In at least one example embodiment, a computer system includes a memory storing instructions and at least one processor configured to executed the instructions to cause the computer system to obtain sensor data, the sensor data corresponding to measurements of at least one component of an electric powertrain system of at least one vehicle and generate a first digital twin based on the obtained sensor data, the first generated twin associated with a type of the at least one vehicle.

An autonomous vehicle (AV) includes features that allows the AV to comply with applicable regulations and statues for performing safe driving operation. An example system for an AV includes a communications gateway device. The communications gateway device includes a plurality of modules each configured for different communication mediums or applications. In particular, the plurality of modules includes a first module for communicating with a remote computer. Via the first module, vehicle operational data is reported to the remote computer, and instructional data is received from the remote computer. The modules further include a second module for communicating with devices located within a vicinity external to the vehicle, and a third module configured to communicate with subsystems located within the vehicle. The example AV system includes a second communications gateway device that is configured to be redundant.

Systems and methods for vehicle lifecycle management using onboard vehicle onboard data capture devices are disclosed. In one embodiment, a method of vehicle lifecycle management may include: enrolling, by a vehicle lifecycle computer program executed by an electronic device, a vehicle in a vehicle lifecycle management service; receiving, by the vehicle lifecycle computer program, a request to initiate a vehicle lifecycle event; enabling, by the vehicle lifecycle computer program, a telematics unit in the vehicle; receiving, by the vehicle lifecycle computer program, vehicle attributes from the telematics unit; requesting, by the vehicle lifecycle computer program, vehicle condition data from an on-board vehicle management computer program; receiving, by vehicle lifecycle computer program, the vehicle condition data from the on-board vehicle management computer program; receiving, by the vehicle lifecycle computer program, a request to terminate the vehicle lifecycle event; and disabling, by the vehicle lifecycle computer program, the telematics unit.

A method for predicting performance of a vehicle NVH system based on deep learning is provided. The method includes preprocessing learning data collected for each channel associated with noise and vibration while driving, learning a model forming a correlation function between multiple inputs and multiple outputs corresponding to the preprocessed learning data using an artificial neural network, and predicting performance using a vehicle NVH system model formed through the learned model.

A testing system for interfacing with a vehicle diagnostic system and performing a diagnostic test on a vehicle. The testing system includes a housing configured to at least partially retain a processor in circuit communication with test circuitry configured to selectively communicate with vehicle's onboard diagnostic system via a test cable. The test cable retrieves diagnostic data from the onboard diagnostic system, and the processor performs a diagnostic test which is sent to an output device for displaying the test results. Results are transmitted to a computing device comprising an application system having an interpreter for displaying diagnostic data on a display of the computing device.

Methods and systems are provided for a coolant system. In one example, a method may include diagnosing a condition of a pump of the coolant system based on a temperature change of coolant. The diagnostic may determine if the pump is stuck on or off.

An electrified tractor includes a vehicle body, a working machine, an electric motor, a battery, an inverter that controls input-output electric power of the battery. The electrified tractor includes a control device that controls the inverter. The control device executes a restriction process, a charging rate calculation process and a relaxation process. In the restriction process, the control device controls the inverter such that the input and output of the battery is restricted within a prescribed electric power range, when a state of the battery satisfies a restriction condition. In the charging rate calculation process, the control device calculates a charging rate of the battery when it is assumed that a work is finished in a farming field, as an estimated charging rate. In the relaxation process, the control device expands the prescribed electric power range, when the estimated charging rate is higher than a first prescribed charging rate.

A vehicle moves through an environment (e.g., a farming, construction, mining, or forestry environment) and performs one or more actions in the environment. Portions of the environment may include moisture, such as puddles or mud patches. A control system associated with the vehicle may include a traversability model or a moisture model to help the vehicle operate in the environment with the moisture. In particular, the control system may employ the traversability model to reduce the likelihood of the vehicle attempting to traverse an untraversable portion of the environment, and the control system may employ the moisture model to reduce the likelihood of the vehicle performing an action that will damage a portion of the environment.

Systems and methods for multi-signal fault analysis are described. The system receives signal message information, over a network, from a collection device comprised of a plurality of mobile devices including a first mobile device and a second mobile device that are associated with a first user. The first signal message information includes a first maintenance message including characterization information that was received by the first mobile device from a component that includes a sensor that operates to sense a first part that is assembled into a vehicle. The second signal message information includes signal information that was received by the second mobile device including an audio signal that a microphone in the second mobile device sensed. The system analyzes the multi-signal information to diagnose a problem and communicate a message to the first user with a diagnosis of the problem.

A monitoring and maintenance system that utilizes imperial and theoretical data to compare parts, vehicles, users, regions, wear intensity indexes over time and tracking information to provide a sophisticated data collection system for heavy-duty equipment or rental equipment. This tracking is designed to better the specifications, designs, training, preventative maintenance, and replacement wear understanding of fleet management.