The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Robert D Lorenz - One of the best experts on this subject based on the ideXlab platform.
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improved nonlinear model for electrode voltage current relationship for more consistent online Battery System identification
IEEE Transactions on Industry Applications, 2013Co-Authors: Larry W Juang, Phillip J Kollmeyer, T M Jahns, Robert D LorenzAbstract:An improved nonlinear model for the electrode voltage-current relationship for online Battery System identification is proposed. In contrast to the traditional linear-circuit model, the new approach employs a more accurate model of the Battery electrode nonlinear steady-state voltage drop based on the Butler-Volmer (BV) equation. The new form uses an inverse hyperbolic sine approximation for the BV equation. Kalman-filter-based System identification is proposed for determining the model parameters based on the measured voltage and current. Both models have been implemented for lead-acid batteries and exercised using test data from a Corbin Sparrow electric vehicle. A comparison of predictions for the two models demonstrates the improvements that can be achieved using the new nonlinear model. The results include improved Battery voltage predictions that provide the basis for more accurate state-of-function readings.
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improved nonlinear model for electrode voltage current relationship for more consistent online Battery System identification
Energy Conversion Congress and Exposition, 2011Co-Authors: Larry W Juang, Phillip J Kollmeyer, T M Jahns, Robert D LorenzAbstract:An improved nonlinear model for the electrode voltage-current relationship for online Battery System identification is proposed. In contrast with the traditional linear-circuit model, the new approach employs a more accurate model of the Battery electrode nonlinear steady-state voltage drop based on the Butler-Volmer equation. The new form uses an inverse hyperbolic sine approximation for the Butler-Volmer equation. Kalman filter-based System identification is proposed for determining the model parameters based on the measured voltage and current. Both models have been implemented for lead-acid batteries and exercised using test data from a Corbin Sparrow electric vehicle. A comparison of predictions for the two models demonstrates the improvements that can be achieved using the new nonlinear model. The results include improved Battery voltage predictions that provide the basis for more accurate state-of-function (SOF) readings.
Larry W Juang - One of the best experts on this subject based on the ideXlab platform.
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improved nonlinear model for electrode voltage current relationship for more consistent online Battery System identification
IEEE Transactions on Industry Applications, 2013Co-Authors: Larry W Juang, Phillip J Kollmeyer, T M Jahns, Robert D LorenzAbstract:An improved nonlinear model for the electrode voltage-current relationship for online Battery System identification is proposed. In contrast to the traditional linear-circuit model, the new approach employs a more accurate model of the Battery electrode nonlinear steady-state voltage drop based on the Butler-Volmer (BV) equation. The new form uses an inverse hyperbolic sine approximation for the BV equation. Kalman-filter-based System identification is proposed for determining the model parameters based on the measured voltage and current. Both models have been implemented for lead-acid batteries and exercised using test data from a Corbin Sparrow electric vehicle. A comparison of predictions for the two models demonstrates the improvements that can be achieved using the new nonlinear model. The results include improved Battery voltage predictions that provide the basis for more accurate state-of-function readings.
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improved nonlinear model for electrode voltage current relationship for more consistent online Battery System identification
Energy Conversion Congress and Exposition, 2011Co-Authors: Larry W Juang, Phillip J Kollmeyer, T M Jahns, Robert D LorenzAbstract:An improved nonlinear model for the electrode voltage-current relationship for online Battery System identification is proposed. In contrast with the traditional linear-circuit model, the new approach employs a more accurate model of the Battery electrode nonlinear steady-state voltage drop based on the Butler-Volmer equation. The new form uses an inverse hyperbolic sine approximation for the Butler-Volmer equation. Kalman filter-based System identification is proposed for determining the model parameters based on the measured voltage and current. Both models have been implemented for lead-acid batteries and exercised using test data from a Corbin Sparrow electric vehicle. A comparison of predictions for the two models demonstrates the improvements that can be achieved using the new nonlinear model. The results include improved Battery voltage predictions that provide the basis for more accurate state-of-function (SOF) readings.
M Ndongo - One of the best experts on this subject based on the ideXlab platform.
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optimal design of a hybrid solar wind Battery System using the minimization of the annualized cost System and the minimization of the loss of power supply probability lpsp
Renewable Energy, 2010Co-Authors: Ould B Bilal, Vincent Sambou, P A Ndiaye, C M F Kebe, M NdongoAbstract:Potou is an isolated site, located in the northern coast of Senegal. The populations living in this area have no easy access to electricity supply. The use of renewable energies can contribute to the improvement of the living conditions of these populations. The methodology used in this paper consists in Sizing a hybrid solar–wind-Battery System optimized through multi-objective genetic algorithm for this site and the influence of the load profiles on the optimal configuration. The two principal aims are: the minimization of the annualized cost System and the minimization of the loss of power supply probability (LPSP).
