122 results about "Power electronic circuit" patented technology

An electric vehicle drive includes a thermal support may receive one or more power electronic circuits. The support may aid in removing heat from the circuits through fluid circulating through the support. Power electronic circuits are thermally matched, such as between component layers and between the circuits and the support. The support may form a shield from both external EMI / RFI and from interference generated by operation of the power electronic circuits. Features may be provided to permit and enhance connection of the circuitry to external circuitry, such as improved terminal configurations. Modular units may be assembled that may be coupled to electronic circuitry via plug-in arrangements or through interface with a backplane or similar mounting and interconnecting structures.

A support may receive one or more power electronic circuits. The support may aid in removing heat from the circuits through fluid circulating through the support. The support, in conjunction with other packaging features may form a shield from both external EMI / RFI and from interference generated by operation of the power electronic circuits. Features may be provided to permit and enhance connection of the circuitry to external circuitry, such as improved terminal configurations. Modular units may be assembled that may be coupled to electronic circuitry via plug-in arrangements or through interface with a backplane or similar mounting and interconnecting structures.

A solar powered hybrid power system including a solar charge collector; a charge storage system comprising at least a first charge storage device adapted to receive and store charge from said solar charge collector; wherein said charge storage system further comprises a power electronic circuit selectively connectable to at least a second charge storage device, said power electronic circuit adapted to transfer said stored charge to said at least a second charge storage device at a selectable voltage level.

A fault diagnosis method for power electronic circuits based on optimizing a deep belief network, including steps. (1) Use RT-LAB hardware-in-the-loop simulator to set up fault experiments and collect DC-link output voltage signals in different fault types. (2) Use empirical mode decomposition to extract the intrinsic function components of the output voltage signal and its envelope spectrum and calculate various statistical features to construct the original fault feature data set. (3) Based on the feature selection method of extreme learning machine, remove the redundancy and interference features, as fault sensitive feature data set. (4) Divide the fault sensitive feature set into training samples and test samples, and primitively determine the structure of the deep belief network. (5) Use the crow search algorithm to optimize the deep belief network. (6) Obtain the fault diagnosis result.

EMI shielding is provided for power electronics circuits and the like via a direct-mount reference plane support and shielding structure. The thermal support may receive one or more power electronic circuits. The support may aid in removing heat from the circuits through fluid circulating through the support. The support forms a shield from both external EMI / RFI and from interference generated by operation of the power electronic circuits. Features may be provided to permit and enhance connection of the circuitry to external circuitry, such as improved terminal configurations. Modular units may be assembled that may be coupled to electronic circuitry via plug-in arrangements or through interface with a backplane or similar mounting and interconnecting structures.

A modular inductor arrangement is provided in which a footprint of an enclosure for single or multiple phase inductors provides enhanced thermal transfer. The inductor coil may be wound about an axis generally parallel to a mounting surface of the package, so as to provide for reduced height and expanded footprint dimensions. The inductor package may be mounted on a thermal support, such as a fluid-cooled support. Heat is extracted from the assembly during operation, so as to establish a reduced maximum internal temperature as compared to here for known structures. The arrangement may be included in various circuit configurations, such as power converters. Other components may be incorporated and integrated into the package, including sensors, capacitor coils, other inductor coils, and so forth.

The invention discloses a method for detecting the open-circuit fault of an inverter circuit. The method comprises the following steps of: (1) defining fault characteristic quantities, wherein the three fault characteristic quantities are available in the method and respectively represent different meanings; (2) computing a three-phase voltage fundamental current amplitude, carrying out the phase shift and the Park conversion on the obtained three-phase voltage in a sampling way respectively, obtaining the size of the fundamental current amplitude by a conversion result, and filtering by a digital filter in the process; (3) detecting the fault of a neural network, and outputting the former two characteristic quantities through the BP (pressure transducer) neural network by the computation result in the step (2); and (4) positioning a fault power tube, testing the maximum value and the minimum value of the obtained three-phase voltage in a sampling way respectively, obtaining the specific position of the fault power tube through simple logical judgment, and outputting the third fault characteristic quantity. According to the method disclosed by the invention, the fault information of the power tube of the inverter circuit can be quickly and exactly obtained only by analyzing the output three-phase voltage, and the method can be realized only by a software algorithm without adding other outer hardware circuits, so that the cost can be reduced, the efficiency can be improved, the method is higher in application ability, and the method has the application value for researching the real-time fault detecting aspect of a power electronic circuit.

