A ring-connected dual active bridge based DC-DC multiport converter for EV fast-charging stations

This paper proposes a multiport DC-DC converter for EV fast-charging stations. The proposed converter is comprised of Ring-Connected Dual Active Bridge (RCDAB) DC-DC converters, where the connection point between every two adjacent DABs provides a DC port. Bypass switches are added to each DAB to eliminate unnecessary power processing stages in the event of idle ports (no EVs) (open circuit ports). The nature of the ring connection of the RCDAB theoretically allows infinite internal power flow solutions within the ring to satisfy a certain power flow scenario at the DC ports, hence, the optimal power flow solution can be selected to minimize total RMS current and losses. Single-phase shift control is applied to this optimization problem to make it simple. A novel closed-loop control scheme using Bisection optimization is developed to minimize the total RMS current. A control-hardware-in-the-loop (CHiL) validation is carried out for a 5-port network of the proposed topology to investigate the converter efficiency and fault tolerance/availability characteristics. Also, an experimental hardware validation is implemented for a 3-port network where different scenarios for power flow and faults are performed. Finally, a comparative discussion between the proposed topology and other multiport topologies in literature is presented revealing the superior performance of the RCDAB topology

Sustainable release of propranolol hydrochloride laden with biconjugated-ufasomes chitosan hydrogel attenuates cisplatin-induced sciatic nerve damage in in vitro/in vivo evaluation

Peripheral nerve injuries significantly impact patients’ quality of life and poor functional recovery. Chitosan–ufasomes (CTS–UFAs) exhibit biomimetic features, making them a viable choice for developing novel transdermal delivery for neural repair. This study aimed to investigate the role of CTS–UFAs loaded with the propranolol HCl (PRO) as a model drug in enhancing sciatica in cisplatin-induced sciatic nerve damage in rats. Hence, PRO–UFAs were primed, embedding either span 20 or 60 together with oleic acid and cholesterol using a thin-film hydration process based on full factorial design (2(4)). The influence of formulation factors on UFAs’ physicochemical characteristics and the optimum formulation selection were investigated using Design-Expert(®) software. Based on the optimal UFA formulation, PRO–CTS–UFAs were constructed and characterized using transmission electron microscopy, stability studies, and ex vivo permeation. In vivo trials on rats with a sciatic nerve injury tested the efficacy of PRO–CTS–UFA and PRO–UFA transdermal hydrogels, PRO solution, compared to normal rats. Additionally, oxidative stress and specific apoptotic biomarkers were assessed, supported by a sciatic nerve histopathological study. PRO–UFAs and PRO–CTS–UFAs disclosed entrapment efficiency of 82.72 ± 2.33% and 85.32 ± 2.65%, a particle size of 317.22 ± 6.43 and 336.12 ± 4.9 nm, ζ potential of −62.06 ± 0.07 and 65.24 ± 0.10 mV, and accumulatively released 70.95 ± 8.14% and 64.03 ± 1.9% PRO within 6 h, respectively. Moreover, PRO–CTS–UFAs significantly restored sciatic nerve structure, inhibited the cisplatin-dependent increase in peripheral myelin 22 gene expression and MDA levels, and further re-established sciatic nerve GSH and CAT content. Furthermore, they elicited MBP re-expression, BCL-2 mild expression, and inhibited TNF-α expression. Briefly, our findings proposed that CTS–UFAs are promising to enhance PRO transdermal delivery to manage sciatic nerve damage

Improved utilization for “smart parking systems” based on paging technique

Considering the rapid urbanization and the road congestion, the development of smart parking solutions becomes more crucial, especially in terms of economic interests. Thanks to IoT-connectivity and the cloud-integrated platforms, drivers can easily find a vacant parking lot with smart parking services. This paper intervenes in the profit of parking management systems. The paper proposes a new technique “paging technique” which increases the utilization factor of parking slots. The proposed method takes advantage of the idle time that exists between two successful parking services in the same slot. Besides, it investigates the possibility of using the idle times from different parking slots to provide a continuous parking time for an additional car. The paging technique is optimally implemented using mixed-integer linear programming that maximizes the utilization factor for the parking slots with minimum car transitions. Moreover, a data model for the parking management system has been constructed while considering the three major customers, namely, regular, prepaid, and walk-in customers. The difference between fixed and dynamic pricing for parking has been investigated. The technique has been validated using GAMS optimization software and hardware using DSP with Coin-or branch and cut solver (CBC) under real-life conditions. The statistical results prove that the revenue for the proposed parking system has increased significantly. Finally, a comparative analysis is performed, benchmarking our proposed method against recent competing algorithms in real world applications to demonstrate its superiority

