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<p>To examine the effects of Pulse Width Modulation (PWM) waveform excitation on Soft Magnetic Composite (SMC) core losses, a magnetic characteristic testing platform with controllable magnetic flux density for PWM excitation is established. This platform measures SMC’s hysteresis and loss characteristics under varying flux densities and modulation ratios. The influence of PWM excitation characteristics on core losses is then analyzed. Concurrently, SMC particle and ring sample models are developed based on actual ring sample geometries, incorporating correction coefficients to facilitate effective computation of core losses during PWM excitation and subsequent error analysis. The simulation and experimental results indicate that the improved model proposed in this paper significantly reduces calculation error compared to the original model, with an overall error of less than 8%. This demonstrates high computational accuracy and suitability for engineering applications.</p>

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Study of Soft Magnetic Composite Core Loss Under PWM Waveform Excitation

  • 期刊论文

  • 发表日期：

    2025年3月4日

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  • Zhen Zhang,
  • Youhua Wang,
  • Chengcheng Liu,
  • Shipu Wu

摘要

To examine the effects of Pulse Width Modulation (PWM) waveform excitation on Soft Magnetic Composite (SMC) core losses, a magnetic characteristic testing platform with controllable magnetic flux density for PWM excitation is established. This platform measures SMC’s hysteresis and loss characteristics under varying flux densities and modulation ratios. The influence of PWM excitation characteristics on core losses is then analyzed. Concurrently, SMC particle and ring sample models are developed based on actual ring sample geometries, incorporating correction coefficients to facilitate effective computation of core losses during PWM excitation and subsequent error analysis. The simulation and experimental results indicate that the improved model proposed in this paper significantly reduces calculation error compared to the original model, with an overall error of less than 8%. This demonstrates high computational accuracy and suitability for engineering applications.