Series-parallel Configuration Research Articles

Kinetostatic and dynamic analyses of planar compliant mechanisms via a two-port dynamic stiffness model

Serial-parallel configurations are widely designed in compliant mechanisms. In this paper, the transfer matrix method is combined with D'Alembert's principle to develop a two-port dynamic stiffness model for analyzing the kinetostatics and dynamics of complex compliant mechanisms with serial-parallel configurations. In detail, two kinds of improved transfer matrices for parallel sub-chains are derived in a unified form by summarizing the common serial-parallel substructures in compliant mechanisms. Then, a two-port dynamic stiffness model describing the frequency-dependent input and output force-displacement relationship of compliant mechanisms is established. Based on the two-port dynamic stiffness model, procedures for solving the static and dynamic performances of compliant mechanisms are presented. The proposed approach is demonstrated by calculating the displacement amplification ratio, input/output stiffness, natural frequencies and forced dynamic response of two typical precision flexure manipulators. The advantage of the proposed approach lies in its capability to describe the simultaneous kinetostatics and dynamics for a large class of serial-parallel configurations with very few degrees of freedom (DOFs), differing from the previous Lagrange-based dynamic modeling methods in the context of compliant mechanisms and should be of interest to designers.

Generator configuration for helicopter quadruplex electric tail rotor

With the move to more electric aircraft (MEA), a key area of investigation is the development of commercially viable systems which are reliable, efficient, low mass, and are compatible and commensurate with the power and multiplex requirements of current and future aircraft. In rotorcraft, the pace of adopting more electric systems, to replace conventional mechanical and hydraulic ones, say, is perceived as being much lower than in fixed wing aircraft. However, recently there has been growing evidence to suggest that a quadruplex electric tail rotor (ETR) is a technically viable solution. This paper shows the methodology to support the most reliable configuration of the four independent generators required to power such a quadruplex tail rotor drive, and takes account of the failure severity due to power loss in each independent channel, target reliability setting, and supporting reliability analyses. The conclusions drawn support a particular hybrid series-parallel configuration of generators, with identification of further work related to the gearbox reliabilities which support the reliability attainment for the configuration.

Concept of a distributed photovoltaic multilevel inverter with cascaded double H-bridge topology

This paper presents proof-of-concept of a novel photovoltaic (PV) inverter with integrated short-term storage, based on the modular cascaded double H-bridge (CHB2) topology, and a new look-up table control approach. This topology combines and extends the advantages of various distributed converter concepts, such as string inverters, microinverters, and cascaded H-bridge (CHB) multilevel inverters. The proposed CHB2 inverter incorporates individual PV elements into modules that can dynamically connect to their neighbors not only in series but also in parallel, which reduces conduction losses and enables simple module balancing. Maximum-power-point tracking of the PV element is performed in each module. As a demonstration of the flexibility of the approach and to filter large power fluctuations before they enter the grid, each module further incorporates batteries for energy storage, which enables continuous power output by compensating solar power fluctuations, while the CHB2 can balance the batteries’ load and state of charge. The inverter provides exceptionally high output quality without large filters, since the multilevel ac output is finely quantized. The elimination of extensive output filtering provides for an extremely rapid dynamic response as well. We furthermore introduce an optimized, computationally efficient, look-up-table-based controller and module scheduler which leverages the large number of degrees of freedom provided by the flexible series-parallel CHB2 configurations to optimize conduction loss, switching loss, and load balance. The method can be extended to CHB2 circuits in general to improve their performance while simplifying control. Finally, we demonstrate that the inverter is robust to open-circuit failure of power switches or PVs.

Design of New Hybrid Neural Controller for Nonlinear CSTR System based on Identification

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm namely Particle Swarm Optimization (PSO) algorithm. The numerical simulation results show that the hybrid NARMA-L2 controller with PSO algorithm is more accurate than BPA in terms of achieving fast learning and adjusting the parameters model with minimum number of iterations, minimum number of neurons in the hybrid network and the smooth output one step ahead prediction controller response for the nonlinear CSTR system without oscillation.

