695 results about "Hybrid drive" patented technology

The invention discloses a model-data hybrid driving-based lithium ion battery variable working condition SOH (state of health) evaluation method, relates to a lithium ion battery state of health evaluation method, and aims to solve the problems of poor applicability and low precision of an existing battery fixed working condition SOH evaluation method. The method comprises the following steps: 1, accelerating aging of a battery under working conditions I and II and acquiring information; 2, aiming at the constant-current discharge curve of the battery under the working condition, performing SP + model parameter identification by using a particle swarm optimization algorithm to obtain a degradation track of the model parameter within the battery health degree of 100%-80%; 3, selecting model parameters with high relevancy with the SOH of the battery as health features, and inputting the health features into a BP neural network algorithm to estimate the SOH of the battery, wherein the first working condition data and the second working condition data are respectively a training set and a test set; 4, according to the BPNN model obtained through data training of the first working condition, after SP + model parameters of the second working condition obtained through simulation are input, the SOH of the battery under the second working condition is output, and evaluation is completed. The invention can be used in battery field.

The invention discloses a physical and data hybrid driven mechanical arm dynamic model identification method which is characterized by comprising the following steps: S1, acquiring parameters of each axis of a robot, establishing a dynamic model of a mechanical arm, and linearizing the dynamic model according to a minimum inertia principle to obtain a dynamic minimum parameter set and a corresponding regression matrix; s2, an excitation track of the mechanical arm is designed based on the finite Fourier series; s3, the mechanical arm runs the designed excitation track, angles, angular velocities, angular accelerations and torque data of all joints of the mechanical arm in the movement process are collected and filtered, and an observation torque vector and an observation matrix are calculated; s4, performing preliminary estimation on the minimum parameter set by using an iterative reweighted least square method; and S5, aiming at the dynamic characteristics of LuGre friction force in the movement process of the mechanical arm, establishing a mechanical arm dynamic model under physical and data hybrid driving.

The invention discloses a photovoltaic array life prediction method based on hybrid driving of a physical model and data. The method comprises the following steps: defining failure time and residual life of a photovoltaic array; preprocessing data; degeneration trend extraction: separating a trend term, a seasonal term and a residual term of output power through block median filtering and seasonal effect correction, and eliminating the influence of environmental fluctuation on degeneration analysis; residual life prediction based on data driving; parameter prediction based on a physical model: identifying degradation parameters of the double-diode model; a degradation parameter trajectory model is established, an output power attenuation curve is inverted, and the remaining life is predicted; and result fusion: comparing data driving and physical model prediction results, and outputting a final residual life value through weighted average or confidence interval fusion. According to the invention, a set of complete photovoltaic array residual life prediction system is constructed, a whole-process closed loop from data acquisition, mechanism analysis to life prediction is realized, and an efficient and accurate solution is provided for reliability evaluation of a photovoltaic system.

The invention discloses a parallel task scheduling method based on node dynamic load and task relevance measurement. The parallel task scheduling method comprises the following steps: constructing a global scheduler for computing resource virtualization, sample allocation based on reinforcement learning and a local scheduler based on hybrid drive model scheduling on a server; in the preprocessing stage, computing resources are counted, and computing resource virtualization, GPU virtualization multiplexing technology, GPU acceleration and the like are carried out; a global scheduling stage oriented to test task parallel optimization: performing sample scheduling feasibility analysis containing fuzzy time, computational node selection based on an EXP3 algorithm, and sample scheduling oriented to node load; and a multilevel model parallelization stage based on domain knowledge and data hybrid driving, wherein a model cohesion coupling degree measurement mechanism, a model coupling mode knowledge base and a multilevel model parallelization method are included. According to the method, the global scheduler and the local scheduler are comprehensively utilized, the parallelism degree between samples and parallelism between models in the samples are achieved, and the method has wide application value and use prospects in all fields.