Modified extended complex Kalman filter for DC offset and distortion rejection in grid-tie transformerless converters

Proper operation of the grid-tie transformerless converters under unbalanced and distorted conditions entails a precise detection of the frequency and fundamental component of the grid voltage. One of the main problems that could arise during the estimation of grid parameters is the existence of a DC offset generated from measurement and A/D conversion. This undesirable induced DC offset could appear as a part of the reference sinusoidal current of grid-tie converters. Although literature has proposed the use of an extended complex Kalman filter (ECKF) for the estimation of positive and negative sequence voltage components as a promising competitor to phase locked loops, mitigating the effect of possible DC offsets when a Kalman filter is employed remains scarce. This paper proposes a new extended complex Kalman filter to improve the filter stability for estimating the frequency and the fundamental positive and negative symmetrical components of the grid voltages, where DC offset, scaling error, and noise can successfully be rejected. The theoretical findings are experimentally validated

Performance evaluation of PI controlled series stacked power delivery architectures for high-efficiency data centers

Series-stacked architectures have been successfully deployed for data center applications at substantially higher efficiencies than conventional power delivery architectures. In the series-stacked architectures, servers are series-connected electrically to reduce the high step-down conversion stage of voltage utilized in the conventional architectures. Differential power processing converters are, therefore, used to regulate the servers’ voltages and compensate for the unpredicted mismatch between servers’ currents. The main contribution of this paper comprises novel control approaches based on PI controllers purposeful for the two architectures that have reported the highest reliability and efficiency in differential power processing namely: server-to-bus and server-to-virtual bus. Both systems employ a dual active bridge (DAB) converter to accommodate the fluctuating loads of each server. Unlike hysteresis current/voltage control commonly employed in the available literature, the proposed control approaches offer less complexity, lower harmonics, and higher immunity towards the noise, thus no need for high-quality sensors to successfully achieve voltage balance and/or optimal string current flow. Moreover, a comparative study has been structured between the investigated series-stacked architectures under the proposed PI control approaches showing the merits and the demerits of each architecture. The proposed controllers have been validated based on simulations and experimentally

Power management optimization of electric vehicles for grid frequency regulation : comparative study

Electric vehicles (EVs) have shown promise in providing ancillary services, e.g., frequency regulation. This is mainly due to their capacities and fast response. On the contrary, the rapid integration of EVs in the grid poses challenges, such as frequency and voltage stability. In order to mitigate the above-mentioned issues, several dispatching strategies have been introduced in the recent literature to optimize the charging/discharging rates of EVs. In this paper, a comparative study of power management strategies for secondary frequency regulation (SFR) employing a fleet of EVs is presented. A hierarchical control scheme is employed to compare two cases, namely control at the charging station (CS) level and novel control at the EVs level. Under both cases, a multi-objective optimization approach is utilized to define the optimal charging and discharging rates of EVs using a pattern search algorithm. Furthermore, the performance of the two models is experimented under contingency cases, a notable contribution of this study. Finally, simulations are carried out using OPAL-RT real time simulator to validate the performance of the two models based on real-time traces obtained from Pennsylvania, New Jersey, and Maryland (PJM) interconnection and California independent system operator (CAISO). To further validate the proposed model, a comparison with a mixed-integer linear programming (MILP) based model is presented

Data-driven-based vector space decomposition modeling of multiphase induction machines

For contemporary variable-speed electric drives, the accuracy of the machine's mathematical model is critical for optimal control performance. Basically, phase variables of multiphase machines are preferably decomposed into multiple orthogonal subspaces based on vector space decomposition (VSD). In the available literature, identifying the correlation between states governed by the dynamic equations and the parameter estimate of different subspaces of multiphase IM remains scarce, especially under unbalanced conditions, where the effect of secondary subspaces sounds influential. Most available literature has relied on simple RL circuit representation to model these secondary subspaces. To this end, this paper presents an effective data-driven-based space harmonic model for n-phase IMs using sparsity-promoting techniques and machine learning with nonlinear dynamical systems to discover the IM governing equations. Moreover, the proposed approach is computationally efficient, and it precisely identifies both the electrical and mechanical dynamics of all subspaces of an IM using a single transient startup run. Additionally, the derived model can be reformulated into the standard canonical form of the induction machine model to easily extract the parameters of all subspaces based on online measurements. Eventually, the proposed modeling approach is experimentally validated using a 1.5 Hp asymmetrical six-phase induction machine