The invention discloses a method for predicting faults of a power electronic circuit based on an FRM-RVM (fuzzy rough membership-relevant vector machine), and the method comprises the following steps: monitoring voltage and current signals, and carrying out wavelet threshold denoising on the signals so as to form multidimensional circuit parameter vectors; carrying out dimensionality reduction on the multidimensional circuit parameter vectors so as to obtain multidimensional fault feature vectors; obtaining a fault feature vector sample set within a health tolerance range of the circuit; obtaining a fault feature vector of the circuit in the process of real-time operation at a periodic interval; computing the health degree of the fault feature vector to the fault feature vector sample set at each time point so as to form a health degree-time sequence of the circuit; giving out the threshold value of the health degree of the circuit; carrying out prediction on the health degree-time sequence of the circuit by using an RVM (Relevance Vector Machine) algorithm so as to obtain the health degree of the circuit in some future time, comparing the obtained health degree with the threshold value of the health degree, and determining the health situation of the circuit in some future time, thereby realizing the fault prediction of the circuit. By using the prediction method disclosed by the invention, the real-time state monitoring and health-status estimation on the power electronic circuit can be realized, thereby realizing the prediction on the future state of the circuit, and then predicting the time of fault occurrence in advance.

A solar photovoltaic module laminate for electric power generation is provided. The module comprises a plurality of solar cells embedded within the module laminate and electrically interconnected to form at least one string of electrically interconnected solar cells within said module laminate. And at least one remote-access module switch (RAMS) power electronic circuit embedded within the module laminate electrically interconnected to and powered with said at least one string of electrically interconnected solar cells and serving as a remote-controlled module power delivery gate switch.

The invention discloses a device for monitoring the state and diagnosing the fault of a power electronic circuit. The device has a structure that: a magnetic field detection module detects the magnetic field strength of the power electronic circuit, a signal conditioning module amplifies a voltage signal and an analog-to-digital conversion module performs analog-to-digital conversion; a fault diagnosis module comprises a time-domain and frequency-domain conversion module, a characteristic sort module and a comprehensive diagnosis module; the time-domain and frequency-domain conversion module is used for extracting the frequency characteristics of a time-domain waveform and supplies the frequency characteristics to characteristic sort sub-modules respectively; the characteristic sort sub-modules compare the received subsets to obtain partial diagnosis results corresponding to each characteristic subset and supply the results to the comprehensive diagnosis module; and the comprehensive diagnosis module synthesizes the partial diagnosis results of each characteristic subset to obtain a final diagnosis result. The device realizes the natural isolation of a detector from a main circuit; the different kinds of information carried by the magnetic field signal are treated respectively and then comprehensively judged, so the accuracy is higher; and the device can be applied to various power electronic circuits.

The invention discloses a power electronic circuit fault diagnosis method based on an optimized deep belief network. The method comprises the following steps: (1) using an RT-LAB semi-physical simulation platform to set a fault expierment, and acquiring direct current side bus output voltage signals under different fault modes to serve as original fault characteristic quantities; (2) extracting anintrinsic mode function component and an envelope spectrum thereof of the output voltage signal by utilizing empirical mode decomposition, calculating a plurality of statistical characteristics, andconstructing an original fault characteristic set; (3) removing redundancy and interference features in the original fault feature set based on a feature selection method of an extreme learning machine, and performing normalization processing to serve as a fault sensitive feature set; (4) dividing the fault sensitive feature set into a training sample and a test sample, and preliminarily determining the structure of the deep belief network; (5) adopting a doodle search algorithm to optimize the deep belief network, and setting the number of hidden neurons of the network; And (5) obtaining a fault diagnosis result. According to the invention, the fault feature data size and the fault identification accuracy are improved.