The invention discloses a permanent magnet synchronous motor temperature monitoring method based on digital-analog hybrid drive, and the method specifically comprises the steps: dividing a motor into a plurality of heat source nodes, including a stator winding, a stator tooth part, a rotor core and the like, connecting the nodes through a thermal resistance and thermal capacity network, building a thermal network model of the motor, and carrying out the thermal network model; calculating the initial values of thermal resistance and thermal capacity of each component of the motor, and optimizing parameters in a thermal network model by using a differential evolution algorithm based on the lumped parameter thermal network model and in combination with a data-driven strategy. Furthermore, temperature rise prediction is dynamically adjusted according to motor state data (such as stator current, rotating speed and the like) collected in real time so as to realize real-time temperature estimation. The method is high in temperature estimation precision, does not affect the performance of the motor, is simple in calculation, is good in real-time performance, and has physical interpretability. The temperature rise of the motor can be predicted in real time under different working conditions, early warning is given out, motor faults caused by too high temperature rise are effectively avoided, and the reliability and safety of the motor are improved.

The invention relates to a physical-data hybrid drive vehicle driving state estimation method, and belongs to the technical field of intelligent vehicle chassis dynamics state estimation. Constructing a mapping relation between the state estimation vector and sensor data by adopting a ridge regression method so as to explicitly express a vehicle movement mechanism; secondly, constructing a data driving model to implicitly extract vehicle sensor data features, and constructing an enhanced LSTM neural network with a double-stage attention mechanism as the data driving model; then, performing dynamic weighted fusion on an output result of the physical model and a sensor sample sequence output by the data driving model to realize deep coupling of physical mechanism knowledge and data driving characteristics; according to the method, the superiority of the method compared with other methods is verified through simulation testing and real vehicle testing.

The invention discloses an augmented reality and digital twin hybrid drive equipment maintenance method and system, and relates to the technical field of equipment maintenance, and the method comprises the steps: obtaining the feature data of target equipment; inputting the feature data into a preset equipment digital twinborn model, and generating a digital mirror image of the target equipment, namely a target equipment twinborn body; a hybrid drive maintenance mode is established through augmented reality hardware equipment and target equipment twin; making a maintenance strategy of the target equipment based on the hybrid drive maintenance mode; and the target equipment is maintained through the maintenance strategy that the augmented reality hardware equipment projects the target equipment step by step. The maintenance efficiency and quality can be improved, and the maintenance cost is reduced.

A hybrid drive system for a motor vehicle includes an internal combustion engine supplying first torques via a drive shaft to drive the motor vehicle and an electric machine having a rotor via which second drive torques can be supplied by the electric machine to drive the motor vehicle. An axle drive has an axle drive input gear wheel via which the axle drive can be driven. The system includes a gearbox having a first partial gearbox and a second partial gearbox. The first partial gearbox has a first planetary gear set having a first element, a second element, and a third element, The first partial gearbox also has a second planetary gear set having a fourth element, a fifth element, and a sixth element.

The invention discloses a paddle-leg hybrid driven underwater adhesion robot, and relates to the technical field of underwater robots, propeller thruster driving, six-foot crawling movement and hydrogel bionic suckers of foot bottom equipment respectively have the advantages of long-distance cruise driving, stable crawling in unstructured terrain and reliable adhesion detection on near wall surfaces. Therefore, the adaptability problem of a single-mode underwater robot in a complex operation scene is solved. According to the invention, the six groups of multi-degree-of-freedom mechanical feet cooperate with the control system through the modular driving units, so that the robot can realize multi-modal motion functions such as seabed crawling, obstacle crossing and climbing, posture adjustment and the like; the robot can stably crawl on a vertical surface or an inverted surface through cooperation between the hydrogel bionic suction cups arranged at the foot ends and the six-foot crawling gaits. Through vector combination of the three vertical propellers and the two horizontal propellers, the robot can meet the multi-degree-of-freedom motion control requirements of advancing, retreating, ascending, sinking, yawing, pitching, pitching and hovering. According to the paddle leg hybrid drive underwater adhesion robot, the underwater hybrid drive potential is developed to the maximum extent, the underwater maneuverability is improved in various challenging underwater environments, and the underwater robot is promoted to develop towards multiple modes and high efficiency.

