196 results about "Smart Battery" patented technology

The invention discloses a storage battery abnormity early warning system based on an intelligent battery gateway, and relates to the technical field of battery monitoring. The system comprises a sensor module used for collecting voltage, internal resistance, temperature, thermal runaway state and floating charge voltage parameters of a single battery in real time; the intelligent battery gateway comprises a data processing module and an early warning module, and the data processing module carries out fusion analysis on sensor data through an intelligent algorithm, calculates the battery remaining capacity SOC and the state of health SOH and executes an intelligent equalization strategy; and the early warning module generates a multi-stage early warning signal according to the parameter threshold and the anomaly detection model. According to the invention, through a multi-dimensional fusion sensing technology and a dual-drive intelligent algorithm, the aging sign of the internal microstructure of the battery is accurately captured, and high-precision estimation of the residual electric quantity and the health state of the storage battery is realized; and in the aspect of early warning performance, a multi-dimensional linkage detection model and an intelligent early warning mechanism are established, so that the accuracy and timeliness of fault early warning are effectively improved, and the early warning time is greatly advanced.

The invention discloses a multi-level feature fusion and time sequence modeling combined lithium battery life prediction method, and relates to the technical field of lithium ion battery health management and life prediction. The method comprises the steps of receiving time sequence observation data in a battery operation process, inputting the time sequence observation data into a pre-constructed local feature extraction model, and introducing a one-dimensional convolutional neural network into the local feature extraction model to perform feature extraction on the time sequence observation data to obtain local feature representation. According to the method, three structures of local feature extraction, global context modeling and bidirectional time sequence modeling are fused, and the battery degradation modeling capability and prediction precision are effectively improved. The TFN adopts an end-to-end architecture design, has good feature perception capability and time-dependent modeling capability, and can adapt to various degradation modes and complex time sequence environments. The method is suitable for life evaluation and health state monitoring in an intelligent battery management system, and has relatively high practical value and popularization prospect.

The invention relates to the technical field of electric forklifts and energy storage, and discloses an intelligent battery management system and prediction method based on optical fiber sensing, the system comprises a distributed optical fiber sensing network, a data acquisition and processing module, an intelligent analysis decision module, a battery management control module and a cloud platform interaction module; the method comprises the following steps: collecting a battery signal through a snakelike-spiral optical fiber network, reconstructing a temperature / strain field through noise reduction and filtering, extracting multi-modal features, inputting the multi-modal features into an LSTM model to predict thermal runaway, generating a risk level in combination with an improved equation, dynamically adjusting charging, discharging and heat dissipation strategies, and realizing three-dimensional visual monitoring through a cloud platform. According to the invention, high-precision distributed monitoring of the temperature / strain field of the battery pack is realized through the BOTDR optical fiber sensing network, the LSTM prediction model is constructed by fusing multi-physical field characteristics, and thermal runaway is warned in advance. The improved algorithm reduces the false alarm rate, charging and discharging parameters are dynamically adjusted to prolong the service life of the battery, and a three-dimensional visual platform improves the operation and maintenance efficiency.

Disclosed is a power electronic intelligent battery unit, including: a battery module, the battery module comprising a plurality of battery cells connected in series and sensors for measuring the voltage, current, pressure and / or temperature of the battery cells; and an intelligent battery interface, the intelligent battery interface being connected to an output side of the battery module and the sensors, and the intelligent battery interface having a power interface and an information interface for the outside, wherein the battery module monitors the voltage, current, pressure and / or temperature information of the battery cells, while providing or absorbing power by means of the intelligent battery interface.

The invention relates to the technical field of digital twinning, and particularly discloses an intelligent battery detection system based on digital twinning, which comprises battery detection equipment, an edge computing gateway, a cloud computing platform and a digital twinning visual interaction platform, the battery detection equipment is used for detecting charging and discharging data of a to-be-detected battery and uploading operation data of the battery detection equipment and the charging and discharging data of the to-be-detected battery to the edge computing gateway; the edge computing gateway is used for preprocessing the received data and uploading the preprocessed data to the cloud computing platform; and the cloud computing platform is used for analyzing and processing the preprocessed charging and discharging data of the to-be-detected battery to obtain a future state index of the to-be-detected battery, and then uploading the preprocessed operation data of the battery detection equipment and the future state index of the to-be-detected battery to the digital twin visual interaction platform for display. According to the invention, the real-time performance and accuracy of battery state prediction can be greatly improved.

