Dynamic voltage regulation charging method and system for electric bicycle based on distributed control

Abstract

The invention discloses an electric bicycle dynamic voltage regulation charging method and system based on distributed control, and the method comprises the steps: enabling each electric bicycle to autonomously collect the electric quantity state and charging intention, and completing the service matching through combining the information of an adjacent vehicle and a power node; after the safe connection is established, the suggested voltage is further dynamically corrected according to the real-time load data of the peripheral homologous power supply, so that the conversion from passively receiving the fixed voltage to actively negotiating the adaptive voltage is realized; in the charging process, the vehicle can also periodically collect power consumption information of surrounding similar equipment and predict the future short-time load trend, and when it is judged that the branch is about to reach the capacity limit, the vehicle actively initiates a power down-regulation proposal and releases the electric energy quota for more emergency users to use; the process does not need to depend on intervention of a central server, and load rebalancing can be completed only through cooperation among local nodes; and the problem of local overload caused by single-point control and fixed output is effectively relieved.

Description

Technical Field

[0001] This invention relates to the field of charging management technology, specifically to a dynamic voltage regulation charging method and system for electric bicycles based on distributed control. Background Technology

[0002] With the increasing popularity of electric bicycles in cities, the large-scale and decentralized charging demand places higher demands on power infrastructure. Traditional charging services mainly rely on centralized charging pile systems. These systems are typically managed by a unified management platform, where all power requests must be uploaded to a central server for processing, and then the backend issues fixed voltage output commands to designated devices. In this model, each charging pile supplies power to the vehicle with a preset constant voltage, lacking the ability to dynamically adjust based on battery status and grid load.

[0003] However, as the number of users increases, this centralized control architecture reveals significant adaptability deficiencies. Especially during peak electricity consumption periods or when vehicles are densely concentrated in a localized area, multiple electric bicycles simultaneously connecting to the same power distribution branch cause a rapid increase in load in that area. Because the charging piles cannot sense each other's operating status or coordinate their output power adjustments, this easily leads to line overload, voltage fluctuations, and even power outages. Furthermore, since all decisions rely on a remote central node, communication delays limit response speed, making it difficult to promptly mitigate the risks posed by sudden load surges. This phenomenon indicates that existing technologies lack a means to achieve localized coordinated control and prevent local grid overload in massive, distributed scenarios, thus restricting the stability and resource utilization efficiency of the charging system. Summary of the Invention

[0004] This invention aims to provide a dynamic voltage regulation charging method and system for electric bicycles based on distributed control, which effectively alleviates the local overload problem caused by single-point control and fixed output, and significantly improves the operational stability of the power distribution network in a high-density charging environment.

[0005] To achieve the above objectives, the technical solution adopted by this invention is: a dynamic voltage regulation charging method for electric bicycles based on distributed control, comprising: Collect the current battery status and charging intention intensity of electric bicycles, calculate the request weight based on the battery status and charging intention intensity, determine the set of nearby vehicles within the effective communication coverage radius based on the request weight, and generate and spread the initial request message; Identify infrastructure nodes with power supply capabilities within the broadcast range, generate a power service quality score by combining historical usage feedback from nearby vehicles, calculate a matching tendency value based on the request weight and the power service quality score, send connection invitations to power sources with high matching tendency values, and establish a secure communication channel. The optimal battery acceptance voltage and real-time load data of surrounding power sources are obtained through a secure communication channel. The initial suggested voltage is dynamically corrected based on the real-time load data to form a negotiated voltage. Based on the negotiated voltage setting, a voltage ramp-up curve is set, and the actual input electrical parameters are collected in each time period. The deviation index is calculated based on the actual input electrical parameters to verify the connection stability. After the connection is stable, the real-time power consumption of nearby charging vehicles is collected periodically. Based on the real-time power consumption, the short-term load peak is predicted. When the predicted load peak approaches the safety threshold, a power reduction initiative is initiated. It receives power transfer notices from surrounding vehicles, assesses its own charging urgency, organizes anonymous bidding within the same power domain to generate a matching scheme, monitors the changing trend of electrical parameters at the end of charging to identify the saturation inflection point, and sends a disconnection request to the power source based on the saturation inflection point and generates service quality feedback.

[0006] Preferably, the generation and dissemination of the initial request message includes: Activate the short-range communication unit to transmit a detection signal at a fixed power and continuously listen for response; Based on the determination that the signal strength is higher than the threshold, nearby vehicles are identified, and the direction angle and estimated distance of each member relative to the vehicle are recorded. Construct a structured request message based on the unique identifier, charge status value, service level, and request weight; When multi-hop forwarding is enabled, duplicate transmissions are avoided based on the unique identifier of the request message, and random delays are set to balance the channel load.

[0007] Preferably, the generation of the power service quality score includes: Extract the power supply device's maximum output power, supported voltage range, and current load information; The collected historical usage feedback from nearby vehicles is processed by weighted averaging, with the weights inversely proportional to the distance between the reporting vehicle and the current vehicle. A comprehensive score is constructed by integrating basic capability score, operational reliability score, and historical reputation score. A recommended access order list is generated based on the comprehensive score in descending order, and a distance penalty term is introduced to optimize the sorting by combining the Euclidean distance from the current location to each power node.

