Abstract: A computer includes a processor and a memory storing instructions executable by the processor to receive a dataset of images; extract feature data from the images; optimize a number of clusters into which the images are classified based on the feature data; for each cluster, optimize a number of subclusters into which the images in that cluster are classified; determine a metric indicating a bias of the dataset toward at least one of the clusters or subclusters based on the number of clusters, the numbers of subclusters, distances between the respective clusters, and distances between the respective subclusters; and after determining the metric, train a machine-learning program using a training set constructed from the clusters and the subclusters.

Abstract: A system and method of planning external electric power usage of a vehicle traction battery includes retrieving, remotely from the vehicle, data including a current charge level of a traction battery in the vehicle and an estimated range of the vehicle based on the charge level. Input of planned power usage of the traction battery by a set of devices is input remotely from the vehicle. An estimated change of the current charge level is determined based upon the planned power usage based on the current charge level, the estimated range, and the planned power usage. Based on the estimated change of the current charge level, a revised charge level of the traction battery and a revised estimated range of the vehicle is determined, and the revised charge level of the traction battery and the revised estimated range of the vehicle is output to a user computing device.