A prepaid subscriber is allowed to simultaneously implement multiple services in online charging mechanism of IP Multimedia Subsystem (IMS). It is a noteworthy discussion to effectively distribute the limited account ...A prepaid subscriber is allowed to simultaneously implement multiple services in online charging mechanism of IP Multimedia Subsystem (IMS). It is a noteworthy discussion to effectively distribute the limited account resources among concurrent services. An account-sharing algorithm is proposed for multi-services,which introduces resource reclamation and redistribution processes based on the resource reservation of standard specifications and dynamically adjusts them according to the changes of Quality of Service (QoS). Three performance indexes are investigated in the simulation experiments, which are average number of accommodated sessions, average number of completed ses- sions, and average number of iterations per accommodated session. The results show that in the normal QoS level, the three indexes of the proposed algorithm averagely increase by 18.7%, 5.4%, and 3.1% compared with the Prepaid Credit Distribution (PCD) algorithm, and by 2.1%, 1.0%, and 1.8% compared with the Prepaid Credit Reclaim (PCR) algorithm. In the poor QoS level, the performance advantages are greater, which averagely increase by 29.1%, 7.1%, and 2.8% compared with PCD, and by 9.4%, 4.1%, and 3.6% compared with PCR.展开更多
锂离子电池由于其高能量密度、高循环寿命等优点被广泛应用于电力储能和新能源汽车中。准确估计电池的荷电状态(state of charge,SOC)对提高电池使用寿命和利用效率具有重要意义。然而,锂电池是一个高度复杂、时变和非线性的电化学系统...锂离子电池由于其高能量密度、高循环寿命等优点被广泛应用于电力储能和新能源汽车中。准确估计电池的荷电状态(state of charge,SOC)对提高电池使用寿命和利用效率具有重要意义。然而,锂电池是一个高度复杂、时变和非线性的电化学系统。因此,精度高的在线SOC估计方法对锂电池的实际应用非常重要。近年来,基于模型的SOC估计方法由于其闭环控制、易于实现等特点被广泛关注和研究。本文从模型分类、模型参数辨识算法、SOC估计算法以及SOC估计影响因素对基于模型的SOC估计方法进行综述,首先归纳总结了各种常见的锂离子电池模型,主要介绍了各种常见电化学模型和等效电路模型并进行对比分析;然后重点对模型建立方法和SOC状态估计算法进行梳理和对比,主要介绍了各种模型参数辨识方法及SOC估计方法并进行了对比分析;之后对影响基于模型的SOC估计方法精度的影响因素及解决方法进行分析和总结,主要从温度、老化以及电池组对电池SOC估计的影响进行分析;最后对未来的研究方向进行了讨论和展望。展开更多
Automatic compensation of grinding wheel wear in dry grinding is accomplished by an image based online measurement method. A kind of PC-based charge-coupled device image recognition system is schemed out, which detect...Automatic compensation of grinding wheel wear in dry grinding is accomplished by an image based online measurement method. A kind of PC-based charge-coupled device image recognition system is schemed out, which detects the topography changes of the grinding wheel surface. Profile data, which corresponds to the wear and the topography, is measured by using a digital image processing method. The grinding wheel wear is evalualed by analyzing the position deviation of the grinding wheel edge. The online wear compensation is achieved according to the measure results. The precise detection and automatic compensation system is integrated into an open structure CNC curve grinding machine. A practical application is carried out to fulfil the precision curve grinding. The experimental results confirm the benefits of the proposed techniques, and the online detection accuracy is less than 5 um. The grinding machine provides higher precision according to the in-process grinding wheel error compensation.展开更多
为了准确和快速地估算电动汽车运行过程中汽车电池的荷电状态(State of Charge,SOC)和健康状态(State of Health,SOH),提出一种基于遗忘因子最小二乘和可变时间尺度扩展卡尔曼滤波器的自适应联合估算算法。为了提高算法的效率和准确度,...为了准确和快速地估算电动汽车运行过程中汽车电池的荷电状态(State of Charge,SOC)和健康状态(State of Health,SOH),提出一种基于遗忘因子最小二乘和可变时间尺度扩展卡尔曼滤波器的自适应联合估算算法。为了提高算法的效率和准确度,引入自适应遗忘因子递归最小二乘(Adaptive Forgetting Factor Recursive Least Square,AFFRLS)方法来识别电池模型中的参数,并采用可变时间尺度扩展卡尔曼滤波器(Variable Time Scale Extended Kalman Filter,VEKF)来指示SOC和SOH,以满足对电池动态状况进行在线快速估算的需求。应用动态应力测试(Dynamic Stress Test,DST)数据库验证了该方法的有效性,实验结果表明,该联合估算方法可以获取准确的电池模型,并实现在线状态估算。展开更多
蓄电池荷电状态(state of charge,SOC)是电池管理系统最为重要的参数之一,由于飞机蓄电池工作环境恶劣复杂,具有较强的非线性,给蓄电池的在线SOC估计带来较大的困难。以提高复杂应力条件下飞机蓄电池在线SOC估计精度为目的,采用性能测...蓄电池荷电状态(state of charge,SOC)是电池管理系统最为重要的参数之一,由于飞机蓄电池工作环境恶劣复杂,具有较强的非线性,给蓄电池的在线SOC估计带来较大的困难。以提高复杂应力条件下飞机蓄电池在线SOC估计精度为目的,采用性能测试实验对蓄电池性能参数的温度、放电率特性进行研究,并提出递推最小二乘法与扩展卡尔曼滤波算法结合的改进EKF方法,实现蓄电池等效电路模型参数的在线辨识以及蓄电池在线SOC的估计。上述方法通过物理实验进行了验证,实验结果表明,改进后EKF方法的SOC估计误差小于0.5%,估计精度获得明显提高。展开更多