The invention discloses an analogical electronic circuit fault diagnostic method based on an M-ary-structure classifier, which belongs to the field of analogical circuit network test. The invention comprises the following steps: firstly, analyzing the testability of an analogical circuit to determine proper test stimulus and a test point; secondly, acquiring to-be-tested outputting signals at a testable node of an electronic circuit; thirdly, compressing acquired circuit fault information to extract fault characteristic samples; finally, designing the tags of the samples in an M-ary encoding way, establishing a hyperspherical sub-classifier in the way of a SVDD classifier, training the samples, and storing information to form a fault dictionary after training. The invention has the advantages of less classifiers, simple method, high reliability, and the like, thereby improving the automation degree and the efficiency of the online fault diagnosis of a power electronic circuit.

The invention discloses a power electronic circuit fault diagnosis method based on an extremely random forest and a stacked sparse auto-encoding algorithm. The method comprises the following steps of signal acquisition and feature extraction; fault feature dimensionality reduction preprocessing, using an extreme tree algorithm ET to calculate importance scores of all features in an original feature data set, sorting the importance scores in descending order, determining the proportion to be removed, and obtaining a new feature set after removing the proportion; fault feature further extraction, using a stacked sparse auto-encoding SSAE algorithm to cascade multiple sparse self-encoders, and performing layer-by-layer feature extraction to obtain a hidden layer feature of a last sparse self-encoder as a fault sample; performing classification training, inputting fault samples in a training set and a test set into a classifier for training, and obtaining a trained classifier; and pattern recognition, using the trained classifier to classify and recognize faults of a power electronic circuit to be diagnosed, and locating the faults.

A system and method for providing extreme fast charging of electric vehicles that mimics the typical gas station experience while also supporting local grid energy management using a distributed network of extremely fast charging stations to form a large virtual resource for the grid. The system consists of a controller unit responsible for system operation tasks, a high-voltage battery pack capable of rapid discharge rates to support extreme fast charging, a cloud-based database to persist and manage system and network data, a DC electric vehicle outlet for providing charging, safety systems, and power electronic equipment configured to allow bi-directional flow of power between a local, low-voltage AC grid and the extreme fast charging station. The bi-directional capabilities of the power electronic circuits within the system allow the charging station to provide power resources, stored within the high-voltage battery pack, to help support local grid power consumption.

A simulator for a switched electronic power converter circuit feeding a load / device uses a modified FAMNM solver. Provided is a method / system for reducing / eliminating spurious power losses and transients inherently caused by the FAMNM solver using an L / C element approach, wherein a switching device in the ‘on’ state is featured as an inductor L, and a switching device that is in the ‘off’ state is featured as either a capacitance C or series-connected resistance and capacitance R-C. The invention uses cross-initialization of the L / C switching elements to their final state of current and voltage when they change their conduction state. The correct cross-initialization is enabled from optional pre-stored tables of events and the system-states at the time of the cross-initialization. The inventive method is an enhancement over known Dommel and Pejovic type FAMNM solvers. The simulator applies to real-time or non-real time simulators and is suitable for all power converter topologies.

The invention provides a zero-current soft switching converter and relates to the field of power electronic circuit topology design. The zero-current soft switching converter comprises a switching tube, a power diode, a voltage source inductor basic circuit and a current source inductor basic circuit, and further comprises a soft switching auxiliary unit. The soft switching auxiliary unit comprises a resonance inductor, a resonance capacitor and an auxiliary switching tube. The switching tube and the auxiliary switching tube are turn-off power switching devices provided with antiparallel diodes or having antiparallel diode characteristics. One end a of the resonance inductor is connected to a connection point of the switching tube and the power diode, and the other end b of the resonance inductor is connected to a current source inductor. The resonance capacitor and the auxiliary switching tube form a serial branch, one end of the serial branch is connected with an end b of the resonance inductor, and the other end c of the serial branch is connected to the negative pole N or the positive pole P or the middle point M of a voltage source. According to the zero-current soft switching converter, resonance current amplitude values of the soft switching converter can be automatically changed along with load current, therefore, loss of the soft switching converter can be further lowered, and efficiency can be further improved.