The invention relates to the technical field of intelligent battery management, and discloses an intelligent battery hybrid parallel access system and a control method. According to the method, a battery pack is divided into a basic energy storage unit and a dynamic adjustment unit, a hybrid parallel access network is constructed based on a layered interaction architecture, unit voltage, loop current and temperature field distribution data are acquired through a multi-dimensional sensing module, feature extraction and weight fusion are performed by using a time sequence association processor, and a temperature field is obtained. And the input state decision module adjusts an access mode, and the two-way instruction analyzer executes mode switching. Meanwhile, real-time data and reference parameters are compared through a grading evaluation mechanism, after operation deviation is determined, an adjusting signal is transmitted through a feedback channel, an operation record is generated, and the response speed of the adjusting signal is in positive correlation with the deviation. The method comprises a hybrid architecture construction module, a multi-source data processing module and an operation deviation feedback module. According to the invention, efficient management and accurate control of the battery pack are realized, and the flexibility, stability and safety of the system are improved.

The invention relates to the technical field of battery management, in particular to a modular intelligent battery management system, which comprises a sensing module for realizing full-dimensional monitoring of a battery through a multi-mode sensor array, implanting an MEMS stress sensing network and constructing a holographic stress tensor model; the operation and maintenance and decision-making module is used for realizing cooperative control of the battery units through dynamic impedance matrix construction, plasma resonance frequency monitoring and unbalanced thermodynamic gradient analysis; and the execution module is used for receiving the instruction sent by the stress analysis and optimization unit, controlling the piezoelectric composite material to generate a self-adaptive support structure, adjusting the internal mechanical structure of the battery, forming a stress shielding area and reducing the influence of stress on the performance and the service life of the battery. Through a dynamic impedance matrix and a main control unit election mechanism, the single-point bottleneck of traditional centralized management is avoided, and even if part of units fail, the system can still maintain the function through matrix recombination, so that the anti-interference capability and reliability are improved.

The invention relates to the technical field of electric vehicle battery thermal management, in particular to an intelligent battery thermal management method and system based on environment temperature self-adaptive adjustment. A real-time response mechanism based on the dynamic temperature difference between the environment temperature and the battery temperature is provided, and through the four steps of temperature index data collection, thermal management battery protection, thermal management adaptive control and thermal management dynamic adjustment, when the environment battery temperature difference is larger than a threshold value, a continuous high-power mode is started, a temperature region can be rapidly converged, and the power consumption is reduced. The target temperature zone arrival time is effectively shortened; when the environment battery temperature difference is smaller than the threshold value, the intermittent low-power mode is switched, and energy consumption minimization can be achieved; the working temperature of the power battery can be quickly controlled near or within the most suitable working temperature, and the probability that the battery is reduced or even does not generate related side reactions is ensured, so that the cycle life of the battery is prolonged.

A smart battery box is provided that includes a battery for selectively powering a trailer main harness coupled to an ABS controller. The smart battery box includes a controller configured to respond to a command to control a switch to close to power the ABS controller through the battery. In this fashion, the ABS controller may be tested through the smart battery box while the trailer is disconnected from a tractor.

A battery pack can comprise a battery monitoring system that can monitor a battery metric of a battery cell of a battery system cluster board, in response to a determination that the battery metric satisfies a first bypass condition, enables a bypass mode applicable to the battery system cluster board, and in response to a determination that the battery metric no longer satisfies the first bypass condition, exits the bypass mode. A primary controller can in response to a determination that a second bypass condition applicable to the battery system cluster board has been satisfied, sends an instruction to the battery monitoring system to enter the bypass mode, and in response to a determination that the second bypass condition is no longer satisfied, sends an override instruction to the battery monitoring system to exit the bypass mode.

The invention relates to the technical field of intelligent battery module rolling detection, in particular to a tab visual inspection rolling system and method suitable for a battery module, and provides a tab visual inspection rolling system comprising a position adjusting mechanism, a rolling mechanism, a top face visual inspection mechanism and a side face visual inspection mechanism. Wherein the adjusting mechanism can adjust the horizontal position and height of the rolling mechanism so as to perform rolling processing on tabs of different batches of battery modules, and the processing condition of the tabs can be detected based on a visual form after rolling processing, so that on one hand, the detection precision is improved compared with the existing manual detection or spot check; and on the other hand, the labor intensity of manual detection is greatly reduced. The first top surface visual detection part, the second top surface visual detection part, the first side surface visual detection part and the second side surface visual detection part are arranged, so that the rolling quality is detected from two dimensions, the defect type thickness uniformity comprehensive evaluation is realized, and the misjudgment rate is reduced.

