def test_FEMM_sym(self):
"""Figure 9: Check that the FEMM can handle symmetry
From pyleecan/Tests/Validation/Simulation/test_EM_SCIM_NL_006.py
"""
simu = Simu1(name="ICEM_2020", machine=SCIM_006)
simu.machine.name = "fig_09_FEMM_sym"
# Definition of the enforced output of the electrical module
Nr = ImportMatrixVal(value=ones(1) * 1500)
Is = ImportMatrixVal(value=array([[20, -10, -10]]))
Ir = ImportMatrixVal(value=zeros((1, 28)))
time = ImportGenVectLin(start=0, stop=0, num=1, endpoint=False)
angle = ImportGenVectLin(start=0,
stop=2 * pi,
num=4096,
endpoint=False)
simu.input = InCurrent(
Is=Is,
Ir=Ir, # zero current for the rotor
Nr=Nr,
angle_rotor=None, # Will be computed
time=time,
angle=angle,
angle_rotor_initial=0.2244,
)
# Definition of the magnetic simulation
# 2 sym + antiperiodicity = 1/4 Lamination
simu.mag = MagFEMM(
is_stator_linear_BH=2,
is_rotor_linear_BH=2,
is_symmetry_a=True,
sym_a=2,
is_antiper_a=True,
)
# Stop after magnetic computation
simu.struct = None
# Run simulation
out = Output(simu=simu)
simu.run()
# FEMM files (mesh and results) are available in Results folder
copyfile(
join(out.path_res, "Femm", "fig_09_FEMM_sym_model.ans"),
join(save_path, "fig_09_FEMM_sym_model.ans"),
)
copyfile(
join(out.path_res, "Femm", "fig_09_FEMM_sym_model.fem"),
join(save_path, "fig_09_FEMM_sym_model.fem"),
)
def test_InCurrent_Ok(self):
"""Check that the input current can return a correct output
"""
test_obj = Simulation(machine=M3)
output = Output(simu=test_obj)
time = ImportGenVectLin(0, 1, 16)
angle = ImportGenVectLin(0, 2 * pi, 20)
Is = ImportGenMatrixSin(is_transpose=True)
Is.init_vector(f=[2, 2, 2],
A=[2, 2, 2],
Phi=[pi / 2, 0, -pi / 2],
N=16,
Tf=1)
S = sqrt(2)
Is_exp = transpose(
array([
[2, S, 0, -S, -2, -S, 0, S, 2, S, 0, -S, -2, -S, 0, S],
[0, S, 2, S, 0, -S, -2, -S, 0, S, 2, S, 0, -S, -2, -S],
[-2, -S, 0, S, 2, S, 0, -S, -2, -S, 0, S, 2, S, 0, -S],
]))
Ir = ImportGenMatrixSin(is_transpose=True)
Ir.init_vector(f=[2, 2], A=[2, 2], Phi=[0, -pi / 2], N=16, Tf=1)
Ir_exp = transpose(
array([
[0, S, 2, S, 0, -S, -2, -S, 0, S, 2, S, 0, -S, -2, -S],
[-2, -S, 0, S, 2, S, 0, -S, -2, -S, 0, S, 2, S, 0, -S],
]))
angle_rotor = ImportGenVectLin(0, 2 * pi, 16)
Nr = ImportMatrixVal(value=ones(16) * 10)
test_obj.input = InCurrent(time=time,
angle=angle,
Is=Is,
Ir=Ir,
angle_rotor=angle_rotor,
Nr=Nr)
test_obj.input.gen_input()
assert_array_almost_equal(output.elec.time, linspace(0, 1, 16))
assert_array_almost_equal(output.elec.angle, linspace(0, 2 * pi, 20))
assert_array_almost_equal(output.elec.Is, Is_exp)
assert_array_almost_equal(output.elec.Ir, Ir_exp)
assert_array_almost_equal(output.elec.angle_rotor,
linspace(0, 2 * pi, 16))
assert_array_almost_equal(output.elec.Nr, ones(16) * 10)
def test_InCurrentDQ_Ok(self):
"""Check that the input current can return a correct output
"""
test_obj = Simulation(machine=M1)
output = Output(simu=test_obj)
time = ImportGenVectLin(0, 1, 7)
angle = ImportGenVectLin(0, 2 * pi, 20)
Is = ImportMatrixVal(value=transpose(
array([
[2, 2, 2, 2, 2, 2, 2],
[0, 0, 0, 0, 0, 0, 0],
])))
Is_exp = transpose(
array([
[2, 1, -1, -2, -1, 1, 2],
[-1, 1, 2, 1, -1, -2, -1],
[-1, -2, -1, 1, 2, 1, -1],
]))
zp = M1.stator.get_pole_pair_number()
angle_rotor_initial = M1.comp_initial_angle()
angle_rotor_exp = linspace(0, 2 * pi / zp, 7) + angle_rotor_initial
Nr = ImportMatrixVal(value=ones(7) * 60 / zp)
test_obj.input = InCurrentDQ(time=time,
