Some new files and a Scipt to plot saved data

DriCy_Selo.py

@@ -651,6 +651,7 @@ def read_drive_cycle(file, vehicle):
     return(cycle, variable_names)
 
 def calc_con(vehicle, qns, qTs):
+    """Calculation of conture plots in the torque-speed plane."""
     ns = np.linspace(1,float(vehicle['basic']['n_max'])/60,qns) 
     T_max = 3/2 * vehicle['electric']['zp'] * ( (vehicle['electric']['PSI'] * (vehicle['electric']['I_max']/np.sqrt(2)) ) + (vehicle['electric']['Ld']-vehicle['electric']['Lq'])*-(vehicle['electric']['I_max']/np.sqrt(2))**2 )
     T_max = np.ceil( T_max/100)*100

README.md

 # DriCy_Selo module
 
-Created on Thu Mar  4 08:53:28 2021
+Created on Thu Oct  27 08:53:28 2022
 
 @author:    Michael Schlüter
 
@@ -11,6 +11,18 @@ Created on Thu Mar  4 08:53:28 2021
 > [m.schlueter@tu-berlin.de](mailto:m.schlueter@tu-berlin.de)
 
 
+## How to install
+Requirement:
+- Python 3.10
+
+```
+git clone https://git.tu-berlin.de/mschluet/dricy-selo.git <clone/copy repository>
+cd dricy-selo <change to folder>
+py -3.10 -m pip install . <Install Scipt and needed packages>
+(pip(3) install .) <alternative>
+DriCy_Selo.exe main  <Start Program and enjoy>
+```
+
 ### _class_ DriCy_Selo.Config()
 Bases: `object`
 

