Naturally degradable capsule provides a platform for sustained fragrance release.However,practical challenges such as low encapsulation efficiency and difficulty in sustained release are still limited in using fragran...Naturally degradable capsule provides a platform for sustained fragrance release.However,practical challenges such as low encapsulation efficiency and difficulty in sustained release are still limited in using fragranceloaded capsules.In this work,the natural materials sodium alginate and gelatine are dissolved and act as the aqueous phase,lavender is dissolved in caprylic/capric triglyceride(GTCC)as the oil phase,and SiO_(2) nanoparticles with neutralwettability as a solid emulsifier to form O/W Pickering emulsions simultaneously.Finally,multi-core capsules are prepared using the drop injection method with emulsions as templates.The results show that the capsules have been successfully prepared with a spherical morphology and multi-core structure,and the encapsulation rate of multi-core capsules can reach up to 99.6%.In addition,the multi-core capsules possess desirable sustained release performance,the cumulative sustained release rate of fragrance at 25℃over 49 days is only 32.5%.It is attributed to the significant protection of multi-core structure,Pickering emulsion nanoparticle membranes,and hydrogel network shell for encapsulated fragrance.This study is designed to deliver a new strategy for using sustained-release technology with fragrance in food,cosmetics,textiles,and other fields.展开更多
由于可再生能源的间歇性特点,储能单元广泛应用于孤岛直流微电网中。为保护储能单元,防止过度充放,需要对储能单元的荷电状态(state of charge,SOC)实行均衡控制,然而各储能单元线路阻抗及容量存在的差异将对SOC均衡造成影响。针对这一...由于可再生能源的间歇性特点,储能单元广泛应用于孤岛直流微电网中。为保护储能单元,防止过度充放,需要对储能单元的荷电状态(state of charge,SOC)实行均衡控制,然而各储能单元线路阻抗及容量存在的差异将对SOC均衡造成影响。针对这一问题,提出了一种基于一致性算法及自适应下垂控制的储能单元SOC均衡控制策略。首先,通过定义电流比例系数,建立了各储能单元下垂系数与SOC之间的函数关系式,实现了储能单元自适应SOC均衡,并通过劳斯判据证明了系统的稳定性。其次,将所提控制策略与其他文献控制方法进行对比,并且考虑了4种不同工况对SOC均衡的影响。最后,通过Matlab/Simulink进行了仿真分析,验证了所提控制策略的有效性。展开更多
为了准确估计动力电池的SOC(state of charge)值,研究一种基于改进长短期记忆(LSTM)的新能源汽车动力电池SOC联合估计方法。分析不同因素对新能源汽车动力电池SOC的影响。基于此,构建基于卷积神经网络(CNN)-LSTM估计模型,以实现电池SOC...为了准确估计动力电池的SOC(state of charge)值,研究一种基于改进长短期记忆(LSTM)的新能源汽车动力电池SOC联合估计方法。分析不同因素对新能源汽车动力电池SOC的影响。基于此,构建基于卷积神经网络(CNN)-LSTM估计模型,以实现电池SOC联合估计。结果表明,改进后的LSTM训练均方误差更小,说明改进后LSTM拟合程度更好,具有实用性。展开更多
针对目前荷电状态(state of charge,SOC)估计方法考虑温度与退化共同影响及其关联耦合关系较少,导致电池性能退化后的模型表征不完善、SOC估计精度不足的问题,提出一种基于退化注入场路耦合模型的锂电池SOC估计方法,以实现全寿命周期下...针对目前荷电状态(state of charge,SOC)估计方法考虑温度与退化共同影响及其关联耦合关系较少,导致电池性能退化后的模型表征不完善、SOC估计精度不足的问题,提出一种基于退化注入场路耦合模型的锂电池SOC估计方法,以实现全寿命周期下SOC的准确估计。首先建立等效电路模型与多物理场模型耦合的场路耦合模型,刻画温度的影响;进而使用离线参数辨识方法将温度、退化等因素注入等效电路模型参数中;最终建立代理模型提高计算效率,实现在线SOC估计。案例验证结果表明,在锂电池经过长时间运行发生退化后,相比于其他方法,所提方法的估计结果具有更平稳的曲线和更高的精度。展开更多
文摘Naturally degradable capsule provides a platform for sustained fragrance release.However,practical challenges such as low encapsulation efficiency and difficulty in sustained release are still limited in using fragranceloaded capsules.In this work,the natural materials sodium alginate and gelatine are dissolved and act as the aqueous phase,lavender is dissolved in caprylic/capric triglyceride(GTCC)as the oil phase,and SiO_(2) nanoparticles with neutralwettability as a solid emulsifier to form O/W Pickering emulsions simultaneously.Finally,multi-core capsules are prepared using the drop injection method with emulsions as templates.The results show that the capsules have been successfully prepared with a spherical morphology and multi-core structure,and the encapsulation rate of multi-core capsules can reach up to 99.6%.In addition,the multi-core capsules possess desirable sustained release performance,the cumulative sustained release rate of fragrance at 25℃over 49 days is only 32.5%.It is attributed to the significant protection of multi-core structure,Pickering emulsion nanoparticle membranes,and hydrogel network shell for encapsulated fragrance.This study is designed to deliver a new strategy for using sustained-release technology with fragrance in food,cosmetics,textiles,and other fields.
文摘由于可再生能源的间歇性特点,储能单元广泛应用于孤岛直流微电网中。为保护储能单元,防止过度充放,需要对储能单元的荷电状态(state of charge,SOC)实行均衡控制,然而各储能单元线路阻抗及容量存在的差异将对SOC均衡造成影响。针对这一问题,提出了一种基于一致性算法及自适应下垂控制的储能单元SOC均衡控制策略。首先,通过定义电流比例系数,建立了各储能单元下垂系数与SOC之间的函数关系式,实现了储能单元自适应SOC均衡,并通过劳斯判据证明了系统的稳定性。其次,将所提控制策略与其他文献控制方法进行对比,并且考虑了4种不同工况对SOC均衡的影响。最后,通过Matlab/Simulink进行了仿真分析,验证了所提控制策略的有效性。
文摘为了准确估计动力电池的SOC(state of charge)值,研究一种基于改进长短期记忆(LSTM)的新能源汽车动力电池SOC联合估计方法。分析不同因素对新能源汽车动力电池SOC的影响。基于此,构建基于卷积神经网络(CNN)-LSTM估计模型,以实现电池SOC联合估计。结果表明,改进后的LSTM训练均方误差更小,说明改进后LSTM拟合程度更好,具有实用性。
文摘针对目前荷电状态(state of charge,SOC)估计方法考虑温度与退化共同影响及其关联耦合关系较少,导致电池性能退化后的模型表征不完善、SOC估计精度不足的问题,提出一种基于退化注入场路耦合模型的锂电池SOC估计方法,以实现全寿命周期下SOC的准确估计。首先建立等效电路模型与多物理场模型耦合的场路耦合模型,刻画温度的影响;进而使用离线参数辨识方法将温度、退化等因素注入等效电路模型参数中;最终建立代理模型提高计算效率,实现在线SOC估计。案例验证结果表明,在锂电池经过长时间运行发生退化后,相比于其他方法,所提方法的估计结果具有更平稳的曲线和更高的精度。