[0008] Preferably, establishing a secure communication channel includes: Verify the validity of the digital signature returned by the power supply device; Based on the verified public key of the power supply device, encrypt the temporary public key generated for this vehicle and then send it back; A shared session key is derived using the elliptic curve Diffie-Hellman protocol and the public keys exchanged between the two parties; The application-derived shared session key is used to encrypt and verify the integrity of all subsequent communication content, protecting voltage negotiation and current regulation commands.

[0009] Preferably, the dynamic correction of the initial suggested voltage includes: The base voltage is compensated and adjusted according to the ambient temperature to form a recommended voltage starting point; Request the total instantaneous power of all charging points under the same branch and the average growth rate over the past five minutes; The adjustment offset is calculated based on the deviation ratio between the predicted load and the safety threshold, and the offset increases as the overload ratio increases. Verify that the corrected voltage is within the power supply's allowable range and the battery's safety limits, and use the verified voltage as the negotiated voltage.

[0010] Preferably, the verification of connection stability includes: Record voltage and current sampling values ​​at a frequency of not less than 10Hz within each time period; The absolute error between the average voltage value and the target voltage value is calculated based on the sampled values. The system assesses whether the average current value is within the theoretical range estimated based on the battery's internal resistance. When the absolute error exceeds a preset threshold or the average current value exceeds the theoretical range, an interruption protection mechanism is triggered to terminate the connection.

[0011] Preferably, the prediction of future short-term load peaks includes: Regularly collect historical sequence data of total branch power; A trend line is fitted based on historical sequence data to obtain the current load growth rate; The system uses an exponentially weighted moving average method to process historical data and predict the load level for the next five minutes. When the predicted load level reaches 95% of the safety threshold, the maximum power margin that can be transferred is calculated, and a power release announcement is generated.

[0012] Preferably, the anonymous bidding within the same power domain of the organization includes: The total supply is formed by summing up all available power transfer quotas within the same power domain. The system receives encrypted uploads of competitive scores from each vehicle. The competitive score is determined by the proportion of missing state of charge and the service level. The allocation of transfer quotas will be determined in descending order of competition scores until the total supply is exhausted. Broadcast the pairing list to all participants and update the charging parameters of vehicles that have successfully obtained incremental resources.

[0013] Preferably, the identification of the saturation inflection point includes: Once the state of charge exceeds the 0.92 threshold, monitoring of input current changes begins. Calculate the slope of the moving average of the input current and determine whether the current decay rate is below the critical value within three consecutive cycles. The output voltage ripple fluctuation amplitude is detected synchronously. When the voltage ripple increases significantly, it is considered that the internal chemical reaction tends to stagnate. When the current decay rate is lower than the critical value and the voltage ripple increases significantly, the saturation inflection point is confirmed.

[0014] On the other hand, this invention proposes a dynamic voltage regulation charging system for electric bicycles based on distributed control, comprising: The request weight calculation module is used to collect the current battery status and charging intention intensity of electric bicycles, and calculate the request weight based on the battery status and charging intention intensity. The request broadcast module is used to determine the set of neighboring vehicles within the effective communication coverage radius based on the request weight, and to generate and spread the initial request message. The power assessment module is used to identify infrastructure nodes with power supply capabilities within the broadcast range and generate a power service quality score by combining historical usage feedback from nearby vehicles. The secure connection module is used to calculate the matching tendency value based on the request weight and the power service quality score, send connection invitations to power supplies with high matching tendency values, and establish a secure communication channel. The voltage negotiation module is used to obtain the optimal battery acceptance voltage and real-time load data of the surrounding power source through a secure communication channel, and dynamically correct the initial suggested voltage based on the real-time load data to form the negotiated voltage. The soft-start control module is used to set the voltage ramp-up curve based on the negotiated voltage, collect the actual input electrical parameters in each time period, and calculate the deviation index based on the actual input electrical parameters to verify the connection stability. The load balancing module is used to periodically collect the real-time power consumption of nearby charging vehicles after the connection is stable, predict the future short-term load peak based on the real-time power consumption, and initiate a power reduction initiative when the predicted load peak approaches the safety threshold. The resource allocation module is used to receive power transfer notices from surrounding vehicles, assess its own charging urgency, and organize anonymous bidding within the same power domain to generate a matching solution. The charging termination module is used to monitor the changing trend of electrical parameters at the end of the charging process, identify the saturation inflection point, send a disconnection request to the power supply based on the saturation inflection point, and generate service quality feedback.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention enables each electric bicycle to autonomously collect its own power status and charging intention, and combines this with information from nearby vehicles and power nodes to complete service matching. After establishing a secure connection, it further dynamically adjusts the suggested voltage based on real-time load data from surrounding power sources, realizing a shift from passively accepting a fixed voltage to actively negotiating and adapting to the voltage. During charging, the vehicle can also periodically collect power consumption information from similar devices in the vicinity, predicting future short-term load trends. When it determines that its branch is about to reach its capacity limit, it proactively initiates a power reduction initiative, releasing power quotas for users with more urgent needs. This process does not rely on central server intervention; load rebalancing can be completed solely through cooperation between local nodes. It effectively alleviates the local overload problem caused by single-point control and fixed output, significantly improves the operational stability of the power distribution network in high-density charging environments, and enhances the overall utilization rate of power resources, providing a feasible path to meet the large-scale charging needs of urban electric bicycle clusters. Attached Figure Description

