This study investigates a new hybrid energy storage system (HESS), which consists of a battery bank and an ultra-capacitor (UC) bank, and a control strategy for this system. The proposed topology uses a bi-directional DC-DC converter with a lower power rating than those used in the traditional HESS topology. The proposed HESS has four operating modes, and the proposed control strategy chooses the appropriate operating mode and regulates the distribution of power between the battery bank and the UC bank. Additionally, the control system prevents surges during mode switching and ensures that both the battery bank and the bi-directional DC-DC converter operate within their power limits. The proposed HESS is used to improve the performance of an existing power-split hybrid electric vehicle (HEV). A method for calculating the parameters of the proposed HESS is presented. A simulation model of the proposed HESS and control strategy was developed, and a scaled-down experimental platform was constructed. The results of the simulations and the experiments provide strong evidence for the feasibility of the proposed topology and the control strategy. The performance of the HESS is not influenced by the power limits of the bi-directional DC-DC converter.

Abstract:Over the last few years; issues regarding the use of hybrid energy storage systems (HESSs) in hybrid electric vehicles have been highlighted by the industry and in academic fields. This paper proposes a fuzzy-logic power management strategy based on Markov random prediction for an active parallel battery-UC HESS. The proposed power management strategy; the inputs for which are the vehicle speed; the current electric power demand and the predicted electric power demand; is used to distribute the electrical power between the battery bank and the UC bank. In this way; the battery bank power is limited to a certain range; and the peak and average charge/discharge power of the battery bank and overall loss incurred by the whole HESS are also reduced. Simulations and scaled-down experimental platforms are constructed to verify the proposed power management strategy. The simulations and experimental results demonstrate the advantages; feasibility and effectiveness of the fuzzy-logic power management strategy based on Markov random prediction.

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Descemet’s membrane (DM) helps maintain phenotype and function of corneal endothelial cells under physiological conditions, while little is known about the function of DM in corneal endothelial wound healing process. In the current study, we performed in vivo rabbit corneal endothelial cell (CEC) injury via CEC scraping, in which DM remained intact after CECs removal, or via DM stripping, in which DM was removed together with CECs. We found rabbit corneas in the CEC scraping group healed with transparency restoration, while there was posterior fibrosis tissue formation in the corneas after DM stripping on day 14. Following CEC scraping on day 3, cells that had migrated toward the central cornea underwent a transient fibrotic endothelial-mesenchymal transition (EMT) which was reversed back to an endothelial phenotype on day 14. However, in the corneas injured via DM stripping, most of the cells in the posterior fibrosis tissue did not originate from the corneal endothelium, and they maintained fibroblastic phenotype on day 14. We concluded that corneal endothelial wound healing in rabbits has different outcomes depending upon the presence or absence of Descemet’s membrane. Descemet’s membrane supports corneal endothelial cell regeneration in rabbits after endothelial injury.