Abstract: A method and a system for determining an assessment indicator for assessing at least one of a performance, a state, and a load condition of a battery storage. A series of measurements of at least one physical parameter of the battery storage, including at least one of voltage and current, is obtained. The measurements correspond to successive points of time of a time segment. The series of measurements is input to an encoder of an autoencoder. A reconstructed series of measurements is received from a decoder of the autoencoder. A value of a reconstruction error is calculated based on the series of measurements and the reconstructed series of measurements, and the assessment indicator is determined based on the calculated value of the reconstruction error.

Abstract: A simulation system and a method for simulating a performance of at least one storage unit of an energy storage. The simulation system includes at least one respective model for a respective storage unit of the energy storage. The encoder-decoder model includes at least one recurrent neural network or at least one neural network having a transformer architecture. The encoder processes an encoder input sequence that describes a measured temporal course of current and voltage or of power and voltage of the storage unit assigned to the model. The encoder generates an initial state of the model. The decoder processes a decoder input sequence describing a temporal course to be simulated of the current or of the power of the storage unit. The decoder generates a decoder output sequence that describes a simulated temporal course of the voltage of the storage unit assigned to the model.

Abstract: A computer-implemented method and an electrical impedance analyzing system for analyzing electrical impedance measurements of an electrochemical battery, including: a translating of respective electrical impedance measurements that corresponds to subtracting an ohmic alternating current resistance value from the real part of electrical impedance; and a scaling using scaling factors, the absolute values of which are based on an electrical impedance that corresponds to a transition between a translated first subseries and a translated second subseries of the series of electrical impedance measurements, the first subseries being associated with a battery behavior of the electrochemical battery in which the electrical impedance is dominated by diffusion processes, the second subseries being associated with a battery behavior of the electrochemical battery in which the electrical impedance is dominated by charge transfer processes at the electrodes of the battery.

Abstract: A computer-implemented method and a battery state estimating system for estimating a battery state of an electrochemical battery, including: weighting the electrical impedance measurements of a provided series of electrical impedance measurements according to a weighting function that is dependent on the index(s) of the series or on the measurement frequency, resulting in at least a series of consecutive elements of the series of measurements, when point-to-point connected in the complex plane of the electrical impedance in a sequence according to the index of the series of measurements, forming at least one loop in the complex plane; calculating a measure of the size of the at least one loop in the complex plane; determining an estimation of a battery state of the electrochemical battery based on the calculated measure of the size of the at least one loop in the complex plane; and outputting the estimation of the battery state.

Abstract: A computer-implemented method and a battery state estimating system for estimating a battery state of an electrochemical battery, including: calculating electrical impedance gradients from a provided series of electrical impedance measurements to generate a series of electrical impedance gradients; and determining a battery state of the electrochemical battery using computational means configured to receive as inputs at least the series of electrical impedance gradients, the computational means receiving and processing at least the provided series of calculated electrical impedance gradients to generate therefrom at least one output signal representing a battery state associated with the electrochemical battery.

Abstract: A computer-implemented method and a temperature estimating system for estimating a temperature of an electrochemical battery, including: providing a series of electrical impedance measurements of an electrochemical battery, each electrical impedance measurement being measured at a respective measurement frequency, the series being ordered according to the respective measurement frequencies; and determining a temperature of the electrochemical battery using artificial neural network means configured to receive as inputs a series of electrical impedance values, wherein a series of electrical impedance values is provided to the artificial neural network means, the series of electrical impedance values corresponding to the provided series of electrical impedance measurements, wherein the artificial neural network means receives and processes the provided series of electrical impedance values to generate therefrom an output signal representing a temperature associated with the electrochemical battery.

Abstract: A computer-implemented method and a battery state estimating system for estimating a battery state of an electrochemical battery, including: providing a series of electrical impedance measurements of an electrochemical battery, the series being ordered according to the respective measurement frequencies; and determining a battery state of the electrochemical battery using artificial convolutional neural network means configured to receive as inputs a series of electrical impedance values, wherein a series of electrical impedance values is provided to the artificial convolutional neural network means, the series of electrical impedance values corresponding to the provided series of electrical impedance measurements, wherein the artificial convolutional neural network means receives and processes the provided series of electrical impedance values to generate therefrom at least one output signal representing a battery

Abstract: A computer-implemented method and a battery state estimating system for estimating a battery state of an electrochemical battery, including: calculating electrical impedance gradients from a provided series of electrical impedance measurements to generate a series of electrical impedance gradients; and determining a battery state of the electrochemical battery using computational means configured to receive as inputs at least the series of electrical impedance gradients, the computational means receiving and processing at least the provided series of calculated electrical impedance gradients to generate therefrom at least one output signal representing a battery state associated with the electrochemical battery.

Abstract: A computer-implemented method and a battery state estimating system for estimating a battery state of an electrochemical battery, including: weighting the electrical impedance measurements of a provided series of electrical impedance measurements according to a weighting function that is dependent on the index(s) of the series or on the measurement frequency, resulting in at least a series of consecutive elements of the series of measurements, when point-to-point connected in the complex plane of the electrical impedance in a sequence according to the index of the series of measurements, forming at least one loop in the complex plane; calculating a measure of the size of the at least one loop in the complex plane; determining an estimation of a battery state of the electrochemical battery based on the calculated measure of the size of the at least one loop in the complex plane; and outputting the estimation of the battery state.

Abstract: A computer-implemented method and a temperature estimating system for estimating a temperature of an electrochemical battery, including: providing a series of electrical impedance measurements of an electrochemical battery, each electrical impedance measurement being measured at a respective measurement frequency, the series being ordered according to the respective measurement frequencies; and determining a temperature of the electrochemical battery using artificial neural network means configured to receive as inputs a series of electrical impedance values, wherein a series of electrical impedance values is provided to the artificial neural network means, the series of electrical impedance values corresponding to the provided series of electrical impedance measurements, wherein the artificial neural network means receives and processes the provided series of electrical impedance values to generate therefrom an output signal representing a temperature associated with the electrochemical battery.

Abstract: A computer-implemented method and an electrical impedance analyzing system for analyzing electrical impedance measurements of an electrochemical battery, including: a translating of respective electrical impedance measurements that corresponds to subtracting an ohmic alternating current resistance value from the real part of electrical impedance; and a scaling using scaling factors, the absolute values of which are based on an electrical impedance that corresponds to a transition between a translated first subseries and a translated second subseries of the series of electrical impedance measurements, the first subseries being associated with a battery behavior of the electrochemical battery in which the electrical impedance is dominated by diffusion processes, the second subseries being associated with a battery behavior of the electrochemical battery in which the electrical impedance is dominated by charge transfer processes at the electrodes of the battery.