5880 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.

A method and system for controlling an electric bicycle are provided. The method may comprise: driving the electric bicycle; generating a deceleration torque command of a driving motor based on a moving distance of a pedal if a driver rotates the pedal installed in the electric bicycle in a reverse direction while the electric bicycle is driving; controlling a current supplied to the driving motor according to the deceleration torque command; and generating a deceleration torque of the driving motor by the current control.

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.

A chainless hybrid electric bicycle includes a bicycle body. A generator, a battery pack, a driving motor and a manual switch are mounted on the bicycle body. The generator is coaxially mounted with the pedal transmission unit, so that the generator generates an electric power when the rider works the pedals. The battery pack is electrically connected to the generator for storing the electric power generated by the generator. The driving motor drives the wheels of the bicycle body to run. The rider selects the electric power from the generator or the battery pack through the manual switch to drive the driving motor to run, which in turn drives the bicycle body to move forward. The chainless hybrid electric bicycle has the advantage of a hybrid power drive system, without using traditional mechanical transmission components such as chains and chainrings.

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.

Drive unit for a vehicle that can be operated by muscle power and / or motor power, in particular an electric bicycle, eBike, pedelec or S-Pedelec, comprising a rotor, a rotor shaft, a first bearing and at least one further bearing, and a shaft, wherein the drive unit has at least a single-stage worm gear or worm gear drive, wherein a worm is non-rotatably connected to the rotor shaft and has at least one helical thread, and a worm wheel which is non-rotatably connected to the shaft and is in mesh with the worm.

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.

There is provided a powertrain of a mid-drive electric bicycle that enables regenerative braking. The powertrain comprising a mid-drive electric motor, a chain rotatably connected to the mid-drive electric motor, a gearing system mounted in a rear wheel bub, the gearing system rotatably connected to the chain, a mechanical brake connected to a component of the gearing system, and a control system. During operation of the mechanical brake, the gearing system is configured to cause rotation of the chain in a backward direction opposite to the forward driving direction, which mechanically forces the mid-drive electric motor to rotate in the backward direction, to thereby regenerate electric energy. There is further provided a crankset configured to prevent rotation of pedals of the electric bicycle in a backwards driving direction during backwards rotation of the chain in braking mode.

The proposed solution concerns a drive system for an electric bicycle, comprising a bottom bracket shaft for applying rider torque with a rider cadence for generating drive power for muscle-powered propulsion of the electric bicycle, at least one drive motor for providing externally generated support power in addition to the drive power depending on at least one operating parameter, a frequency unit for determining the rider cadence and a torque unit for determining the rider torque.The drive system also includes an electronic control unit for determining at least one operating parameter based on the rider's cadence and torque. This control unit comprises a filter unit configured to filter one or more values ​​of the rider torque based on the rider's cadence to determine a filtered rider torque value. It also includes an evaluation unit configured to determine the at least one operating parameter from a predefined map, which is at least two-dimensional, based on the filtered rider torque and the rider's cadence. The proposed solution also relates to a method for determining at least one operating parameter.

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.

In at least one embodiment, the assembly (100) for an electric bicycle comprises a frame element (1) for the frame of the electric bicycle with a frame-side interface (11) and a drive unit (2) for the electrically assisted drive of the electric bicycle with a drive-side interface (21). The drive unit and the frame element are mechanically coupled to each other via the interfaces, so that the drive unit is attached to the frame element. A deformable damping element (4) is provided in the area of ​​the interfaces, so that structure-borne noise transmission from the drive unit to the frame element is suppressed.

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.

A method for the maintenance of an electric bike includes (i) activating a maintenance mode of a drive unit of the electric bike in response to an activation signal, wherein the electric bike, during the maintenance mode, is in a stationary state relative to surroundings, and (ii) operating the drive unit in the maintenance mode in response to a one-time user input by way of the input unit.

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 invention discloses fully-immersed power battery integrated equipment for an electric bicycle and application of the fully-immersed power battery integrated equipment to the electric bicycle. The fully-immersed power battery integrated equipment for the electric bicycle comprises a box body and a battery cell, the box body is provided with a containing space and is used for containing cooling liquid, the cooling liquid comprises at least one of halogenated hydrocarbon and an insulating medium, and the battery cell is immersed in the cooling liquid. According to the fully-immersed power battery integrated equipment provided by the invention, the safety performance of the battery can be effectively improved, so that the problem that fire disasters cannot be effectively prevented from occurring and spreading when the battery of an electric bicycle is subjected to thermal runaway can be solved.

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.