Abstract:
A prediction algorithm in equation form is developed by testing a battery (F) to acquire given battery parameters and develop numerical weighting factors for the parameters. To predict the available energy, the battery (F) is tested to acquire data of the parameters and the data values are applied to the equation.
Abstract:
A method of predicting by non-invasive testing the available energy of a battery at any state of charge by acquiring data of the parameters of internal resistance (IR), open circuit voltage (OCV) and temperature (T), the points of voltage and current of the slope on a positive current ramp of Vup and Iup at the transition from charge to overcharge and on a negative current ramp of Vdn and Idn at the transition from overcharge to charge for a plurality of batteries. Next an algorithm in the form of a linear equation is developed using this data. The available energy of a battery under test is predicted by acquiring from it the numerical data values of these parameters and applying them to the algorithm.
Abstract:
A prediction algorithm in equation form is developed by testing a battery (F ) to acquire given battery parameters and develop numerical weighting factors for the parameters. To predict the available energy, the battery (F) is test ed to acquire data of the parameters and the data values are applied to the equation.
Abstract:
A prediction algorithm in equation form is developed by testing a battery (F ) to acquire given battery parameters and develop numerical weighting factors for the parameters. To predict the available energy, the battery (F) is test ed to acquire data of the parameters and the data values are applied to the equation.
Abstract:
A method of predicting by non-invasive testing the available energy of a battery at any state of charge by acquiring data of the parameters of internal resistance (IR), open circuit voltage (OCV) and temperature (T), the points of voltage and current of the slope on a positive current ramp of Vup and Iup at the transition from charge to overcharge and on a negative current ramp of Vdn and Idn at the transition from overcharge to charge for a plurality of batteries. Next an algorithm in the form of a linear equation is developed using this data. The available energy of a battery under test is predicted by acquiring from it the numerical data values of these parameters and applying them to the algorithm.
Abstract:
A method (Fig. 1) for determining the state of charge (SOC) of a battery by measuring its open circuit voltage (OCV) either with the battery in a fully rested state of chemical and electrical equilibrium or an active state durin g a period in which the battery settles after charge or discharge is stopped. A first type algorithm (Fig. 4) is developed to correlate the OCV in a fully rested condition (OCVREST) to the state of charge at which that measurement is taken. A second type algorithm is developed that predicts a final settling O CV of a battery (OCVPRED), based on the set of parameters of OCV, rate of chang e of OCV, and battery case temperature, acquired during the settling period of a battery not at rest. To determine the SOC of a battery being tested that is in the fully settled state the measured OCVREST is applied to the first type algorithm (Fig. 4). To determine the SOC of a battery that has not fully settled, the data of the OCV, rate of change of OCV and battery temperature is applied to a second type algorithm to determine OCVPRED and the OCVPRED valu e is used in the first type algorithm to determine SOC.
Abstract:
Un método de predecir la energía disponible de una batería de plomo-ácido mediante una prueba independiente del estado de carga de la batería, comprendiendo dicho método las operaciones de: determinar la resistencia interna (IR) de la batería que se prueba; medir el voltaje en circuito abierto (OCV) y la temperatura (T) de la batería que se prueba; calcular los puntos de voltaje y de intensidad (Vgas e Igas) a los que la batería realiza una transición desde un estado de carga a uno de sobrecarga o de un estado de sobrecarga a uno de carga en respuesta a, por lo menos, una de entre las condiciones de carga y de descarga, cuya operación de calcular Vgas e Igas comprende: aplicar a la batería una corriente en rampa (I) en cada una de las direcciones positiva y negativa, vigilar la respuesta de voltaje (V) a la intensidad (I) aplicada, y determinar los puntos máximos de la pendiente; desarrollar un algoritmo de predicción de la energía disponible en función de los parámetros de la batería; y aplicar los valores adquiridos de los parámetros de la batería que se prueba al algoritmo para predecir la energía disponible en la batería que se prueba, caracterizado porque los puntos máximos de Vgas e Igas de la pendiente en la rampa de corriente positiva son Vsubida e Isubida en la transición de carga a descarga y, en la rampa negativa son Vbajada e Ibajada en la transición de sobrecarga a carga; la operación de desarrollar el algoritmo comprende utilizar los parámetros OCV, T, IR, Vsubida e Isubida y Vbajada e Ibajada de la batería, y la operación de aplicar los valores adquiridos de los parámetros de la batería comprende aplicar los valores de los parámetros OCV, T, IR, Vsubida e Isubida y Vbajada e Ibajada de la batería que se prueba al algoritmo para predecir la energía disponible en la batería que se prueba.
Abstract:
A method of predicting by non-invasive testing the available energy of a battery at any state of charge by acquiring data of the parameters of internal resistance (IR), open circuit voltage (OCV) and temperature (T), the points of voltage and current of the slope on a positive current ramp of Vup and Iup at the transition from charge to overcharge and on a negative current ramp of Vdn and Idn at the transition from overcharge to charge for a plurality of batteries. Next an algorithm in the form of a linear equation is developed using this data. The available energy of a battery under test is predicted by acquiring from it the numerical data values of these parameters and applying them to the algorithm.