29 results about "Electric bus" patented technology

This invention relates to a method, system, device, and medium for synchronous control of dual motors in an electric bus door enclosure, belonging to the fields of smart home and automatic control technology. The method includes: collecting local motor speed data and sending it in real-time to other motor control systems within the same linkage group; receiving motor position data from other motor control systems; calculating speed and position deviations in real-time based on the local motor speed data and the received motor position data; and then, based on the deviations and preset full-stroke friction characteristic data, compensating for the speed of the local motor to ensure synchronous operation of all motors within the same linkage group. This application can reduce the false alarm rate of stall, reduce mechanical impact noise, extend the life of transmission components, and achieve accurate fault identification.

This invention relates to the field of electric bus control, and particularly to a method, system, device, and medium for dual-motor coordinated control of an electric bus. The method involves acquiring multi-source state data of a pure electric bus during operation and constructing a working condition feature vector. Based on the working condition feature vector, historical operating data is subjected to working condition clustering analysis to establish a mapping relationship between working condition features and coordinated control parameters. A dual-motor coordinated control parameter optimization model is constructed, and under constraints of motor efficiency spectrum, battery power boundary, and system stability, the coordinated control parameters are optimized through multi-objective optimization to obtain the optimal coordinated control parameter vector. This enhances the adaptability of the vehicle control system under complex operating conditions, extends the service life of the motor and power system, improves the stability and reliability of the vehicle control system, reduces the impact of torque fluctuations, and improves passenger comfort.

This invention relates to a method, device, and medium for optimizing the matching of flexibility resources for electric buses. It constructs a single-vehicle energy consumption prediction model for electric buses that includes a quadratic temperature term, and establishes a battery capacity correction model that considers low-temperature degradation and limited regenerative braking to obtain the physical boundary of flexibility resources. The method uses kernel density estimation to fit the probability distribution of bus return time and dwell time, and combines this with the energy consumption prediction model to establish state-of-charge (SOC) opportunity constraints. Under the physical boundary of flexibility resources and SOC opportunity constraints, a hierarchical response mechanism with dead-zone control is used to implement vehicle-grid flexibility supply and demand matching, and to formulate an optimal vehicle-grid coordinated flexibility resource allocation scheme. Compared with existing technologies, this invention can correct the energy consumption prediction bias of traditional linear models under extreme temperatures, alleviate the scheduling mismatch problem caused by the randomness of return time, and improve the response capability of electric bus clusters to participate in grid peak load reduction while considering battery life.

This invention discloses a traffic control method and system for an inspection robot and an electric shuttle bus. The method includes: S1. collecting laser ranging data of the wheel axle cross-section of the electric shuttle bus; S2. performing large-step sliding median filtering; S3. filtering valid data segments containing axle data; S4. extracting valid data segments and performing small-step sliding median filtering on them; S5. calculating the mode of the amplitude in the valid data segments and replacing abnormal amplitudes exceeding a preset threshold with the mode; S6. identifying abrupt change points in the wheel axle profile in the valid data segments; S7. filtering abrupt change points; S8. calculating the position and forward speed of the electric shuttle bus; S9. transmitting the position and forward speed of the electric shuttle bus to the robot scheduling system; S10. making traffic control decisions based on the real-time position and speed prediction results of the electric shuttle bus and the real-time task path of the robot. This invention has advantages such as improved operational efficiency and safety.

The present application relates to electric bus charging joint scheduling technical field, provide electric bus fixed and dynamic wireless charging joint scheduling method and system. Electric bus fixed and dynamic wireless charging joint scheduling method includes that fixed and dynamic wireless charging coordination problem is modeled as limited time domain constraint Markov decision process, and then the power of fixed and dynamic wireless charging is determined as charging scheduling strategy based on system state, and the optimization objective function is constructed as minimizing cumulative expected energy cost within the set operation period; the optimization objective function is solved by using the rolling time domain model predictive control method, and the terminal SOC shortage cost is decomposed into the expansion and contraction of the stage cost by using the convex potential function, while keeping the optimal charging scheduling strategy, the end of the day requirement is internalized in the rolling time domain of the rolling time domain model predictive control method.