The invention provides an intelligent battery diagnosis system and method based on vehicle operation data and a large model of a hybrid electric vehicle. The method comprises the following steps: collecting charging and discharging data of operating vehicles of various types in different working modes; fault data, fault types and fault handling suggestions of all vehicle types are collected in a classified mode according to the fault types; constructing a fault prediction model based on multi-model fusion based on the collected data; training the large language model according to a mapping relation generated by the fault prediction model, and constructing an intelligent fault knowledge base; and inputting the charging and discharging data and the fault data output by the vehicle-mounted BMS into the intelligent fault knowledge base to obtain a disposal scheme corresponding to the fault data. According to the method, charging, discharging and fault data of the series plug-in hybrid electric vehicle are considered, the fault prediction model is constructed by adopting an intelligent algorithm, and the fault knowledge base is constructed through the fault data and the fault disposal data, so that the fault recognition accuracy and efficiency of the power battery and the fault disposal efficiency of the power battery can be greatly improved.

An electrical power supply system for an aircraft comprising: a string of a plurality of connected smart battery modules, wherein the string is configured to provide a common output voltage; wherein each of the smart battery modules comprises, terminals for outputting an output voltage to a device external to the smart battery module; a battery assembly configured to supply a DC voltage between two poles; a power converter electrically connected to the terminals and the poles, and a controller operably coupled to the semiconductor stage and configured to control the semiconductor stage for regulating the voltage conversation of the DC voltage into the output voltage a control unit operably coupled to the controller of each smart battery module and configured to set an output voltage and / or current setpoint or limit for each controller individually or configured to set an output voltage and / or current setpoint or limit for all controllers collectively.

The invention discloses a high-precision intelligent battery residual capacity detection method and device, and relates to the technical field of battery capacity detection. The method comprises the steps of collecting end current and end voltage of a target battery module in real time, and judging whether the target battery module triggers a characteristic load scene or not; when the characteristic load scene meets any one of a plurality of triggering conditions, recording a triggering moment; analyzing a polarization voltage difference value based on the trigger time, and introducing a polarization energy loss model to perform polarization loss analysis on the polarization voltage difference value to obtain polarization loss data; obtaining the basic battery residual capacity of the target battery module; and performing polarization loss correction on the residual capacity of the basic battery by taking the polarization loss data as correction data to obtain and output the corrected residual capacity of the battery. The technical problem that the detection precision of the residual capacity of the battery is low due to the fact that the influence of battery polarization on the residual capacity is not fully considered in the prior art is solved, and the technical effect of improving the detection precision of the residual capacity of the battery is achieved.

The present invention discloses a sensory battery cell including a plurality of battery cells arranged in a first battery network, wherein the first battery network is a series network or a parallel network or a combination thereof, and a sensing integrated circuit connected in parallel with each battery cell to sense performance parameters of the plurality of battery cells, wherein the sensing integrated circuit includes a function circuit able to take an action for the battery cell that reaches a set condition. The present invention further discloses a intelligent battery using the sensory battery cell, a power battery using the intelligent battery, a battery management system and related methods thereof.

The invention relates to the field of photovoltaic technology, in particular to a photovoltaic power storage intelligent battery pack management system based on intelligent regulation and control, which is characterized in that a mobile battery vehicle carries a plurality of independent drawer type battery packs, is provided with positive and negative relays, is connected with a bus through a low-resistance copper bar, and is automatically conducted with an electric equipment interface through a power conversion connector after the battery packs are connected in series; each battery pack is provided with an independent sensor node, data of each drawer type battery pack is obtained through the sensor nodes, all the nodes are connected in series through twisted-pair shielded wires, and multi-node communication is achieved based on a CAN protocol; according to the real-time electricity demand, an optimal drawer type battery pack combination is dynamically selected by applying a greedy algorithm, and a BMS host controls the on-off states of a plastic shell switch, an air switch and a relay array according to a decision result; an emergency stop protection mechanism is arranged and comprises DI1 and DO2. Each drawer type battery pack is an independent energy storage unit, so that a single battery pack can be conveniently maintained, overhauled and replaced, and the work of other battery packs is not influenced.

The invention relates to the technical field of new energy equipment charging, and particularly discloses an intelligent monitoring system for the charging state of an inland ship, and the system comprises a charging track system which employs a parallel overhead contact network mode; the top of the ship powered device is provided with a liftable pantograph with an intelligent adjusting device; the ship end control system and the central control system are in two-way communication; the ship power supply system comprises a power supply access and power supply conversion system, an intelligent tension adjusting system and a power supply monitoring system and is used for supplementing power to the ship; meanwhile, the intelligent battery management system distributes and dispatches electric energy according to the charging requirement of the ship and the real-time load condition of the overhead contact system; when the high-voltage mains supply is powered off or unstable, the standby power supply system can switch a high-capacity energy storage battery pack mode or a small emergency generator mode; the safety of the ship in the charging process is guaranteed through the safety protection system; the urgent demand that the ship cannot be quickly charged during sailing is solved, and reliable charging service is provided.

