223 resultados para Vehicle electrical systems.


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The amount of reactive power margin available in a system determines its proximity to voltage instability under normal and emergency conditions. More the reactive power margin, better is the systems security and vice-versa. A hypothetical way of improving the reactive margin of a synchronous generator is to reduce the real power generation within its mega volt-ampere (MVA) ratings. This real power generation reduction will affect its power contract agreements entered in the electricity market. Owing to this, the benefit that the generator foregoes will have to be compensated by paying them some lost opportunity cost. The objective of this study is three fold. Firstly, the reactive power margins of the generators are evaluated. Secondly, they are improved using a reactive power optimization technique and optimally placed unified power flow controllers. Thirdly, the reactive power capacity exchanges along the tie-lines are evaluated under base case and improved conditions. A detailed analysis of all the reactive power sources and sinks scattered throughout the network is carried out in the study. Studies are carried out on a real life, three zone, 72-bus equivalent Indian southern grid considering normal and contingency conditions with base case operating point and optimised results presented.

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Recently, we reported a low-complexity likelihood ascent search (LAS) detection algorithm for large MIMO systems with several tens of antennas that can achieve high spectral efficiencies of the order of tens to hundreds of bps/Hz. Through simulations, we showed that this algorithm achieves increasingly near SISO AWGN performance for increasing number of antennas in Lid. Rayleigh fading. However, no bit error performance analysis of the algorithm was reported. In this paper, we extend our work on this low-complexity large MIMO detector in two directions: i) We report an asymptotic bit error probability analysis of the LAS algorithm in the large system limit, where N-t, N-r -> infinity keeping N-t = N-r, where N-t and N-r are the number of transmit and receive antennas, respectively. Specifically, we prove that the error performance of the LAS detector for V-BLAST with 4-QAM in i.i.d. Rayleigh fading converges to that of the maximum-likelihood (ML) detector as N-t, N-r -> infinity keeping N-t = N-r ii) We present simulated BER and nearness to capacity results for V-BLAST as well as high-rate non-orthogonal STBC from Division Algebras (DA), in a more realistic spatially correlated MIMO channel model. Our simulation results show that a) at an uncoded BER of 10(-3), the performance of the LAS detector in decoding 16 x 16 STBC from DA with N-t = = 16 and 16-QAM degrades in spatially correlated fading by about 7 dB compared to that in i.i.d. fading, and 19) with a rate-3/4 outer turbo code and 48 bps/Hz spectral efficiency, the performance degrades by about 6 dB at a coded BER of 10(-4). Our results further show that providing asymmetry in number of antennas such that N-r > N-t keeping the total receiver array length same as that for N-r = N-t, the detector is able to pick up the extra receive diversity thereby significantly improving the BER performance.

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An approximate dynamic programming (ADP)-based suboptimal neurocontroller to obtain desired temperature for a high-speed aerospace vehicle is synthesized in this paper. A I-D distributed parameter model of a fin is developed from basic thermal physics principles. "Snapshot" solutions of the dynamics are generated with a simple dynamic inversion-based feedback controller. Empirical basis functions are designed using the "proper orthogonal decomposition" (POD) technique and the snapshot solutions. A low-order nonlinear lumped parameter system to characterize the infinite dimensional system is obtained by carrying out a Galerkin projection. An ADP-based neurocontroller with a dual heuristic programming (DHP) formulation is obtained with a single-network-adaptive-critic (SNAC) controller for this approximate nonlinear model. Actual control in the original domain is calculated with the same POD basis functions through a reverse mapping. Further contribution of this paper includes development of an online robust neurocontroller to account for unmodeled dynamics and parametric uncertainties inherent in such a complex dynamic system. A neural network (NN) weight update rule that guarantees boundedness of the weights and relaxes the need for persistence of excitation (PE) condition is presented. Simulation studies show that in a fairly extensive but compact domain, any desired temperature profile can be achieved starting from any initial temperature profile. Therefore, the ADP and NN-based controllers appear to have the potential to become controller synthesis tools for nonlinear distributed parameter systems.

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The problem addressed is one of model reference adaptive control (MRAC) of asymptotically stable plants of unknown order with zeros located anywhere in the s-plane except at the origin. The reference model is also asymptotically stable and lacking zero(s) at s = 0. The control law is to be specified only in terms of the inputs to and outputs of the plant and the reference model. For inputs from a class of functions that approach a non-zero constant, the problem is formulated in an optimal control framework. By successive refinements of the sub-optimal laws proposed here, two schemes are finally design-ed. These schemes are characterized by boundedness, convergence and optimality. Simplicity and total time-domain implementation are the additional striking features. Simulations to demonstrate the efficacy of the control schemes are presented.

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This paper presents the analysis and study of voltage collapse at any converter bus in A C-DC systems considering the dynamics of DC system. The problem of voltage instability is acute when HVDC links are connected to weak AC systems, the strength determined by short circuit ratio (SCR) at the converter bus. The converter control strategies are important in determining voltage instability. Small signal analysis is used to identify critical modes and evaluate the effect of AC system strength and control parameters. A sample two-terminal DC system is studied and the results compared with those obtained from static analysis. Also, the results obtained from small signal analysis are validated with nonlinear simulation.

