Shandong University

Chenghui Zhang

Bin Duan

Yunlong Shang

Ke Li

Qi Zhang

Bo Sun

Naxin Cui

Zhongkai Zhou

Xiangyang Xing

Yu Wang

Feng Gao

Yan Li

Tao Xu

Xiaoyan Li

Changwei Qin

Haiyang Wang

Jing Chen

Hankun Liu

Yuchen Mu

Deyin Ma

Xi Liu

Gaotong Wu

Jinqiu Song

Shi Zhang

Che Liu

Yanzhao Ren

Xiangjian Meng

Alian Chen

Ying Jiang

Shunquan Hu

Hua Geng

The present invention provides a dual-level thermal runaway warning method of a lithium battery based on a sound signal, comprising: obtaining a battery sound signal sequence; performing outlier identification on the battery sound signal sequence, and providing a level-1 thermal runaway warning when an abnormal data point exists; extracting a time-frequency domain feature of the abnormal data point, and identifying a presence of a thermal runaway expansion sound through a sparrow search algorithm-optimized eXtreme Gradient Boosting (SSA-XGBoost) algorithm, to providing a level-2 thermal runaway warning. In the SSA-XGBoost algorithm, optimal parameter adjustment is performed on a number of iterations, a learning rate, and a decision tree depth of the XGBoost algorithm through the SSA. A dual-level thermal runaway warning strategy is adopted to perform grading identification on general anomalies or deep anomalies, thereby effectively improving identification accuracy of a weak abnormal sound signal in an early stage.

Dual-level thermal runaway warning method and system of lithium battery based on sound signal

Provided is a system and method for the distributed networked test of electric vehicles based on a cloud platform, comprising a cloud computing platform and a plurality of remote test benches, wherein the remote test benches, being provided at least two, to form a remote distributed networked structure and transmit test data to the cloud computing platform; the cloud computing platform, being in real-time bidirectional data communication with the remote test bench and configured to receive each test data in real-time, perform a data cleaning, a data classing washing, a data fusion and a data mining, extract useful data information from the test data, build corresponding a data model and a mechanism model on the cloud computing platform according to historical data and a mechanism of control object, control for different test benches, and complete a fault diagnosis and an early warning.

System and method for distributed networked test of electric vehicles, storage medium and terminal device

The present invention belongs to the technical field of integrated energy system (IES), and provides a method and system of multi-time scale compound control of IES based on dual-loop feedback robust model predictive control (RMPC), comprising: analyzing multi-time scale characteristics of typical equipment and integrated demand response (IDR), establishing a compound control framework for equipment-side-load-side coordination, carrying out differential control on different time scales through intra-day three-layer controller aiming at the difference in regulation rate and response characteristics between the multi-energy equipment and the IDR, modifying, layer by layer, a reference of upper layer and issuing control strategies in real-time, which fully stimulates flexibility on both sides of supply and demand.

Method and system of multi-time scale compound control of integrated energy system based on dual-loop feedback robust model predictive control

A method and system for performing analysis and calculation of multi-energy flow for integrated energy system (IES), comprising establishing electrical power flow model, hydraulic model and thermal model, to form preliminary model of IES; constructing DHL-LSTM neural network for nonlinear regression of electrical power flow model, construct SHL-LSTM neural network for nonlinear regression of hydraulic model, and finding optimal parameters of two neural networks; training the two models, and adding error compensations into the two models; simplifying the thermal model, to obtain mechanism-driven linear thermal mode; and embedding mechanism-driven linear thermal model into error-compensated hydraulic model and error-compensated electrical power flow model respectively, to form and use final model of the IES to perform analysis and calculation of multi-energy flow. The present invention fully considers the coupling property inside the system, and avoids the situation that the convergence speed is slowed down when solving high nonlinear problems.

