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Lithium-ion power batteries have been widely used in transportation due to their advantages of long life, high specific power, and energy. However, the safety problems caused by the inaccurate estimation and prediction of battery health state have attracted wide attention in academic circles. In this paper, the degradation mechanism and main definitions of state of health (SOH) were described by summarizing domestic and foreign literatures. The estimation and prediction methods of lithium-ion power battery SOH were discussed from three aspects: model-based methods, data-driven methods, and fusion technology methods. This review summarizes the advantages and disadvantages of the current mainstream SOH estimation and prediction methods. This paper believes that more innovative feature parameter extraction methods, multi-algorithm coupling, combined with cloud platform and other technologies will be the development trend of SOH estimation and prediction in the future, which provides a reference for health state estimation and prediction of lithium-ion power battery.

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In this work, a revised Bingham model for magneto-rheological damper is used to investigate the primary resonance reduction in the double-layer semi-active isolation system of marine auxiliary machinery. An analytical solution for the auxiliary double-layer semi-active isolation system's primary resonance is obtained with an averaging method, and this is verified numerically using the Maple software. The effect of model parameters of magneto-rheological damper on the system's vibration transmissibility is studied. The research results show that the damping of magneto-rheological damper and the control force have a significant effect on the vibration transmissibility in the resonance region. The vibration transmissibility of the double-layer semi-active isolation system decreases with increase in damping of the magnetorheological damper and control force. Yet the zero force velocity contributes very little to changes in vibration transmissibility.

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