4087 results about "Electric bicycle" patented technology

The invention discloses an electric bicycle lithium battery data real-time monitoring and early warning system and method, and relates to the technical field of battery management, and the system comprises a multi-dimensional data collection module which is used for obtaining a multi-source heterogeneous data set of a lithium battery system; the collaborative feature extraction module is used for generating a comprehensive evaluation parameter set; the dynamic threshold generation module is used for constructing a self-adaptive early warning boundary model according to the comprehensive evaluation parameter set; the intelligent decision module is used for generating a hierarchical control instruction set based on a multi-objective optimization algorithm; and the cloud collaboration module is used for synchronizing the hierarchical control instruction set to the edge computing node and the cloud management platform, and triggering a multi-level linkage protection mechanism based on the game theory when the thermal runaway risk index is detected to exceed a first dynamic threshold value. According to the electric bicycle lithium battery data real-time monitoring and early warning system and method provided by the invention, the safety and reliability of a battery system are improved.

The invention provides an electric bicycle charging method and system based on a mutual recognition mechanism, and relates to the technical field of battery management, and the method comprises the steps: detecting the state of a battery through a multi-sensor fusion algorithm, predicting the endurance mileage and charging demands through deep reinforcement learning, and predicting the destination and arrival time through track analysis; a charging pile is optimized based on a multi-constraint path planning model and an improved multi-target genetic algorithm, a target charging pile adopts dual encryption identity authentication, a self-adaptive charging control algorithm based on a fuzzy neural network is used for optimizing a charging process, and data is uploaded to a charging scheduling server.

A battery device and a battery management method are provided. The battery device includes two battery packs and a management module that can obtain a piece of battery health data for each of the two battery packs. When the management module detects that a first variation between two pieces of the battery health data is greater than 2%, the management module selects one of the two battery packs in which the battery health data is high to supply power to an electric bicycle, and another one of the two battery packs in which the battery health data is low to suspend operation. When the management module detects that the first variation between the two pieces of the battery health data is less than 2%, the management module selects one of the battery packs to supply power to the electric bicycle according to a first rule.

The invention discloses an energy management method of an electric bicycle system and the electric bicycle system.The method comprises the steps that battery parameters, motor parameters and whole vehicle kinetic parameters of an electric bicycle are obtained, and digital mapping processing is carried out to obtain a digital twin system; acquiring operation parameters of the battery, the motor and the whole vehicle, and performing distributed feature extraction processing to obtain feature data; training the bionic optimization model fusing the genetic algorithm and the ant colony algorithm to obtain a scenarized energy optimization strategy; performing hierarchical regulation and control processing on the control system to obtain a hierarchical control instruction sequence; and performing dynamic regulation and control processing on energy distribution to obtain a real-time energy optimization control instruction. According to the technical scheme of the invention, intelligent prediction and dynamic optimization distribution of energy demands are realized.

The invention relates to the technical field of electric bicycles, and discloses a data-driven electric bicycle battery fire hazard detection and protection method, which comprises the following steps: S1, multi-modal data acquisition and fusion, S2, data preprocessing and feature extraction, S3, data-driven intelligent detection: classifying normal and abnormal states through a supervised learning model, S4, hierarchical protection strategy, and S5, data-driven intelligent detection. S5, cloud data optimization and model continuous learning; S6, model data updating; S7, intelligent linkage and long-term optimization; S8, cloud risk data acquisition; and low, middle and high three-level protection mechanisms are adopted. Through dynamic risk assessment, charging and discharging power is limited in a medium risk, a charger is automatically disconnected, a user is prompted to stop operation, active protection is triggered in a high risk, and sound-light alarm and remote notification are triggered at the same time, so that accidents are prevented from further spreading.

