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Description
The basic operation of a Marx generator is well known and simple: capacitors are charged in parallel through high impedances and discharged in series, thus multiplying the output voltage compared to the charging voltage. As a basic explanation, in a Marx generator using spark gap switches, triggering the first stage is sufficient to double the voltage on the second stage’s switch and so on. All the switches are then switched on in an avalanche mode. However, the behaviour is often more complex. The parasitic impedances of the geometry play an important role for the creation of overvoltages. This can make the design and the development of Marx generators quite challenging, especially when aiming for good reproducibility and precise timing.
To achieve the best performances, various triggering techniques have been developed, but unfortunately, there is no “best practice” technique that can be applied systematically. For each new design, the engineers must establish the best way to obtain the required performances. If the initial choice of the triggering scheme does not achieve the expected performances, a lot of time could be spent experimenting to optimize the triggering scheme. This study presents SPICE simulation methods that could be helpful to compare different triggering schemes and their effects on the generator erection time, jitter and reliability.
By using a spark gap model, the simulations presented give a thorough understanding of the benefits and drawbacks of the various available triggering schemes. These simulations could facilitate the optimization of the erection time and the delay by adjusting triggering methods. Secondly, by coupling LTspice and Python, a more complete approach is presented to take into account the statistical behaviour of the closing time of the switches and its effects on the jitter and the complete generator’s operation efficiency.