A bi-directional dual coil half bridge converter adapted to be coupled to a dual coil actuator of a cylinder valve in an internal combustion engine is described. In one example, the converter has a first and second capacitor and a voltage source, where the converter is actuated via switches to individually energizing coils in said dual coil actuator. A voltage regulator is also shown for maintaining midpoint voltage during unequal loading of different actuator coils in the converter.

The demand for automation design of power electronic circuits becomes higher and higher with the development of the power electronic technology. In the invention, a particle swarm algorithm is applied to the design and optimization of the power electronic circuits, and the invention mainly relates to the power electronics field and the intelligent computation field. In the optimization method, an optimization process is divided into two parts by a decoupling technology to respectively optimize the power transmission of the power electronic circuit and a feedback network. Meanwhile, a mutation operator is introduced into the particle swarm algorithm to increase diversity of the swarm and improve the optimization efficiency of the algorithm. The optimization design of a buck converter is taken as an example for testing, which proves that the optimization method is very effective.

The invention discloses - a power electronic circuit optimizing method based on an ant-colony-algorithm, which relates to the fields of the intelligent calculation and the power electron. The invention discretizes the possible values of all elements of the power electronic circuit into a series of standard values, and then maps the standard values into a structural diagram of an ant-colony-algorithm optimizing circuit. The ant-colony algorithm is adopted to select the best route in the structural diagram, namely, a best element value is selected to meet the required circuit performance. The ant-colony algorithm is very applicable to the discretization combinational optimization, thereby can rapidly and effectively optimize the power electronic circuit. The optimized results of the method are the standard values of all elements, so the optimized results can be directly applied to the actual production without any approximation.

A technique is disclosed for cooling connections points in power electronic circuits, such as points at which wire bonding connections are made. A phase change heat spreader is thermally coupled at or near the connection point and a continuous phase change takes place in the heat spreader to extract heat from the connection point during operation. The heat spreader may extend over a area larger than the connection point to enhance cooling and to dissipate heat over a larger area. Small, specifically directed applications are possible in which specific points are cooled together or individually.

The invention discloses an IECMAC parameter identification-based power electronic circuit failure predicting method, belonging to the technical field of power electronic failure test. The method comprises the following steps of: taking a set power device parameter value as an input training minimum neural network to obtain a failure sample set; judging the failure modal of an electronic circuit to be tested using information entropy-added detecting point electric signal training minimum neural network, and comparing the future time circuit performance parameter predicted by the SVR (support vector regression) with a circuit health threshold, to judge the failure modal of the electronic circuit to be tested; and predicting the real-time failure modal of the power electronic circuit to be tested by taking each detecting node electric signal which is timely monitored as an input repetition training minimum neural network. According to the method, a mathematical model of complex nonlinear system can not be built, and the generalization capability of an identifier can be further improved; and the regression can be carried out on the time sequence formed by system performance parameters by the SVR (support vector regression), the predicting precision and efficiency can be improved, and the on-line and real-time failure prediction can be realized.

Embodiments of the subject invention relate to a method and apparatus for providing an electrical energy system. A specific embodiment can incorporate at least one energy harvesting module (H-module), at least one energy storage module (S-module), and at least one power electronic circuit module (C-module). The various modules can be integrated into a standard battery configuration. Specific embodiments pertain to a reconfigurable energy system with modules that can be disconnected and reconnected into different shapes and configurations.