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optimal design of a hybrid solar wind Battery System using the minimization of the annualized cost System and the minimization of the loss of power supply probability lpsp
Renewable Energy, 2010Co-Authors: Ould B Bilal, Vincent Sambou, P A Ndiaye, C M F Kebe, M NdongoAbstract:Abstract Potou is an isolated site, located in the northern coast of Senegal. The populations living in this area have no easy access to electricity supply. The use of renewable energies can contribute to the improvement of the living conditions of these populations. The methodology used in this paper consists in Sizing a hybrid solar–wind-Battery System optimized through multi-objective genetic algorithm for this site and the influence of the load profiles on the optimal configuration. The two principal aims are: the minimization of the annualized cost System and the minimization of the loss of power supply probability (LPSP). To study the load profile influence, three load profiles with the same energy (94 kW h/day) have been used. The achieved results show that the cost of the optimal configuration strongly depends on the load profile. For example, the cost of the optimal configuration decreases by 7% and 5% going from profile 1 to 2 and for those ones going from 1 to 3.
Arturs Purvins - One of the best experts on this subject based on the ideXlab platform.
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optimal management of stationary lithium ion Battery System in electricity distribution grids
Journal of Power Sources, 2013Co-Authors: Arturs Purvins, M SumnerAbstract:Abstract The present article proposes an optimal Battery System management model in distribution grids for stationary applications. The main purpose of the management model is to maximise the utilisation of distributed renewable energy resources in distribution grids, preventing situations of reverse power flow in the distribution transformer. Secondly, Battery management ensures efficient Battery utilisation: charging at off-peak prices and discharging at peak prices when possible. This gives the Battery System a shorter payback time. Management of the System requires predictions of residual distribution grid demand (i.e. demand minus renewable energy generation) and electricity price curves (e.g. for 24 h in advance). Results of a hypothetical study in Great Britain in 2020 show that the Battery can contribute significantly to storing renewable energy surplus in distribution grids while being highly utilised. In a distribution grid with 25 households and an installed 8.9 kW wind turbine, a Battery System with rated power of 8.9 kW and Battery capacity of 100 kWh can store 7 MWh of 8 MWh wind energy surplus annually. Annual Battery utilisation reaches 235 cycles in per unit values, where one unit is a full charge-depleting cycle depth of a new Battery (80% of 100 kWh).
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application of Battery based storage Systems in household demand smoothening in electricity distribution grids
Energy Conversion and Management, 2013Co-Authors: Arturs Purvins, Ioulia T Papaioannou, Luigi DebarberisAbstract:Abstract This article analyses in technical terms the application of Battery-based storage Systems for household-demand smoothening in electricity-distribution grids. The analysis includes case studies of Denmark, Portugal, Greece, France and Italy. A high penetration of photovoltaic Systems in distribution grids is considered as an additional scenario. A sensitivity analysis is performed in order to examine the smoothening effect of daily demand profiles for different configurations of the Battery System. In general, Battery-storage Systems with low rated power and low Battery capacity can smooth the demand sufficiently with the aid of a simple management process. For example, with 1 kW of peak demand, a 30–45% decrease in the variability of the daily demand profile can be achieved with a Battery System of 0.1 kW rated power and up to 0.6 kW h Battery capacity. However, further smoothening requires higher Battery-System capacity and power. In this case, more elaborate management is also needed to use the Battery System efficiently.
T M Jahns - One of the best experts on this subject based on the ideXlab platform.
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improved nonlinear model for electrode voltage current relationship for more consistent online Battery System identification
IEEE Transactions on Industry Applications, 2013Co-Authors: Larry W Juang, Phillip J Kollmeyer, T M Jahns, Robert D LorenzAbstract:An improved nonlinear model for the electrode voltage-current relationship for online Battery System identification is proposed. In contrast to the traditional linear-circuit model, the new approach employs a more accurate model of the Battery electrode nonlinear steady-state voltage drop based on the Butler-Volmer (BV) equation. The new form uses an inverse hyperbolic sine approximation for the BV equation. Kalman-filter-based System identification is proposed for determining the model parameters based on the measured voltage and current. Both models have been implemented for lead-acid batteries and exercised using test data from a Corbin Sparrow electric vehicle. A comparison of predictions for the two models demonstrates the improvements that can be achieved using the new nonlinear model. The results include improved Battery voltage predictions that provide the basis for more accurate state-of-function readings.
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improved nonlinear model for electrode voltage current relationship for more consistent online Battery System identification
Energy Conversion Congress and Exposition, 2011Co-Authors: Larry W Juang, Phillip J Kollmeyer, T M Jahns, Robert D LorenzAbstract:An improved nonlinear model for the electrode voltage-current relationship for online Battery System identification is proposed. In contrast with the traditional linear-circuit model, the new approach employs a more accurate model of the Battery electrode nonlinear steady-state voltage drop based on the Butler-Volmer equation. The new form uses an inverse hyperbolic sine approximation for the Butler-Volmer equation. Kalman filter-based System identification is proposed for determining the model parameters based on the measured voltage and current. Both models have been implemented for lead-acid batteries and exercised using test data from a Corbin Sparrow electric vehicle. A comparison of predictions for the two models demonstrates the improvements that can be achieved using the new nonlinear model. The results include improved Battery voltage predictions that provide the basis for more accurate state-of-function (SOF) readings.