Real-Time Energy Economy Optimization Based on Nonlinear MPC for Hybrid Electrical Buses

Hybrid electric vehicles (HEVs) which combine at least two energy sources are characterized by high efficiency and seem to strongly support the objective to cut greenhouse gases. In this paper, hybrid electric bus (HEB) with coaxial series-parallel configuration is proposed and very little research on the economy optimization of this powertrain has been done. Considering that predictive control has the mechanism for controlling the nonlinear process while tackling equality or inequality constraints, nonlinear model predictive control (NMPC) is applied to the energy management strategy (EMS) for the HEB. The NMPC-based EMS is formulated and then converted into optimal control problem based on Pontryagin’s Minimum Principle (PMP) which can be solved with an iterative method. Finally, the architecture of the EMS problem established and the results of the proposed optimization strategy are illustrated and turn out to be satisfying.

An improved series-parallel optimization approach for cooling water system

Conventional cooling networks are usually operated in a parallel configuration. Although this configuration is easy operated, it results in inefficient use of water. A series configuration can effectively reduce water flow rate, while its arrangement is relatively complex, incurring more operating and capital cost. This paper proposes a water and energy conservation strategy to save energy cost and to simplify the network structure. Heat exchangers are arranged in series-parallel configuration to reduce the water flow rate for water conservation, and two kinds of installation conditions with or without static pressure drop are taken into account for energy conservation. A main-auxiliary pump structure is applied to reduce the operating consumption. The number of reuse branch for the economic performance is analyzed. Mixed-integer nonlinear programming based on a superstructure description is formulated by considering the configuration of pumps and heat exchanger networks simultaneously. Two case studies are employed to demonstrate the effectiveness of the proposed approach. The results show that the improved series-parallel configuration approach can save 10.9% of the total cost compared with the two-step sequential optimization and 4.7% compared with the simultaneous optimization method.

An intelligent interconnected network with multiple reservoir computing

In this paper, considering the decomposition and composition mechanism of the traditional reservoir, an intelligent interconnected network with multiple reservoir computing in series–parallel configuration, called MRC-IIN, is proposed for multivariate time series classification and prediction. Firstly, according to the unsupervised learning of restricted Boltzmann machine and the Pearson correlation of multivariate inputs, the number of 1st column reservoirs of MRC-IIN can be determined, and each row interconnected reservoirs of MRC-IIN can also be determined. Secondly, according to the input autocorrelation of 1st column reservoirs, the number of each row reservoirs of MRC-IIN can be determined, such that the dynamic characteristics of the corresponding input can be fully reflected. Thirdly, through using the advantages of principal component analysis, each reservoir size of MRC-IIN can be determined, such that the feature information of each row reservoir states can be reduced layer by layer, and the most essential feature information can be retained. Fourthly, in order to ensure the stable application of MRC-IIN, a sufficient condition for global echo state property of MRC-IIN is given. Finally, the simulation results show that the MRC-IIN can improve classification and prediction performance.

Analysis of Bi-Te Based Thermoelectric Modules Connected to Square Series–Parallel Configuration with Isolated Power Electronics Converter for DC Micro-grid Applications

This research paper offers a thermoelectric energy harvesting system that makes use of the heat generated within the stator windings of a wind generator in the operation of a 1.25 MW wind turbine. A single thermoelectric generator can generate only lower power. To deliver higher output power, the Bi-Te based thermoelectric modules (TEMs) may be associated as an array. The square series–parallel configuration is adopted in this work owing to the advantage of unaffected internal resistance value for any quantity of TEMs. The power generated by the TEMs is unsteady owing to irregular wind velocity. Therefore, a power converter is desired before the load. The proposed energy harvesting system makes use of an isolated converter that has the benefits of better efficiency, higher voltage gain, and ability for supplying a DC micro-grid system. Furthermore, a maximum power point tracking (MPPT) is required, since no matching exists between the total internal resistance of modules and load resistance. In this work, the incremental conductance MPPT technique is used to track the maximum power at every instant of time. The performance of the proposed isolated converter has been compared with other similar converters and the results obtained are tabulated to prove the effectiveness. From the acquired experimental results, it is observed that the proposed system produces a voltage gain of 29, steadier output power during the dynamics of load and efficiency of 91.35% at a wind velocity of 12.9 m/s.