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This paper analyses the behaviour of a general class of learning automata algorithms for feedforward connectionist systems in an associative reinforcement learning environment. The type of connectionist system considered is also fairly general. The associative reinforcement learning task is first posed as a constrained maximization problem. The algorithm is approximated hy an ordinary differential equation using weak convergence techniques. The equilibrium points of the ordinary differential equation are then compared with the solutions to the constrained maximization problem to show that the algorithm does behave as desired.

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A new design technique for an SVC-based power system damping controller has been proposed. The controller attempts to place all plant poles within a specified region on the s-plane to guarantee the desired closed loop performance. The use of Horowitz's quantitative feedback theory (QFT) permits the design of a 'fixed gain controller' that maintains its performance in spite of large variations in the plant parameters during its normal course of operation. The required controller parameters are arrived at by solving an optimization problem that incorporates the control specifications. The performance of this robust controller has been evaluated on a single machine infinite bus system equipped with a mid point SVC, and the results are shown to be consistent with the expected performance of the stabilizer. (C) 1998 Elsevier Science S.A. All rights reserved.

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We present through the use of Petri Nets, modeling techniques for digital systems realizable using FPGAs. These Petri Net models are used for logic validation at the logic design phase. The technique is illustrated by modeling practical circuits. Further, the utility of the technique with respect to timing analysis of the modeled digital systems is considered. Copyright (C) 1997 Elsevier Science Ltd

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The problem of estimating multiple Carrier Frequency Offsets (CFOs) in the uplink of MIMO-OFDM systems with Co-Channel (CC) and OFDMA based carrier allocation is considered. The tri-linear data model for generalized, multiuser OFDM system is formulated. Novel blind subspace based estimation of multiple CFOs in the case of arbitrary carrier allocation scheme in OFDMA systems and CC users in OFDM systems based on the Khatri-Rao product is proposed. The method works where the conventional subspace method fails. The performance of the proposed methods is compared with pilot based Least-Squares method.

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Zero padded systems with linear receivers are shown to be robust and amenable to fast implementations in single antenna scenarios. In this paper, properties of such systems are investigated when multiple antennas are present at both ends of the communication link. In particular, their diversity and complexity are evaluated for precoded transmissions. The linear receivers are shown to exploit multipath and receive diversities, even in the absence of any coding at the transmitter. Use of additional redundancy to improve performance is considered and the effect of transmission rate on diversity order is analyzed. Low complexity implementations of Zero Forcing receivers are devised to further enhance their applicability.

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We consider a time division duplex multiple-input multiple-output (nt × nr MIMO). Using channel state information (CSI) at the transmitter, singular value decomposition (SVD) of the channel matrix is performed. This transforms the MIMO channel into parallel subchannels, but has a low overall diversity order. Hence, we propose X-Codes which achieve a higher diversity order by pairing the subchannels, prior to SVD preceding. In particular, each pair of information symbols is encoded by a fixed 2 × 2 real rotation matrix. X-Codes can be decoded using nr very low complexity two-dimensional real sphere decoders. Error probability analysis for X-Codes enables us to choose the optimal pairing and the optimal rotation angle for each pair. Finally, we show that our new scheme outperforms other low complexity precoding schemes.

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We develop an optimal, distributed, and low feedback timer-based selection scheme to enable next generation rate-adaptive wireless systems to exploit multi-user diversity. In our scheme, each user sets a timer depending on its signal to noise ratio (SNR) and transmits a small packet to identify itself when its timer expires. When the SNR-to-timer mapping is monotone non-decreasing, timers of users with better SNRs expire earlier. Thus, the base station (BS) simply selects the first user whose timer expiry it can detect, and transmits data to it at as high a rate as reliably possible. However, timers that expire too close to one another cannot be detected by the BS due to collisions. We characterize in detail the structure of the SNR-to-timer mapping that optimally handles these collisions to maximize the average data rate. We prove that the optimal timer values take only a discrete set of values, and that the rate adaptation policy strongly influences the optimal scheme's structure. The optimal average rate is very close to that of ideal selection in which the BS always selects highest rate user, and is much higher than that of the popular, but ad hoc, timer schemes considered in the literature.

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In this paper we develop an analytical heat transfer model, which is capable of analyzing cyclic melting and solidification processes of a phase change material used in the context of electronics cooling systems. The model is essentially based on conduction heat transfer, with treatments for convection and radiation embedded inside. The whole solution domain is first divided into two main sub-domains, namely, the melting sub-domain and the solidification sub-domain. Each sub-domain is then analyzed for a number of temporal regimes. Accordingly, analytical solutions for temperature distribution within each subdomain are formulated either using a semi-infinity consideration, or employing a method of quasi-steady state, depending on the applicability. The solution modules are subsequently united, leading to a closed-form solution for the entire problem. The analytical solutions are then compared with experimental and numerical solutions for a benchmark problem quoted in the literature, and excellent agreements can be observed.

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The paper deals with the existence of a quadratic Lyapunov function V = x′P(t)x for an exponentially stable linear system with varying coefficients described by the vector differential equation S0305004100044777_inline1 The derivative dV/dt is allowed to be strictly semi-(F) and the locus dV/dt = 0 does not contain any arc of the system trajectory. It is then shown that the coefficient matrix A(t) of the exponentially stable sy