The utility model discloses an electric bus three electricity dust removal workshop of preventing dust to escape, and dust removal passageway is constituted by both side walls and bottom, and the import and export are equipped with door frame, and the door frame top outside is equipped with air curtain machine, and the both sides are equipped with vertical installation groove and transverse groove intercommunication formed installation groove, and are equipped with soft curtain sealing assembly that can move to the door frame middle. Soft curtain sealing assembly includes winding up part and stretching part, and winding up part realizes soft curtain winding through drive motor, rotary column and synchronous belt, and stretching part stretches soft curtain with extension motor and telescopic link, and the both ends of soft curtain are fixed to rotary column and telescopic link respectively. The door frame top is equipped with air groove hole that is aligned with the air curtain machine air outlet. The utility model discloses through " air curtain + curtain " double seal, and combines the automatic winding and stretching of soft curtain with the automatic winding and stretching, effectively blocks dust to escape, improves dust control ability of dust removal workshop, and has good sealing effect, transmission stability, strong adaptability and the advantages such as.

This invention provides a method and system for scheduling pure electric buses with a hybrid charging mode. It transforms a complex operational scheduling problem into a mathematical optimization problem with the objective of minimizing total cost, constrained by multiple real-world conditions such as time, energy, and resources. The system first coordinates infrastructure deployment at the physical level: deploying battery swapping stations at route endpoints to utilize the natural intervals between vehicle scheduling for rapid energy reset; and deploying pantograph charging facilities at suitable intermediate stops to utilize passenger stop times for "opportunistic charging." Next, at the decision-making level, a mixed-integer linear programming model is constructed. This model includes considerations such as vehicle energy consumption patterns, dynamic changes in battery capacity, continuous connection of bus routes, and limitations on the number of charging facilities. Finally, a mathematical optimization solver solves the model, outputting the cost-optimal vehicle scheduling plan and hybrid charging strategy.

This invention discloses a defrosting control method, device, computer equipment, and storage medium for a roof-mounted air conditioner in an electric bus. The method includes: if a forced defrosting command is received within a preset power-on time, closing the four-way valve in the air conditioner, controlling the compressor in the air conditioner to enter the start-up operation phase, and controlling the evaporator fan in the air conditioner to operate at the highest fan speed; if a preset first condition is met after the compressor enters the start-up operation phase, controlling the compressor to enter a frequency-increasing operation phase; if a preset second condition is met after the compressor enters the frequency-increasing operation phase, controlling the compressor to enter a high-frequency defrosting operation phase; if a defrosting exit condition is met, controlling the compressor to enter a frequency-reducing operation phase, and ending forced defrosting when a preset third condition is met. This invention can automatically clear snow accumulation on the vehicle roof or frost from the condenser before the vehicle travels, improving efficiency and ensuring safety.

The present invention discloses a method for determining the charging and swapping strategy of electric buses considering battery degradation effects, which relates to the technical fields of urban public transportation and electric vehicle energy management. According to the information of the electric bus system, the working processes of electric buses passing through the starting station, swapping station, and terminal station are designed. Further, a charging and swapping decision-making model including an objective function and constraint conditions is constructed, and a battery degradation cost function is introduced. By discretizing the decision-making model and using a standard solver for solution, the optimal strategies of the charging amounts of each electric bus vehicle at different travel stages and whether to perform swapping operations are determined. The present invention can reduce the degree of battery degradation and the daily operating cost of the system on the premise of meeting the constraints of continuous vehicle operation and facility capabilities, and is applicable to the operation decision-making and management of electric bus systems with in-transit swapping conditions.