The invention belongs to the field of road vehicle control systems, and relates to a method for predicting the risk of collision between an electric bicycle and a vehicle based on the multi-modal behavior of the electric bicycle, which utilizes physical modeling and takes the influence of the braking distance and the transverse and longitudinal stability of the electric bicycle on the vehicle as a basic risk; automobile risks caused by the environment are further considered, and multi-dimensional environment risk assessment modeling is carried out by integrating four dimensions of dynamic distance-speed, adjacent vehicle types, traffic flow density and weather conditions (precipitation, temperature, wind speed and visibility); the risk of electric bicycle operation behaviors (acceleration change and steering angle and frequency) to the automobile is combined; the complex relation between the environment change and the whole vehicle risk is captured in real time by using the environment sensitivity coefficient, and finally a set of comprehensive, accurate and real-time multi-dimensional comprehensive risk assessment method is provided for the vehicle for the multi-mode riding behavior of the electric bicycle, so that the collision risk in the complex traffic flow environment is reduced.

The invention provides an instrument gesture control method based on a millimeter wave radar and related equipment, and relates to the technical field of instrument intelligent control. The method comprises the steps of firstly obtaining a target reflection signal through a built-in millimeter wave radar, then identifying the signal to determine whether a target is a palm, and then identifying a target action according to a preset palm template library to obtain palm action information; then, a control instruction is determined by combining the information with an instrument control mapping library (storing a palm action and control instruction mapping relation), and finally, corresponding parts of the electric bicycle are controlled according to the instruction. According to the scheme, non-contact gesture control is achieved by means of the millimeter wave radar technology and a multi-layer feature recognition mechanism, the convenience and the intelligent level of interaction of the electric bicycle can be improved, and a more flexible control mode is provided for a user.

The invention is suitable for the technical field of resource recommendation, and provides a shared electric bicycle and battery charging and replacing integrated base station intelligent interaction dynamic resource recommendation method, which comprises the following steps: acquiring battery state data, user behavior data and charging demand identification of a shared electric bicycle in real time; collecting resource state data of the charging and battery replacing integrated base station; evaluating availability characteristics of available batteries of the base stations, and generating recommendation priorities of the base stations; a resource locking request containing dynamic reserved duration is sent to a target base station with the highest priority, the dynamic reserved duration is dynamically adjusted according to the real-time position of a user and navigation estimated time, and when it is detected that a path is blocked or user requirements are changed, the recommendation priority is updated; and after the battery replacement operation is completed, a recommendation strategy is optimized based on the actual performance data of the battery and user operation feedback. According to the invention, highly intelligent and personalized base station recommendation can be provided for the user, the resource configuration of the whole system is optimized, and the user experience and the operation efficiency are remarkably improved.

The invention relates to the technical field of fire safety, in particular to an electric bicycle shed automatic fire extinguishing device and system.The method comprises the following steps that S1, data of a plurality of fire factors are collected; s2, performing fusion analysis on various fire factor data, and outputting a fire risk judgment result; s3, dynamic fire risk assessment is carried out, and a fire early warning threshold value is adjusted in real time; s4, identifying a section where the fire occurs; s5, on the basis of the fire sections identified in the S4, automatically controlling fire extinguishing devices in the corresponding areas to be started; s6, the fire area is cooled through a water spraying device; and S7, after the fire is extinguished, storing all data to a remote cloud server. According to the electric bicycle shed, through multi-dimensional fire monitoring, intelligent algorithm dynamic evaluation and automatic control technologies, accurate fire early warning, effective fire extinguishing, continuous cooling and safety data storage are achieved, and the fire prevention and control efficiency and safety of the electric bicycle shed are remarkably improved.

A method for pairing a control device for an electric bicycle includes (i) connecting the control device to a first server, (ii) connecting the control device to an electric bicycle, (iii) providing a first bicycle ID and a second bicycle ID of the electric bicycle, (iv) providing pairing data from the first server on the basis of the first bicycle ID, (v) connecting the control device to a second server, and (vi) providing further pairing data from the second server on the basis of the second ID.

The invention relates to the technical field of electric bicycle frame testing, and discloses an electric bicycle frame bearing capacity testing device which is used for testing the bearing capacity of an electric bicycle frame. Comprising an equipment base, a supporting frame arranged above the equipment base, an arc-shaped overturning assembly, a supporting overturning mechanism, a movable downward pressing assembly sliding on the top of the supporting frame, and a control host arranged on one side of the equipment base. A connecting block extends out of the telescopic cylinder in the vertical direction of the connecting groove to be connected with the rotating square block, and the clamping column is moved in the clamping groove to be limited and fixed; when a front end impact resistance test needs to be carried out on the vehicle frame, the connecting block extends out of the telescopic cylinder in the horizontal direction of the connecting groove and is connected with the rotating square block, so that the vehicle frame can be connected with devices with different functions, the vehicle frame can be tested at different angles and postures, and the accuracy and reliability of a test result are improved.

