Transistor reliability voltage dependence (πU) formulas & tables

SN29500-3 specifies the following relationship for the voltage a transistor is used at:

\[ \pi_U = \exp \left\{ C_3 \times \left( \left( \frac{U}{U_{\text{max}}} \right)^{C_2} - \left( \frac{U_{\text{ref}}}{U_{\text{max}}} \right)^{C_2} \right) \right\} \]

where:

Since the constants are the same for all transistors, the formula can be simplified to:

\[ \pi_U = \exp \left\{ 1.4 \times \left( \left( \frac{U}{U_{\text{max}}} \right)^8 - \frac{1}{256} \right) \right\} \]

Plotting $π_U$ using Python

pi U voltage dependence.svg

example.py
#!/usr/bin/env python3
import numpy as np
import matplotlib.pyplot as plt

# Constants from the formula
C2 = 8
C3 = 1.4
U_ref = 0.5  # 50% of U_max (as a fraction)

# Voltage range from 1% to 100% of U_max
voltage_percent = np.linspace(1, 100, 1000)
voltage_fraction = voltage_percent / 100

# Calculate pi_U
pi_U = np.exp(C3 * ((voltage_fraction)**C2 - (U_ref)**C2))

# Create the plot
plt.figure(figsize=(10, 6))
plt.plot(voltage_percent, pi_U, 'b-', linewidth=2)
plt.title('Voltage Dependence Factor $\pi_U$')
plt.xlabel('Operating Voltage (% of $U_{\max}$)')
plt.ylabel('$\pi_U$')
plt.grid(True, linestyle='--', alpha=0.7)
plt.xlim(1, 100)
plt.xticks(np.arange(0, 101, 10))  # Percentage ticks every 10%

# Mark the reference voltage (50%)
plt.axvline(x=50, color='r', linestyle='--', label=f'$U_{{ref}} = 50\%$ of $U_{{max}}$')
plt.legend()

plt.savefig('pi_U_voltage_dependence.svg')

Table of $π_U$ values at specific voltage percentages:

Voltage Dependence Factor (π_U) for 60V Transistor

Voltage (% of U_max)π_U
1%0.994546
2%0.994546
3%0.994546
4%0.994546
5%0.994546
6%0.994546
7%0.994546
8%0.994546
9%0.994546
10%0.994546
11%0.994546
12%0.994546
13%0.994546
14%0.994546
15%0.994547
16%0.994547
17%0.994547
18%0.994548
19%0.994549
20%0.994550
21%0.994551
22%0.994554
23%0.994557
24%0.994562
25%0.994567
26%0.994575
27%0.994586
28%0.994599
29%0.994616
30%0.994638
31%0.994665
32%0.994699
33%0.994742
34%0.994795
35%0.994860
36%0.994939
37%0.995035
38%0.995152
39%0.995292
40%0.995459
41%0.995659
42%0.995895
43%0.996175
44%0.996504
45%0.996890
46%0.997341
47%0.997867
48%0.998478
49%0.999184
50%1.000000
51%1.000939
52%1.002018
53%1.003253
54%1.004664
55%1.006274
56%1.008104
57%1.010183
58%1.012538
59%1.015202
60%1.018210
61%1.021600
62%1.025416
63%1.029706
64%1.034520
65%1.039918
66%1.045962
67%1.052724
68%1.060281
69%1.068721
70%1.078141
71%1.088648
72%1.100363
73%1.113419
74%1.127969
75%1.144181
76%1.162248
77%1.182386
78%1.204841
79%1.229892
80%1.257861
81%1.289113
82%1.324071
83%1.363224
84%1.407137
85%1.456473
86%1.512005
87%1.574641
88%1.645459
89%1.725736
90%1.816997
91%1.921075
92%2.040179
93%2.176996
94%2.334804
95%2.517635
96%2.730478
97%2.979549
98%3.272648
99%3.619637
100%4.033084

Check out similar posts by category: Functional Safety, Reliability, Electronics, Components