The invention discloses a method for improving hybrid power drive by adding a motor to an automobile engine, and relates to the technical field of automobile hybrid power drive systems, an independent PO motor is added to a gasoline car, and a drive controller, a group of high-capacity power batteries and a 12V DC-DC power supply module are added to the gasoline car. A vehicle networking data interface and a hardware interface of an AI algorithm processing unit are reserved in the vehicle control module, and the system has the advantages that the vehicle networking communication unit and the AI algorithm processing unit are integrated in the vehicle control module, real-time traffic flow, road condition parameters and driving behavior data are collected, a road condition prediction model is constructed by using an LSTM neural network, and the driving behavior data are predicted by using the LSTM neural network. The dynamic power distribution strategy is generated in combination with the driving habits of the user, the defects that in the prior art, an energy management strategy is fixed and cannot adapt to road conditions and driving behavior changes are overcome, fuel consumption is reduced by predicting the energy requirement of the front road condition in advance, and the intelligence and economical efficiency of the hybrid power driving system are enhanced.

The invention relates to a hybrid drive type bionic light-weight nursing mechanical arm which comprises a shoulder joint module, a rope-driven elbow joint module and a rope-driven wrist joint module which are connected in sequence. The shoulder joint module is of a series-parallel structure, a first servo motor directly drives a center linkage platform to achieve forward flexion and backward extension of the shoulder, and a second servo motor and a third servo motor cooperatively drive a closed-loop structure formed by a driven branch chain unit to achieve adduction, abduction, internal rotation and external rotation of the shoulder. The elbow joint module achieves elbow bending and stretching and inward and outward rotation driven by a fifth servo motor through rope wheel transmission and gear meshing. The wrist joint module achieves forward flexion, backward extension, abduction and adduction of the wrist through a rope winding path and bevel gear meshing. Compared with the prior art, the adaptability and efficiency of the mechanical arm in rehabilitation nursing are improved, it is ensured that all the joints can work precisely and cooperatively under multi-degree-of-freedom movement, and the control precision and stability of a driving system are optimized while the high-load bearing capacity is ensured.

A hybrid transmission system with a multi-speed gearbox. The multi-speed gearbox is configured to rotationally couple a prime mover and an electric machine to different gear ratios during a hybrid drive mode. The multi-speed gearbox includes an electric drive interface gear positioned coaxial to a first primary shaft and a second primary shaft and idly mounted, free to spin, to the second primary shaft and an output shaft that includes an output shaft gear which is fixedly coupled thereto meshes with a gear on a secondary shaft.

The invention relates to the technical field of hybrid power gearboxes, in particular to a series hybrid power gearbox with a longitudinally-arranged engine, which comprises a longitudinally-arranged engine, a generator and a driving motor, the gear clutch transmission system is connected with the three power sources, transmits power of the three power sources and realizes power generation and driving; the gear clutch transmission system comprises a power generation system, a drive motor pure electric drive system, a generator two-gear pure electric drive system, an engine two-gear drive system and a front drive transfer system. On one hand, rear wheel two-gear driving and double-motor pure electric driving with the engine arranged longitudinally can be achieved, on the other hand, four-wheel hybrid driving is achieved through the built-in front-drive transfer shaft, and meanwhile parts such as a hydraulic control wet clutch or a driving motor and a gear thereof, the front-drive transfer shaft and the like are omitted; various hybrid power transmission products with different functions can be designed on the same platform and produced on the same line, and the requirements of different users and vehicle types are met.

The invention discloses a shield tunneling machine attitude prediction method and system, and relates to the field of shield tunneling machine construction.The shield tunneling machine attitude prediction method comprises the steps that firstly, shield tunneling machine construction parameters, geological environment parameters and tunnel planning parameters are obtained and preprocessed, and related characteristics are extracted; secondly, mapping the extracted features into nodes by using a heterogeneous graph model, and updating node features in real time through weighted processing of a graph attention mechanism; then, the node features and the connection relation are input into the trained hybrid drive prediction model, and time sequence, physical and space prediction values of the attitude angle of the shield tunneling machine are obtained; and finally, constructing a Bayesian causal graph to quantify the influence of each factor on the attitude angle, carrying out dynamic weighted fusion based on a quantization result, and outputting a final predicted value and a confidence interval. The problem that the prediction effect is poor under the complex geological condition due to the fact that prediction only depends on single shield tunneling machine parameters in the prior art is solved, and accurate prediction of the attitude angle of the shield tunneling machine can be achieved.