[0016] Figure 1 This is a flowchart of the dynamic voltage regulation charging method for electric bicycles based on distributed control according to the present invention; Figure 2 This is a block diagram of the dynamic voltage regulation charging system for electric bicycles based on distributed control according to the present invention. Detailed Implementation

[0017] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0018] like Figure 1 As shown, this invention proposes a dynamic voltage regulation charging method for electric bicycles based on distributed control. Using a distributed collaborative framework with each bicycle as the basic decision-making unit, each electric bicycle participating in the charging process can autonomously generate the optimal input voltage value based on real-time acquired surrounding state information, combined with its own battery characteristics and grid conditions. It can also exchange adjustment intentions with other nearby bicycles through short-range communication links, achieving a group-level supply-demand balance without the need for intervention from a central controller. Specifically, the method includes the following steps: The system collects the current battery status and charging intention intensity of electric bicycles, calculates request weights based on these data, determines the set of nearby vehicles within the effective communication coverage radius based on the request weights, and generates and disseminates an initial request message. Specifically, this includes: activating short-range communication units to transmit probe signals at a fixed power and continuously monitoring response; determining nearby vehicles based on signal strength exceeding a threshold, recording the direction angle and estimated distance of each member relative to the vehicle; constructing structured request messages based on unique identifiers, state of charge values, service levels, and request weights; and when multi-hop forwarding is enabled, avoiding duplicate transmissions based on the unique identifier of the request message and setting random delays to balance channel load when necessary.

[0019] By autonomously generating and disseminating initial messages containing request weights, localized expression and propagation of charging demands are achieved. Each vehicle quantifies its access priority based on its real-time status, making resource allocation differentiated and avoiding channel congestion caused by disorderly competition.

[0020] The system identifies infrastructure nodes with power supply capabilities within the broadcast range and generates a power service quality score by combining historical usage feedback from nearby vehicles. Specifically, this includes: extracting the maximum output power, supported voltage range, and current load information of the power supply equipment; performing a weighted average processing on the collected historical usage feedback from nearby vehicles, with the weight inversely proportional to the distance between the reporting vehicle and the current vehicle; constructing a comprehensive score based on the fusion of basic capability score, operational reliability score, and historical reputation score; generating a recommended access order list by sorting the comprehensive scores in descending order, and optimizing the sorting by incorporating a distance penalty term based on the Euclidean distance from the current location to each power node.

[0021] By integrating the hardware capabilities and operational stability of power supply equipment with user experience, a multi-dimensional service quality assessment system has been constructed. This system enables vehicles to identify truly reliable and efficient charging nodes, reducing the risk of connection failures or charging interruptions due to the selection of inferior or overloaded power sources. A distance-related weighting mechanism has been introduced to enhance the spatiotemporal relevance of feedback information, ensuring that local decision-making is more relevant and practical.

[0022] The matching tendency value is calculated based on the request weight and power service quality score. A connection invitation is sent to the power supply with a high matching tendency value and a secure communication channel is established. Specifically, this includes: verifying the validity of the digital signature returned by the power supply device; encrypting the temporary public key generated by the vehicle based on the verified public key of the power supply device and sending it back; deriving a shared session key using the elliptic curve Diffie-Hellman protocol and the public keys exchanged by both parties; and using the derived shared session key to encrypt and verify the integrity of all subsequent communication content, protecting voltage negotiation and current regulation commands.

[0023] By evaluating request weights and power service quality in a two-way manner, value matching between supply and demand is achieved, making it easier for high-priority requests to receive high-quality resource responses, while incentivizing power nodes to maintain good service status. Establishing an end-to-end secure communication channel ensures the confidentiality and integrity of subsequent critical commands such as voltage negotiation and parameter adjustment during transmission, effectively resisting potential security threats such as forged access points and command tampering.

[0024] The system acquires the optimal battery acceptance voltage and real-time load data of surrounding power sources through a secure communication channel. Based on the real-time load data, it dynamically corrects the initial suggested voltage to form a negotiated voltage. Specifically, this includes: compensating and adjusting the base voltage according to the ambient temperature to form a suggested voltage starting point; requesting the total instantaneous power of all charging points under the same branch and the average growth rate over the past five minutes; calculating the adjustment offset based on the deviation ratio between the predicted load and the safety threshold, with the offset increasing as the overload ratio increases; and verifying whether the corrected voltage is within the allowable range of the power supply and the battery safety limit, using the verified voltage as the negotiated voltage.

[0025] By dynamically adjusting voltage parameters based on the battery's own state and the regional power grid load trend, the charging process satisfies both the optimal acceptance characteristics of individual devices and the load constraints of the local power system. When the overall load on the power supply side approaches a critical level, the output voltage is proactively reduced to decrease instantaneous power demand, effectively suppressing the peak superposition effect caused by mass access and avoiding power outages due to local overload.

[0026] Based on the negotiated voltage setting voltage ramp-up curve, the actual input electrical parameters are collected in each time period, and the deviation index is calculated based on the actual input electrical parameters to verify the connection stability. Specifically, this includes: recording voltage and current sampling values ​​at a frequency of not less than 10Hz in each time period; calculating the absolute error between the average voltage value and the target voltage value based on the sampling values; evaluating whether the average current value is within the theoretical range estimated based on the battery internal resistance; and triggering an interruption protection mechanism to terminate the connection when the absolute error exceeds a preset threshold or the average current value exceeds the theoretical range.