The application provides a power system control method of a pure electric bus, comprising the following steps: obtaining driving control information or braking control information; switching to a corresponding mode according to the value of the driving or braking pedal change rate, and outputting the driving or braking pedal opening curve in the corresponding mode to a corresponding torque control module; calculating the vehicle driving torque value or the target braking torque value through the driving or braking pedal opening curve, and outputting the corresponding torque control instruction to a motor controller. The application identifies the driving intention by recognizing the speed of the driving or braking pedal change rate of the driver, switches different driving or braking modes in real time, realizes the acceleration and torque control of the pure electric bus under different driving or braking conditions, meets the power demand of the driver under various complex conditions, improves the followability and stability of the driving or braking torque, and more effectively ensures the vehicle power and driving safety.

This application relates to the field of battery state monitoring technology for electric vehicles, and particularly to a method, apparatus, and electronic device for multi-parameter prediction of electric bus batteries. The method includes: acquiring battery condition data of the electric bus; extracting multi-scale features from the battery condition data using an encoder employing a fusion-like attention mechanism; inputting the multi-scale features into a hidden state layer, which outputs online updated features; filtering battery feature data based on the online updated features; inputting the battery feature data into a decoder; and outputting prediction results for multiple battery parameters of the electric bus from the decoder. This solves the problems in related technologies, such as lengthy data processing for multi-parameter prediction of electric bus batteries, weak capture of long-term dependencies, poor computational efficiency, and low prediction accuracy.

This invention discloses a hybrid scheduling method for charging and operation of electric bus fleets, belonging to the field of intelligent scheduling technology for urban electric bus systems. The method first constructs a bus information collection module to acquire real-time data on fleet operation and charging. Then, it constructs virtual environments for charging and operation scheduling that integrate the nonlinear charging characteristics of batteries and the capacity decay during charging and discharging. The operation and charging processes are modeled as two interrelated Markov decision processes. Finally, a dual-SAC combined training framework is constructed to complete model training and obtain a collaborative scheduling strategy. This invention achieves closed-loop collaborative dynamic scheduling of charging and operation for electric bus fleets, adapting to complex dynamic operating environments. While improving bus punctuality and reducing passenger congestion, it effectively reduces battery capacity decay during charging and discharging, extends battery life, and significantly reduces the total life-cycle operating cost of the fleet, possessing strong engineering practical value.

The application discloses a kind of electric bus multi-gun charging scheduling methods considering power dynamic allocation, it is related to electric bus charging technical field, solve the technical problem that existing electric bus single-gun charging mode cannot effectively reduce the total energy cost and power grid load pressure of system under the premise of satisfying bus strict operation timetable;The application includes collecting basic data for pretreatment;Build electric bus multi-gun charging scheduling optimization model considering dynamic power allocation, the model introduces continuous variable to represent charging power;The model is solved by using solver, and the optimal decision variable is obtained;Based on optimal decision variable, extract electric bus charging plan and evaluate the effect of charging plan;The application can intelligently suppress the instantaneous peak when multiple vehicles are charging simultaneously, thereby significantly reducing the peak power demand of power grid under the premise of strictly meeting the bus operation timetable, significantly reducing the demand charge expenditure.

This invention relates to the field of power battery safety management and intelligent control technology for electric vehicles, specifically a method and system for intelligent full-link control of electric bus battery safety based on multi-condition data fusion. The method includes collecting multi-condition data such as battery status, driving conditions, environmental conditions, and charging status; performing noise reduction, anomaly removal, time alignment, and normalization to form an input sequence; obtaining a fused feature vector through a multi-modal fusion model; estimating the equivalent internal resistance, reversible thermal coefficient, and thermal response time constant online to construct thermal balance constraints and calculate thermal safety indicators; using the above parameters and estimating rate stress parameters to construct lifetime consumption constraints and calculate degradation stress indicators; performing constraint optimization based on the two indicators, outputting an optimized set, and generating current limiting, power limiting, behavioral constraints, thermal management, and scheduling actions.