angle=angle,
Is=Is,
Ir=None,
angle_rotor=None,
Nr=Nr,
angle_rotor_initial=angle_rotor_initial,
rot_dir=1)
test_obj.input.gen_input()
assert_array_almost_equal(output.elec.time, linspace(0, 1, 7))
assert_array_almost_equal(output.elec.angle, linspace(0, 2 * pi, 20))
assert_array_almost_equal(output.elec.Is, Is_exp)
assert_array_almost_equal(output.elec.angle_rotor, angle_rotor_exp)
assert_array_almost_equal(output.elec.Nr, ones(7) * 60 / zp)
from pyleecan.Classes.ImportGenVectLin import ImportGenVectLin
from pyleecan.Classes.ImportMatrixVal import ImportMatrixVal
from pyleecan.Classes.ImportMatlab import ImportMatlab
from pyleecan.Classes.MagFEMM import MagFEMM
from pyleecan.Classes.Output import Output
from pyleecan.Tests import DATA_DIR
simu = Simu1(name="EM_SIPMSM_AL_001", machine=SIPMSM_001)
# Definition of the enforced output of the electrical module
Nr = ImportMatrixVal(value=ones(2) * 150)
Is = ImportMatrixVal(
value=array([[14.1421, -7.0711, -7.0711], [-14.1421, 7.0711, 7.0711]])
)
time = ImportGenVectLin(start=0, stop=0.1, num=2, endpoint=True)
angle = ImportGenVectLin(start=0, stop=2 * pi, num=1024, endpoint=False)
Ar = ImportMatrixVal(value=array([2.5219, 0.9511]) + pi / 6)
simu.input = InCurrent(
Is=Is,
Ir=None, # No winding on the rotor
Nr=None,
angle_rotor=Ar, # Will be computed
time=time,
angle=angle,
angle_rotor_initial=0,
)
# Definition of the magnetic simulation (is_mmfr=False => no flux from the magnets)
simu.mag = MagFEMM(
from pyleecan.Classes.InCurrent import InCurrent
from pyleecan.Classes.ImportGenVectLin import ImportGenVectLin
from pyleecan.Classes.ImportMatrixVal import ImportMatrixVal
from pyleecan.Classes.MagFEMM import MagFEMM
from pyleecan.Classes.ForceMT import ForceMT
from pyleecan.Classes.Output import Output
simu = Simu1(name="EM_IPMSM_FL_002", machine=IPMSM_A)
# Definition of the enforced output of the electrical module
Nr = ImportMatrixVal(value=ones(1) * 2504)
Is_mat = zeros((1, 3))
Is_mat[0, :] = array([0, 12.2474, -12.2474])
Is = ImportMatrixVal(value=Is_mat)
time = ImportGenVectLin(start=0, stop=0, num=1, endpoint=False)
angle = ImportGenVectLin(start=0, stop=2 * pi, num=2048, endpoint=False)
simu.input = InCurrent(
Is=Is,
Ir=None, # No winding on the rotor
Nr=Nr,
angle_rotor=None, # Will be computed
time=time,
angle=angle,
angle_rotor_initial=0.86,
)
# Definition of the magnetic simulation (no symmetry)
simu.mag = MagFEMM(
is_stator_linear_BH=0,
from pyleecan.Classes.InFlux import InFlux
from pyleecan.Classes.ImportGenVectLin import ImportGenVectLin
from pyleecan.Classes.ImportMatrixVal import ImportMatrixVal
from pyleecan.Classes.ImportMatlab import ImportMatlab
from pyleecan.Classes.MagFEMM import MagFEMM
from pyleecan.Classes.Output import Output
from pyleecan.Tests import DATA_DIR
simu = Simu1(name="EM_SCIM_NL_006", machine=SCIM_006)
# Definition of the enforced output of the electrical module
Nr = ImportMatrixVal(value=ones(1) * 1500)
Is = ImportMatrixVal(value=array([[20, -10, -10]]))
Ir = ImportMatrixVal(value=zeros((1, 28)))
time = ImportGenVectLin(start=0, stop=0, num=1, endpoint=False)
angle = ImportGenVectLin(start=0, stop=2 * pi, num=4096, endpoint=False)
simu.input = InCurrent(
Is=Is,
Ir=Ir, # zero current for the rotor
Nr=Nr,
angle_rotor=None, # Will be computed
time=time,
angle=angle,
angle_rotor_initial=0.2244,
)
# Definition of the magnetic simulation (no symmetry)
simu.mag = MagFEMM(is_stator_linear_BH=2,
