Robert Boschgmbh

Stefan Schindler

Christian Simonis

Maurice Caspar

The disclosure concerns a method for determining a predicted state of health of a device battery in a battery-operated machine. A state of health characteristic model for a state of health time characteristic is provided using a number of linked parameterizable characteristic functions that each indicate a state of health over a time period of ageing times, the characteristic functions being initially parameterized. A number of data points are captured that each indicate a state of health and an ageing time. A parameter of one of the characteristic functions is adapted based on the data points in the respective time periods of the characteristic functions. A parameter of another of the characteristic functions, for which there is no data point available, is also adapted. The state of health characteristic model is provided based on the adapted characteristic functions.

Method and apparatus for predicting a state of health of a device battery in a battery-operated device

A method for determining a state of health trajectory of a device battery is based on state of health values of device batteries of an identical battery type. The method includes providing time characteristics of operating variables of a multiplicity of device batteries of battery-operated machines in a central processing unit, and determining one or more state of health values of one or more of the multiplicity of device batteries by evaluating a respective characteristic of the operating variables within an evaluation period. The one or more state of health values with the applicable aging times each indicate a data point for the relevant device battery. The method further includes eliminating data points from the determined data points to obtain a set of cleaned-up data points, and ascertaining the state of health trajectory with an accuracy statement for each trajectory point based on the set of cleaned-up data points.

A method for determining a trajectory function to represent an aging state trajectory for at least one electrical energy storage unit of one or more devices includes determining uncertainty-containing model values of aging states of the at least one electrical energy storage unit, cleaning error-containing model values of the determined uncertainty-containing model values, determining the aging state trajectory based on the cleaned model values, and determining the trajectory function based on the determined aging state trajectory.

Method and apparatus for determining and fusing an aging state trajectory of an electrical energy storage unit based on statistical, model-based, and machine-learning methods

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Bietigheim-Bissingen, Germany

Stefan Schindler