[0027] By applying voltage gradually in stages and monitoring the electrical response in real time, dynamic verification of connection quality is achieved, effectively identifying unstable connections caused by poor contact, equipment malfunction, or parameter mismatch. The high-frequency acquisition and deviation analysis mechanism can capture early signal deviation trends and terminate charging in time before overcurrent or voltage runaway occurs, avoiding potential damage to the battery and power supply facilities.

[0028] After the connection is stabilized, the system periodically collects real-time power consumption data from nearby charging vehicles. Based on this real-time power consumption, it predicts future short-term load peaks. Specifically, this includes: periodically collecting historical sequence data of total power in the branch; fitting a trend line based on the historical sequence data to obtain the current load growth rate; applying an exponentially weighted moving average method to process historical data and predict the load level for the next five minutes; calculating the maximum power margin that can be transferred when the predicted load level reaches 95% of the safety threshold and generating a power release announcement; and initiating a power reduction initiative when the predicted load peak approaches the safety threshold. By continuously sensing the regional electricity consumption situation and predicting load change trends, the system achieves proactive identification of grid pressure and can take adjustment measures proactively before local branches reach overload conditions. By dynamically extrapolating future loads based on historical data, the system effectively captures the signs of concentrated increases in charging demand and avoids the risk of passive power rationing or power outages caused by delayed response.

[0029] The system receives power concession notices from surrounding vehicles, assesses its own charging urgency, and organizes anonymous bidding within the same power domain to generate matching solutions. Specifically, this includes: summarizing all available power concession quotas within the same power domain to form a total supply; receiving encrypted uploads of competition scores from each vehicle, with the competition score determined by the percentage of missing state of charge and service level; allocating concession quotas in descending order of competition scores until the total supply is exhausted; broadcasting the matching list to all participants and updating the charging parameters of vehicles that successfully obtain incremental resources.

[0030] By responding to the release of power resources in the surrounding area and participating in local resource redistribution, the system achieves efficient recovery and reuse of idle power supply capacity. A competitive mechanism based on a quantitative assessment of charging urgency ensures that vehicles with low battery levels and urgent needs receive priority access to charging, improving the fairness and practicality of resource allocation.

[0031] The system monitors the changing trends of electrical parameters at the end of the charging process to identify the saturation inflection point. Based on this inflection point, it sends a disconnection request to the power supply and generates service quality feedback. Identifying the saturation inflection point specifically includes: monitoring input current changes after the state of charge exceeds a 0.92 threshold; calculating the sliding average slope of the input current to determine if the current decay rate is below a critical value over three consecutive cycles; simultaneously detecting changes in the output voltage ripple fluctuation amplitude; when the voltage ripple increases significantly, it is considered that the internal chemical reaction is stagnating; when both the current decay rate is below the critical value and the voltage ripple increases significantly, the saturation inflection point is confirmed.

[0032] By using multi-parameter collaborative judgment to determine the saturation state at the end of charging, accurate identification of battery energy absorption capacity degradation is achieved, avoiding overcharging or premature termination issues caused by relying solely on the state of charge threshold. The dual-condition verification mechanism effectively distinguishes between normal float charging and the chemical reaction stagnation stage, improving the reliability of disconnection timing determination.

[0033] On the other hand, this invention proposes a dynamic voltage regulation charging system for electric bicycles based on distributed control, such as... Figure 2 As shown, it includes: The request weight calculation module is used to collect the current battery status and charging intention intensity of electric bicycles, and calculate the request weight based on the battery status and charging intention intensity. The request broadcast module is used to determine the set of neighboring vehicles within the effective communication coverage radius based on the request weight, and to generate and spread the initial request message. The power assessment module is used to identify infrastructure nodes with power supply capabilities within the broadcast range and generate a power service quality score by combining historical usage feedback from nearby vehicles. The secure connection module is used to calculate the matching tendency value based on the request weight and the power service quality score, send connection invitations to power supplies with high matching tendency values, and establish a secure communication channel. The voltage negotiation module is used to obtain the optimal battery acceptance voltage and real-time load data of the surrounding power source through a secure communication channel, and dynamically correct the initial suggested voltage based on the real-time load data to form the negotiated voltage. The soft-start control module is used to set the voltage ramp-up curve based on the negotiated voltage, collect the actual input electrical parameters in each time period, and calculate the deviation index based on the actual input electrical parameters to verify the connection stability. The load balancing module is used to periodically collect the real-time power consumption of nearby charging vehicles after the connection is stable, predict the future short-term load peak based on the real-time power consumption, and initiate a power reduction initiative when the predicted load peak approaches the safety threshold. The resource allocation module is used to receive power transfer notices from surrounding vehicles, assess its own charging urgency, and organize anonymous bidding within the same power domain to generate a matching solution. The charging termination module is used to monitor the changing trend of electrical parameters at the end of the charging process, identify the saturation inflection point, send a disconnection request to the power supply based on the saturation inflection point, and generate service quality feedback.

[0034] In addition, the modules mentioned above are also used to implement other steps of the aforementioned dynamic voltage regulation charging method for electric bicycles based on distributed control, as follows: Step 1: Establish a decentralized charging request initiation mechanism This step aims to break away from the passive model of relying on fixed stations to register electricity demand, and instead build a request broadcast system actively triggered by electric bicycles and carrying complete contextual information. After entering an accessible area, each bicycle independently generates a comprehensive request message containing time sensitivity, capacity expectation, and geographical coordinates based on locally sensed energy gaps and environmental constraints, and periodically broadcasts it to similar devices within a certain range using a low-power wireless channel. This method avoids time losses caused by waiting for central authorization and provides a raw data foundation for subsequent multilateral negotiations.