is_rotor_linear_BH=2,
mat = uniform(0, 1, (4, 4))
# Direct import
ImportMatrix_test.append(
{"test_obj": ImportMatrixVal(value=mat, is_transpose=False), "exp": mat}
)
# Direct import transpose
ImportMatrix_test.append(
{"test_obj": ImportMatrixVal(value=mat, is_transpose=True), "exp": transpose(mat)}
)
# Lin Vector generation
exp = array([0, 1, 2, 3, 4, 5, 6, 7])
ImportMatrix_test.append(
{
"test_obj": ImportGenVectLin(
start=0, stop=7, num=8, endpoint=True, is_transpose=False
),
"exp": exp,
}
)
# Lin Vector generation + transpose
exp = transpose(array([0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]))
ImportMatrix_test.append(
{
"test_obj": ImportGenVectLin(
start=0, stop=1, num=10, endpoint=False, is_transpose=True
),
"exp": exp,
}
)
135.0,
150.0,
165.0,
180.0,
]) * pi / 180)
Is_list = list()
for Phi in Phi0:
Is = zeros((Nt_tot, qs))
for q in range(qs):
Is[:, q] = Imax * cos(2 * pi * freq0 * time - q * 2 * pi / qs + Phi)
Is_list.append(Is)
# Definition of the main simulation
simu = Simu1(name="EM_SynRM_FL_001", machine=SynRM_001)
time_obj = ImportMatrixVal(value=time)
angle = ImportGenVectLin(start=0, stop=2 * pi, num=2016, endpoint=False)
alpha_rotor = ImportMatrixVal(value=array([0, pi / 9, 2 * pi / 9]) + 2.6180)
simu.input = InCurrent(
Is=None,
Ir=None, # No winding on the rotor
Nr=None,
angle_rotor=alpha_rotor,
time=time_obj,
angle=angle,
angle_rotor_initial=0,
)
# Definition of the magnetic simulation (1/2 symmetry)
simu.mag = MagFEMM(
is_stator_linear_BH=0,
from numpy import linspace, ones, pi, zeros, array, sqrt, transpose from numpy.testing import assert_array_almost_equal from pyleecan.Classes.ImportGenMatrixSin import ImportGenMatrixSin from pyleecan.Classes.ImportGenVectLin import ImportGenVectLin from pyleecan.Classes.ImportGenVectSin import ImportGenVectSin from pyleecan.Classes.ImportMatrixVal import ImportMatrixVal from pyleecan.Classes.InCurrent import InCurrent from pyleecan.Classes.LamSlotWind import LamSlotWind from pyleecan.Classes.Machine import Machine from pyleecan.Classes.Simulation import Simulation from pyleecan.Methods.Simulation.Input import InputError InCurrent_Error_test = list() time_wrong = ImportMatrixVal(value=zeros((10, 2))) time = ImportGenVectLin(0, 10, 100) angle_wrong = ImportMatrixVal(value=zeros((10, 4))) angle = ImportGenVectLin(0, 2 * pi, 1024) I_1 = ImportMatrixVal(value=zeros((100, 3))) I_2 = ImportMatrixVal(value=zeros((100, 2))) I_3 = ImportMatrixVal(value=zeros((2, 100))) I_4 = ImportMatrixVal(value=zeros((100))) angle_rotor_wrong = ImportMatrixVal(value=zeros((10, 2))) angle_rotor_wrong2 = ImportMatrixVal(value=zeros((102))) angle_rotor = ImportMatrixVal(value=zeros((100))) Nr_wrong = ImportMatrixVal(value=zeros((10, 2))) Nr_wrong2 = ImportMatrixVal(value=zeros((102)))
def test_zdt3():
# ### Defining reference Output
# Definition of the enforced output of the electrical module
Nt = 2
Nr = ImportMatrixVal(value=np.ones(Nt) * 3000)
Is = ImportMatrixVal(value=np.array([
[6.97244193e-06, 2.25353053e02, -2.25353060e02],
[-2.60215295e02, 1.30107654e02, 1.30107642e02],
# [-6.97244208e-06, -2.25353053e02, 2.25353060e02],
# [2.60215295e02, -1.30107654e02, -1.30107642e02],
]))
Ir = ImportMatrixVal(value=np.zeros(30))
time = ImportGenVectLin(start=0, stop=0.015, num=Nt, endpoint=True)
angle = ImportGenVectLin(start=0, stop=2 * np.pi, num=64,