Method and system for dispatching multiple energy sources in integrated energy system

A power compensation control method and apparatus for a high-power multi-functional efficient charging system. A topology structure of the charging system includes at least two parallel high frequency link matrix converters. The power compensation control method includes: calculating a difference between an input voltage phase of an iconverter and an ideal reference input current phase under a dq two-phase synchronous rotating coordinate system, where i is an odd number; calculating, according to the above difference, a required rotating phase angle of a space current vector of an (i+1)converter, where by total instantaneous reactive power at input sides of the iconverter and the (i+1)converter is zero; correspondingly rotating the vector, and judging a sector to which the rotated vector belongs; and generating a corresponding control pulse signal based on the corresponding sector and modulation ratio, so as to act on the (i+1)converter to realize power compensation.

Power compensation control method and apparatus for high-power multi-functional efficient charging system

A method and system for predicting regional short-term energy power by taking weather into consideration includes: obtaining meteorological data of all moments in a set time in the future through a network; extracting respectively, from a historical database according to the obtained meteorological data, historical weather station meteorological data, historical network API meteorological data, and historical measured power generation power data within a set time period that meet meteorological conditions corresponding to all the moments; obtaining historical total error data; obtaining real-time error meteorological data; obtaining total error meteorological data; combining the obtained meteorological data of all the moments in the set time in the future with total error meteorological data of all the moments to obtain predicted meteorological data; obtaining predicted power data according to the predicted meteorological data; and optimizing an energy generation plan of a system according to the obtained predicted power data.

Method and system for predicting regional short-term energy power by taking weather into consideration

The present disclosure discloses a dynamic equivalent circuit of a combined heat and power system, and a working method thereof. Controlled sources are used to represent a thermoelectric coupling source; equivalent inductance is used to represent a delay of a heat transmission pipeline; equivalent resistance is used to represent a heat load and a heat loss of the heat transmission pipeline; and equivalent capacitance is used to represent a heat storage water tank. A circuit model is used to uniformly represent two thermoelectric heterogeneous energy sources, and a single power simulation tool may be used to simulate a combined heat and power system, so that the simulation system has a simple structure and is easy to develop and maintain.

Dynamic equivalent circuit of combined heat and power system, and working method thereof

A multi-fault diagnosis method has the following steps: measuring cell voltages of a battery pack to be diagnosed; constructing a cell voltage sequence according to measured cell voltages of the battery pack to be diagnosed, and calculating a sample entropy value of the cell voltage sequence; setting a correction coefficient for representing voltage fluctuation information, and correcting the sample entropy value through the correction coefficient to obtain a corrected sample entropy value; and judging and outputting a fault type of the battery pack to be diagnosed according to a numerical value change of the corrected sample entropy value. Faults of cells can be accurately diagnosed without a model, sample entropy values under different faults can be distinguished by setting the correction coefficient, the intuitiveness and efficiency of fault detection are improved, and the fault type and time of the lithium-ion cells can be quickly, accurately and stably diagnosed and predicted.

Multi-fault diagnosis method and system for battery packs based on corrected sample entropy

The present disclosure provides a method and system for predicting building energy consumption based on a Holt-Winters and an extreme learning machine, the method including: constructing a building simulation model based on actual operation parameters of a building to obtain an original energy consumption data set of the building; decomposing the original energy consumption data set to obtain a linear energy consumption data set and a nonlinear energy consumption data set; performing prediction on the linear energy consumption data set by using a trained Holt-Winters model to obtain a linear energy consumption prediction result; and inputting the nonlinear energy consumption data set, the original energy consumption data set, and the linear energy consumption prediction result into a trained extreme learning machine model to output a building energy consumption prediction value of the building simulation model.

Method and system for predicting building energy consumption based on holt-winters and extreme learning machine

A fractional-order KiBaM battery model considering nonlinear capacity characteristics and a parameter identification method includes a temporary capacity portion and an available capacity portion for describing nonlinear capacity characteristics of a battery, wherein the temporary capacity portion represents the power that can be directly obtained during the discharge, indicating the state of charge (SOC) of the battery; the available capacity portion represents the power that cannot be directly obtained, and such two portions are connected; when the battery is discharged, the load current i flows out from the temporary capacity portion, and a power passing rate coefficient of such capacity portions is obtained; and the nonlinear capacity effect and recovery effect of the battery are denoted by the height ratio of the temporary capacity and available capacity portions in view of the magnitude of the fractional order of battery capacity characteristics.

