Abstract: A vehicle includes a propulsion system having multiple electric motors. A battery system is connected to the electric motors via a direct current to direct current (DC-DC) converter and an inverter. The battery system includes a battery assembly having a plurality of battery modules. Each of the battery modules has multiple individual battery cells arranged in battery packs, a set of sensors configured to monitor a set of parameters of each battery pack, and a plurality of battery pack mounts. Each battery pack mount includes a base plate and a top plate and an actuator configured to alter a distance between plates. A monitoring unit is configured to monitor a value representative of a battery pack pressure, determine whether the value falls within a pressure threshold window, and maintain the value within the pressure threshold window by actively altering the battery pack pressure.

Abstract: A battery monitoring system for a vehicle includes a processor and a memory. The memory stores instructions for causing the processor to estimate a state of charge of a battery based on a current cell pressure of the battery while the state of charge of the battery is below a threshold state of charge and to estimate a state of charge of the battery based on a voltage output by the battery while the state of charge of the battery is greater than or equal to the threshold state of charge.

Abstract: Simultaneous parallel charging of a first and second electrical energy storage devices coupled to a charge source is carried out by directly coupling the charge source to one of the first ESD and the second ESD and through a DC to DC converter to the other of the first ESD and the second ESD. The charge source provides a current that is allocated to the two ESDs by controlling the DC to DC converter. Priority of charging may be given to either ESD.

Abstract: An apparatus and a method for segmenting a steel microstructure phase are provided. The apparatus includes a storage configured for storing a machine learning algorithm and a processing device that segments a microstructure phase using the machine learning algorithm. The processing device is configured to receive label data, to learn a machine learning model by use of the label data as learning data for the machine learning model, and to segment a phase of a steel microstructure image by use of the learned machine learning model.

Abstract: An apparatus and a method for segmenting a steel microstructure phase are provided. The apparatus includes a storage configured for storing a machine learning algorithm and a processing device that segments a microstructure phase using the machine learning algorithm. The processing device is configured to receive label data, to learn a machine learning model by use of the label data as learning data for the machine learning model, and to segment a phase of a steel microstructure image by use of the learned machine learning model.