endpoint=False) # num=1024
# Definition of the simulation
simu = Simu1(name="Test_machine", machine=SCIM_001)
simu.input = InCurrent(
Is=Is,
Ir=Ir, # zero current for the rotor
Nr=Nr,
angle_rotor=None, # Will be computed
time=time,
angle=angle,
angle_rotor_initial=0.5216 + np.pi,
)
# Definition of the magnetic simulation
simu.mag = MagFEMM(
is_stator_linear_BH=2,
is_rotor_linear_BH=2,
is_symmetry_a=True,
is_antiper_a=False,
)
simu.mag.Kmesh_fineness = 0.01
# simu.mag.Kgeo_fineness=0.02
simu.mag.sym_a = 4
simu.struct = None
output = Output(simu=simu)
# ### Design variable
my_vars = {}
for i in range(30):
my_vars["var_" + str(i)] = OptiDesignVar(
name="output.simu.input.Ir.value[" + str(i) + "]",
type_var="interval",
space=[0, 1],
function=lambda space: np.random.uniform(*space),
)
# ### Objectives
objs = {
"obj1":
OptiObjFunc(
description="Maximization of the torque average",
func=lambda output: output.mag.Tem_av,
),
"obj2":
OptiObjFunc(
description="Minimization of the torque ripple",
func=lambda output: output.mag.Tem_rip,
),
}
# ### Evaluation
def evaluate(output):
x = output.simu.input.Ir.value
f1 = lambda x: x[0]
g = lambda x: 1 + (9 / 29) * np.sum(x[1:])
h = lambda f1, g: 1 - np.sqrt(f1 / g) - (f1 / g) * np.sin(10 * np.pi *
f1)
output.mag.Tem_av = f1(x)
output.mag.Tem_rip = g(x) * h(f1(x), g(x))
# ### Defining the problem
my_prob = OptiProblem(output=output,
design_var=my_vars,
obj_func=objs,
eval_func=evaluate)
solver = OptiGenAlgNsga2Deap(
problem=my_prob,
size_pop=40,
nb_gen=100,
p_mutate=0.5,
)
res = solver.solve()
def plot_pareto(self):
"""Plot every fitness values with the pareto front for 2 fitness
Parameters
----------
self : OutputMultiOpti
"""
# TODO Add a feature to return the design_varibles of each indiv from the Pareto front
# Get fitness and ngen
is_valid = np.array(self.is_valid)
fitness = np.array(self.fitness)
ngen = np.array(self.ngen)
# Keep only valid values
indx = np.where(is_valid)[0]
fitness = fitness[indx]
ngen = ngen[indx]
# Get pareto front
pareto = list(np.unique(fitness, axis=0))
# Get dominated values
to_remove = []
N = len(pareto)
for i in range(N):
for j in range(N):
if all(pareto[j] <= pareto[i]) and any(pareto[j] < pareto[i]):
to_remove.append(pareto[i])
break
# Remove dominated values
for i in to_remove:
for l in range(len(pareto)):
if all(i == pareto[l]):
pareto.pop(l)
break
pareto = np.array(pareto)
fig, axs = plt.subplots(1, 2, figsize=(16, 6))
# Plot Pareto front
axs[0].scatter(
pareto[:, 0],
pareto[:, 1],
facecolors="b",
edgecolors="b",
s=0.8,
label="Pareto Front",
)
axs[0].autoscale()
axs[0].legend()
axs[0].set_title("Pyleecan results")
axs[0].set_xlabel(r"$f_1(x)$")
axs[0].set_ylabel(r"$f_2(x)$")
try:
img_to_find = img.imread(
"pyleecan\\Tests\\Validation\\Optimization\\zdt3.jpg",
format="jpg")
axs[1].imshow(img_to_find, aspect="auto")
axs[1].axis("off")
axs[1].set_title("Pareto front of the problem")
except TypeError:
print("Pillow is needed to import jpg files")
return fig
fig = plot_pareto(res)
plt.savefig("pyleecan\\Tests\\Results\\Validation\\test_zdt3.png")
def test_Optimization_problem(self):
"""
Figure19: Machine topology before optimization
Figure20: Individuals in the fitness space
Figure21: Pareto Front in the fitness space
Figure22: Topology to maximize first torque harmonic
Figure22: Topology to minimize second torque harmonic
WARNING: The computation takes 6 hours on a single 3GHz CPU core.
