Robust state of charge and state of health estimation for batteries using a novel multi model approach

Estimation of state-of-charge and state-of-health for batteries is one of the most important feature for modern battery management system(BMS).Robust or adaptive methods are the most investigated because a more intelligent BMS could lead to sensible cost reduction of the entire battery system.We propose a new robust method,called ERMES(extendible range multi-model estimator),for determining an estimated state-of-charge(SoC),an estimated state-of-health(SoH)and a prediction of uncertainty of the estimates(state-of-uncertainty—SoU),thanks to which it is possible to monitor the validity of the estimates and adjust it,extending the robustness against a wider range of uncertainty,if necessary.Specifically,a finite number of models in state-space form are considered starting from a modified Thevenin battery model.Each model is characterized by a hypothesis of SoH value.An iterated extended Kalman filter(EKF)is then applied to each model in parallel,estimating for each one the SoC state variable.Residual errors are then considered to fuse both the estimated SoC and SoH from the bank of EKF,yielding the overall SoC and SoH estimates,respectively.In addition,a figure of uncertainty of such estimates is also provided.

A new generic reaction for modeling fluid catalytic cracking risers

A new generic reaction in the form of PC_i→PC_m+[i,m]→PC_m+λi,m coke+surplusage has been proposed for describing the catalytic cracking behavior of petroleum narrow cuts or pseudo-components(PCs),where the rate constant formula is derived from the transition state theory and the coking amount is correlated to the properties of the intermediate substance [i,m].In composing the cracking reaction network for feedstock and product oils,only the product PC m of the proposed generic reaction is used,which together with a criterion for excluding exothermic reactions,distinctly reduces the number of reactions in the network.With the proposed cracking reaction scheme coupled with special pseudo-components,a predictive one-dimensional steady state model for fluid catalytic cracking risers is formulated in the sense that for a given riser and given catalyst,the model parameters are independent of stock oils,product schemes and other operational conditions.The great correlating and predicting capability of the resulted model is tested with production data in different scenarios of four commercial risers.