The invention relates to a steering engine and piezoelectric patch hybrid driven variable camber wing, belongs to the technical field of aerospace, and solves the problems of poor wing surface deformation continuity and poor transmission effect in the prior art. The plurality of flexible trailing edge deflection modules are arranged in the straight wing main body; the skin structure is arranged on the outer surfaces of the straight wing main body and the flexible trailing edge deflection module; the module connecting structure is connected with the plurality of flexible trailing edge deflection modules; wherein the straight wing main body comprises a front edge D-shaped structure wing box, a plurality of wing ribs arranged on the rear side of the front edge D-shaped structure wing box, and a bearing rear wall arranged on the rear sides of the wing ribs; each flexible trailing edge deflection module comprises a driving rib assembly fixed to the bearing rear wall, driven rib assemblies arranged on the two sides of the driving rib assembly, carbon rods sequentially connected with the driving rib assembly and the driven rib assemblies, an inhaul cable driving mechanism and a piezoelectric driving mechanism, and the driving rib assembly and the driven rib assemblies are sequentially arranged in the longitudinal direction of the variable-camber wing.

Methods and systems are provided for selectively controlling hybrid drive modes of a hybrid vehicle to reduce emissions. In one example, a method may include using route planning and vehicle operating conditions to identify emissions reducing opportunities. In one example, in response to a route distance not exceeding an electric range, the method includes suppressing an operation of an engine based on the route data, ambient temperature, and cabin pre-conditioning. In response to the route distance exceeding the electric range, further in anticipation of a fuel station along the route, where the fuel station has a fuel with a carbon footprint less than a low carbon threshold, the method includes operating the hybrid vehicle in a charge sustaining or charge increasing mode prior to a refueling event at the fuel station.

The invention discloses a lithium battery remaining service life prediction method based on an intelligent hybrid drive model, and the method comprises the steps: carrying out the modeling of a long-term degradation trend of a target system through a double-index degradation model (DEDM), and fitting model parameters through a nonlinear least square method; performing dynamic learning on the residual fluctuation of the actual observation data and the degradation trend through a fuzzy random configuration network (F-SCN); and finally, integrating trend prediction and residual prediction results through Gaussian process regression (GPR) to realize high-precision residual life prediction. According to the method, through collaborative optimization of the physical model and the data-driven model, the problem that trend fitting and local fluctuation are difficult to consider under limited data in a traditional method is solved, and the prediction precision and reliability are remarkably improved.

The invention discloses an electric power inspection exoskeleton modular structure, and belongs to the technical field of human body exoskeleton machine assistance, the electric power inspection exoskeleton modular structure comprises a supporting system, the supporting system comprises a back supporting plate, a waist supporting frame and thigh supporting rods, and a main body supporting frame is formed; the modular interface system comprises at least one group of mechanical interfaces, electrical interfaces and data interfaces which are uniformly distributed on a force transmission path of the support system; the functional module comprises a plurality of interchangeable power assisting modules, operation modules and protection modules, and the functional module is detachably connected with the supporting system through the modular interface system; a hybrid drive system includes a rigid driver and a flexible driver for providing position control and compliance force control, respectively. By means of the modular interface system, plug-and-play of functional modules such as power assisting, operation and protection is achieved, needed exoskeleton configuration can be rapidly assembled, multiple sets of exoskeleton equipment do not need to be arranged, and the equipment utilization rate and task adaptability are greatly improved.

The invention relates to the technical field of big data processing, in particular to an offshore wind plant generation power prediction method and system based on big data. According to the method, an ultra-short-term generated power prediction model based on data and physical hybrid driving is adopted to predict the generated power of the offshore wind plant, and the ultra-short-term generated power prediction model based on data and physical hybrid driving comprises a deep learning model, a physical model module, a reinforcement learning module and a dynamic switching mechanism; the dynamic switching mechanism is used for dynamically selecting the deep learning model module or the physical model module according to a wind speed fluctuation threshold value and feedback of the reinforcement learning module; according to the model selection logic provided by the invention, the prediction precision can be remarkably improved; meanwhile, in combination with feedback of a wind speed fluctuation threshold value and reinforcement learning, a dynamic switching mechanism improves the robustness and generalization ability of a prediction model.

A hybrid drive carrier frame includes a front rail comprising a first end, a second end, and a body extending along a transverse direction between the first and second ends. The frame comprises a first side rail extending from the first end of the front rail perpendicular to the transverse direction and a second side rail extending from the second end of the front rail perpendicular to the transverse direction and parallel to the first side rail. The first side rail is formed from a metal material and includes a locking tab extending along the transverse direction. The front and second side rails are formed from a plastic material. The front rail includes a locking channel at the first end of the front rail and the first side rail is connected to the first end of the front rail via engagement of the locking tab within the locking channel.