The algorithm uses randomization at different steps so
the results won't be exactly the same as the one in the publication
"""
# ------------------ #
# DEFAULT SIMULATION #
# ------------------ #
# First, we need to define a default simulation.
# This simulation will the base of every simulation during the optimization process
# Load the machine
SPMSM_001 = load("pyleecan/Tests/Validation/Machine/SPMSM_001.json")
# Definition of the enforced output of the electrical module
Na = 1024 # Angular steps
Nt = 32 # Time step
Is = ImportMatrixVal(value=np.array([
[1.73191211247099e-15, 24.4948974278318, -24.4948974278318],
[-0.925435413499285, 24.9445002597334, -24.0190648462341],
[-1.84987984757817, 25.3673918959653, -23.5175120483872],
[-2.77234338398183, 25.7631194935712, -22.9907761095894],
[-3.69183822565029, 26.1312592975275, -22.4394210718773],
[-4.60737975447626, 26.4714170945114, -21.8640373400352],
[-5.51798758565886, 26.7832286350338, -21.2652410493749],
[-6.42268661752422, 27.0663600234871, -20.6436734059628],
[-7.32050807568877, 27.3205080756888, -20.0000000000000],
[-8.21049055044714, 27.5454006435389, -19.3349100930918],
[-9.09168102627374, 27.7407969064430, -18.6491158801692],
[-9.96313590233562, 27.9064876291883, -17.9433517268527],
[-10.8239220029239, 28.0422953859991, -17.2183733830752],
[-11.6731175767218, 28.1480747505277, -16.4749571738058],
[-12.5098132838389, 28.2237124515809, -15.7138991677421],
[-13.3331131695549, 28.2691274944141, -14.9360143248592],
[-14.1421356237309, 28.2842712474619, -14.1421356237310],
[-14.9360143248592, 28.2691274944141, -13.3331131695549],
[-15.7138991677420, 28.2237124515809, -12.5098132838389],
[-16.4749571738058, 28.1480747505277, -11.6731175767219],
[-17.2183733830752, 28.0422953859991, -10.8239220029240],
[-17.9433517268527, 27.9064876291883, -9.96313590233564],
[-18.6491158801692, 27.7407969064430, -9.09168102627375],
[-19.3349100930918, 27.5454006435389, -8.21049055044716],
[-20, 27.3205080756888, -7.32050807568879],
[-20.6436734059628, 27.0663600234871, -6.42268661752424],
[-21.2652410493749, 26.7832286350338, -5.51798758565888],
[-21.8640373400352, 26.4714170945114, -4.60737975447627],
[-22.4394210718772, 26.1312592975275, -3.69183822565031],
[-22.9907761095894, 25.7631194935712, -2.77234338398184],
[-23.5175120483872, 25.3673918959653, -1.84987984757819],
[-24.0190648462341, 24.9445002597334, -0.925435413499304],
]))
Nr = ImportMatrixVal(value=np.ones(Nt) * 400)
Ir = ImportMatrixVal(value=np.zeros((Nt, 28)))
time = ImportGenVectLin(start=0,
stop=1 / (400 / 60) / 24,
num=Nt,
endpoint=False)
angle = ImportGenVectLin(start=0,
stop=2 * np.pi,
num=Na,
endpoint=False)
SPMSM_001.name = (
"Default SPMSM machine" # Rename the machine to have the good plot title
)
# Definition of the simulation
simu = Simu1(name="Default simulation", machine=SPMSM_001)
simu.input = InCurrent(
Is=Is,
Ir=Ir, # zero current for the rotor
Nr=Nr,
angle_rotor=None, # Will be computed
time=time,
angle=angle,
angle_rotor_initial=0.39,
)
# Definition of the magnetic simulation
simu.mag = MagFEMM(
is_stator_linear_BH=2,
is_rotor_linear_BH=2,
is_symmetry_a=True,
is_antiper_a=False,
)
simu.mag.sym_a = 4
simu.struct = None