Investigation of six-phase surface permanent magnet machine with typical slot/pole combinations for integrated onboard chargers through methodical design optimization

This article presents an analytical magnetic equivalent circuit (MEC) modeling approach for a six-phase surface-mounted permanent magnet (SPM) machine equipped with fractional slot concentrated winding (FSCW) for integrated onboard chargers. For the sake of comparison, the selected asymmetrical six-phase slot/pole combinations with the same design specifications and constraints are first designed based on the parametric MEC model and then optimized using a multiobjective genetic algorithm (MOGA). The commercial BMW i3 design specifications are adopted in this article. The main focus of this study is to achieve optimal design of the SPM machine considering both the propulsion and charging performances. Thus, a comparative study of the optimization cost functions, including the peak-to-peak torque ripple and core losses under both motoring and charging modes and electromagnetic forces (EMFs) under charging, is conducted. In addition, the demagnetization capability in the charging mode and the overall cost of the employed machines are optimized. Since the average propulsion torque is crucial in electric vehicle (EV) applications, it is maintained through the design optimization process. Furthermore, finite element (FE) simulations have been carried out to verify the results obtained from the analytical MEC model. Eventually, the effectiveness of the proposed design optimization process is corroborated by experimental tests on a 2-kW prototype system

Potential bioactivity of Phoenix dactylifera fruits, leaves, and seeds against prostate and pancreatic cancer cells

The use of functional foods’ phytochemicals in the chemoprevention of different cancer diseases has become one of the hot scientific areas in the clinical nutrition field. For instance, the Khalas palm cultivar (KPC; Phoenix dactylifera) is one of the natural sustainable resources that have high bioactivity and functionality. This study aimed to investigate the antiproliferative activity and mode of action of KPC’s different parts on prostate (Pc3) and pancreatic (panc1) cancer cells at a molecular level. In the methods, KPC’s leaves, seeds, and fruits’ chemical composition and phytochemical analysis were analyzed. Also, the cytotoxic effects of each extract were assessed against pc3 and panc1 cell lines. Besides, induction of apoptosis, cell cycle analysis, and gene expression of both Cap3 and Cap9 were studied. The obtained results indicated that KPC leaves extract exhibited the highest significant (P < 0.01) anti-proliferation activity against the utilized cancer cell lines compared to fruits and seeds extracts. Also, there were significant (P < 0.05) differences in the phenolic contents, flavonoid of compounds, and antioxidant power of the leaves when compared to the seeds and fruits. Additionally, the highest cytotoxic effect (lowest IC50) was recorded with leave extract than seeds and fruits. Meanwhile, the seeds extract induced (P < 0.05) the apoptosis and arrested cells in the G2/M phase as well as up-regulated the gene expression of the apoptotic-related genes (Casp3 and Casp9) compared to the control group. In conclusion, this study showed that the presence of bioactive components in the KPC different parts extracts have the significant ability to induce the apoptotic pathway that could down-regulate the proliferation of prostate (pc3) and pancreatic (panc1) cancer cells. The pathway mechanism of action was induced by the phytol molecule presented in its leaves extract

Electrospun highly corrosion-resistant polystyrene–nickel oxide superhydrophobic nanocomposite coating

A key challenge in producing superhydrophobic coatings (SHC) is to tailor the surface morphology on the micro-nanometer scale. In this work, a feasible and straightforward route was employed to manufacture polystyrene/nickel oxide (PSN) nanocomposite superhydrophobic coatings on aluminum alloys to mitigate their corrosion in a saline environment. Different techniques were employed to explore the influence of the addition of NiO nanoparticles to the as-prepared coatings. PSN-2 composite with ~ 4.3 wt% of NiO exhibited the highest water contact angle (WCA) of 155° ± 2 and contact angle hysteresis (CAH) of 5°. Graphic abstract: EIS Nyquist plots of 3 g of electrospun polystyrene coatings (a) without and with (b) 0.1, (c) 0.15, and (d) 0.2 g of NiO. [Figure not available: see fulltext.