Heat and mass transfer modeling and investigation of multiple LiFePO4/graphite batteries in a pack at low C-rates with water-cooling

Li-ion batteries (LIBs) are found to be deep spots in the Electric Vehicles (EVs) as well as Hybrid Electric Vehicles (HEVs) application. Combination of such high capacity LIBs in large serial-parallel configurations have been wrapped up with serious problems such as safety, durability, cost, and uniformity, which are imposing limitations on this broad application. A narrow area of these limitations, in which LIBs should operate safely and reliably, is the essential requirement of an effective control-thermal management scenario. In this paper, we examined the heat and mass transfer (temperature and mass flow rate of water) field as well as voltage profiles for a 20 Ah Graphite/LiFePO4 LIB pack at low currents of 20 A (1 C) and 40 A (2 C) with the selected ambient conditions using unique water-cooling methods with 35 °C, 25 °C, 15 °C, and 5 °C. This gives significant data information for the thermal behavior of LIB packs to design the temperature control (or thermal management) systems and develop an empirical voltage-thermal estimation model. In such manner, 3 prismatic LIBs with 20 Ah nominal capacity are arranged in a series with 4 micro-channel cooling plates placed within cells. There are six evenly placed thermocouples on the surface of each of these 3 battery cells used to extract time dependent temperatures. To make the data compatible for EV/HEV application, we developed a modified exponential-polynomial equivalent circuit model to simulate the temperature and voltage field. Outputs of the simulations are compared with the test data with specified C-rates and ambient conditions. The results demonstrate that increasing discharge currents and ambient conditions result in an increased surface temperature at 3 spots; close to the −ve electrode, close to the +ve electrode, and near the middle part of the LIB cell.

Design of New Hybrid Neural Structure for Modeling and Controlling Nonlinear Systems

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number of epoch, minimum number of neurons in the hybrid network, high accuracy in the output without oscillation response as well as useful model for a one step ahead prediction controller for the nonlinear CSTR system that is used in the MATLAB simulation.

Minimization of Losses in Solar Photovoltaic Modules by Reconfiguration under Various Patterns of Partial Shading

Configurations of photovoltaic (PV) modules, such as series-parallel (SP), bridge-linked (BL), and total cross-tied (TCT) configurations, always utilize a number of connecting switches. In a simulation, the ideal switch with no loss is used to optimize the reconfiguration method for a solar PV array. However, in practice, the switches are non-ideal, causing losses and resulting in a decrease in the total output power of the PV array. In this work, MATLAB/Simulink (R2016a) was employed to simulate nine PV modules linked in a 3 × 3 array, and they were reconfigured using series-parallel (SP), bridge-linked (BL), and total cross-tied (TCT) configurations for both ideal and non-ideal switch cases. It was not surprising that non-ideal switches deteriorated the output power compared with ideal cases. Then, the minimization of losses (ML) configuration was proposed by minimizing the number of switches to give the highest output power. A 5% higher power output was set as the criterion to reconfigure the PV modules when partial shading occurred. The results showed that if 50% or more of the area was partially shaded, reconfiguration was unnecessary. On the other hand, when the shaded area was less than 50%, reconfiguration gave a significant increase in power. Finally, the ML method had different configurations for various shading patterns, and provided better results than those of the TCT method.