load_plot_save.py

+# -*- coding: utf-8 -*-
+"""
+Created on Tue May 31 13:27:15 2022
+
+@author: Micha
+"""
+import pickle
+import matplotlib.pyplot as plt
+from matplotlib import cm
+import os
+import matplotlib.ticker
+import numpy as np
+
+plt.rcParams.update({
+        "text.usetex": True,
+        "font.family": "serif",
+        "font.serif": "Times",
+        "font.size": 11,
+        "legend.fontsize": 11,
+        "xtick.labelsize": 10,
+        "ytick.labelsize": 10,
+        "text.latex.preamble": r'\usepackage{siunitx} \sisetup{detect-all} \usepackage{helvet} \usepackage{sansmath} \sansmath' # makes the plot very slow but I want to use sans-serif font
+        })
+
+print(os.listdir('save'))
+
+[cycle, variable_names] = pickle.load( open(os.path.join('save', 'EQS 450+ 800 V_WLTC_Class_3_v53_2022_10_22_14-31.p'),'rb') )
+
+
+cycle[:,25][-1] / (cycle[:,25][-1] + cycle[:,19][-1]) # ETA MOSFET
+
+cycle[:,25][-1] / (cycle[:,25][-1] + cycle[:,24][-1]) # ETA IGBT
+
+max(cycle[:,1]) # max speed
+
+max(cycle[:,6]) # max Power
+
+np.average(abs(cycle[:,6]))/1000 # average Power
+
+np.cumsum(cycle[:,4])[-1] # distance traveld
+
+# fig, ax = plt.subplots(figsize=(6,5))
+# p1 = ax.plot(cycle[:,0], cycle[:,nr], label = variable_names[nr])
+# # p2 = ax.bar(labels, V_inv_sim, label = 'Ploss inverter sim', alpha = .6)
+# # p3 = ax.bar(labels, V_s_sim, label='Ploss static sim', alpha = .6)
+# # p4 = ax.bar(labels, V_d_sim, bottom = V_s_sim, label='Ploss dynamic sim', alpha = .6)
+# ax.legend(loc=1)
+# if nr >=14:
+#     ax.set_ylim( (0, max( max(cycle[:,14]), max(cycle[:,17]) ) ) )
+# #ax.set_xlim(43.5,72.5)
+# #ax.bar_label(p1,fmt='%0.4f', label_type='edge')
+# # ax.bar_label(p2,fmt='%0.0f', label_type='edge')
+# # ax.bar_label(p3,fmt='%0.0f', label_type='center')
+# # ax.bar_label(p4,fmt='%0.0f', label_type='center')
+# ax.set_ylabel(variable_names[nr])
+# ax.set_xlabel('Time [s]')
+# ax.grid(True, axis='both', ls="-", color='0.8')
+
+
+fig, ax = plt.subplots(figsize=(6,5))
+nr = 1
+p1 = ax.plot(cycle[0:590,0], cycle[0:590,nr],'tab:blue', label = variable_names[nr])
+p2 = ax.plot(cycle[589:1023,0], cycle[589:1023,nr], 'tab:green', label = variable_names[nr])
+p3 = ax.plot(cycle[1022:1476,0], cycle[1022:1476,nr], 'tab:orange', label = variable_names[nr])
+p4 = ax.plot(cycle[1475:1801,0], cycle[1475:1801,nr], 'tab:red', label = variable_names[nr])
+ax.set_ylabel(variable_names[nr])
+ax.yaxis.set_label_coords(-.07, .4)
+ax.set_xlabel('Time [s]')
+ax2 = ax.twinx()
+nr = 3
+p1 = ax2.plot(cycle[0:590,0], cycle[0:590,nr],'tab:blue', label = variable_names[nr])
+p2 = ax2.plot(cycle[589:1023,0], cycle[589:1023,nr], 'tab:green', label = variable_names[nr])
+p3 = ax2.plot(cycle[1022:1476,0], cycle[1022:1476,nr], 'tab:orange', label = variable_names[nr])
+p4 = ax2.plot(cycle[1475:1801,0], cycle[1475:1801,nr], 'tab:red', label = variable_names[nr])
+ax2.set_ylabel(r'acceleration $[m/s^2]$')
+ax2.yaxis.set_label_coords(1.1, 0.9)
+# ax2.set_xlabel('Time [s]')
+#ax.legend(loc=1)
+ax2.set_ylim((-19,3))
+ax.set_ylim((0,210))
+ax.set_yticks([0,20,40,60,80,100,120,140,160])
+ax2.set_yticks([-1.5,0,1.5])
+ax2.grid(True, axis='y')
+ax.grid(True, axis='both', ls="-", color='0.8')
+fig.tight_layout()
+# plt.savefig('WoWo2.svg')
+
+
+fig, ax = plt.subplots(figsize=(6,5))
+nr = 15 # P_total_MOSFET
+p1 = ax.plot(cycle[:,0], cycle[:,nr],'tab:blue', label = variable_names[nr], linewidth=1.0, alpha = 0.6)
+nr = 20 # P_total_IGBT
+p2 = ax.plot(cycle[:,0], cycle[:,nr], 'tab:green', label = variable_names[nr], linewidth=1.0, alpha = 0.6)
+#p3 = ax.plot(cycle[1022:1476,0], cycle[1022:1476,nr], 'tab:orange', label = variable_names[nr])
+#p4 = ax.plot(cycle[1475:1801,0], cycle[1475:1801,nr], 'tab:red', label = variable_names[nr])
+ax.set_ylabel(variable_names[15] + ' / ' + variable_names[20])
+#ax.yaxis.set_label_coords(-.07, .4)
+ax.set_xlabel('Time [s]')
+ax2 = ax.twinx()
+nr = 19 # E_total_MOSFET
+p1 = ax2.plot(cycle[:,0], cycle[:,nr],'tab:blue', label = variable_names[nr], linewidth=3.0, alpha = 0.8)
+nr = 24 # E_total_IGBT
+p2 = ax2.plot(cycle[:,0], cycle[:,nr], 'tab:green', label = variable_names[nr], linewidth=3.0, alpha = 0.8)