A hybrid drive omni-directional motion actuator based on an origami structure, comprising at least one actuating module. The actuating module comprises a columnar shell deforming based on the origami structure, an upper cover plate and a lower cover plate. The columnar shell is the origami structure derived from Waterbomb crease, and a cavity containing gas is formed inside the shell. The two ends of the cavity are open, and the openings are respectively connected with the upper cover plate and the lower cover plate for blocking the openings. The lower cover plate is provided with vent holes communicating with the cavity, and the upper cover plate and the lower cover plate are pulled by driving ropes arranged in a crossed manner. Through the cooperation of gas and tendon drive, the columnar shell can have deformations of contraction, bending and torsion, so that a single actuating module has omni-directional movement capability.

The invention relates to the technical field of voltage transformer fault diagnosis, in particular to a voltage transformer fault diagnosis method, which comprises the following steps of data acquisition, data preprocessing, feature selection, fault classification, model evaluation and practical application. According to the method, short-time Fourier transform, a maximum information coefficient, a convolutional neural network and a long short-term memory network are effectively combined by adopting a predictive maintenance method based on hybrid driving, so that fault diagnosis of a capacitor breakdown fault, a turn-to-turn short circuit fault, a ferromagnetic resonance fault and an oil leakage fault of the voltage transformer is realized; and in the data preprocessing stage, a simulated three-phase voltage signal is calculated through a discrete time model formula, the real three-phase voltage signal is replaced to a certain extent, and abnormal points are manufactured on the generated data, so that the problem of less three-phase voltage signal data is solved, and the diagnosis accuracy is improved.

The invention provides a hybrid drive system and a vehicle with the same. The hybrid drive system comprises a differential mechanism, a first half shaft of the differential mechanism is connected with a left front wheel, and a second half shaft of the differential mechanism is connected with a right front wheel; the driving motor is provided with a motor input shaft, the motor input shaft is connected with the first half shaft through a first gear pair, the output torque of the driving motor is transmitted to the first half shaft through the motor input shaft and the first gear pair, and then the left front wheel is driven to rotate; the generator is provided with a generator input shaft, the generator input shaft is connected with the second half shaft through a second gear pair, and the output torque of the generator is transmitted to the second half shaft through the generator input shaft and the second gear pair so as to drive the right front wheel to rotate. According to the scheme, the left front wheel and the right front wheel can be independently driven, independent torque control is provided for each wheel, a distributed driving mode under electric driving is achieved, and the technical problem that a hybrid driving system in the prior art cannot adapt to complex road surfaces is solved.

The invention relates to the technical field of robots, in particular to a hybrid drive leg device and a humanoid robot. The leg device comprises a thigh assembly and a shank assembly. The thigh assembly comprises a first driving mechanism, a second driving mechanism, a thread shifting device and a pair of first structural plates. The first driving mechanism comprises a first motor, a first conical wheel, a first guide wheel and a first rope. The first motor drives the first conical wheel to rotate and drives the first structural plate to swing. The shank assembly comprises a pair of second structural plates, and the second driving mechanism is used for driving the second structural plates to swing. The thread shifting device drives the first rope to move in the axial direction of the first conical wheel and drives the second rope to move in the axial direction of the second conical wheel, so that the leg device can stably operate under the conditions of different gaits and loads. In addition, the leg device of the scheme comprises the elastic buffer piece and the hydraulic damper, the elastic buffer piece and the hydraulic damper can absorb impact force borne by the leg device in real time in the movement or landing impact process of the leg device, and the overall stability of the leg device is improved.

The invention discloses an active and passive hybrid driving flexible lower limb exoskeleton system and a coordination control method.The skeleton system comprises an elastic energy storage element, a rope driving system, a flexible binding device, a sensing system and a control system, and the control system comprises a gait recognition algorithm, a power-assisted trajectory planning algorithm and a force trajectory tracking algorithm; the gait recognition algorithm detects the angle and the angular speed and detects the motion state, the assistance trajectory planning algorithm calculates the rope drive assistance, the force trajectory tracking algorithm converts the expected force into the motor speed, correction is conducted through the feedback information of the force sensor, and accurate expected force trajectory tracking is achieved. An active power assisting stage and a passive power assisting stage in a gait cycle are divided through a finite-state machine, and the power assisting magnitude of the active power assisting stage and active and passive power assisting mode switching are controlled in a coordinated mode according to the passive energy storage principle and the active power assisting principle. According to the invention, the active and passive hybrid driven flexible lower limb exoskeleton can be controlled in a coordinated manner, and high-precision, high-robustness and high-response-speed force control is realized.