Optimization of Hybrid Fiber Amplifier Utilizing Combined Serial-Parallel Configuration

In this paper, the optimum pump conditions are determined for C+L band combined serial-parallel hybrid fiber amplifier (CSP-HFA), utilizing gain control technique via OptiSystem 7.0. The optimization includes determining the optimum pump power (OPP), the optimum pump wavelength (OPW) and optimum coupling ratio (OCR), within the longest 3– dB flat gain bandwidth. The proposed HFA at optimum conditions, produced 65 nm flat gain bandwidth ranging from 1530 nm to 1595 nm within average gain of 16 dB and average NF of 7.29 dB. The proposed architecture provided two advantages over the conventional P-HFA includes; 1) improved flat gain bandwidth by 8.33 %, 2) constant optimum coupling ratio for both small and large signal at 0.7.

Presenting a Series-Parallel Redundancy Allocation Problem with Multi-State Components Using Recursive Algorithm and Meta-Heuristic

Redundancy Allocation Problem (RAP) is one of the most important problems in the field of reliability. This problem aims to increase system reliability, under constraints such as cost, weight, etc. In this paper, we work on a system with series-parallel configuration and multi-state components. To draw the problem nearer to real condition, we merge this problem with discount levels in purchasing components. For calculating sub-systems reliability, we used recursive algorithm. Because RAP belongs to Np. Hard problems, for optimizing the presented model a new Genetic algorithm (GA) was used. The algorithm parameters tuned using Response surface methodology (RSM) and for validation of GA an enumeration method was used.

PENGUJIAN EKSPERIMENTAL DAN SIMULASI ANSYS PERFORMANSI POMPA SENTRIFUGAL RANGKAIAN SERI DAN PARALEL

This study was conducted to identify the performance of centrifugal pump series configuration and parallel configuration experimentally and Ansys simulation. In the previous study, the performance of centrifugal pumps was calculated by varying the valve opening. In this study researchers varied motor rotation of 1000 rpm, 1200 rpm, 1400 rpm, 1600 rpm and 1800 rpm with open valve 100%. The results show that series configuration has higher head value than parallel configuration. While the parallel configuration has a higher capacity value than the series configuration. The highest pump efficiency for this pump performance test is in series configuration of 1800 rpm is 83.4% for experimental and 85% for simulation. While the lowest pump efficiency is in parallel configuration pumps of 1800 rpm with an efficiency 14.1% for experimental and 15.5% for simulation.

A Switchable Diplexer Using Switchable Impedance Matching Circuit Technique

A new type of switchable diplexer is proposed by using switchable impedance matching circuit (SIMC) to connect two quasi-elliptic bandpass filters. The proposed SIMC consists of two different T-network phase shifters to provide the desired impedance matching and a pair of series-parallel configuration p-i-n diode switches to switch the channels on/off. The designed switchable diplexers have four available operation states, so that they realize multiple functional blocks in a single module. The fabricated switchable diplexer features compact size, wide passband, high isolation and independently switchable operation states.

Modeling, simulation, and performance analysis of PV array configurations (Series, Series-Parallel, Bridge-Linked, and Honey-Comb) to harvest maximum power under various Partial Shading Conditions

ABSTRACT A major challenge for the progress of Photovoltaic (PV) power generation systems is to make them energy efficient. Partial Shading Condition (PSC) is one of the most important factors that contribute to the reduction in output power due to the mismatching power losses between the PV modules. These losses depend on the PV system structures; PV array configurations; shading patterns; physical location of shaded modules and the position of the tilt angle. This paper presents the modeling, simulation, and comparing the performance of 5 × 5 Series, Series-Parallel, Bridge-Linked, and Honey-Comb PV array configurations under uneven row, uneven column, diagonal, random, short and narrow, short and wide, long and narrow, and long and wide shading patterns. The performance of configurations is evaluated by comparing the open-circuit voltage; short-circuit current; Global maximum power point (GMPP); voltages and currents corresponding to GMPP;Local maximum power points (LMPPs); mismatching power losses; Fill Factor (FF) and efficiency. The variations in series resistance and shunt resistance of a PV module under different irradiance levels are also determined by considering the effect of thermal voltage. The KYOCERA-KC200GT PV modules are used for the simulation of 5 × 5 PV array configurations in MATLAB/Simulink software.