1. Name of the product in this design: Tire (JU701). 2. Application of this design: This design is used for automobile tires, and is especially suitable for electric bus tires. 3. The key design features of this product are the combination of shape and pattern. 4. The image or photograph that best illustrates the design's key points: a 3D model. 5. If the rear view is the same as the front view, the rear view is omitted; if the top view is the same as the front view, the top view is omitted; if the bottom view is the same as the front view, the bottom view is omitted; if the right view is the same as the left view, the right view is omitted. 6. Other situations requiring explanation: Other explanation: The enlarged view of part A is point A in the main view.

The application provides a kind of based on charging pile state optimization public transport charging station regulation and control method, including collecting the load data of the feeder area where bus station is located and the charging data of individual electric bus, establishes electric bus regulation potential evaluation model;Establish cluster electric bus charging state regulation and control optimization model;According to actual data, obtain regulation and control electric bus charging regulation and control scheme.The application proposes electric bus regulation peak potential evaluation model based on the state of electric bus, on this basis, comprehensively consider the demand response income of aggregator and regulation and control response deviation two factors, establish electric vehicle bus charging state regulation and control double-layer optimization model;The application can maximize the peak shaving and valley filling effect of regulation and control under the premise of considering the maximization of demand response of aggregator and the minimization of response deviation, through the state regulation and control of electric bus, compared with the power continuity regulation of prior art, has more convenient implementation condition in actual engineering application.

The application belongs to the technical field of urban traffic planning, and relates to a pure electric bus line network planning method considering fairness, comprising the following steps: obtaining site distribution and site distance of a design area to obtain a road network structure diagram of the design area; constructing an objective function of a fairness model of a pure electric bus system with the minimum traffic Gini coefficient as the target and constructing an objective function of a total cost model of a pure electric bus line network with the minimum total social travel cost as the target, and further constructing a pure electric bus line network double-target nonlinear programming model; adopting an NAGS-II genetic algorithm, setting constraint conditions of the pure electric bus line network double-target nonlinear programming model, solving the pure electric bus line network double-target nonlinear programming model, and obtaining a pure electric bus planning line network. The method can reduce the traffic Gini coefficient while making the total travel cost as small as possible, effectively improves the fairness of the bus line network design scheme under the premise of controlling the total cost, and has important reference significance.

This invention discloses a composite energy storage system for electric buses and its energy management method, comprising a physical road condition generation module, a high-fidelity vehicle dynamics and thermal management environment module, a dual-source composite energy storage module, a safety reinforcement learning peak shaving decision-making module, and a digital twin visualization interaction module. This invention addresses the problem in existing technologies where new energy buses face massive instantaneous charging and discharging current surges under complex urban conditions, leading to severe localized heat accumulation in the battery and reduced cycle life. It also solves the problem that traditional peak shaving and valley filling strategies are difficult to effectively combine three-dimensional physical road conditions with battery thermodynamic characteristics, and that purely data-driven algorithms lack hard physical boundary constraints, resulting in a sudden increase in the risk of failure and thermal runaway under extreme long-tail conditions.

The present application relates to the technical field of urban public transport, and discloses a charging pile deployment method and system for electric buses considering double uncertainty. The method constructs the charging facility planning as a two-stage stochastic programming model, determines the number, type and power grid expansion scheme of charging piles in the first stage, and optimizes the operation cost in combination with double uncertainty in the second stage. A multi-agent simulation system is constructed to restore the vehicle scheduling and charging process, and two algorithms of reinforcement learning and radial basis function agent optimization are used to solve the model, and the optimal deployment scheme is output. The present application can significantly reduce the total cost of the system, improve the operation stability under high uncertainty, and provide a quantitative basis for power grid expansion.

