This paper proposes an improved common mode (CM) electromagnetic interference (EMI) suppression method in switching power supplies. The lossless snubber circuit can reduce du/dt and EMI in the high-frequency band. Nevertheless, it has a weak EMI suppression effect on the low-frequency band. A method combining the chaotic spread spectrum and the lossless snubber (CSS–LS) is proposed to improve the EMI suppression effect of the lossless snubber. It is an effective means to suppress CM EMI further. The paper used a Boost PFC converter as the object of analysis to study the CM EMI suppression effect of CSS–LS. Firstly, a CM EMI-equivalent model of the lossless snubber PFC converter was established. Then, the power spectral density function under chaotic spread-spectrum modulation was derived. The simulation analysis was performed. Finally, an experimental prototype was built, and relevant EMI tests were carried out. The experimental results show that CSS–LS can reduce CM EMI by 4~20 dBµV with little impact on converter stability. Fewer extra costs are needed for this optimization method, which is suitable for high-power-density power electronic devices.

When utilizing high-dimensional chaotic signals for frequency modulation, achieving a uniformly distributed power spectrum is a challenging task. This paper addresses this challenge by proposing a power spectrum homogenization strategy based on distribution transformation. The strategy transforms the task of achieving a uniformly distributed power spectrum in frequency modulation of high-dimensional chaotic signals to solve and equalize the probability density function of the chaotic signals, thereby further enhancing the ability of high-dimensional chaotic signals to suppress electromagnetic interference. Firstly, the difficulty of obtaining a smooth probability density function of chaotic modulation signals is solved using the kernel density estimation algorithm. Then, a distribution transformation algorithm is proposed to convert non-uniformly distributed chaotic modulation signals into uniformly distributed chaotic modulation signals. By using uniformly distributed chaotic modulation signals for frequency modulation, the objective of power spectrum equalization is achieved. Finally, taking the Chua’s chaotic signal as an example, the effectiveness of the proposed strategy is verified using an experimental platform based on a digital signal processor-controlled active clamping flyback converter.

Given the constraints on the invariant distribution in chaotic systems, flexibly setting the probability distribution of chaotic signals poses a significant challenge. To tackle this issue, this paper proposes a strategy that transforms the task into solving and modifying the probability density function of the chaotic intrinsic signal. Initially, kernel density estimation algorithms are employed to address the issue of obtaining smooth probability density functions for high-dimensional chaotic signals. Any chaotic signal can serve as the intrinsic signal source, with its probability density function and distribution function being solvable using this algorithm. Subsequently, a graph-based transformation algorithm is introduced for the flexible adjustment of chaotic signal probability distribution. This algorithm can convert the intrinsic signal into a chaotic signal with the desired distribution type based on the characteristics of the target distribution, providing an analytical expression for the transformation relationship. Finally, the effectiveness of this strategy is validated by generating uniform distribution chaotic signals using a Chua chaotic signal as the intrinsic source. The outstanding performance of this signal in suppressing common-mode conducted electromagnetic interference in high-frequency converters is highlighted. The experimental results demonstrate this strategy’s ability to flexibly configure probability distribution types of chaotic signals. Additionally, chaotic signals with a uniform distribution can achieve uniform power spectrum shaping, with a suppression effect on maximum common-mode conducted electromagnetic interference reaching 16.56 dB.