46results about How to "Optimize energy management" patented technology

The embodiment of the present application discloses a receiving mode selection method and device based on signal diversity receiving. In the technical solution provided by the embodiment of the present application, in the initial signal receiving mode, several signals are independently received through the main antenna, and the first signal quality parameter of the received signal is determined. When the first signal quality parameter is lower than the first signal quality parameter When the threshold is reached, the current signal receiving mode is switched to the diversity receiving mode, and the master antenna and several slave antennas perform diversity reception of signals, and combine the signals received by diversity to obtain a combined signal, and within the set first time period, continuously The set number of times detects that the first signal quality parameter of the signal received by the main antenna reaches the first signal quality parameter threshold, and restores the current signal receiving mode to the initial signal receiving mode. Using the above-mentioned technical means can guarantee the signal receiving performance of the system, optimize the energy consumption management of the system, and improve the signal processing efficiency.

The invention discloses a double-plate clutch hybrid power assembly suitable for a new energy automobile. An engine, an elastic damping connecting unit, a first motor, a double-plate clutch and a second motor of the double-plate clutch hybrid power assembly are coaxially connected in sequence. An output shaft of the second motor is connected with a drive axle assembly. An energy-storing power source is electrically connected with a first motor controller, a second motor controller and a vehicle control unit. The first motor controller is electrically connected with the vehicle control unit and the first motor. The second motor controller is electrically connected with the vehicle control unit and the second motor. The double-plate clutch does not generate axial force to the motors and the engine, and the functions of the clutch, a two-gear transmission, impact overload protection, forward and reverse separation, non-power-interruption speed-differential gear shifting and the like are achieved. Switching response is rapid, reliability is high, energy consumption is low, and efficiency is high. Energy output can be randomly switched between the engine and the energy-storing power source according to working conditions, energy can be recycled, and energy management fit is more reasonable.

The invention provides a method for power generation and voyage optimization of a mobile energy network influenced by wind resources, including: selecting four characteristics of wind speed, temperature, air pressure and cloud cover as the data input for prediction; Training set and test set; normalize the sample data. Based on the data-driven mobile energy network power generation and voyage joint optimization method, the present invention takes the influence of the offshore wind speed on the speed of the all-electric ship into account, and can more effectively adjust the actual ship speed and achieve better ship energy management; The operation cost objective function is optimized, and the operation cost of energy storage is taken into account, which is more in line with the actual operation scenario; through the piecewise linearization method, the optimization model is converted into a mixed integer linear programming model, which solves the problem that mixed integer nonlinear programming is difficult to solve. problem; not limited to all-electric ship power systems, but can also be used in mobile energy networks such as land electric vehicles.

The invention discloses a lithium battery state estimation method used in a distributed energy storage system, belonging to the application field of lithium ion batteries. The method includes using the gated cyclic unit cyclic neural network to establish a deep learning-based lithium battery health state estimation model; using the second-order equivalent circuit model of the lithium battery combined with the extended Kalman filter algorithm to estimate the distributed energy storage unit management system in real time. Lithium battery state of charge; through information interaction, the battery capacity and lithium battery state of health estimation model in the lithium battery state of charge estimation process are updated synchronously. On the premise of not increasing the system hardware cost, the present invention provides accurate lithium battery capacity for SOC estimation through information interaction, and at the same time provides training samples for the big data SOH estimation model; and further improves the relationship between the SOC and SOH of the lithium battery in the system The estimation accuracy is convenient for the subsequent effective completion of energy management and scheduling of the system.

The embodiment of the present application discloses a method and a device for selecting a signal receiving processing mode at a signal receiving end. The technical solution provided by the embodiment of the present application pre-constructs the first binding relationship between the service type and the signal receiving mode and the second binding relationship between each signal transmitting end and the corresponding diversity combining mode. Afterwards, by parsing the currently received signal, extracting the service type information of the signal and the identification information of the signal transmitter, querying the first binding relationship according to the service type information, and determining the signal receiving mode of the current signal, if the signal receiving mode of the current signal is determined In the multi-antenna receiving mode, the second binding relationship is queried according to the identification information of the signal transmitting end, and the diversity combining mode of the current signal is determined. Adaptive selection of signal receiving mode and diversity combining mode through different service types and different signal transmitters to optimize signal receiving and processing effects, improve signal processing efficiency and optimize system energy consumption management.