Lithium ion batteries are complicated distributed parameter systems that can be described preferably by partial differential equations and a field theory. To reduce the solution difficulty and the calculation amount, ...Lithium ion batteries are complicated distributed parameter systems that can be described preferably by partial differential equations and a field theory. To reduce the solution difficulty and the calculation amount, if a distributed parameter system is described by ordinary differential equations （ODE） during the analysis and the design of distributed parameter system, the reliability of the system description will be reduced, and the systemic errors will be introduced. Studies on working condition real-time monitoring can improve the security because the rechargeable LIBs are widely used in many electronic systems and electromechanical equipment. Single particle model （SPM） is the simplification of LIB under some approximations, and can estimate the working parameters of a LIB at the faster simulation speed. A LIB modelling algorithm based on PDEs and SPM is proposed to monitor the working condition of LIBs in real time. Although the lithium ion concentration is an unmeasurable distributed parameter in the anode of LIB, the working condition monitoring model can track the real time lithium ion concentration in the anode of LIB, and calculate the residual which is the difference between the ideal data and the measured data. A fault alarm can be triggered when the residual is beyond the preset threshold. A simulation example verifies that the effectiveness and the accuracy of the working condition real-time monitoring model of LIB based on PDEs and SPM.展开更多
This paper considers the additive hazards iliary covariate information to improve the efficiency regression analysis by utilizing continuous aux- of the statistical inference when the primary covariate is ascertained ...This paper considers the additive hazards iliary covariate information to improve the efficiency regression analysis by utilizing continuous aux- of the statistical inference when the primary covariate is ascertained only for a randomly selected subsample. The authors construct a martingale based estimating equation for the regression parameter and establish the asymptotic consistency and normality of the resultant estimators. Simulation study shows that the proposed method can greatly improve the efficiency compared with the estimator which discards the auxiliary covariate information in a variety of settings. A real example is also provided as an illustration.展开更多
文摘Lithium ion batteries are complicated distributed parameter systems that can be described preferably by partial differential equations and a field theory. To reduce the solution difficulty and the calculation amount, if a distributed parameter system is described by ordinary differential equations （ODE） during the analysis and the design of distributed parameter system, the reliability of the system description will be reduced, and the systemic errors will be introduced. Studies on working condition real-time monitoring can improve the security because the rechargeable LIBs are widely used in many electronic systems and electromechanical equipment. Single particle model （SPM） is the simplification of LIB under some approximations, and can estimate the working parameters of a LIB at the faster simulation speed. A LIB modelling algorithm based on PDEs and SPM is proposed to monitor the working condition of LIBs in real time. Although the lithium ion concentration is an unmeasurable distributed parameter in the anode of LIB, the working condition monitoring model can track the real time lithium ion concentration in the anode of LIB, and calculate the residual which is the difference between the ideal data and the measured data. A fault alarm can be triggered when the residual is beyond the preset threshold. A simulation example verifies that the effectiveness and the accuracy of the working condition real-time monitoring model of LIB based on PDEs and SPM.
基金supported by the National Natural Science Foundation of China under Grant Nos.11171263,41261087the Doctoral Fund of Ministry of Education of China under Grant Nos.20110141110004,20110141120004
文摘This paper considers the additive hazards iliary covariate information to improve the efficiency regression analysis by utilizing continuous aux- of the statistical inference when the primary covariate is ascertained only for a randomly selected subsample. The authors construct a martingale based estimating equation for the regression parameter and establish the asymptotic consistency and normality of the resultant estimators. Simulation study shows that the proposed method can greatly improve the efficiency compared with the estimator which discards the auxiliary covariate information in a variety of settings. A real example is also provided as an illustration.