An ensemble learning-based electric power electronic switch device network fault diagnosis method includes the following steps of: (1) collecting an output voltage or current signal vector set {Vn<q>}, n=1,2...N of an electric power electronic circuit in different switch device fault modes; (2) using principal component analysis to extract normalized fault characteristic vectors in the fault mode Fq from a signal vector Vn<q>, and obtaining a normalized fault characteristic vector set shown in the description according to the normalized fault characteristic vectors shown in the description; (3) using the normalized fault characteristic vector set shown in the description to train k neural network element classifiers in turn, and setting the number limitation K of the neural network element classifiers as 50 and a system error threshold e0; and (4) repeating steps (1) and (2) aiming at the circuits to be detected, obtaining a fault characteristic vector V* to be detected, enabling the fault characteristic vector to access the trained k neural network element classifiers, and using an ensemble learning method to obtain an ensemble recognition result. The ensemble learning-based electric power electronic switch device network fault diagnosis method can avoid defects of over learning of a single neural network and falling in local minimum, improves the classification precision of the neural network element classifiers.

A bi-directional dual coil half bridge converter adapted to be coupled to a dual coil actuator of a cylinder valve in an internal combustion engine is described. In one example, the converter has a first and second capacitor and a voltage source, where the converter is actuated via switches to individually energizing coils in said dual coil actuator. A voltage regulator is also shown for maintaining midpoint voltage during unequal loading of different actuator coils in the converter.

A support may receive one or more power electronic circuits. The support may aid in removing heat from the circuits through fluid circulating through the support. The support, in conjunction with other packaging features may form a shield from both external EMI / RFI and from interference generated by operation of the power electronic circuits. Features may be provided to permit and enhance connection of the circuitry to external circuitry, such as improved terminal configurations. Modular units may be assembled that may be coupled to electronic circuitry via plug-in arrangements or through interface with a backplane or similar mounting and interconnecting structures.

A mixed type direct current breaker is composed of mechanical switches (17, 18 and 20) and power electronic devices (16, 19, 13, 14, 15, 21, 22, 23, 24, 25, 26 and 27). When direct current high-voltage transmission lines run normally, a low-loss current path is formed through the mechanical switches (17, 18 and 20) and the power electronic devices (16, 19, 13, 14, 21 and 22), and when the direct current high-voltage transmission lines break down, rapid disconnection is achieved through an electronic switch (19), and therefore rapid disconnection of the mechanical switch (18) under a zero current situation is achieved. The problem that a capacitor (15) and an inductor (22) cause current turn-off time to be long in an oscillation process is solved through control of power electronic circuits (13, 14, 15, 27, 21, 22, 23 and 26), and rapid tuning-off of fault currents is achieved.

A modular inductor arrangement is provided in which a footprint of an enclosure for single or multiple phase inductors provides enhanced thermal transfer. The inductor coil may be wound about an axis generally parallel to a mounting surface of the package, so as to provide for reduced height and expanded footprint dimensions. The inductor package may be mounted on a thermal support, such as a fluid-cooled support. Heat is extracted from the assembly during operation, so as to establish a reduced maximum internal temperature as compared to here for known structures. The arrangement may be included in various circuit configurations, such as power converters. Other components may be incorporated and integrated into the package, including sensors, capacitor coils, other inductor coils, and so forth.

Embodiments provide systems and methods for controlling electronic circuitry. A system can include at least a first controller and a second controller and at least one power electronic circuitry module. The first controller can be in electrical communication with the power electronic circuitry module via a first high-speed serial link (HSSL). The second controller can be in electrical communication with the power electronic circuitry module via a second HSSL.

On board charger for electric vehicles, having an AC input and a DC power output and comprising a housing that contains a power electronic circuit, a control electronic circuit, capacitors, inverters, at least one transformer, input inductor and output inductor inside to allow the conversion of input AC power into output DC power, the base of the housing incorporating a cooling circuit (12), such that the at least one transformer, the at least one input inductor and the at least one output inductor are arranged in a compartment delimited by several side walls and the base of the housing of the on board charger and at least one internal wall, the compartment being at least partially filled with potting which at least partially covers the at least one transformer, the at least one input inductor and the at least one output inductor, these three elements constituting one magnetic block.