[0035] Step 1.1: Collect current battery status and charging intention intensity. Each electric bicycle preparing to connect to the power grid first activates its internal monitoring circuit to read the actual remaining power of its battery pack. (Unit: kWh), and the total capacity set at the factory. By comparing, the current charge level can be determined. At the same time, the in-vehicle human-machine interface records the moment when the driver most recently manually triggered the "urgent charging" prompt. If the event occurred within the past 30 minutes, the current charging action is marked as high priority; otherwise, it is considered a regular supply task. This results in two basic attributes: and Both reflect the vehicle's current urgency regarding electrical power input.

[0036] Step 1.2: Determine the set of neighboring vehicles within the effective communication coverage radius. After determining its own energy status and service level, the vehicle activates its short-range communication unit, transmitting a detection signal at a fixed power to continuously listen for responses from other electric bicycles. All responses occur when the signal strength is above a threshold. Devices that receive feedback within a certain range are considered to be in the same physical space cluster, denoted as the neighboring vehicle set. Each element This represents a vehicle of the same type with two-way communication capabilities. The size of this set... This will directly affect the assessment of the intensity of subsequent resource competition. In addition, the system also records the azimuth angle of each member relative to their vehicle. Estimated distance It is used to construct local topological maps.

[0037] Step 1.3: Generate an initial request message with weight labels. Based on the information obtained in the first two steps, this vehicle constructs a structured request message. Its content includes: unique identification. ,current value, Level, location coordinates and a formula ; Calculated request weight .in, These are non-negative constants, used to adjust the influence of the power shortage ratio and service level on the final weight; This is an indicator function that returns 1 if the condition within the parentheses is true, and 0 otherwise. Vehicles that are closer to exhaustion and have been manually marked as urgent will have higher competitiveness in resource allocation. This weight value will serve as a primary reference in subsequent negotiation processes.

[0038] Step 1.4: Distribute the request to potential cooperating nodes via multi-hop forwarding. Due to the limited wireless coverage of a single device, this vehicle is not limited to sending requests only to directly connected neighbors, in order to ensure that requests can reach potential sharing partners in a wider area. Instead, it employs a message propagation path based on a flooding strategy. Specifically, when a nearby vehicle... Upon receiving the original message, if it has not yet forwarded a message with the same ID, it temporarily stores it in the buffer and waits for a random delay. Then it was broadcast again, in which To prevent infinite loops, a maximum waiting limit is set. This process allows request messages to traverse multiple relay nodes, eventually reaching remote vehicles that, while not within the original transmission radius, can be connected via an intermediate carrier. All participating devices maintain a local list of processed request IDs to avoid duplicate transmissions that could cause channel congestion.

[0039] Step 2: Construct a profile of available power nodes under local consensus After the initial requests are widely disseminated, each electric bicycle begins to filter through the received information stream to identify power supply facilities that meet the access criteria. Based on feedback from multiple sources, a comprehensive evaluation of the service capacity of each power point is generated. This differs from the previous method of a data center uniformly publishing a list of available ports. By aggregating observations from different perspectives, each bicycle can build a dynamic view of the surrounding power supply landscape, providing a basis for subsequent matching decisions.

[0040] Step 2.1: Identify infrastructure nodes with power supply capabilities within the broadcast range. The various request messages were received not only by other electric bicycles, but also by smart socket-type power outlets scattered along streets, at park entrances, and in underground parking garages of commercial buildings. These devices are also equipped with communication interfaces and, upon detecting nearby power demand, proactively respond with a notification frame containing their basic information. This vehicle captured these signals during continuous monitoring and extracted key fields: power outlet number. Maximum output power (Unit: kW), Supported voltage range (Unit: V) Current load (Unit: kW) and a sign indicating whether it is serving other vehicles. All satisfied Power points meeting certain conditions are considered potential accessible objects and included in the candidate set. .

[0041] Step 2.2: Collect historical usage feedback from neighboring vehicles of this power node To compensate for potential biases from single-point observations, this vehicle further moves to the set of neighboring vehicles identified in step 1.2. Initiate a query to request them to share recent information about candidate power sources. The interaction experience. If the vehicle receiving the inquiry has connected to the corresponding interface within the past two hours, it will send back a brief evaluation, covering the actual output stability. (Higher values ​​indicate smaller voltage fluctuations), connection success rate And subjective judgment regarding whether there are signs of physical damage (such as a loose socket). If a power supply receives multiple feedback reports, they are weighted and averaged. For example, for stability metrics: ; in Indicates for power supply The total number of feedback, For the first The credibility of a report is usually related to the distance between the reported vehicle and the current vehicle. Inversely proportional, that is This is a decay factor. This measure makes the opinions of vehicles that have been in close proximity and frequent contact more influential.

[0042] Step 2.3: Integrate local detection and group experience to generate a power service quality score. After integrating direct detection data and indirect feedback information, this vehicle analyzes each candidate power source. Construct a comprehensive quality score This score quantifies its suitability as a charging target. The score consists of three parts: a basic capability score... Origin and Normalized results; operational reliability analysis , taken from Geometric mean; historical credit score The percentage is determined by the proportion of unreported damage. The final result is: ; in The normalized weight coefficients satisfy... The purpose of this expression is to balance the relationship between hardware specifications and actual performance, preventing misleading selection decisions based solely on theoretical parameters. The rating is out of 1; the closer the rating is to this value, the more reliable the power supply.

