Abstract: A method for monitoring a battery system is proposed. The method includes providing a sequence of pairs of measured current and voltage values that follow one another in time. The pairs of current and voltage values indicate the current flowing through the battery system and the voltage present at the battery system. The method also provides for an electrical equivalent model of the battery system to be provided. The equivalent electrical model has several impedances connected in series. Initial impedance parameter values are provided for the impedances of the equivalent electrical model. The method provides for adjusting a first impedance parameter of an impedance of the equivalent electrical model based on the difference between a first voltage value simulated based on the initial impedance parameter values and the first current value of the finite sequence and the first measured voltage value of the finite sequence. An optimized first impedance parameter value is thereby obtained.

Abstract: The invention relates to a system for modelling at least one state of a battery, the system comprising a parametric battery model, configured to receive one or more inputs and to provide a first output based thereon, a machine learning model, which has been trained to correct an output of the parametric battery model based on battery operation comprising aging, configured to receive one or more inputs and the first output and to provide a second output based thereon, a combiner, configured to receive the first output and the second output and to provide a third output based thereon.

Abstract: Various examples of the disclosure pertain to determining a set of calendar aging values of a test cell of a rechargeable battery, e.g., LIBs. The set of calendar aging values of the test cell of the rechargeable battery corresponds to a set of Temperature-State of Charge (T-SOC) value pairs. The set of calendar aging values of the test cell of the rechargeable battery is determined based on a battery-generic reference model for calendar aging of a (specific or random) battery cell and on a further set of calendar aging values of the test cell of the rechargeable battery. The further set of calendar aging values is obtained/derived from measurements of the test cell of the rechargeable battery and corresponds to a further set of T-SOC value pairs.

Abstract: The dependency of the open circuit voltage on the state of charge of a battery, i.e., the OCV curve is determined, e.g., to facilitate determination of the state of health or state of charge of the battery. The OCV curve is determined based on the values of multiple independent parameters, e.g., half-cell potentials derived from degradation modes such as loss of lithium inventory or loss of active material at the cathode or anode.

Abstract: A method for monitoring a battery system is proposed. The method includes providing a sequence of pairs of measured current and voltage values that follow one another in time. The pairs of current and voltage values indicate the current flowing through the battery system and the voltage present at the battery system. The method also provides for an electrical equivalent model of the battery system to be provided. The equivalent electrical model has several impedances connected in series. Initial impedance parameter values are provided for the impedances of the equivalent electrical model. The method provides for adjusting a first impedance parameter of an impedance of the equivalent electrical model based on the difference between a first voltage value simulated based on the initial impedance parameter values and the first current value of the finite sequence and the first measured voltage value of the finite sequence. An optimized first impedance parameter value is thereby obtained.