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Statistical Analysis of the Serial Connected Diode Chain Under Reverse Bias Devices

机译:反向偏置装置下串联二极管链的统计分析

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This article deals with the reverse voltage distribution along a chain of large number serial connected power silicon diodes. Reverse properties of an individual diode can be affected by random influences of its production process. The consequence of this fact implies an inequality distribution of reverse bias inside the diode chain. This is the cause of so called High Voltage Diode Stack (HVDS). Each HVDS consists of 50-100 diode chips and its total reverse voltage usually exceeds 100 kV. While reverse current - voltage characteristics can be measured in detail for each diode chip, no direct measurement of the voltage distribution is possible during operation HVDS, with respect to the its compact construction. That is why a physical model was created for the course of reverse current - voltage HVDS' characteristics and sufficiently precise estimations were made by means of suitable statistical methods as to the individual voltage distribution. This model is also generalized for case of avalanche multiplication. Important conditions of the device reliable operation are defined and the courses of real and computed characteristics are compared. It is shown that the credible prediction can be made as to the reverse characteristics shapes model at low and high applied voltages.
机译:本文涉及沿着大量串行连接功率硅二极管链的反向电压分布。各个二极管的反向特性可能受到其生产过程的随机影响的影响。该事实的结果意味着二极管链内反向偏置的不等式分布。这是所谓的高压二极管堆栈(HVDS)的原因。每个HVDS由50-100二极管芯片组成,其总反向电压通常超过100kV。虽然可以对每个二极管芯片详细测量反向电流 - 电压特性,但是在操作HVDS期间没有直接测量电压分布,相对于其紧凑的结构。这就是为什么在反向电流 - 电压HVDS的过程中创建物理模型的特性以及通过适当的统计方法对各个电压分布进行充分精确的估计。对于雪崩乘法的情况,该模型也概括。定义了设备可靠操作的重要条件,并比较了实际和计算特性的课程。结果表明,可以在低施加电压下对逆转特性进行可信预测。

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