Characterization of SiPM arrays with common bias and common readout for applications in liquid argon

Abstract We have built a number of test arrays made of 16 SiPMs of 3 × 3 mm 2 with a mixed series–parallel configuration and common bias and readout. With this technique it is possible to increase the total active area keeping low the bias voltage and readout channels. To further increase the total area we connected few arrays together. Tests were performed in terms of pulse amplitude, charge and timing features.

Performance of double effect H2O–LiCl absorption refrigeration systems and comparison with H2O–LiBr systems, Part 2: Exergy analysis

In this article, exergy analysis is carried out to evaluate and compare the thermodynamic performances of the series, parallel and reverse parallel configurations of double effect H2O–LiCl vapour absorption refrigeration system (VARS). A comparison between double effect H2O–LiCl and H2O–LiBr systems is also provided to compare their exergetic performances under identical conditions. Initially, in Part 1 of this article, a detailed analysis was provided to identify the optimal operating conditions for the H2O–LiCl VARS configurations within the possible operational limits under certain fixed temperatures in the other VARS components. In this study, the exergy analysis is performed by evaluating the exergy efficiency and total system irreversibility of the double effect VARS configurations through parametric variations of component temperatures and distribution ratio. The present exergy based results conform well to the previously analyzed energy based results in Part 1. The optimal operating conditions, identified through energy analysis in Part 1, with respect to maximum COPs are almost identical with the ones corresponding to maximum exergy efficiencies and minimum total system irreversibility. Further, the exergy based performance comparison between the double effect H2O–LiCl and H2O–LiBr systems confirm superior performances of the H2O–LiCl systems not only with higher COP but also with higher exergy efficiency and comparatively lower total system irreversibility.

Performance of double effect H2O–LiCl absorption refrigeration systems and comparison with H2O–LiBr systems, Part 1: Energy analysis

In this study, the series, parallel and reverse parallel configurations of double effect H2O–LiCl vapour absorption refrigeration system (VARS) are thermodynamically modeled to provide performance comparison among the three systems under identical operating conditions. Parametric analysis is performed to investigate the effect of component temperatures and distribution ratio on coefficient of performance (COP) of the double effect VARS configurations. Results show that the maximum solution concentration, which is limited to 0.5 in H2O–LiCl VARS, is mainly controlled by the system operating temperatures. In case of the parallel and reverse parallel systems, maximum solution concentration also depends upon the distribution ratio. It was found that there exists an optimal combination of HPG and low pressure generator (LPG) temperature at which the COP of a particular double effect H2O-LiCl system is maximized. This optimal combination however varies with temperatures in the other components (absorber, condenser and evaporator). A performance comparison between double effect H2O–LiCl and H2O–LiBr systems under identical conditions showed better performance in case of the double effect H2O–LiCl VARS configurations. Due to its low maximum concentration limit (0.5 against 0.65 of H2O–LiBr VARS), double effect H2O–LiCl VARS configurations would be more appropriate and efficient compared to the H2O–LiBr systems, particularly at low LPG and HPG temperature applications.

“Parallel Training Considered Harmful?”: Comparing series-parallel and parallel feedforward network training

Neural network models for dynamic systems can be trained either in parallel or in series-parallel configurations. Influenced by early arguments, several papers justify the choice of series-parallel rather than parallel configuration claiming it has a lower computational cost, better stability properties during training and provides more accurate results. Other published results, on the other hand, defend parallel training as being more robust and capable of yielding more accu- rate long-term predictions. The main contribution of this paper is to present a study comparing both methods under the same unified framework. We focus on three aspects: i) robustness of the estimation in the presence of noise; ii) computational cost; and, iii) convergence. A unifying mathematical framework and simulation studies show situations where each training method provides better validation results, being parallel training better in what is believed to be more realistic scenarios. An example using measured data seems to reinforce such claim. We also show, with a novel complexity analysis and numerical examples, that both methods have similar computational cost, being series series-parallel training, however, more amenable to parallelization. Some informal discussion about stability and convergence properties is presented and explored in the examples.