tierod_inner
# | |
# | |
# | | lca_outer
# | | *------------*lca_rear
# ----------- \ /⁻\
# \ ///
# \
# *lca_front
# /⁻\
# ///
+-----------------+--------------------------+--------+
| Points Name | Description | Type |
+=================+==========================+========+
| wheel center | Center of the Wheel | mobile |
+-----------------+--------------------------+--------+
| UCA FRONT | Upper Control Arm Front | fixed |
+-----------------+--------------------------+--------+
| UCA REAR | Upper Control Arm Rear | fixed |
+-----------------+--------------------------+--------+
| uca outer | Upper Control Arm Outer | mobile |
+-----------------+--------------------------+--------+
| LCA FRONT | Lower Control Arm Front | fixed |
+-----------------+--------------------------+--------+
| LCA REAR | Lower Control Arm Rear | fixed |
+-----------------+--------------------------+--------+
| lca outer | Lower Control Arm Outer | mobile |
+-----------------+--------------------------+--------+
| TIEROD INNER | Inner Tie Rod | fixed |
+-----------------+--------------------------+--------+
| tierod outer | Outer Tie Rod | mobile |
+-----------------+--------------------------+--------+
| pushrod outer | Pushrod Exterior | mobile |
+-----------------+--------------------------+--------+
| pushrod inner | Pushrod Interior | mobile |
+-----------------+--------------------------+--------+
| ROCKER PIVOT | Rocker pivot | fixed |
+-----------------+--------------------------+--------+
| ROCKER PIVOT | Rocker pivot axis | fixed |
| AXIS | | |
+-----------------+--------------------------+--------+
| U SPRING MOUNT | Spring/damper | fixed |
| | Upper Mount | |
+-----------------+--------------------------+--------+
| l spring mount | Spring/Damper | mobile |
| | Lower Mount | |
+-----------------+--------------------------+--------+
"""
if path is None:
path = os.getcwd()
prepare_simulation(path, result_folder_name)
logger_suspension_kinematics(data, max_height_increase, max_height_decrease, height_step, save_to_txt, result_folder_name, path)
wheel, index = generate_wheel_center_heights(
data["wheel_center"], max_height_increase, max_height_decrease, height_step)
def get_L():
L = np.array([
data["uca_outer"] - data["UCA_FRONT"],
data["uca_outer"] - data["UCA_REAR"],
data["lca_outer"] - data["LCA_FRONT"],
data["lca_outer"] - data["LCA_REAR"],
data["tierod_outer"] - data["TIEROD_INNER"],
data["tierod_outer"] - data["uca_outer"],
data["tierod_outer"] - data["lca_outer"],
data["lca_outer"] - data["uca_outer"],
data["wheel_center"] - data["uca_outer"],
data["wheel_center"] - data["lca_outer"],
data["wheel_center"] - data["tierod_outer"],
data["push_rod_outer"] - data["UCA_FRONT"],
data["push_rod_outer"] - data["UCA_REAR"],
data["push_rod_outer"] - data["uca_outer"],
data["push_rod_inner"] - data["push_rod_outer"],
data["push_rod_inner"] - data["ROCKED_PIVOT"],
data["push_rod_inner"] - data["ROCKED_PIVOT_AXIS"],
data["l_spring_mount"] - data["UCA_FRONT"],
data["l_spring_mount"] - data["ROCKED_PIVOT"],
data["l_spring_mount"] - data["push_rod_inner"],
])
return L
L_squared = np.linalg.norm(get_L(), axis=1)**2
def residual(vars, wheel_center_z):
uca_outer = vars[0:3]
lca_outer = vars[3:6]
tierod_outer = vars[6:9]
wheel_center = vars[9:12]
push_rod_outer = vars[12:15]
push_rod_inner = vars[15:18]
l_spring_mount = vars[18:21]
diff = np.array([
uca_outer - data["UCA_FRONT"],
uca_outer - data["UCA_REAR"],
lca_outer - data["LCA_FRONT"],
lca_outer - data["LCA_REAR"],
tierod_outer - data["TIEROD_INNER"],
tierod_outer - uca_outer,
tierod_outer - lca_outer,
lca_outer - uca_outer,
wheel_center - uca_outer,
wheel_center - lca_outer,
wheel_center - tierod_outer,
push_rod_outer - data["UCA_FRONT"],
push_rod_outer - data["UCA_REAR"],
push_rod_outer - uca_outer,
push_rod_inner - push_rod_outer,
push_rod_inner - data["ROCKED_PIVOT"],
push_rod_inner - data["ROCKED_PIVOT_AXIS"],
l_spring_mount - data["UCA_FRONT"],
l_spring_mount - data["ROCKED_PIVOT"],
l_spring_mount - push_rod_inner,
])
F = np.linalg.norm(diff, axis=1)**2 - L_squared
return np.append(F, np.array([-wheel_center[2] + wheel_center_z]))
initial_guess = [data["uca_outer"], data["lca_outer"],
data["tierod_outer"], data["wheel_center"],
data["push_rod_outer"] , data["push_rod_inner"],
data["l_spring_mount"]]
solution_save = solve(wheel, index, initial_guess, residual, jacobian=None)
solution = {
"UCA_FRONT": data["UCA_FRONT"],
"UCA_REAR": data["UCA_REAR"],
"LCA_FRONT": data["LCA_FRONT"],
"LCA_REAR": data["LCA_REAR"],
"TIEROD_INNER": data["TIEROD_INNER"],
"ROCKED_PIVOT": data["ROCKED_PIVOT"],
"ROCKED_PIVOT_AXIS": data["ROCKED_PIVOT_AXIS"],
"U_SPRING_MOUNT": data["U_SPRING_MOUNT"],
"uca_outer": solution_save[:, 0:3],
"lca_outer": solution_save[:, 3:6],
"tierod_outer": solution_save[:, 6:9],
"wheel_center": solution_save[:, 9:12],
"push_rod_outer": solution_save[:, 12:15],
"push_rod_inner": solution_save[:, 15:18],
"l_spring_mount": solution_save[:, 18:21],
"index_reference": index
}
wheel_variables = get_wheel(solution)
if save_to_txt:
saved_defined_geometry(data, os.path.join(result_folder_name, "input_geometry.suspgeo"))
save_results_2_txt(wheel_variables, os.path.join(result_folder_name, "wheel_variables.suspvar"))
return solution, wheel_variables
