为了提升锂离子电池组均衡系统的性能,提出了一种基于模糊自适应模型预测控制(fuzzy adaptive model predictive control,FAMPC)的模块化均衡系统。首先,由改进的buck-boost电路和反激变压器组成双层均衡拓扑结构;其次,以不同电池剩余容...为了提升锂离子电池组均衡系统的性能,提出了一种基于模糊自适应模型预测控制(fuzzy adaptive model predictive control,FAMPC)的模块化均衡系统。首先,由改进的buck-boost电路和反激变压器组成双层均衡拓扑结构;其次,以不同电池剩余容量(state of charge,SOC)的状态作为模糊逻辑算法的输入,对均衡电流的约束条件进行调节;再次,基于FAMPC均衡控制方法,直接利用开关管的占空比作为系统输入;最后,在改变电池组状态并不使用额外电流控制机制的情况下进行仿真实验。结果表明,与传统的模糊控制方法相比,所提系统在正常条件下均衡速度提高了约24.51%,在电池低SOC的极端条件下均衡速度可以进一步提高至34.48%。所提系统将模糊算法提供的稳定性与模型预测控制算法的快速性相结合,保证了电池组更安全稳定的运行,可为电池组性能提升研究提供参考。展开更多
近年来,随着我国科学技术的发展,金融业也发生了显著的变化。在多元化金融领域,以金融科技为首的多元化金融体系逐渐占据主导地位。金融科技的出现对提升金融服务效率起到了非常重要的作用。然而,金融科技与金融科技风险密切相关。本文...近年来,随着我国科学技术的发展,金融业也发生了显著的变化。在多元化金融领域,以金融科技为首的多元化金融体系逐渐占据主导地位。金融科技的出现对提升金融服务效率起到了非常重要的作用。然而,金融科技与金融科技风险密切相关。本文运用AHP + 模糊综合评价模型,寻求50位金融专家对金融业风险进行综合量化,探究当前我国金融业风险的主导因素,从而进行可预测的干预。研究发现,技术风险、道德风险和法律风险,权重为76%,模糊评价指标为“高”,是影响金融科技风险的主要因素,而传统金融风险占多数但仅占24%。虽然权重占比不大,但仍不容忽视。本文旨在对模糊的金融业风险进行量化,探讨金融科技风险和传统金融风险在当前金融业中的主导地位,得出面对中国金融业未来的发展,需要更加重视介入金融科技带来的风险,以优化资源配置,但传统金融风险也不容忽视。In recent years, with the development of science and technology in China, the financial industry has also undergone significant changes. In the diversified financial field, the diversified financial system headed by financial technology gradually occupies a dominant position. The cash of financial technology has played a very important role in improving the efficiency of financial services. However, fintech goes hand in hand with fintech risks. This paper uses AHP + fuzzy comprehensive evaluation model, seeks 50 financial experts to comprehensively quantify the risk of financial industry, and explores the leading factors of China’s financial industry risks at present, so as to make predictable intervention. It is found that technical risk, moral risk and legal risk, with a weight of 76% and a fuzzy evaluation index of “high”, are the main factors affecting financial technology risks, while traditional financial risks account for the majority but only account for 24%. Although the weight ratio is not large, it still cannot be ignored. The purpose of this paper is to quantify the vague financial industry risks, explore the dominance of financial technology risks and traditional financial risks in the current financial industry, and conclude that in the face of the future development of China’s financial industry, it is necessary to pay more attention to intervening in the risks brought by financial technology, so as to optimize resource allocation, but traditional financial risks cannot be ignored.展开更多
文摘为了提升锂离子电池组均衡系统的性能,提出了一种基于模糊自适应模型预测控制(fuzzy adaptive model predictive control,FAMPC)的模块化均衡系统。首先,由改进的buck-boost电路和反激变压器组成双层均衡拓扑结构;其次,以不同电池剩余容量(state of charge,SOC)的状态作为模糊逻辑算法的输入,对均衡电流的约束条件进行调节;再次,基于FAMPC均衡控制方法,直接利用开关管的占空比作为系统输入;最后,在改变电池组状态并不使用额外电流控制机制的情况下进行仿真实验。结果表明,与传统的模糊控制方法相比,所提系统在正常条件下均衡速度提高了约24.51%,在电池低SOC的极端条件下均衡速度可以进一步提高至34.48%。所提系统将模糊算法提供的稳定性与模型预测控制算法的快速性相结合,保证了电池组更安全稳定的运行,可为电池组性能提升研究提供参考。
文摘近年来,随着我国科学技术的发展,金融业也发生了显著的变化。在多元化金融领域,以金融科技为首的多元化金融体系逐渐占据主导地位。金融科技的出现对提升金融服务效率起到了非常重要的作用。然而,金融科技与金融科技风险密切相关。本文运用AHP + 模糊综合评价模型,寻求50位金融专家对金融业风险进行综合量化,探究当前我国金融业风险的主导因素,从而进行可预测的干预。研究发现,技术风险、道德风险和法律风险,权重为76%,模糊评价指标为“高”,是影响金融科技风险的主要因素,而传统金融风险占多数但仅占24%。虽然权重占比不大,但仍不容忽视。本文旨在对模糊的金融业风险进行量化,探讨金融科技风险和传统金融风险在当前金融业中的主导地位,得出面对中国金融业未来的发展,需要更加重视介入金融科技带来的风险,以优化资源配置,但传统金融风险也不容忽视。In recent years, with the development of science and technology in China, the financial industry has also undergone significant changes. In the diversified financial field, the diversified financial system headed by financial technology gradually occupies a dominant position. The cash of financial technology has played a very important role in improving the efficiency of financial services. However, fintech goes hand in hand with fintech risks. This paper uses AHP + fuzzy comprehensive evaluation model, seeks 50 financial experts to comprehensively quantify the risk of financial industry, and explores the leading factors of China’s financial industry risks at present, so as to make predictable intervention. It is found that technical risk, moral risk and legal risk, with a weight of 76% and a fuzzy evaluation index of “high”, are the main factors affecting financial technology risks, while traditional financial risks account for the majority but only account for 24%. Although the weight ratio is not large, it still cannot be ignored. The purpose of this paper is to quantify the vague financial industry risks, explore the dominance of financial technology risks and traditional financial risks in the current financial industry, and conclude that in the face of the future development of China’s financial industry, it is necessary to pay more attention to intervening in the risks brought by financial technology, so as to optimize resource allocation, but traditional financial risks cannot be ignored.