[0043] Step 2.4: Update the dynamic power map on local storage and set access priorities. Complete all After calculating the score, this vehicle will combine this information with its geographical location. This data is written to the local cache, forming a power distribution map that evolves over time. Simultaneously, according to... Sort in descending order to generate a recommended access order list. The power sources at the top of the list will be prioritized for connection attempts. It's important to note that this map is not static; whenever a new batch of feedback arrives or a power source's status changes (e.g., it's fully occupied or out of power), the relevant entry is marked for updating, and the evaluation process is re-executed in the next cycle. Furthermore, to reduce unnecessary energy consumption during movement, the system also calculates the energy consumption from the current location. To each Euclidean distance And a distance penalty term is introduced during the final sorting, so that It is closer to actual accessibility.

[0044] Step 3: Perform two-way preference matching to identify initial access targets. Based on their understanding of their own power needs and the availability of external resources, each electric bicycle begins searching for the most suitable power source, while also considering whether the other party is willing to accept the connection. This stage introduces a game-like, two-sided matching logic: the vehicle not only evaluates which power source is best suited for it but also predicts whether that source will accept it. By exchanging signals of intent, both parties can reach a temporary pairing without global coordination, laying the foundation for subsequent voltage negotiations.

[0045] Step 3.1: Calculate the preliminary matching tendency value based on the request weight and power score. The recommended list generated in step 2.4 of this vehicle traversal For each of these power sources Calculate a matching propensity index Its size depends on two factors: first, the vehicle's desire for the power source, which is reflected in its service quality rating. Secondly, the likelihood of the power source accepting this type of request from the vehicle depends on the weight of the request itself. The decision is made. The two are coupled through the following product relationship: ; Even if a power supply is of very high quality ( High, but if the demand for this vehicle itself is not urgent ( If the value is low, the overall matching power is still relatively weak; conversely, if it is high, the overall matching power is also weak. Therefore, This essentially reflects the potential of this connection in terms of bilateral value matching. All candidates are categorized as follows: Arrange in descending order to form a new intentional sequence. This serves as a target list for further contact.

[0046] Step 3.2: Send a tentative connection invitation to the first potential power source and wait for a response. from Selected from highest power Construct a connection request command This includes the vehicle's identification. ,current Expected charging time (Calculated from remaining battery power and daily driving mileage), and the declared maximum input power. (As specified in the battery datasheet). This command is sent to the target power device via a pre-established communication link. To prevent a surge of requests from overwhelming a single node, the transmission action is accompanied by a [missing information - likely a parameter or parameter]. random backoff window ,in This serves as a baseline delay constant to ensure high-priority users can enter the queue faster. After being sent, this vehicle switches to listening mode, waiting for the other party to respond within the specified time limit. It returns an confirmation or rejection signal.

[0047] Step 3.3: Adjust the matching strategy based on power feedback and initiate alternative solution exploration. If in Received a positive response within a short period of time This indicates the power supply If we are willing to reserve interface resources for it, we will immediately proceed to the next stage to prepare for formal integration. Conversely, if a rejection code is received... If no response is received within the timeout period, the matching process is considered a failure, and the current strategy needs to be re-evaluated. At this point, the vehicle will... Remove from the list and check the remaining number of candidates: if there are still available options, select the second-best. Repeat step 3.2; if there are no other options, initiate an enhanced search procedure—aggregate from nearby vehicles. Broadcast a distress signal, asking if any companions know of any undiscovered available power sources nearby, paying particular attention to those not appearing in the original candidate set. New nodes in the process. Once a valid clue is obtained, immediately add it to the list. And resume the matching process.

[0048] Step 3.4: Exchange encrypted handshake keys with the successfully responding power node to establish a secure channel. When power is received After receiving the response, both parties immediately proceeded with the identity authentication and channel protection process. First, the power supply side generated a temporary public-private key pair. and the public key The plaintext is sent to this vehicle; after verifying the validity of its digital signature, this vehicle generates its own temporary key pair. ,use The encrypted data is then sent back. Subsequently, both parties derive a shared session key using the Elliptic Curve Diffie-Hellman Protocol (ECDH). This secure channel is used for encryption and integrity verification of all subsequent communication content. The establishment of this secure channel ensures that critical commands such as voltage negotiation and current adjustment are not tampered with or eavesdropped on, and also provides basic protection against maliciously disguised devices impersonating legitimate power sources.

[0049] Step 4: Conduct voltage parameter negotiation based on load balancing prediction After establishing an initial cooperative relationship and setting up a secure connection with the target power source, both parties enter the core electrical parameter coordination phase. This process no longer involves the power source unilaterally determining the output value; instead, the vehicle takes the lead in proposing a suggested voltage suitable for its own battery state, while also considering the load distribution trends of the entire local network. By predicting the group's electricity consumption trends over a future period, potential overload risks can be mitigated in advance, achieving dual optimization of individual performance and collective stability.

