8 results about "Bus network" patented technology

The invention discloses a high-integration intelligent ignition head device and an automobile safety communication power supply system thereof. The device comprises an input unit, a power management module, a communication module, a communication judgment module, an MCU, a voltage sensing module, a current sensing module, an ignition control module, an ignition element and a substrate, and an environment self-adaption unit, a dual-mode wireless energy supply unit and an optical fiber diagnosis channel can be additionally arranged. The system adopts the device, communicates with a central control unit through a redundant optical fiber bus and a double-wire bus, and further comprises the central control unit, a dynamic topology reconstruction unit and a pre-ignition energy distribution unit. Through digital signal control, multi-dimensional sensing module integration and a double-wire bus topological structure, ignition threshold multi-stage protection, state real-time monitoring and feedback, multi-ignition-head parallel independent control and miniaturized function integration are achieved, and the reliability, the intelligent degree and the driving efficiency of an automobile safety system are improved.

The invention is suitable for the technical field of energy storage control, and provides a direct current energy storage control system of a distributed sodium ion battery, which comprises a distributed energy storage unit, a direct current bus network, an intelligent monitoring unit and an energy management unit, the distributed energy storage unit is connected with the direct current bus network; the intelligent monitoring unit is connected with the sodium ion battery module in the distributed energy storage unit, and transmits monitored data to the energy management unit through the CAN communication module; the energy management unit is connected with the non-isolated bidirectional DC converter in the distributed energy storage unit, performs fault analysis based on the received parameters, generates a duty ratio adjustment instruction, and dynamically adjusts the duty ratio of the non-isolated bidirectional DC converter according to the duty ratio adjustment instruction. And the bus voltage of the direct-current bus network is adaptively adjusted within the preset range. According to the method, the loss in the energy conversion process is reduced, and the energy utilization efficiency is improved by flexibly configuring the energy storage capacity in a direct-current load scene.

The invention relates to the technical field of automobile interior lighting, in particular to a method and device for automatically calibrating the color of an automobile atmosphere lamp based on machine learning. An automobile atmosphere lamp color automatic calibration device based on machine learning is characterized in that an atmosphere lamp holder is connected with an automobile domain controller through an LIN bus to form an LIN bus network, and an intelligent learning system is used for data acquisition; establishing a learning model and training; the automobile domain controller runs the trained model and sets a dynamic compensation mechanism; and carrying out system verification and optimization. According to the scheme, automatic calibration of colors and temperature drifts of different LEDs of the automobile atmosphere lamp is realized based on machine learning, the calibration acquisition precision of a production line for each LED is reduced, and automatic calibration can be carried out more quickly and more accurately.

The application provides a kind of urban multi-mode traffic network post-disaster repair strategy efficiency evaluation method and system, belongs to the technical field of urban traffic operation management, constructs multi-mode traffic network structure model using road network and bus network open source data;Using traffic travel demand data to simulate urban traffic distribution, construct multi-mode traffic network function model;Based on multi-mode traffic network function model, according to the spatial distribution characteristics of disaster and post-disaster network repair strategy, construct multi-mode traffic network structure recovery model, evaluate the efficiency of structure recovery;Based on multi-mode traffic network structure recovery model, reload travel demand, construct multi-mode traffic network function recovery model, evaluate the efficiency of function recovery.The application can comprehensively consider various traffic modes and the complex dynamic game between travelers, provide more accurate and more comprehensive repair strategy evaluation, can enhance the resilience of urban integrated transport system, so that it can better cope with various disasters and emergencies.

The invention discloses an over-path traffic solving method for a completely-crowded large-scale public transportation network, and the method comprises the steps: obtaining a getting-on arc and a corresponding effective departure frequency through a first algorithm; the second algorithm calculates the use probability of passing through all the upper turning arcs under the super path, so that the complete upper turning arc flow distribution of the super path, the use probability vector of the upper turning arcs and the use probability vector upper turning arcs of the nodes are obtained; then, adopting column generation to construct an OD pair sub-problem, and determining the optimal transfer amount from a non-reference super path to a reference super path in the OD pair sub-problem through binary search; and the fourth algorithm obtains an over-path traffic equilibrium solution under the public transportation network equilibrium condition. Therefore, by setting the first algorithm, the second algorithm and the like, a complete algorithm capable of processing large-scale public transportation network distribution is constructed, so that the super path is constructed based on the effective departure frequency, and the method is suitable for practical application of the city-level large-scale public transportation network.

The invention discloses a bus network intelligent scheduling method based on a machine learning model, and belongs to the technical field of data processing, and the method comprises the following steps: receiving network sensing data, generating a network operation situation snapshot when detecting that the network sensing data has an abnormal evolution trend, and transmitting the snapshot to a scheduling information coordination processing unit, each scheduling information entry is generated; calling each scheduling information entry for overlapping detection, outputting an overlapping relation matrix, and dividing to obtain a normal scheduling information set and each conflict scheduling information set; machine learning model training parameters of all conflict scheduling information entries are obtained, a model historical stability index and a model generalization credibility index of a machine learning model are obtained through analysis, and all conflict scheduling execution instructions are obtained through screening according to the model historical stability index and the model generalization credibility index so as to execute public transit network intelligent scheduling. The technical problem that in the prior art, different scheduling information has deviation and inconsistency in the state cognition level is solved.

The application relates to an electronic and electrical system of a vehicle and the vehicle. The electronic and electrical system of the vehicle comprises a mobile data center, a main area controller and a backup area controller; wherein different area controllers are arranged in different sub-areas of the vehicle, the main area controller is connected with a main bus network segment, and the backup area controller is connected with a backup bus network segment; the main area controller is configured to communicate with the mobile data center, a main braking assembly and a main steering assembly in the main bus network segment, and the backup area controller is configured to communicate with the mobile data center, a backup braking assembly and a backup steering assembly in the backup bus network segment. The scheme can realize redundant control of vehicle braking and vehicle steering, and improve the safety of vehicle driving.

Active seat module for vehicle seat, vehicle seat comprising such an active seat module, and methods for manufacturing and modifying such a vehicle seat. The active seat module is intended for a modularly constructed vehicle seat formed from a plurality of seat modules and having an electrical seat controller (16). The active seat module comprises one or more functional components (30) and two module connectors (34, 36) for connecting the seat module in series with the electrical seat controller (16) and at least one other active seat module, forming a linear network (18) or a bus network, the network (18) being configured for the transmission of power and communication signals intended for the functional components (30) of each active seat module. Figure 2