The invention belongs to the field of vehicle industry design, and discloses an electric bicycle form design method and system, electronic equipment and a storage medium, and the method comprises the steps: mining user emotion vocabularies through online comments, constructing an emotion lexicon in combination with an improved word frequency-inverse document frequency algorithm and a D-S evidence theory, and screening out key perceptual vocabularies; constructing a convolutional long-short-term memory neural network model optimized by a snake swarm algorithm to realize a mapping model between customer sensibility and product morphological characteristics; carrying out subjective and objective comprehensive evaluation on the design scheme in combination with an eye movement experiment and subjective evaluation so as to screen out an optimal design scheme; an optimal scheme is selected and input into a generative AI platform for multi-angle visual rendering, ergonomic modeling and aerodynamics simulation are assisted, and the structural feasibility and performance are verified. The method provides systematic technical support for emotional value improvement and design optimization of industrial products.

The invention is suitable for the technical field of load identification, and relates to an electric bicycle home-entry charging identification method, a medium and a terminal, and the method comprises the steps: S10, carrying out the real-time data collection of a voltage u (t) and a current i (t) of a wire inlet of a main ammeter, and calculating the time sequence of an active power P and a reactive power Q; s20, through an inverted Z-shaped window sliding event detection method, the maximum active power difference value of the left window and the right window is calculated through the sliding window, whether the difference value exceeds a set threshold value or not is judged, and therefore the starting event of the electric equipment is determined; s30, identifying a maximum active power difference value, a maximum reactive power difference value and a ratio of the maximum active power difference value to the maximum reactive power difference value by adopting a characteristic increment threshold value, and if the three values meet conditions at the same time, executing the step S40; and S40, analyzing the output data by using a one-dimensional convolutional neural network model, and identifying a charging starting event of the electric bicycle. According to the invention, the electric bicycle battery charging identification accuracy is improved, and the false alarm rate and the missing report rate are reduced.

The invention relates to the technical field of power battery health state evaluation and anomaly recognition, in particular to a remote health state analysis and anomaly recognition method for an electric bicycle battery, which comprises the following steps of: under an access working condition, applying small-signal active excitation and synchronously acquiring to form an opportunity diagnosis excitation data window; time-frequency coupling modeling including equivalent impedance modeling, harmonic wave and intermodulation fingerprint modeling, Koopman operator modeling and entropy coefficient difference is carried out, and a spectral measurement geometric distance is constructed through optimal transmission to generate a multi-domain response packet, a physical invariant vector and an uncertainty matrix; according to the geometric distance and consistency score gating and hierarchical standardization, obtaining a health state estimation record and an abnormal event set by adopting a shape-limited health mapping model; and in combination with mapping Jacobian and dual potential, generating an opportunity diagnosis incentive plan of a next period by adopting D-optimal test design, and updating a group health manifold, thereby realizing cross-environment, cross-equipment and traceable remote health assessment and early anomaly recognition.

The invention provides a battery car dynamic charging optimization management system based on battery health state evaluation, and belongs to the technical field of battery car charging management. The system comprises a data acquisition module which is connected with an environment sensing device and a battery management system and acquires environment and battery parameters in real time; the data storage module is used for storing an initial training data set, a charging and discharging data set and a battery aging feature library; the model building module is used for building a battery health state evaluation model through a migration strategy and building a response model through a modeling strategy; the health state evaluation module is used for extracting associated features with a critical damage threshold value as a core through a mapping algorithm based on the battery parameters, the environmental parameters and an aging feature library; and the charging strategy generation module comprises a strategy generation unit, a reference parameter generation unit and a dynamic correction unit. The system effectively improves the adaptability of battery car charging, guarantees the efficient and stable operation of the battery, and remarkably improves the safety and prolongs the service life of the battery.

