Due to the poor heating performance and operating safety in low ambient temperature,traditional Air Source Heat Pump(ASHP)for Electric Vehicles(EVs)has many limits in cold region,which can be solved by the ASHP with r...Due to the poor heating performance and operating safety in low ambient temperature,traditional Air Source Heat Pump(ASHP)for Electric Vehicles(EVs)has many limits in cold region,which can be solved by the ASHP with refrigerant injection.During the start-up stage of EV in winter,the inlet air temperature of the in-car condenser is the same as the ambient temperature.At this situation,the performance and control strategy of the heat pump require special attention.In the present study,a series of experiments were carried out on the heating performance of the Refrigerant Injection Heat Pump(RIHP)system in start-up stage of EV,at the ambient temperature from–20℃ to–5℃.The effects of compressor speed and injected refrigerant state on the heating performance of the system were discussed in depth.According to the results,the control strategies during start-up stage have been discussed in the end of the article.The study provides a practical control strategy for the RIHP system during the start-up stage of electric vehicles,helping to efficiently operate electric vehicles in cold regions.展开更多
信息通信技术的发展和智能设备的引入使电力系统逐渐演变为电力信息物理系统,而信息层与物理层之间的深度耦合也加剧了电力系统遭受网络攻击的风险。虚假数据注入攻击(false data injection attack,FDIA)作为一种兼具隐蔽性、灵活性和...信息通信技术的发展和智能设备的引入使电力系统逐渐演变为电力信息物理系统,而信息层与物理层之间的深度耦合也加剧了电力系统遭受网络攻击的风险。虚假数据注入攻击(false data injection attack,FDIA)作为一种兼具隐蔽性、灵活性和攻击导向性的网络攻击方式,对电力数据采集与监控(supervisory control and data acquisition,SCADA)系统的安全稳定构成很大威胁。为应对这一威胁挑战,学者们研究了各种各样的FDIA检测方法。该文对面向电力SCADA系统的FDIA检测方法进行综述,首先介绍了FDIA的攻击原理及构建方法,梳理了FDIA检测算法的发展历程,并按照模型驱动和数据驱动对算法进行了分类整理,针对模型驱动中的基于状态估计、图论、物理特性等检测方法和数据驱动中的有监督学习、无监督学习、半监督学习、对抗博弈学习和强化学习等检测方法分别进行了机理分析;然后对比分析了相关算法的检测性能、优缺点及其适用场景;最后,对FDIA检测防御的后续研究方向进行了展望。展开更多
基金support by the National Natural Science Foundation of China(No.51576203)。
文摘Due to the poor heating performance and operating safety in low ambient temperature,traditional Air Source Heat Pump(ASHP)for Electric Vehicles(EVs)has many limits in cold region,which can be solved by the ASHP with refrigerant injection.During the start-up stage of EV in winter,the inlet air temperature of the in-car condenser is the same as the ambient temperature.At this situation,the performance and control strategy of the heat pump require special attention.In the present study,a series of experiments were carried out on the heating performance of the Refrigerant Injection Heat Pump(RIHP)system in start-up stage of EV,at the ambient temperature from–20℃ to–5℃.The effects of compressor speed and injected refrigerant state on the heating performance of the system were discussed in depth.According to the results,the control strategies during start-up stage have been discussed in the end of the article.The study provides a practical control strategy for the RIHP system during the start-up stage of electric vehicles,helping to efficiently operate electric vehicles in cold regions.
文摘信息通信技术的发展和智能设备的引入使电力系统逐渐演变为电力信息物理系统,而信息层与物理层之间的深度耦合也加剧了电力系统遭受网络攻击的风险。虚假数据注入攻击(false data injection attack,FDIA)作为一种兼具隐蔽性、灵活性和攻击导向性的网络攻击方式,对电力数据采集与监控(supervisory control and data acquisition,SCADA)系统的安全稳定构成很大威胁。为应对这一威胁挑战,学者们研究了各种各样的FDIA检测方法。该文对面向电力SCADA系统的FDIA检测方法进行综述,首先介绍了FDIA的攻击原理及构建方法,梳理了FDIA检测算法的发展历程,并按照模型驱动和数据驱动对算法进行了分类整理,针对模型驱动中的基于状态估计、图论、物理特性等检测方法和数据驱动中的有监督学习、无监督学习、半监督学习、对抗博弈学习和强化学习等检测方法分别进行了机理分析;然后对比分析了相关算法的检测性能、优缺点及其适用场景;最后,对FDIA检测防御的后续研究方向进行了展望。
