氢燃料电池数字孪生技术的系统集成与智能管理:研究进展与未来挑战

System integration and intelligent management of hydrogen fuel cells based on digital twin technology: research progress and future challenges

  • 摘要: 随着温室效应等环境问题的日益突出,化石资源存在的问题越来越明显,寻求可替代的绿色能源是大势所趋,而燃料电池是未来发展趋势,发展燃料电池是非常有前景的工作。同时,随着互联网技术的发展,大数据,云计算和物联网等新兴技术迎来了蓬勃的发展,数字孪生技术得到了广泛的应用。通过构建氢燃料电池数字孪生模型,能够实现对电池运行状态的实时监控和动态分析,有效预测电池的退化趋势和潜在故障,从而提前采取维护措施,延长电池寿命。本文对燃料电池结构、数字孪生技术原理及关键技术进行了简要概述,并且针对数字孪生应用于燃料电池六大系统可行性进行了分析,探讨了数字孪生技术在热管理、水管理、气管理、故障诊断、故障预测、剩余使用寿命预测、健康状态估计、系统优化等方面的潜力和实际应用情况。同时,针对目前数字孪生在氢燃料电池上面的研究进行了归纳总结,并提出了一种基于数字孪生的先进燃料电池管理系统,旨在为后续氢燃料电池数字化工作提供借鉴意义。

     

    Abstract: With the greenhouse effect and other environmental problems becoming more and more prominent, the problem of fossil resources is becoming more and more obvious, and the search for alternative green energy is the general trend. Therefore, fuel cell is the future development trend, the development of fuel cell is very promising work, in which hydrogen fuel cell due to its high efficiency, cleanliness, pollution-free characteristics gradually received attention and ushered in the development opportunities. At the same time, with the development of Internet technology, big data, cloud computing and the Internet of Things and other emerging technologies have ushered in the vigorous development of digital twin industrial technology has been widely used. By constructing a digital twin model of hydrogen fuel cell, real-time monitoring and dynamic analysis of the battery operation state can be realized, and the degradation trend and potential failure of the battery can be effectively predicted, so that maintenance measures can be taken in advance to extend the battery life. In addition, digital twin technology also provides an efficient simulation platform for battery design, which helps to optimize battery performance and reduce the research and development cost. In this paper, a brief overview of the fuel cell structure, principles and key technologies of digital twin technology is given, and statistics on the application of hydrogen fuel cells in new energy vehicles in recent years are presented. Then it analyzes the feasibility of applying digital twins to the six systems of fuel cells, and discusses the potential and practical applications of digital twin technology in thermal management, water management, gas management, fault diagnosis, fault prediction, remaining service life prediction, health state estimation, and system optimization. Meanwhile, the current research on digital twins over hydrogen fuel cells is summarized, and an advanced fuel cell management system based on digital twins is proposed, aiming to provide a reference meaning for the subsequent digitization work on hydrogen fuel cells.

     

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