The application discloses a charging pile number determination method for an electric bus station, and relates to the technical field of charging piles.The technical scheme mainly comprises the following steps: constructing a corresponding demand analysis data table according to vehicle operation data of a target bus station; identifying the demand analysis data table according to a preset demand analysis rule to obtain a target demand field; determining a module associated field associated with the target demand field based on the target demand field and a corresponding source data table structure; verifying the number management code and the module associated field according to a preset demand verification rule to obtain a verified target verification field and a corresponding source data table; and outputting an optimal charging pile configuration number of the electric bus station based on the target verification field, the source data table and the number management code, so that the operation efficiency and the return on investment of the charging facilities of the bus station are improved.

This invention relates to the field of electronic digital data processing technology and discloses a method for predicting anomalies in electric bus charging station charging systems. The method includes: acquiring operational data, equipment data, and environmental monitoring data of the charging device; preprocessing the multi-source data to construct a high-dimensional time-series feature matrix; constructing and training a hierarchical ensemble learning model that integrates confidence perception, where the base learners include a time-series prediction model and a tree model, outputting prediction results and confidence scores; and a meta-learner performs weighted fusion based on the outputs of each base learner to output prediction results. The method further involves dividing scenarios according to region type and charging mode, training differentiated hierarchical ensemble learning models for each scenario to form a scenario-based model library; calling the corresponding model according to the target scenario to generate early warning information; and collecting newly labeled samples to incrementally learn the meta-learner, updating the model fusion weights and confidence parameters. This method solves the problems of slow anomaly identification and reliance on manual intervention, achieving the goals of early warning, high accuracy, and low cost.

The application discloses a control method and device of a pure electric bus, the pure electric bus, and a storage medium. The battery of the pure electric bus is provided with an auxiliary relay and a main relay. The method comprises the following steps: after receiving a high-voltage request sent by a BMS, it is determined whether to pre-charge the battery according to first-stage state parameters before pre-charging starts, the auxiliary relay is turned on, and the battery is pre-charged; it is determined whether the pre-charging is completed according to second-stage state parameters after the pre-charging starts and before charging starts, the auxiliary relay is turned off to end the pre-charging, and the main relay is turned on to charge; and it is determined whether the charging is completed according to third-stage state parameters after the charging starts and before the charging is completed, and the main relay is turned off to end the charging. According to the scheme, the battery and the whole vehicle are pre-charged in the pre-charging stage, and the charging is performed only when it is determined that the whole vehicle is in a chargeable state, so that the safety of the charging can be ensured.

This invention relates to a rolling optimization method for the operating speed of an autonomous electric bus fleet, comprising the following steps: Step 1, defining model parameters; Step 2, establishing a bus fleet operating speed generation algorithm; Step 3, establishing a collaborative optimization model for bus fleet operating speed; Step 4, solving the collaborative optimization model for bus fleet operating speed; Step 5, deriving the rolling optimization method for fleet operating speed. This invention, based on factors such as intersection signal timing schemes, further considers the safety distance constraints and weaving effects between buses in front and behind. It rolls out the inter-station travel speed scheme when a single bus in the fleet is about to depart from a stop, avoiding situations where the safety distance constraints between buses in the fleet are not met, effectively improving the economy and on-time arrival of buses, thereby increasing the attractiveness of the public transportation system.

This invention relates to the field of power dispatching technology, specifically to a dynamic dispatching method and system for a virtual energy storage power station based on an electric bus fleet. The method involves acquiring vehicle stopping intervals and state of charge (SOC) to segment time segments, comparing available energy of vehicles with operational task requirements to select vehicles eligible for dispatch and form a capacity sequence, calculating the distribution network load gap and aligning it with the time segments, summarizing the virtual energy storage power capacity of the bus fleet in each segment, and allocating vehicle output based on the capacity-gap matching results to generate the dynamic dispatching result of the virtual energy storage power station. This invention constructs a time segment energy representation structure to map SOC, combines operational task constraints to select dispatchable vehicles and construct an eligible capacity sequence, correlates load gaps with bus fleet power capacity on the same scale, forms a hierarchical output arrangement based on supply and demand, and integrates time scale and multi-constraint judgment to achieve precise matching of energy state and dispatching, improving response consistency and group coordination capabilities.