[0050] Step 4.1: Calculate the optimal acceptable voltage for the vehicle's battery and generate an initial recommended value. This vehicle is based on the current Consult the built-in electrochemical characteristic comparison table to determine the most suitable charging voltage for the current stage. For example, when When charging is needed, constant current fast charging mode should be used. near ;when At that time, it enters the constant pressure floating charging zone. Maintain a moderate level; when Then gradually reduce To prevent excessive polarization. Additionally, ambient temperature must be considered. To mitigate the impact, a correction factor is introduced: ; in This is the temperature sensitivity coefficient. This refers to the standard operating temperature (e.g., 25°C). In low-temperature environments, the voltage is appropriately increased to compensate for the decrease in ion migration rate; in high-temperature environments, the voltage is adjusted in the opposite direction to extend the lifespan. This results in... This serves as the starting point for the initial voltage recommendation submitted to the power supply.

[0051] Step 4.2: Obtain real-time load data from surrounding power sources to assess regional stress. To avoid individual optimality leading to global imbalance, this vehicle requests power through the established safety channel. Provides a summary of the current load of all similar equipment under its corresponding distribution branch. The power supply side responds with a set of anonymized statistics, including: the total number of connected devices on this branch. Active charging points, total instantaneous power Average growth rate over the past 5 minutes And the predicted peak load to be reached in the next 10 minutes. This information reveals the overall pressure situation of the current power grid branches. If... Exceeding the preset safety threshold This indicates that the area is about to face a power shortage and needs to proactively reduce individual request values ​​to alleviate the pressure.

[0052] Step 4.3: Apply dynamic correction to the initial recommended voltage based on regional load trends. Based on the macro-level situation obtained in the previous step, this vehicle... Apply an adjustment offset This allows it to meet its own needs without exacerbating local congestion. The revised logic is as follows: ; in To adjust the sensitivity parameters and control the rate at which the voltage drop increases with the overload ratio, only a small correction is performed when the predicted load slightly exceeds the safety limit; however, when approaching the critical breakdown point, more aggressive peak-shaving measures are taken. The final negotiated output voltage is: ; This value will not be lower than the power supply's allowance. It will not exceed the maximum input limit allowed by the battery, ensuring that it is always within the safe operating range.

[0053] Step 4.4: Send the revised voltage proposal to the power supply and wait for joint confirmation. After the voltage adjustment is completed, this vehicle will Expected duration and the corresponding average power Packaged into a formal proposal Send to power source via encrypted channel Upon receiving the voltage, the power supply first checks whether it falls within its adjustable range. The system then calculates whether its remaining capacity can support the request. If everything is compliant, a confirmation message is sent back. This indicates agreement to perform charging according to these parameters; if there is a conflict, a correction suggestion will be returned. A compromise was proposed. Both parties could then engage in multiple rounds of fine-tuning until an agreement was reached. Once the final parameters were finalized, the power supply would immediately configure the internal converter to enter the designated operating mode and simultaneously send a start command to the vehicle. This signifies the formal establishment of the electrical connection, allowing the charging process to begin.

[0054] Step 5: Initiate phased progressive voltage loading and initial response verification After both parties agree on the power supply parameters and establish an encrypted communication channel, the power supply equipment will not immediately output full power. Instead, it will adopt a gradually increasing voltage strategy to avoid battery damage or circuit failure caused by instantaneous high current surges. This process simulates traditional soft-start logic, but its adjustment rhythm is dynamically guided by the electric bicycle based on its own battery's real-time feedback, rather than relying on a preset schedule. By monitoring the current response characteristics during the voltage ramp-up phase, the vehicle can initially determine the connection stability and power supply regulation accuracy, and decide whether to continue to full-load operation accordingly.

[0055] Step 5.1: Set the time segments and increment step size of the voltage ramp-up curve. This vehicle is based on the final target voltage agreed upon through negotiation. and recommended upper limit of charging current Plan a smooth voltage rise trajectory. Divide the entire boost range into... There are several isochronous phases, each with a duration of [length missing]. ,in This is the total climb time (usually taken as 30 seconds). The system resolution is set to 5. The target voltage value for each stage is calculated in a linear increment: ; The physical meaning of this formula is: starting from zero, every... The timeframe is set to allow the power output to increase to the next level until it reaches its full value. This segmented design enables subsequent monitoring to capture dynamic trends at discrete nodes, facilitating the timely detection of abnormal fluctuations.

[0056] Step 5.2: Send the first voltage command to the power supply and start the synchronization timer. After completing the internal planning, this vehicle will supply power. Send the first control signal It clearly indicates the voltage level that should be output at the moment. and allowed duration At the same time, a high-precision countdown timer is started locally. This timer is used to maintain consistency with the power supply's operating rhythm. It not only determines whether each stage is completed on time but also serves as a time reference for subsequent data sampling. Once a command is issued, the vehicle immediately switches to high-frequency acquisition mode, ready to receive voltage and current readings from the battery management unit.

[0057] Step 5.3: Collect actual input electrical parameters and calculate deviation index within each time segment. In the first During the cycle, this vehicle continuously records the actual input voltage at the power battery terminal. and input current The sampling frequency is no less than 10Hz. After the period ends, the average value of all sampling points is calculated. And calculate the absolute error relative to the target value: ; At the same time, assess the rationality of the current increase, if Beyond the theoretical range estimated based on Ohm's law If so, it indicates a risk of nonlinear impedance abrupt change, where The internal resistance of the battery is obtained from a table. This refers to the tolerance bandwidth. The two indicators mentioned above together constitute a comprehensive evaluation of the execution quality at this stage.