Hybrid drive snowmobile comprising an IC engine, a variable speed drive comprising a first pulley connected to a drive shaft of the IC engine, a second pulley and a belt coupled to the first and second pulleys, an intermediate shaft-connected to the second pulley of the variable speed drive, an output shaft connected to the intermediate shaft by a transmission and a drive wheel of a motor track of the snowmobile connected to the output shaft and a reversible electrical machine connected to the intermediate shaft.

This invention provides a hybrid power drive device and a vehicle having the same. The hybrid power drive device includes an engine, a first motor, a second motor, and a compound planetary gear set. The output end of the engine is driven to the motor shaft of the first motor. The motor shaft of the second motor drives the wheels to rotate. A first sun gear meshes with a first planetary gear, and both the second sun gear and the first planetary gear mesh with a second planetary gear. The second planetary gear meshes with a ring gear, and the ring gear is driven to the wheels. A brake controls the operating state of the second sun gear, a first clutch controls the engagement or disengagement of the engine output end with the first sun gear, and a second clutch controls the engagement or disengagement of the engine output end with the planetary carrier. The technical solution provided in this application solves the problem in related technologies where hybrid power drive devices struggle to simultaneously achieve efficiency and compactness across multiple operating modes, as well as flexible drive switching.

A hybrid drive system for a motor vehicle has an internal combustion engine having a drive shaft via which first drive torques can be supplied by the internal combustion engine to drive the motor vehicle. The system also has an electric machine having a rotor via which second drive torques can be supplied by the electric machine to drive the motor vehicle. The system further has an axle drive having an axle drive input gear via which the axle drive can be driven and a gearbox having a first partial gearbox and a second partial gearbox. The first partial gearbox has a first planetary gear set having a first element, a second element, and a third element, as well as a second planetary gear set having a fourth element and a fifth element connected permanently in a rotationally fixed manner to the first element, and a sixth element.

The invention provides a hybrid drive type hand function rehabilitation device. The hybrid drive type hand function rehabilitation device comprises a supporting plate, a glove, five finger bending assemblies and a pneumatic drive part. The palm part of the glove is connected with one side of the supporting plate; the five finger bending assemblies are arranged on the side, away from the glove, of the supporting plate, the ends, close to the palm portion of the glove, of the five finger bending assemblies are connected with the supporting plate, and the ends, close to the finger portions of the glove, of the five finger bending assemblies are connected with the glove. The pneumatic driving part is used for controlling inflation and deflation of the finger bending assembly; the finger bending assembly comprises a delay control structure and at least two connected pneumatic bending parts. The two pneumatic bending parts are arranged in the length direction and have the same bending direction; the delay control structure is used for controlling the pneumatic bending parts to be sequentially inflated and bent in the direction from the finger root to the finger tip. The finger knuckle bending sequence of normal human fingers can be simulated, the problem that no time lag exists in the current human finger bending simulation process is solved, and the more accurate rehabilitation treatment effect is achieved.

The utility model provides a hybrid power driving system and a vehicle, the system comprises a first driving mechanism and a second driving mechanism, the first driving mechanism comprises an engine, a first clutch, a second clutch, a first motor, a first gear transmission mechanism and a first differential mechanism; the second driving mechanism comprises a second motor, a second gear transmission mechanism and a second differential mechanism; the engine is used for outputting power; the first motor is used for converting power output by the engine into electric energy; the first clutch is used for connecting or disconnecting an engine and the first motor; the second clutch is used for connecting or disconnecting the first motor and the first driving mechanism; the first gear transmission mechanism is arranged between the second clutch and the first differential mechanism and is in transmission connection with the second clutch and the first differential mechanism; the second gear transmission mechanism is arranged between the second motor and the first differential mechanism and is in transmission connection with the second motor and the second differential mechanism.