The invention discloses a small electric freight vehicle SOC prediction method, and belongs to the technical field of electric vehicle battery management. According to the method, aiming at the problem that a traditional SOC prediction model is insufficient in precision under a cross-speed working condition, the driving working condition is divided into three typical scenes, namely a low-speed scene, a medium-speed scene and a high-speed scene through K-means clustering; for each scene, screening key features by adopting an SHAP method to construct a scene feature set; constructing a hybrid model by using a time sequence convolutional network and a long short-term memory network, and training by using each scene feature set to obtain a corresponding scene prediction model; in practical application, according to a real-time vehicle speed matching scene, a corresponding model is called to carry out SOC prediction. According to the method, the SOC prediction precision under different speed working conditions can be improved, the model scene adaptability is enhanced, and support is provided for electric vehicle endurance estimation and intelligent battery management.

The invention discloses an electric vehicle battery replacement encryption system and method, and relates to the technical field of electric vehicle battery replacement encryption systems.The electric vehicle battery replacement encryption system comprises a communication unit, a biological characteristic collection unit and an encryption chip and is used for conducting identity authentication and initiating a battery replacement request; the intelligent battery replacement cabinet module comprises a rail type battery bin array, a battery identification unit and an emergency power supply unit; the transfer guarantee module is used for automatically transferring by using a mechanical arm; the cloud collaboration platform is used for deploying a block chain node and a privacy calculation module and is used for verification code distribution, battery full life cycle tracking and cross-regional resource scheduling; the intelligent battery module comprises a multi-dimensional sensor group and an anti-disassembly self-locking mechanism. According to the electric vehicle battery replacement encryption system and method, by arranging the user terminal module, the intelligent battery replacement cabinet module, the transfer guarantee module, the cloud collaboration platform, the intelligent battery module, the payment gateway module and the like, the potential safety hazard of identity counterfeiting in the prior art is solved, battery information matching is guaranteed, and the situation that a high-quality battery is replaced stealthily is effectively avoided.

The invention relates to the technical field of intelligent battery manufacturing, and discloses an intelligent battery automatic manufacturing system and a management system. A raw material acquisition module of the system obtains battery manufacturing raw material data in an initial time period and converts the battery manufacturing raw material data into a standardized format; after the intelligent analysis module receives the standardized data, physical and chemical characteristics of the raw materials are analyzed through a deep learning model, and a characteristic analysis report is generated; the production planning module determines production parameters according to the report and generates a production instruction; the execution control module controls production equipment to complete battery automatic manufacturing based on the production instruction; the quality detection module detects the battery after being manufactured and generates quality detection data; and the feedback optimization module adjusts deep learning model parameters according to the quality detection data, and optimizes a subsequent production instruction generation process. According to the system, intelligent closed-loop management of battery manufacturing from raw material analysis to production optimization is realized through cooperation of all the modules.

1. Name of the Design Product: Intelligent Battery for Drone Countermeasure Equipment. 2. Use of the Design Product: For power supply of drone countermeasure equipment. 3. Design Key Points of the Design Product: Lies in the shape. 4. Picture or Photograph that Best Illustrates the Design Key Points: 3D View of Design 1. 5. Design 1 is designated as the basic design.

To provide a method for immediately determining whether there is a welding error in a battery pack.SOLUTION: In a smart battery detection device, a battery pack comprises a microcontroller and at least one battery cell. The microcontroller includes: the battery pack that acquires an initial direct current internal resistance (DCIR) value corresponding to the battery pack in a charging mode, and detects a DCIR value currently corresponding to the battery pack at each relative state of charge (RSOC) check point; and a processor that is coupled to the battery pack and obtains the DCIR value. At least one of the microcontroller and the processor determines whether there are any errors in the battery pack.SELECTED DRAWING: Figure 3

The invention discloses a transmission shaft square intelligent battery structure, and relates to the technical field of intelligent batteries, the structure comprises a square battery shell, an upper bin cover, a middle bin partition plate, a lower bin cover, a sealing gasket, a buffer pad, a support ring, a shock pad, a square key groove, a BMS system, a battery pack, a glue injection heat dissipation hole, a long circular key groove, a positioning plate and a circular positioning groove; the square battery shell, the upper bin cover and the lower bin cover form a square split bin structure, the interior of the square battery shell is divided into an upper bin chamber and a lower bin chamber by the middle bin partition plate, and the upper bin cover and the positioning plate are respectively provided with a long circular key groove and synchronously rotate with the transmission shaft through a connecting key. Through the composite connection design of the upper bin long circular key, the lower bin square key and circular positioning, reliable synchronous rotation is achieved, vibration interference can be reduced, and the transmission stability is obviously better than that of a traditional annular clamp structure.