+#p3 = ax2.plot(cycle[:,0], cycle[1022:1476,nr], 'tab:orange', label = variable_names[nr])
+#p4 = ax2.plot(cycle[1475:1801,0], cycle[1475:1801,nr], 'tab:red', label = variable_names[nr])
+ax2.set_ylabel(variable_names[19] + ' / ' + variable_names[24])
+#ax2.yaxis.set_label_coords(1.1, 0.9)
+# ax2.set_xlabel('Time [s]')
+ax2.legend(['MOSFET', 'IGBT'], loc=0)
+#ax2.set_ylim((-19,3))
+#ax.set_ylim((0,210))
+#ax.set_yticks([0,20,40,60,80,100,120,140,160])
+#ax2.set_yticks([-1.5,0,1.5])
+#ax2.grid(True, axis='y')
+ax.grid(True, axis='both', ls="-", color='0.8')
+fig.tight_layout()
+
+
+
+# datan in MJ/kg, MJ/L -> 1/3.6 to kW/(L / kg)
+data = (
+    ('Butanol', 36.6, 29.2, {'halign': 'right', 'valign': 'top', 'x': 0, 'y': 0}),
+    ('Diesel', 46.2, 37.3, {'halign': 'right', 'valign': 'bottom', 'x': 0, 'y': 0}),
+    ('Ethanol', 30, 24, {'halign': 'right', 'valign': 'top', 'x': 0, 'y': 0}),
+    ('Gasoline', 46.4, 34.2, {'halign': 'left', 'valign': 'center', 'x': 0, 'y': 0}),
+    ('Hydrogen gas', 143, 0.01079),
+    ('Hydrogen gas (700 bar)', 143, 5.6, {'valign': 'top', 'x': 0}),
+    ('Kerosene', 42.8, 33, {'halign': 'right', 'valign': 'center', 'x': 0, 'y': 0}),
+    ('Liquid hydrogen', 143, 10.1),
+    ('Liquid natural gas', 53.6, 22.2, {'halign': 'left', 'valign': 'top', 'x': 0, 'y': 0}),
+    ('LPG propane', 49.6, 25.3, {'halign': 'left', 'valign': 'center', 'x': 0}),
+    ('Lead-acid battery', 0.14, 0.27, {'halign': 'left', 'valign': 'top', 'x': 0, 'y': 0}),
+    ('Methanol', 19.7, 15.6, {'halign': 'right', 'valign': 'top', 'x': 0, 'y': 0}),
+    ('Natural gas', 53.6, 0.0364),
+    ('Natural gas (250 bar)', 53.6, 9, {'valign': 'top', 'x': 0}),
+    ('Zinc–air battery', 1.59, 6.02),
+    # 0.54-0.72, 0.9-1.9 (values used are from the Li-Ion battery article)
+    ('LiFePO4 battery', 0.58, 1.2),
+    ('NMC battery', 0.74, 2.1),
+)
+
+#https://en.wikipedia.org/wiki/Comparison_of_commercial_battery_types
+#https://en.wikipedia.org/wiki/Energy_density
+
+# font12 = FontProperties(family=['serif'], size=12)
+# font10 = FontProperties(family=['serif'], size=10)
+# font8 = FontProperties(family=['serif'], size=8)
+
+# plt.rcParams.update({'figure.figsize': [12, 7.5]})
+fig, ax = plt.subplots(figsize=(6,5))
+# fig=plt.figure(1)
+# ax=plt.axes([0.05, 0.07, 0.97 - 0.05, 0.95 - 0.07])
+
+for v in data:
+    # (name, MJ/kg, MJ/L, label-adjustments)
+    label = v[0]
+    x = v[1]/3.6
+    y = v[2]/3.6
+
+    if len(v) < 4:
+        halign = 'center'
+        valign = 'bottom'
+        x_text = x
+        y_text = y 
+    else:
+        halign = v[3].get('halign', 'center')
+        valign = v[3].get('valign', 'bottom')
+        x_text = x + v[3].get('x', 0)
+        y_text = y + v[3].get('y', 0)
+        if valign == 'bottom':
+            y_text += 0
+        elif valign == 'top':
+            y_text -= 0
+
+    plt.scatter(x=[x], y=[y], c='r', s=5 , marker = 'o', alpha=(.8))
+    plt.text(x=x_text, y=y_text, s=label,
+                horizontalalignment=halign,
+                verticalalignment=valign,)
+#               fontproperties=font10)
+
+#plt.title('Selected energy densities')#,
+            #fontproperties=font12)
+
+plt.ylabel('kWh/L')#, fontproperties=font10)
+plt.xlabel('kWh/kg')#, fontproperties=font10)
+
+# plt.xticks(fontproperties=font8)
+# plt.yticks(fontproperties=font8)
+fmt = matplotlib.ticker.StrMethodFormatter("{x}")
+ax.xaxis.set_major_formatter(fmt)
+ax.yaxis.set_major_formatter(fmt)
+
+
+# ax.xaxis.grid(True)
+# ax.yaxis.grid(True)
+ax.grid(True, axis='both', ls="-", color='0.9', which="both")
+ax.set_axisbelow(True)
+ax.set_yscale('log')
+ax.set_xscale('log')
+
+plt.xlim(3e-2, 2e2)
+# #plt.ylim(1e-2, 1e2)
+
+# plt.savefig('energy_density2.svg')
+
+
+# # surf/countour plot
+# b1=1
+# b2=0.003
+# b3=0.000017
+# b4=0.0000082
+# b5=0.000000018
+# b6=0.00000096
+
+
+# def f(T,n):
+#     return 2*np.pi*n*(T-(b1 + b2*T +b3*n+b4*T**2+b5*n**2+b6*T*n)) / (2*np.pi*n*T)
+# #plt.style.use('seaborn-white')
+
+# T = np.linspace(0,250,100)
+# n = np.linspace(0,12500,100)
+
+# X, Y = np.meshgrid(n, T)
+# Z = f(Y,X)
+
+
+# cf = plt.contourf(X, Y, Z, np.linspace(0 ,1,3)**(1/6),  vmax=1, colors=['red','blue','green']);
+# CBI = plt.colorbar(cf, orientation='vertical')