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In this paper, a co-estimation scheme of the state of charge (SOC) and available capacity is proposed for lithium−ion batteries based on the adaptive model-based algorithm. A three-dimensional response surface (TDRS) in terms of the open circuit voltage, the SOC and the available capacity in the scope of whole lifespan, is constructed to describe the capacity attenuation, and the battery available capacity is identified by a genetic algorithm (GA), together with the parameters related to SOC. The square root cubature Kalman filter (SRCKF) is employed to estimate the SOC with the consideration of capacity degradation. The experimental results demonstrate the effectiveness and feasibility of the co-estimation scheme.

• A new adaptive controller to control nonlinear multi-story buildings is introduced. • The controller uses the advantages of nonlinear static analysis in Clipped Optimal algorithms. • The controller is applied to a set of torsional multi-story buildings equipped with MR dampers. • The robustness of the strategy to control the seismic inelastic responses of torsional buildings is illustrated. The simplified one-story asymmetric models cannot simulate the inelastic performance of controlled irregular multi-story frame type buildings subjected to extreme dynamic loadings, especially when the effect of higher modes on distribution of engineering demand parameters (EDPs) over the height of the structures is an important design factor. In the present study, controlled nonlinear seismic response of coupled translational–torsional irregular multi-story smart buildings is investigated. In order to control such nonlinear systems, a new robust adaptive model-based controller is introduced. This new adaptive model-based strategy, due to using adjustable parameters such as instant stiffness, could well consider the nonlinear behavior of the structure and act more precisely in controlling the torsional behavior of Magneto- Rheological (MR) dampers-equipped multi-story torsional buildings. The proposed controller uses the advantages of nonlinear static analysis in order to introduce the instant nonlinear stiffness of the structure into model-based control strategies such as LQR (Linear–Quadratic–Regulator) or LQG (Linear–Quadratic–Gaussian) and also Clipped Optimal algorithms. The proposed controller is applied to a set of low and mid-rise multi-story buildings equipped with MR dampers considering three different torsional behavior. The Fiber elements are employed to simulate the non-linear behavior of structural members. The findings of this study revealed the robustness of the proposed strategy to control the seismic inelastic torsional responses of multi-story buildings subjected to ordinary and pulse-like ground motions. [ABSTRACT FROM AUTHOR]

In this paper, a co-estimation scheme of the state of charge (SOC) and available capacity is proposed for lithium–ion batteries based on the adaptive model-based algorithm. A three-dimensional response surface (TDRS) in terms of the open circuit voltage, the SOC and the available capacity in the scope of whole lifespan, is constructed to describe the capacity attenuation, and the battery available capacity is identified by a genetic algorithm (GA), together with the parameters related to SOC. The square root cubature Kalman filter (SRCKF) is employed to estimate the SOC with the consideration of capacity degradation. The experimental results demonstrate the effectiveness and feasibility of the co-estimation scheme. [ABSTRACT FROM AUTHOR]