# Default Output
output = Output(simu=simu)
# Modify magnet width and the slot opening height
output.simu.machine.stator.slot.H0 = 0.001
output.simu.machine.rotor.slot.magnet[0].Wmag *= 0.98
# FIG21 Display default machine
output.simu.machine.plot()
fig = plt.gcf()
fig.savefig(
join(save_path, "fig_21_Machine_topology_before_optimization.png"))
fig.savefig(
join(save_path, "fig_21_Machine_topology_before_optimization.svg"),
format="svg",
)
# -------------------- #
# OPTIMIZATION PROBLEM #
# -------------------- #
# Objective functions
def harm1(output):
"""Return the average torque opposite (opposite to be maximized)"""
N = output.simu.input.time.num
x = output.mag.Tem[:, 0]
sp = np.fft.rfft(x)
sp = 2 / N * np.abs(sp)
return -sp[0] / 2
def harm2(output):
"""Return the first torque harmonic """
N = output.simu.input.time.num
x = output.mag.Tem[:, 0]
sp = np.fft.rfft(x)
sp = 2 / N * np.abs(sp)
return sp[1]
objs = {
"Opposite average torque (Nm)":
OptiObjFunc(description="Maximization of the average torque",
func=harm1),
"First torque harmonic (Nm)":
OptiObjFunc(
description="Minimization of the first torque harmonic",
func=harm2),
}
# Design variables
my_vars = {
"design var 1":
OptiDesignVar(
name="output.simu.machine.stator.slot.W0",
type_var="interval",
space=[
0.2 * output.simu.machine.stator.slot.W2,
output.simu.machine.stator.slot.W2,
],
function=lambda space: random.uniform(*space),
),
"design var 2":
OptiDesignVar(
name="output.simu.machine.rotor.slot.magnet[0].Wmag",
type_var="interval",
space=[
0.5 * output.simu.machine.rotor.slot.W0,
0.99 * output.simu.machine.rotor.slot.W0,
], # May generate error in FEMM
function=lambda space: random.uniform(*space),
),
}
# Problem creation
my_prob = OptiProblem(output=output, design_var=my_vars, obj_func=objs)
# Solve problem with NSGA-II
solver = OptiGenAlgNsga2Deap(problem=my_prob,
size_pop=12,
nb_gen=40,
p_mutate=0.5)
res = solver.solve()
# ------------- #
# PLOTS RESULTS #
# ------------- #
res.plot_generation()
fig = plt.gcf()
fig.savefig(join(save_path, "fig_20_Individuals_in_fitness_space.png"))
fig.savefig(join(save_path, "fig_20_Individuals_in_fitness_space.svg"),
format="svg")
res.plot_pareto()
fig = plt.gcf()
fig.savefig(join(save_path, "Pareto_front_in_fitness_space.png"))
fig.savefig(join(save_path, "Pareto_front_in_fitness_space.svg"),
format="svg")
# Extraction of best topologies for every objective
pareto = res.get_pareto() # Extraction of the pareto front
out1 = [pareto[0]["output"], pareto[0]["fitness"]] # First objective
out2 = [pareto[0]["output"], pareto[0]["fitness"]] # Second objective
for pm in pareto:
if pm["fitness"][0] < out1[1][0]:
out1 = [pm["output"], pm["fitness"]]
if pm["fitness"][1] < out2[1][1]:
out2 = [pm["output"], pm["fitness"]]
# Rename machine to modify the title
name1 = "Machine that maximizes the average torque ({:.3f} Nm)".format(
abs(out1[1][0]))
out1[0].simu.machine.name = name1
name2 = "Machine that minimizes the first torque harmonic ({:.4f}Nm)".format(
abs(out1[1][1]))
out2[0].simu.machine.name = name2
# plot the machine
out1[0].simu.machine.plot()
fig = plt.gcf()
fig.savefig(
join(save_path, "fig_21_Topology_to_maximize_average_torque.png"),
format="png",
)
