Abstract:
Methods and systems are provided for controlling a vehicle engine to adjust exhaust warm-up strategy based on a vehicle network information. In one example, in response to an expected decrease in temperature of a catalyst of a vehicle below a threshold and an estimated duration thereof based on communications external from the vehicle, a method may include delaying catalyst heating actions, when the catalyst heating actions are determined to be unable to heat up the catalyst to threshold temperatures. However, the catalyst heating actions may be enabled when the catalyst heating actions are determined to be able to achieve the threshold temperature within the duration.
Abstract:
Various systems and methods are described for managing ammonia storage in an SCR catalyst. In one example approach, a method comprises, in response to a vehicle-off event, injecting ammonia during a final exhaust blowdown until a predetermined value of ammonia is stored in the SCR catalyst; and in response to a subsequent vehicle-on event when an amount of ammonia stored in the SCR catalyst is less than the predetermined value, injecting ammonia until the predetermined value of ammonia is stored in the SCR catalyst.
Abstract:
Exhaust aftertreatment systems and methods are described for reducing emissions output therefrom. In one example, an exhaust gas aftertreatment system comprises a first catalyst downstream of a branchpoint in a first exhaust pathway, a second catalyst downstream of the branchpoint in a second exhaust pathway, an electrical heater positioned upstream of the branchpoint for heating the exhaust flow, a control unit for adjusting an exhaust heating current of the electrical heater, and a valve for adjusting a distribution of exhaust flow to the first and second catalyst, the control unit including instructions to adjust the valve responsive to a substrate temperature within one or more of the first and second catalysts. In this way, an exhaust system with increased efficiency across a range of operating temperatures is realized that reduces emissions and energy expended during usage.
Abstract:
A method including generating a plurality of synthetic images of a material, where each synthetic image from among the plurality of synthetic images is associated with a feasibility value greater than a threshold synthetic feasibility value. The method includes determining, for each synthetic image from among the plurality of synthetic images, one or more material properties of the material and one or more process parameters of the material based on the synthetic image and generating a plurality of data points and a pareto surface based on the one or more material properties and the one or more process parameters. The method includes selecting a target data point based on the plurality of data points and a distance between a set of data points from among the plurality of data points and the pareto surface.
Abstract:
A system is disclosed that includes a computer and memory, the memory including instructions to transform acoustic data to an order spectrum and input the order spectrum to a decoder to determine a feature vector. The feature vector can be input to a one-class classifier to classify the order spectrum as anomalous or non-anomalous and the classified order spectrum can be output.
Abstract:
A far-infrared camera mounted in a vehicle generates an image frame. When an image of a large animal is identified in the image frame, a pixel intensity of the large animal image is determined. An estimated distance to the large animal from the far-infrared camera based on the pixel intensity is determined. When the animal is classified as a tracked animal, and future trajectories of the tracked animal and the vehicle intersect, a component in the vehicle is actuated.
Abstract:
A plurality of thermal images forward of a vehicle are collected. Thermal data in the plurality of thermal images is normalized based on an ambient air temperature to generate a plurality of normalized thermal images. The plurality of normalized thermal images are input to a machine learning program trained to output an identification of an object based on the ambient air temperature and a risk of collision between the vehicle and the object. A vehicle component is actuated based on the identification of the object and the risk of collision with the object.
Abstract:
Methods and systems are provided for increasing an accuracy of anomaly detection in assets such as vehicle components. In one example, a method provides for continuous health monitoring of connected physical assets, comprising adapting thresholds for anomaly detection and root cause analysis algorithms for the connected assets based on an aggregation of new connected data using machine learning; updating and ranking advanced statistical and machine learning models based on their performance using connected data until confirming a best performing model; and deploying the best performing model to monitor the connected physical assets.
Abstract:
A computer, including a processor and a memory, the memory including instructions to be executed by the processor to train a neural network included in a memory augmented neural network based on one or more images and corresponding ground truth in a training dataset by transforming the one or more images to generate a plurality of one-hundred or more variations of the one or more images including variations in the ground truth and process the variations of the one or more images and store feature points corresponding to each variation of the one or more images in memory associated with the memory augmented neural network. The instructions can include further instructions to process an image acquired by a vehicle sensor with the memory augmented neural network, including comparing a feature variance set for the image acquired by the vehicle sensor to the stored processing parameters for each variation of the one or more images, to obtain an output result.
Abstract:
A method includes defining a sensor layout of a digital twin based on one or more sensor parameters and one or more routing control locations of the digital twin. The method includes simulating a manufacturing routine of a plurality of pallets and a plurality of workstations based on one or more pallet parameters associated with the plurality of pallets and one or more workstation parameters associated with the plurality of workstations and calculating, for each routing control location from among the one or more routing control locations, a transient production value and a steady state production value based on the manufacturing routine. The method includes iteratively adjusting the sensor layout of the digital twin until each transient production value is less than or equal to a threshold transient production value and each steady state production value is less than or equal to a threshold steady state production value.