Fractional-order KiBaM battery model considering nonlinear capacity characteristics and parameter identification method

An on-line quantitative evaluation method for the stability of a welding process includes the steps of monitoring and acquiring the arc voltage U and the welding current I during the welding process, and drawing a phase diagram of each U-I cycle; converting the phase diagram of each U-I cycle into a binary image K; obtaining an area Jthrough which a dynamic working curve passes in the binary image K; obtaining a welding process stability evaluation index P according to the formula (1), where Jis the area of a U-I curve, N is the number of cycles passed, L is the total number of samples in N cycles, and P is the repetition rate of the i-th U-I cycle and other cycles (i=1 . . . N); and evaluating the stability of the welding process according to the obtained welding stability evaluation index P.

On-line quantitative evaluation method for stability of welding process

A hybrid cascaded APF topology and control method therefor for improving the ability of a system to compensate for higher harmonics, raise the quality of electric energy of output currents, and reduce costs. The topology includes: a three-phase cascaded H-bridge including bridge arms of three phases, each bridge arm including a plurality of H-bridge cells connected in series, and the bridge arms of the three phases connected to a power system needing active filtering via inductors; and a three-phase H-bridge circuit connected at star connection points of the three-phase cascaded H-bridge, the three-phase H-bridge circuit including branches of the three phases and two capacitors connected in parallel across the branches of the three phases, and the branch of each phase including two switching transistors connected in series, where switching transistors of the H-bridge cells use Si devices, and the switching transistors of the three-phase H-bridge circuit use SiC devices.

Hybrid cascaded APF topology and control method therefor

A neutral-point voltage balance control method and system for a three-level converter in a full power factor range. The method includes: using a large, medium, and zero vector modulation method to synthesize a reference voltage vector, and duty cycles of a large vector, a medium vector, and a zero vector; obtaining a voltage difference between two dc-link capacitors of signal acquisition, and the voltage difference as a neutral-point potential of the three-level converter; according to a value relationship between the neutral-point potential of the three-level converter and a specified threshold, selecting a small vector and calculating a duty cycle of the small vector; and updating a duty cycle of each basic vector, and obtaining a switching sequence for controlling a power switch of a three-phase bridge arm. An amplitude of a common-mode voltage of an NPC three-level converter is equal to one sixth of a dc-link voltage.

Neutral-point voltage balance control method and system for three-level converter in full power factor range

The present disclosure provides a method and system for power prediction of a photovoltaic power station based on operating data of grid-connected inverters, including: constructing a photovoltaic module model according to parameters of a photovoltaic module in a photovoltaic power station; constructing a power prediction model based on an artificial neural network algorithm; acquiring output data of a photovoltaic array when being shaded by static shadows of different thicknesses and different shading areas, constructing a training set to train the power prediction model, and obtaining a trained power prediction model; and acquiring, classifying, and normalizing output powers in real-time operating data of an inverter when the photovoltaic array is under a clear sky condition, and predicting a output power of the entire photovoltaic power station by using the trained power prediction model, the power prediction including a rolling prediction of the output power of the photovoltaic power station under a clear sky condition and a minute-level power prediction of the photovoltaic power station when being shaded by a dynamic cloud cluster. The present disclosure reduces a device cost and overcomes the defect that cloud clusters of different thicknesses affect the precision of power prediction of the photovoltaic array.

Method and system for power prediction of photovoltaic power station based on operating data of grid-connected inverters

A new method for iteratively identifying parameters of an equivalent circuit model of battery, including the steps of: Firstly, dividing the model parameters into two parts, and the parameters in the first part are set to initial values, and the ones in the second part are identified with a least square method. Secondly, determining whether the obtained values of the second part meet the requirements of the equivalent circuit model of battery. If the requirements are not met, the parameters that do not meet the requirements in the second part are set to zeros. Then, the parameters in the first part are identified with the least square method. Otherwise, the ones in the first part are directly identified with the same method. Terminating the iteration process until all the parameters meet the requirements.

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Jinan, China

Chenghui Zhang