fig.savefig(
join(save_path, "fig_21_Topology_to_maximize_average_torque.svg"),
format="svg",
)
out2[0].simu.machine.plot()
fig = plt.gcf()
fig.savefig(
join(save_path,
"fig_21_Topology_to_minimize_first_torque_harmonic.png"),
format="png",
)
fig.savefig(
join(save_path,
"fig_21_Topology_to_minimize_first_torque_harmonic.svg"),
format="svg",
)
def test_ecc_FEMM(self):
"""Figure 19: transfrom_list in FEMM for eccentricities
"""
simu = Simu1(name="ICEM_2020", machine=SPMSM_015)
simu.machine.name = "fig_19_Transform_list"
# Modify stator Rext to get more convincing translation
SPMSM_015.stator.Rext = SPMSM_015.stator.Rext * 0.9
gap = SPMSM_015.comp_width_airgap_mec()
# Definition of the enforced output of the electrical module
Nr = ImportMatrixVal(value=ones(1) * 3000)
Is = ImportMatrixVal(value=array([[0, 0, 0]]))
time = ImportGenVectLin(start=0, stop=0, num=1, endpoint=True)
angle = ImportGenVectLin(start=0,
stop=2 * 2 * pi / 9,
num=2043,
endpoint=False)
simu.input = InCurrent(
Is=Is,
Ir=None, # No winding on the rotor
Nr=Nr,
angle_rotor=None,
time=time,
angle=angle,
angle_rotor_initial=0,
)
# Definition of the magnetic simulation (is_mmfr=False => no flux from the magnets)
simu.mag = MagFEMM(
is_stator_linear_BH=0,
is_rotor_linear_BH=0,
is_sliding_band=False, # Ecc => No sliding band
is_symmetry_a=False, # No sym
is_mmfs=False,
is_get_mesh=True,
is_save_FEA=True,
sym_a=1,
)
simu.struct = None
# Set two transformations
# First rotate 3rd Magnet
transform_list = [{
"type": "rotate",
"value": 0.08,
"label": "MagnetRotorRadial_S_R0_T0_S3"
}]
# Then Translate the rotor
transform_list.append({
"type": "translate",
"value": gap * 0.75,
"label": "Rotor"
})
simu.mag.transform_list = transform_list
# Run the simulation
out = Output(simu=simu)
simu.run()
# FEMM files (mesh and results) are available in Results folder
copyfile(
join(out.path_res, "Femm", "fig_19_Transform_list_model.ans"),
join(save_path, "fig_19_Transform_list_model.ans"),
)
copyfile(
join(out.path_res, "Femm", "fig_19_Transform_list_model.fem"),
join(save_path, "fig_19_Transform_list_model.fem"),
)
# Plot, check, save
out.plot_mesh(mesh=out.mag.meshsolution.mesh[0], title="FEMM Mesh")
fig = plt.gcf()
fig.savefig(join(save_path, "fig_19_transform_list.png"))
fig.savefig(join(save_path, "fig_19_transform_list.svg"), format="svg")
from pyleecan.Classes.InCurrent import InCurrent
from pyleecan.Classes.InFlux import InFlux
from pyleecan.Classes.ImportGenVectLin import ImportGenVectLin
from pyleecan.Classes.ImportMatrixVal import ImportMatrixVal
from pyleecan.Classes.ImportMatlab import ImportMatlab
from pyleecan.Classes.MagFEMM import MagFEMM
from pyleecan.Classes.Output import Output
from pyleecan.Tests import DATA_DIR
simu = Simu1(name="EM_SPMSM_NL_001", machine=SPMSM_015)
# Definition of the enforced output of the electrical module
Nr = ImportMatrixVal(value=ones(1) * 3000)
Is = ImportMatrixVal(value=array([[0, 0, 0]]))
time = ImportGenVectLin(start=0, stop=0, num=1, endpoint=True)
angle = ImportGenVectLin(start=0,
stop=2 * 2 * pi / 9,
num=2043,
endpoint=False)
simu.input = InCurrent(
Is=Is,
Ir=None, # No winding on the rotor
Nr=Nr,
angle_rotor=None,
time=time,
angle=angle,
angle_rotor_initial=0,
)