1. Name of the product in this design: Smart Battery and its Main Body (TATTU5.0). 2. Application of this design: for use in batteries for drones and other devices that require charging and discharging. 3. The key design feature of this product is its shape. 4. The picture or photo that best illustrates the key design points: Design 1 3D diagram 1. 5. Design 1 is designated as the basic design. 6. Other situations requiring explanation: In Design 2, the dashed lines represent parts that do not require protection.

1. Name of the product in this design: Intelligent Battery Swapping Cabinet. 2. Purpose of this design: For charging and swapping batteries. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The invention provides a rechargeable battery system. The rechargeable battery system includes: a battery cell having a laminated case encapsulating an electrolyte and an electrode stack; the thermal sensing pad is embedded in the battery unit, the thermal sensing pad comprises a plurality of temperature sensors arranged at different positions in the battery unit, and each temperature sensor is packaged in an electrolyte-resistant material; the integrated circuit board is electrically connected with the thermal sensing pad; the integrated circuit board is configured to: (1) receive a sensing signal from the temperature sensor; (2) converting the sensing signal into digital temperature data; and (3) transmitting the digital temperature data to a battery management system. The battery management system is configured to analyze the digital temperature data to evaluate an internal temperature condition of the battery cell.

1. The name of the design product: smart battery clamp shell. 2. The use of the design product: the design product is used for battery clamp shell. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

The invention relates to the technical field of battery energy storage box equipment, in particular to a waterproof intelligent battery energy storage box which comprises a box body, a box cover is detachably installed on the box body, a battery module and a control unit are installed in the box body, and the control unit comprises a storage battery monitoring management system, a WIFI module, an indicator lamp module and an air switch. A hanging assembly is mounted on the box body and comprises a hanging bottom and a hanging seat, the hanging bottom comprises a base, a movable seat is mounted on the base in a sliding manner, a lug for hanging the hanging seat is mounted on the movable seat, and a bayonet is formed in the movable seat; the hanging seat comprises a bottom plate mounted on the box body, a hanging plate and a hanging piece are mounted on the bottom plate, and a locking plate clamped into the bayonet is mounted on the hanging plate; a fixing assembly for fixing the lock plate is installed on the base, a hanging plate is installed on the base, the hanging plate is arranged between the fixing assembly and the lug piece, and a supporting plate for protecting the lock plate is hinged to the hanging plate. The waterproof intelligent battery energy storage box has the effect of improving the convenience of the waterproof intelligent battery energy storage box in the use process.

The invention discloses an intelligent battery charging control method, which relates to the technical field of intelligent battery charging and comprises the following steps of: extracting time continuous characteristics of gradient mutation according to a thermal response dynamic mapping surface, generating an electrochemical polarization direction evolution track and constructing a polarization mutation recognition template; the deviation rate of the electron migration path relative to the ideal conductive path is calculated, and an electron channel correction function is established; the charging current density of the abrupt change area is adjusted in a segmented mode through a correction function, and local potential inversion is weakened through a buffer type current control strategy; and constructing a layered energy distribution mechanism according to a coupling relationship between the polarization direction and the temperature response, and implementing regional control on the charging power. Precise identification and dynamic regulation and control of the polarization direction are realized by constructing a thermal response dynamic mapping surface, local potential inversion and electron aggregation are prevented in advance, energy input and thermal diffusion balance are realized through layered energy distribution and regionalized power control, the charging safety of a battery cell is improved, and the service life of the battery cell is prolonged.

The invention discloses a sea-air integrated multi-source heterogeneous sensing intelligent system which comprises an intelligent system power module, a high-endurance energy module, a multi-source heterogeneous sensing module, an unmanned aerial vehicle folding and unfolding and intelligent system positioning correction module and a multi-source data heterogeneous communication and integrated sensing module. By designing the high-endurance energy module and adopting the wide-temperature-range inorganic solid-state battery and the intelligent battery management module, the energy guarantee capability of the system in an extreme environment is improved, and the problem that an existing sensing system is insufficient in endurance in a cold region or in long-time operation is solved. According to the invention, a multi-source heterogeneous sensing module is constructed, multiple groups of optical cameras and laser scanners are fused, full-visual-angle three-dimensional sensing of underwater, water surface and airspace is realized, the space coverage rate and precision of sensing are effectively improved, and the problems of large blind area and single data of a traditional single sensing means are solved.