Abstract: A battery pack assembly includes, among other things, a tray, a lid secured to the tray to provide an enclosure having an interior, at least one battery module disposed within the interior, a cross-member disposed within the interior adjacent to the at least one battery module, and a stanchion secured to the cross-member. The stanchion disposed entirely within the interior. The assembly further includes a fastener that extends through an opening in the lid to engage the stanchion.

Abstract: An article, such as a battery pack system, includes a battery pack that is comprised of a plurality of battery cells. An external housing covers at least a portion of the battery pack. A silicate-based thermal barrier coating is configured to block heat emitted from the battery pack.

Abstract: A traction battery pack for an electrified vehicle may include a protection bracket for shielding a vent feature of the traction battery pack. An exemplary protection bracket may be made of a polymeric material and is designed to shield the vent feature from debris impingement. The protection bracket may include features such as a mesh venting pattern and a melting point that is lower than the temperature of battery vent byproducts that may be released during battery thermal events of the traction battery pack.

Abstract: A traction battery pack assembly includes, among other things, first and second pieces of an enclosure having an interior area. An attachment rim is disposed at a periphery of the first piece. The attachment rim has a stand-off that includes a platform portion and turned flange. The platform portion extends outward from the interior area in a first direction. The platform portion provides an aperture. The turned flange extends away from the platform portion in a second direction and terminates at an end face. The second direction is transverse to the first direction. The aperture is configured to receive a fastener that clamps the end face against the second piece.

Abstract: This disclosure details battery assemblies for use within electrified vehicle battery packs. An exemplary battery assembly includes a grouping of battery cells and an array plate assembly contacting a portion of the battery assembly. The array plate assembly may embody a split panel design that includes an outer panel and an inner panel that are arranged to nest together. One or both of the outer panel and the inner panel may include an embossing pattern. Among various other advantages, the split panel design increases the stiffness of the array plate assembly without significantly increasing the overall package depth of the array plate assembly or the battery assembly.

Abstract: A structural enclosure includes a pair of aluminum rails with an upper wall and a lower wall spaced apart from the upper wall, a plurality of sleeves extending into and captured within the aluminum rails, and each of the plurality of sleeves having a head with a predefined thickness disposed on an outer surface of the aluminum rails and configured to separate the outer surface of the aluminum rails from a steel vehicle chassis to which the aluminum rails are mounted. The structural enclosure can be an aluminum battery box for an electric vehicle and the aluminum battery box can be mounted to and electrochemically isolated from the steel vehicle chassis.

Abstract: A system for characterizing a specimen is disclosed. In one embodiment, the system includes a characterization sub-system configured to acquire one or more images a specimen, and a controller communicatively coupled to the characterization sub-system. The controller may be configured to: receive from the characterization sub-system one or more training images of one or more defects of a training specimen; generate one or more augmented images of the one or more defects of the training specimen; generate a machine learning classifier based on the one or more augmented images of the one or more defects of the training specimen; receive from the characterization sub-system one or more target images of one or more target features of a target specimen; and determine one or more defects of the one or more target features with the machine learning classifier.

Abstract: A battery pack assembly includes, among other things, a tray, a lid secured to the tray to provide an enclosure having an interior, at least one battery module disposed within the interior, a cross-member disposed within the interior adjacent to the at least one battery module, and a stanchion secured to the cross-member. The stanchion disposed entirely within the interior. The assembly further includes a fastener that extends through an opening in the lid to engage the stanchion.

Abstract: A battery assembly according to a non-limiting aspect of the present disclosure includes, among other things, an array of battery cells, and a thermal exchange plate assembly adjacent the array. The thermal exchange plate assembly includes an inlet, an outlet, a main channel, and a bypass channel configured to direct fluid from the inlet to the outlet while substantially bypassing the main channel.

Abstract: A structural enclosure includes a pair of aluminum rails with an upper wall and a lower wall spaced apart from the upper wall, a plurality of sleeves extending into and captured within the aluminum rails, and each of the plurality of sleeves having a head with a predefined thickness disposed on an outer surface of the aluminum rails and configured to separate the outer surface of the aluminum rails from a steel vehicle chassis to which the aluminum rails are mounted. The structural enclosure can be an aluminum battery box for an electric vehicle and the aluminum battery box can be mounted to and electrochemically isolated from the steel vehicle chassis.

Abstract: Methods and systems for determining information for a specimen are provided. One system includes a computer subsystem and one or more components executed by the computer subsystem. The one or more components include a deep learning model configured for denoising an image of a specimen generated by an imaging subsystem. The computer subsystem is configured for determining information for the specimen from the denoised image.

Abstract: A traction battery pack assembly includes, among other things, first and second pieces of an enclosure having an interior area. An attachment rim is disposed at a periphery of the first piece. The attachment rim has a stand-off that includes a platform portion and turned flange. The platform portion extends outward from the interior area in a first direction. The platform portion provides an aperture. The turned flange extends away from the platform portion in a second direction and terminates at an end face. The second direction is transverse to the first direction. The aperture is configured to receive a fastener that clamps the end face against the second piece.

Abstract: A traction battery pack assembly includes, among other things, an enclosure having a lid and a tray. The enclosure has a corner area connecting a first side of the enclosure to a second side of the enclosure. The first side is transverse to the second side. The assembly further includes a patch secured to the corner area.

Abstract: A battery pack assembly includes, among other things, a tray and a lid. The lid is secured to the tray to provide an enclosure having an interior. At least one battery module is disposed within the interior. A cross-member is disposed within the interior adjacent to at least one battery module. A touch latch secures the tray or the lid to the cross-member.

Abstract: Methods and systems for improved detection and classification of defects of interest (DOI) is realized based on values of one or more automatically generated attributes derived from images of a candidate defect. Automatically generated attributes are determined by iteratively training, reducing, and retraining a deep learning model. The deep learning model relates optical images of candidate defects to a known classification of those defects. After model reduction, attributes of the reduced model are identified which strongly relate the optical images of candidate defects to the known classification of the defects. The reduced model is subsequently employed to generate values of the identified attributes associated with images of candidate defects having unknown classification. In another aspect, a statistical classifier is employed to classify defects based on automatically generated attributes and attributes identified manually.

Abstract: Machine learning approaches provide additional information about semiconductor wafer inspection stability issues that makes it possible to distinguish consequential process variations like process excursions from minor process variations that are within specification. The effect of variable defect of interest (DOI) capture rates in the inspection result and the effect of variable defect count on the wafer can be monitored independently.

Abstract: An article, such as a battery pack system, includes a battery pack that is comprised of a plurality of battery cells. An external housing covers at least a portion of the battery pack. A silicate-based thermal barrier coating is configured to block heat emitted from the battery pack.

Abstract: A battery pack includes a support structure, an array frame including a fastener housing, and a fastener received through the fastener housing for mounting the array frame to the support structure. The array frame may be mounted to the support structure using a top-down approach that includes inserting a fastener through a fastener housing of the array frame.

Abstract: Wafer inspection with stable nuisance rates and defect of interest capture rates are disclosed. This technique can be used for discovery of newly appearing defects that occur during the manufacturing process. Based on a first wafer, defects of interest are identified based on the classified filtered inspection results. For each remaining wafer, the defect classifier is updated and defects of interest in the next wafer are identified based on the classified filtered inspection results.

Abstract: Battery pack designs for use in electrified vehicles may include a polymer-based enclosure having features for sealing external joints, retaining components inside the battery pack, securing electrical and coolant lines to the polymer-based enclosure, etc. The proposed designs reduce the number of overall parts in assembly, such as fasteners and brackets, and simplify the overall battery pack manufacturing and assembly processes.