The invention discloses a heat dissipation control method and system for an electric bicycle charging pile, and relates to the technical field of charging control, and the method comprises the steps: arranging a temperature sensor on a power conversion device of the electric bicycle charging pile, monitoring the temperature in real time, and obtaining the output power; heat dissipation gears and environment temperature data are obtained, heat dissipation control fitting and loss analysis are carried out, and temperature control loss compensation is established; according to the power variation, the temperature sequence and the environment temperature, temperature development fitting is carried out, heat dissipation control optimization is executed, and heat dissipation control is carried out. The technical problems that the control precision of the charging process of the charging pile is insufficient and the charging efficiency and the safety of equipment are affected due to the fact that the heat dissipation intensity cannot be accurately and dynamically adjusted in the prior art are solved, and the purposes of ensuring the stable temperature control of the charging pile under various charging conditions through real-time temperature monitoring and dynamic heat dissipation control optimization and improving the charging efficiency are achieved. And the charging process control precision, the equipment safety and the charging efficiency of the charging pile are improved.

The invention belongs to the technical field of battery replacement, and provides a battery replacement cabinet system applied to an electric bicycle, which comprises the following steps: analyzing the fluctuation condition of temperature data and establishing a dynamic threshold compensation mechanism by using the temperature data collected by a temperature sensing monitoring unit and a composite monitoring unit; the method comprises the following steps: performing time sequence construction on temperature data collected by a temperature sensing monitoring unit and a composite monitoring unit, analyzing the time sequence to obtain an intrinsic mode function component, converting the intrinsic mode function component to obtain a Hilbert spectrum, distinguishing a low-frequency intrinsic mode function component and a high-frequency intrinsic mode function component according to the Hilbert spectrum, and calculating the intrinsic mode function component according to the low-frequency intrinsic mode function component and the high-frequency intrinsic mode function component. Integrating the low-frequency intrinsic mode function and the high-frequency intrinsic mode function to obtain a temperature change time domain envelope line; analyzing the slope of the smooth rising stage of the temperature change time domain envelope, judging whether the charging temperature change of the battery is normal or not in real time, and if not, generating a pre-alarm signal; and based on the generated pre-alarm signal, analyzing a Pearson's correlation coefficient between the monitoring units, and positioning and adjusting a temperature anomaly region.

The utility model discloses an electric bicycle battery testing device. The electric bicycle battery testing device comprises a charging module, a discharging module, a charging switch module, a discharging switch module, an acquisition module, a control module and an analysis module. The charging module and the discharging module are connected with a to-be-tested battery. The charging switch module is connected between the charging module and the power supply; the discharge switch module is connected between the discharge module and the control module; the control module is connected with the charging switch module, the control module is also connected with the discharging switch module, the acquisition module is arranged in a battery to be tested, and the control module is connected with the acquisition module; the acquisition module is used for acquiring test parameters of a to-be-tested battery; the control module charges or discharges the to-be-tested battery according to the test parameters; and the analysis module is connected with the acquisition module and determines a test result of the to-be-tested battery according to the test parameters. The electric bicycle battery testing device provided by the embodiment of the utility model is beneficial to improving the testing efficiency and accuracy.

The structure and operation of a logistical system for charging electrical vehicles (EVs) are described. The logistical system may include synergistically interacting hardware and software components on a computer of a charging service, a plurality of EVs, and a plurality of charging stations. Charge information describing conditions of a battery of an EV, and EV location information, may be sent to the charging service computer. An application operating on the EV and / or driver's mobile device may receive data from the charging service, which may include a location of a charging station capable of charging the EV and an estimated charging time and / or cost for the battery charging. Charging stations, in communication with the charging service, provide information that assists the charging service to select an appropriate charging station. Mobile charging-vehicles may be directed to particularly needed locations by the charging service, and may charge electrically assisted bicycles and other vehicles.