The present invention relates to a charging station for charging electric buses and a charging method using the same. The charging station includes a power rail extending in an axial direction above a plurality of electric buses parked in parking spaces, a pantograph disposed at a lower portion of the power rail to be horizontally movable in the axial direction and to be spread in a gravitational direction from above the electric buses to make electrical contact with the electric buses, and a controller configured to calculate a charging order of the electric buses based on position information of the electric buses, wherein the controller is configured to control horizontal movement of the pantograph and electrical contact with the electric buses according to the charging order, thereby supplying electric power applied from an external power grid to the electric buses through the pantograph.

This invention provides an adaptive phase change dehumidification and anti-icing system and control method for brake air compressors in pure electric buses, relating to the field of pure electric bus chassis braking technology. It includes an intelligent integrated controller and a three-stage dehumidification and separation structure. The three-stage dehumidification and separation structure comprises an intake pretreatment and cold storage module, an active phase change dehumidification core module, and a deep air-water separation and protection module, sequentially connected along the intake direction. The intelligent integrated controller is linked to the brake air compressor's operating condition signal for feedback, coordinating the operation of each module. This application achieves efficient three-stage coordinated dehumidification and anti-icing through the linkage feedback between the intelligent integrated controller and the brake air compressor's operating condition signal, thereby completely preventing liquid water from entering the brake air compressor. It can actively and efficiently remove moisture from the brake air compressor's intake air from the source and can deeply coordinate with the actual working rhythm of the brake air compressor, meeting the safe supply requirements of brake air source for pure electric buses in cold and humid environments.

The utility model relates to tire technical field discloses a kind of wear-resistant electric bus tires with strong grip, including carcass, middle pattern groove, side pattern groove and connecting groove, the middle pattern groove and side pattern groove adopt zigzag water ripple design, inflection point place all adopt arc transition, pattern saturation reaches more than 80%, the side pattern groove is formed continuous groove network with middle pattern groove through connecting groove, shoulder pattern saturation reaches more than 43%.In the utility model, zigzag water ripple and arc transition design are used, cooperate with ultra-wide driving surface to make pattern saturation reach more than 80%, optimize inner contour curve by balance profile theory, in combination with low heat generation wear-resistant formula and high-strength skeleton material, effectively solve the problem of abnormal wear and sub-port crack, significantly improve tire carrying capacity, wear resistance and service life.

The present application relates to the technical field of power dispatch, in particular to a virtual energy storage power station dynamic scheduling method and system based on electric bus vehicle group, vehicle stopping interval and state of charge are obtained to segment time slices, available energy of vehicles and running task demand are compared to screen vehicles that can participate in scheduling to form capacity sequence, load gap of distribution network is calculated and aligned with time slices, virtual energy storage power of each slice vehicle group is summarized, vehicles are allocated according to matching results of capacity and gap, and virtual energy storage power station dynamic scheduling result is generated. The present application maps state of charge by constructing energy expression structure of time slice, screens scheduling vehicles by combining with running task constraints to construct available capacity sequence, correlates load gap and power capacity of vehicle group in the same scale, forms hierarchical output arrangement based on supply and demand relationship, integrates time scale and multiple constraint judgments, realizes fine matching of energy state and scheduling, and improves response consistency and group coordination ability.

The utility model provides a kind of electric bus with fireproof structure, including battery cabin and passenger cabin, the battery cabin and passenger cabin are isolated by isolation structure;The isolation structure includes metal isolation base material and non-metal isolation base material;For metal isolation base material, its surface is provided with fireproof coating, for non-metal isolation base material, its surface is sequentially provided with heat insulation coating and fireproof coating.The electric bus of this embodiment can control the temperature of passenger cabin in an acceptable range after battery explosion accident, and give passengers enough escape time, greatly improve its driving safety.