基金Supported by the National Natural Science Fund for Distinguished Young Scholars (No.60525110)the National 973 Program (No.2007CB307100, No.2007CB 307103)the Development Fund Project for Elec-tronic and Information Industry (Mobile Service and Application System Based on 3G)
文摘A prepaid subscriber is allowed to simultaneously implement multiple services in online charging mechanism of IP Multimedia Subsystem (IMS). It is a noteworthy discussion to effectively distribute the limited account resources among concurrent services. An account-sharing algorithm is proposed for multi-services,which introduces resource reclamation and redistribution processes based on the resource reservation of standard specifications and dynamically adjusts them according to the changes of Quality of Service (QoS). Three performance indexes are investigated in the simulation experiments, which are average number of accommodated sessions, average number of completed ses- sions, and average number of iterations per accommodated session. The results show that in the normal QoS level, the three indexes of the proposed algorithm averagely increase by 18.7%, 5.4%, and 3.1% compared with the Prepaid Credit Distribution (PCD) algorithm, and by 2.1%, 1.0%, and 1.8% compared with the Prepaid Credit Reclaim (PCR) algorithm. In the poor QoS level, the performance advantages are greater, which averagely increase by 29.1%, 7.1%, and 2.8% compared with PCD, and by 9.4%, 4.1%, and 3.6% compared with PCR.
文摘锂离子电池由于其高能量密度、高循环寿命等优点被广泛应用于电力储能和新能源汽车中。准确估计电池的荷电状态(state of charge,SOC)对提高电池使用寿命和利用效率具有重要意义。然而,锂电池是一个高度复杂、时变和非线性的电化学系统。因此,精度高的在线SOC估计方法对锂电池的实际应用非常重要。近年来,基于模型的SOC估计方法由于其闭环控制、易于实现等特点被广泛关注和研究。本文从模型分类、模型参数辨识算法、SOC估计算法以及SOC估计影响因素对基于模型的SOC估计方法进行综述,首先归纳总结了各种常见的锂离子电池模型,主要介绍了各种常见电化学模型和等效电路模型并进行对比分析;然后重点对模型建立方法和SOC状态估计算法进行梳理和对比,主要介绍了各种模型参数辨识方法及SOC估计方法并进行了对比分析;之后对影响基于模型的SOC估计方法精度的影响因素及解决方法进行分析和总结,主要从温度、老化以及电池组对电池SOC估计的影响进行分析;最后对未来的研究方向进行了讨论和展望。
基金This project is supported by Science and Technology Development Foundation of Shanghai Municipal Commission of Science and Technology, China (No.021111125).
文摘Automatic compensation of grinding wheel wear in dry grinding is accomplished by an image based online measurement method. A kind of PC-based charge-coupled device image recognition system is schemed out, which detects the topography changes of the grinding wheel surface. Profile data, which corresponds to the wear and the topography, is measured by using a digital image processing method. The grinding wheel wear is evalualed by analyzing the position deviation of the grinding wheel edge. The online wear compensation is achieved according to the measure results. The precise detection and automatic compensation system is integrated into an open structure CNC curve grinding machine. A practical application is carried out to fulfil the precision curve grinding. The experimental results confirm the benefits of the proposed techniques, and the online detection accuracy is less than 5 um. The grinding machine provides higher precision according to the in-process grinding wheel error compensation.
文摘为了准确和快速地估算电动汽车运行过程中汽车电池的荷电状态(State of Charge,SOC)和健康状态(State of Health,SOH),提出一种基于遗忘因子最小二乘和可变时间尺度扩展卡尔曼滤波器的自适应联合估算算法。为了提高算法的效率和准确度,引入自适应遗忘因子递归最小二乘(Adaptive Forgetting Factor Recursive Least Square,AFFRLS)方法来识别电池模型中的参数,并采用可变时间尺度扩展卡尔曼滤波器(Variable Time Scale Extended Kalman Filter,VEKF)来指示SOC和SOH,以满足对电池动态状况进行在线快速估算的需求。应用动态应力测试(Dynamic Stress Test,DST)数据库验证了该方法的有效性,实验结果表明,该联合估算方法可以获取准确的电池模型,并实现在线状态估算。
文摘蓄电池荷电状态(state of charge,SOC)是电池管理系统最为重要的参数之一,由于飞机蓄电池工作环境恶劣复杂,具有较强的非线性,给蓄电池的在线SOC估计带来较大的困难。以提高复杂应力条件下飞机蓄电池在线SOC估计精度为目的,采用性能测试实验对蓄电池性能参数的温度、放电率特性进行研究,并提出递推最小二乘法与扩展卡尔曼滤波算法结合的改进EKF方法,实现蓄电池等效电路模型参数的在线辨识以及蓄电池在线SOC的估计。上述方法通过物理实验进行了验证,实验结果表明,改进后EKF方法的SOC估计误差小于0.5%,估计精度获得明显提高。
