Abstract: A vehicle data processing system receives a set of data logged, during operation of each of a fleet of vehicles, by a data logger communicatively coupled to a controller area network (CAN) bus in each of the vehicles. The set of logged data can include a plurality of measurements generated by a sensor configured to transmit the measurements across the CAN bus, and can be received from a storage device to which the set of logged data was uploaded after the vehicle completed one or more trips. The system processes the logged data using a set of alerting rules. When a criterion in the set of alerting rules is satisfied by the set of logged data, the system outputs an alert.

Abstract: The technology enables an in-vehicle control computer located in an autonomous vehicle to control an output of a propulsion apparatus based on an estimate of the electrical load of one or more devices on or in the autonomous vehicle. An example method of autonomous driving operation includes determining, at a first time, by a computer located in the vehicle, a second energy or power consumption value of a plurality of devices that are expected to operate at a second time later than the first time, where the second energy or power consumption value is a different than a first energy or power consumption value of the plurality of devices at the first time; and sending, by the computer, the second energy or power consumption value to control an engine or a motor located in the vehicle.

Abstract: A method, apparatus and device for predicting wall temperature deviation of a high-temperature heating surface tube panel of a boiler. The method comprises: acquiring factor data that affects wall temperature deviation of a high-temperature heating surface tube panel of a boiler; according to the factor data and a boiler structure, establishing a three-dimensional boiler simulation model in CFD software, and in the boiler simulation model, calculating the swirl intensity of a boiler furnace outlet by using a swirl momentum moment formula, and calculating a wall temperature deviation coefficient of the high-temperature heating surface tube panel of the boiler by using a wall temperature deviation coefficient calculation formula; and performing quadratic fitting processing on the swirl intensity and the wall temperature deviation coefficient, so as to obtain a prediction model.