The invention discloses an electric bicycle parking detection method, electronic equipment and a storage medium. The method comprises the steps of obtaining a current left eye image and a current right eye image of a target electric bicycle based on a binocular camera; determining a current 3D target detection frame of the target electric bicycle according to the current left eye image and the current right eye image; determining whether the target electric bicycle is parked in a preset parking area according to the current 3D target detection frame; when it is determined that the target electric bicycle is parked in the preset parking area, whether the parking orientation of the target electric bicycle meets the specification or not is determined; and when it is determined that the parking orientation conforms to the specification, a target electric bicycle parking specification is determined. According to the method, whether the parking of the electric bicycle is standard or not is detected according to the obtained left eye image and the right eye image of the electric bicycle, and the detection efficiency and the detection accuracy of detecting whether the parking of the electric bicycle is standard or not are improved.

The disclosure relates to an electric Bicycle Drive Unit for arrangement in a Bottom Bracket Area of a Bicycle Frame. The Drive Unit has an Electric Motor Device and a Bottom Bracket Assembly having a Bottom Bracket Shaft. The disclosure also relates to a Bicycle Frame or Frame Interface Unit, and an Energy Storage Device for the Electric Bicycle Drive Unit. The Drive Unit includes s an Integrative Energy Storage Device for supplying energy to the motor device. The Integrative Energy Storage Device can be arranged adjacent to the motor device in such a way that the center of gravity position of the Energy Storage Device and the center of gravity position of the Drive Unit lie within the Bottom Bracket Area.

The invention discloses an electric bicycle health state evaluation method, system and device and a storage medium, and belongs to the field of lithium battery electric bicycles, and the method comprises the following steps: obtaining historical SOC data and current SOC data of an electric bicycle battery; calculating the current cycle index of the battery, and calculating the habitual charging depth of the user; obtaining the charging nominal capacity of the battery, and calculating to obtain a capacity attenuation empirical model; calculating a mean health state under the current cycle index; the current charging depth and the current charging capacity are calculated, whether the current charging depth meets the calibration condition or not is judged, and if yes, the average health state is calibrated through the charging nominal capacity and the current charging capacity, and the current cycle number is corrected; and if the calibration condition is not met or the calibration is completed, outputting the average health state of the electric bicycle. According to the invention, the battery health state can be monitored in an electric bicycle scene, a user is helped to know the health degree of the battery, and the use safety of the battery is improved.

According to the electric bicycle data collaborative sharing method based on multi-party security computing, the collaborative computing system is constructed, the collaborative control nodes in the collaborative computing system are independent of the business departments, and the collaborative computing system allocates at least one computing execution node to each business department. The calculation execution nodes are in communication connection with a database of a business department, and each calculation execution node is in communication connection with the coordination control node; the method comprises the following steps: splitting a calculation task in a collaborative governance service related to cross-department data sharing based on service logic, and obtaining a single-department calculation sub-task and a cross-department calculation sub-task after splitting; each calculation execution node executes a calculation task which only relates to the data of the business department, and only submits a calculation result to the coordination control node; all calculation tasks related to cross-department data are completed at the coordination control node; and then the coordination control node feeds back the data requested by the business department to the requesting department.

The embodiment of the invention provides an assisting power output control method of an electric bicycle, the electric bicycle and a storage medium, and the method comprises the steps that the current motor rotating speed of the electric bicycle and the current torque value applied to pedals of the electric bicycle are collected; adjusting the cut-off frequency of a first low-pass filter based on the current motor rotating speed, and filtering the current motor rotating speed through the adjusted first low-pass filter to obtain a smooth rotating speed; determining a motor torque compensation value based on the motor rotating speed fluctuation quantity between the smooth rotating speed and the current motor rotating speed; and determining a motor torque output value based on the motor torque compensation value and the current torque value, and controlling the power output of the electric bicycle according to the motor torque output value. By means of the power assisting device, the technical problem that power assisting output of the electric bicycle is not smooth due to mechanical shaking or resonance is solved.

A control system for an electric bicycle includes an operating unit which is configured to control a ride controller of the electric bicycle. The operating unit is configured to allow a user to select among a plurality of assistance modes via an operating interface, and to control the ride controller in such a way that a drive control for a motor of the bicycle is carried out according to the selected assistance mode.

