Abstract: A device for detecting a thermal runaway of a battery module with a number of cells includes a current acquisition module that is configured to capture a set of currents, and a temperature acquisition module that is configured to capture a set of temperatures. The device includes a state of charge capturing module that is configured to capture a set of states, and a resistance calculation module that is configured to derive a set of resistances. The device includes a temperature prediction module that is configured to calculate a set of temperature predictors, and a runaway prediction module that is configured to calculate a set of runaway predictors. A warning module that is configured to set a warning indicator when at least one runaway predictor value of the set of runaway predictors exceeds a predefined threshold value.

Abstract: A battery module is disclosed, which includes: a multiplicity of battery cells; a printed circuit board with a first series-connector with a first pad area and a second pad area, and a second series-connector with a third pad area and a fourth pad area; a cross-connector, which connects the first series-connector between the first pad area and the second pad area with the second series-connector between the third pad area and the fourth pad area; and a sensor configured to detect a cross-current at the cross-connector. The first contact electrode of a first battery cell is connected with the first pad area. The second contact electrode of a second battery cell is connected with the second pad area. The first contact electrode of a third battery cell is connected with the third pad area. The second contact electrode of a fourth battery cell is connected with the fourth pad area.

Abstract: A state of charge of a battery is estimated by a battery model specific to the battery. The battery model provides a section-wise defined correlation of terminal voltage values depending on state of charge values. Each of sections of the battery model delimits a monotonic dependence of the correlation from others of the sections. By segmenting the correlation of terminal voltage values depending on a state of charge value into sections, each segment within such the section-wise defined correlation of terminal voltage values depending on state of charge values is mathematically spoken a bi-unique function suitable for transformation into an inverse function defined within the section. The estimated state of charge may be continuously refined by an iterative feedback loop including coulomb counting for estimating a battery charge value, where refined estimated battery charge values state of charge values at a previous cycle are projected forward to the current cycle.

Abstract: Method for determining the degradation of a battery module or a battery cell that each deliver energy to an electric load, wherein a) a battery parameter set comprising an actual temperature of the battery module is captured, b) a load parameter set is captured, c) an environmental parameter set is captured, d) a machine learning model is set up and trained with the battery parameter set, the load parameter set and the environmental parameter set, e) a predicted temperature and a standard deviation thereof is calculated using the machine learning model, and the degradation of the battery module is determined using a predicted temperature, the standard deviation and the actual temperature, where a change over the time of the probability of measuring the actual module or cell temperature, which is normal distributed, is an indicator for the degradation of the battery module or battery cell.

Abstract: A method for enhancing a battery module model of a battery module type includes a) exposing a battery module to a first environment and measuring an initial battery parameter, b) training the battery module model of the battery module type with the initial battery parameter based on machine learning techniques, c) operating the battery module at a second environment with changing environmental conditions and capturing an operating battery parameter, d) training the battery module model with the operating battery parameter, e) calculating an end-of life (EOL) parameter (40) relating to an EOL prediction of the battery module, where if the EOL parameter exceeds a predetermined threshold value, then the method continues with step f), other a return to step c) occurs, f) exposing the battery module to a third environment and measuring a final battery parameter, and g) training the battery module model with the final battery parameter.

Abstract: A device for detecting a thermal runaway of a battery module with a number of cells includes a current acquisition module that is configured to capture a set of currents, and a temperature acquisition module that is configured to capture a set of temperatures. The device includes a state of charge capturing module that is configured to capture a set of states, and a resistance calculation module that is configured to derive a set of resistances. The device includes a temperature prediction module that is configured to calculate a set of temperature predictors, and a runaway prediction module that is configured to calculate a set of runaway predictors. A warning module that is configured to set a warning indicator when at least one runaway predictor value of the set of runaway predictors exceeds a predefined threshold value.

Abstract: A stator is provided for a permanent magnet synchronous motor. The stator includes a multiplicity of stator teeth, each stator tooth having a tooth axis. The stator further includes a stator ring with a stator axis, wherein the multiplicity of stator teeth is arranged radially along the circumference of the stator ring, and the tooth axes cross the stator axis orthogonally within one plane.

Abstract: A state of charge of a battery is estimated by a battery model specific to the battery. The battery model provides a section-wise defined correlation of terminal voltage values depending on state of charge values. Each of sections of the battery model delimits a monotonic dependence of the correlation from others of the sections. By segmenting the correlation of terminal voltage values depending on a state of charge value into sections, each segment within such the section-wise defined correlation of terminal voltage values depending on state of charge values is mathematically spoken a bi-unique function suitable for transformation into an inverse function defined within the section. The estimated state of charge may be continuously refined by an iterative feedback loop including coulomb counting for estimating a battery charge value, where refined estimated battery charge values state of charge values at a previous cycle are projected forward to the current cycle.

Abstract: A winding head for a stator tooth of an electric motor is provided. A stator core has a first stator flange and a second stator flange that are joined by a stator joint part. The stator core has an I-shaped cross section perpendicular to a longitudinal elongation with a first end and a second end. The winding head is configured to extend the longitudinal elongation at the first end. The winding head has a first winding head flange and a second winding head flange that are joined by a winding head joint part, and the winding head extends at least partially an elongation of a shape of the stator core. The winding head also has a winding hole at the first winding head flange and a winding opening at the winding head joint part. The winding hole and opening are connected by a groove in the winding head joint part.

Abstract: A battery module is disclosed, which includes: a multiplicity of battery cells; a printed circuit board with a first series-connector with a first pad area and a second pad area, and a second series-connector with a third pad area and a fourth pad area; a cross-connector, which connects the first series-connector between the first pad area and the second pad area with the second series-connector between the third pad area and the fourth pad area; and a sensor configured to detect a cross-current at the cross-connector. The first contact electrode of a first battery cell is connected with the first pad area. The second contact electrode of a second battery cell is connected with the second pad area. The first contact electrode of a third battery cell is connected with the third pad area. The second contact electrode of a fourth battery cell is connected with the fourth pad area.