The invention belongs to the technical field of tire detection, and particularly relates to a full-automatic tire pressure detection device for an electric bicycle tire, the full-automatic tire pressure detection device comprises a base, a clamping mechanism, a lifting mechanism and a detection mechanism, the base is rotatably connected with a rotating disc; the lifting mechanism is used for driving the detection mechanism to lift, the detection mechanism comprises a connecting seat, and a positioning plate is connected below the connecting seat; the guide frame is vertically and fixedly connected with the positioning plate; the guide frame is connected with a movable seat, the movable seat is fixedly connected with a fixed plate, and the fixed plate is connected with a detection joint matched with a tire valve; the detector is connected with the detection joint through an air pipe; the clamping mechanism drives the tire to rotate, the inflating valve is rotated to the position below the detection mechanism, the lifting mechanism drives the detection mechanism to descend, in the descending process, the detection connector is automatically connected with the tire inflating valve in an aligned mode, and therefore the tire pressure is automatically detected, and the detection efficiency is high.

In order to solve the problem that in a bicycle or an electric bicycle, people carrying by installing a rear child seat and object carrying by installing a rear tail box are difficult to consider at the same time, the utility model provides the multifunctional child seat of the two-wheeled vehicle and the turnover safety device installed on the multifunctional child seat of the two-wheeled vehicle. The backrest piece and the side wing pieces of the multifunctional child seat of the two-wheeled vehicle can be folded forwards along with the rear base, and an enclosed space is formed by the backrest piece, the side wing pieces, the front base and the front enclosure piece. The front base and the rear base are hinged through the folding mechanism, and after the enclosed space is formed, the folding locking piece enters the clamping groove to limit the folding mechanism, so that vehicle-mounted articles can be stored. The folding safety device is used for limiting the folding locking piece, on one hand, the reliability of the folding mechanism can be improved, and on the other hand, anti-theft storage of the vehicle-mounted articles can be achieved.

The invention discloses an electric bicycle shed intelligent management and abnormity alarm method and system, and relates to the technical field of electric bicycle charging safety, and the method comprises the following steps: collecting electric bicycle charging information, and carrying out the feature analysis; based on an analysis result, performing charging load detection on the electric vehicle, and performing battery health state evaluation; and giving out fault diagnosis of the single battery of the electric vehicle according to an evaluation result. According to the electric bicycle charging load detection method, verification is carried out in data with the sampling frequency being 1 / 60 Hz, and it is proved that the electric bicycle charging load is accurately detected through the electric bicycle charging load detection method based on the global features.

The invention relates to the technical field of electric bicycle detection, in particular to an electric bicycle frame strength detection device and method.The electric bicycle frame strength detection device comprises a base, the upper end of the base is provided with two vibration units symmetrically arranged front and back, and the upper end of the base is further provided with a testing unit used for clamping a frame and vibrating the frame up and down in cooperation with the vibration units; the positions, corresponding to the vibration units, of the base are each provided with two adjusting units which are arranged in a bilateral symmetry mode. According to the invention, the two hinged vibration plates and the test unit cooperate to carry out vibration test on the strength of the frame, and the vibration plates and the test unit cooperate to drive the vertical vibration amplitude of the frame to be adjusted according to the included angle between the two hinged vibration plates. Therefore, the frame strength of the electric vehicle when the electric vehicle runs on the road surfaces with different road conditions can be tested, the frame testing efficiency is improved, meanwhile, the frame strength of the electric vehicle when the electric vehicle runs on the continuously changing road surfaces can be tested, and the frame strength testing accuracy is improved.

A method for changing a transmission ratio of an electrically controllable gearing of a bicycle, in particular of an electric bicycle, includes (i) measuring a pedaling frequency of the bicycle rider on the pedal shaft, (ii) measuring a pedaling force of the bicycle rider, and (iii) determining a gear change operating state on the basis of the measured pedaling frequency and on the basis of the measured pedaling force if the measured pedaling frequency is less than or equal to a lower frequency threshold value or is greater than or equal to an upper frequency threshold value, and / or the measured pedaling force is less than or equal to a lower force threshold value or is greater than or equal to an upper force threshold value. After determining the gear change operating state, a control signal is generated for the gearing according to the determined gear change operating state.