[0058] Step 5.4: Determine whether to proceed to the next stage or terminate the connection based on the degree of deviation. This vehicle will With preset threshold Comparison: If and If the current condition is within a reasonable range, the current phase is considered successful, and a continue command is sent to the power supply. If any condition is not met, the second stage of pressurization is triggered; if any condition is not met, the power supply regulation capability is determined to be insufficient or the connection is unstable, and an interrupt command is immediately sent. Stop power transfer and mark the power supply as having a potential quality problem in the local logs. Regardless of the outcome, package the entire interaction process into a diagnostic report. Stored in the cache for later optimization and matching decisions. Only when all... Only when all stages are successfully completed is the soft start considered complete, and the system is ready to enter a stable charging state.

[0059] Step Six: Implement Dynamic Load Rebalancing Based on Group Behavior Prediction Even when an individual connection is in normal operating mode, the local power grid may still experience pressure imbalances due to new access requests or sudden changes in external load. To maintain the sustainable operation of the overall system, each electric bicycle charging needs to continuously monitor the surrounding dynamics and predict the resource competition situation in the next few minutes based on historical patterns. Once it is predicted that its branch will be overloaded, it will proactively propose to reduce its own power consumption and release capacity to users with more urgent needs, thereby achieving cross-individual coordinated regulation.

[0060] Step 6.1: Periodically collect real-time power consumption and remaining charging time of nearby charging vehicles. This vehicle is at fixed intervals Seconds, gather to nearby vehicles All members within the same power distribution area broadcast query requests to obtain their current actual input power. The estimated charging time is still needed. This information is transmitted encrypted through a previously established secure channel to prevent interception by unauthorized parties. Upon receiving a reply, it is compiled into a dynamic list. This serves as the foundational dataset for analyzing local load structures.

[0061] Step 6.2: Estimate the current branch's total load growth rate based on power supply reported data. In addition to information from peer nodes, this vehicle also periodically sends data to the connected power source. Request the latest branch summary statistics, including the current total power. Number of active terminals And the numerical sequences from the past three sampling periods. A linear trend line is fitted using these discrete points: ; Where the slope This indicates the current load growth rate (unit: kW / min). The purpose of this formula is to reveal the direction of change in electricity intensity—if... And if it is significantly greater than the historical average, it indicates that new access requests are frequently flooding in, and the system is becoming strained; if This indicates that some vehicles have completed resupply and withdrawn, and resources are being released.

[0062] Step 6.3: Predict future short-term load peaks based on the time decay model To further predict risk windows, this vehicle uses an exponentially weighted moving average method to analyze future risk trends. The load level will be projected minutes later. Weighting factors will be defined. To give more influence to recent observations, the predicted value is calculated as follows: ; in Indicates the first The total power of each historical sampling point This represents the number of samples involved in the calculation (e.g., 5). The advantage of this expression is its ability to quickly respond to sudden increases while filtering out transient noise. If... Approaching or exceeding the safety threshold If this occurs, an early warning mechanism will be triggered, and preparations will be made to perform a load reduction operation.

[0063] Step 6.4: Based on the forecast results, initiate a power reduction initiative and broadcast the willingness to relinquish power. When detected At that time, the vehicle determined that the area's power supply capacity was about to reach its limit, and therefore initiated a self-adjustment program. First, it calculated the maximum power margin that could be transferred. ,in This represents the current actual power consumption. The threshold value required to maintain the minimum charging rate. Subsequently, a "Power Release" announcement is generated. The content includes: self-identification and the power quota willing to be reduced. (Assignment coefficient), and expected duration. The announcement, encrypted, was broadcast simultaneously to nearby vehicles and their respective power sources, indicating a willingness to sacrifice some charging speed in exchange for overall stability, and inviting other high-priority users to apply to take over this idle resource.

[0064] Step 7: Construct a resource reallocation channel driven by multilateral negotiation When vehicles voluntarily release capacity, the system must provide a fair and transparent mechanism to ensure that individuals genuinely in need of electricity can promptly take over these freed-up power quotas. This stage moves beyond point-to-point negotiation, forming a temporary resource trading circle that allows multiple parties to simultaneously submit their demand and supply intentions. An anonymous, auction-style matching process is then used to achieve optimal reallocation. The entire process requires no central server intervention and relies entirely on local consensus to reach an agreement.

[0065] Step 7.1: Receive power transfer notices from surrounding vehicles and establish a demand pool. This vehicle captured several [data / information] in standard monitoring mode. The messages originated from vehicles charging at different locations. After verifying the validity of each message's digital signature, key fields were extracted: the donor ID and available power. Duration The information includes the power node number and the associated power source. This information is categorized and organized, and stored in multiple resource sub-pools grouped by power source affiliation. Each corresponds to a specific power supply facility. For the vehicle connected to... The relevant branch, focus on Available credit limit.

[0066] Step 7.2: Assess your own charging urgency and generate resource request input. If this vehicle is currently Still below the preset threshold If the driver does not cancel the "emergency" flag, it is deemed necessary to request additional input capability. At this point, a resource request message should be constructed. The content includes: its own ID, and the required additional power. (not exceeding) ), Expected duration and a competitive score The score is composed of two parts: ; in This is a balancing factor. A higher score indicates greater influence in resource competition. This value is not publicly disclosed and is used only for internal ranking.

[0067] Step 7.3: Organize anonymous bidding and generate matching solutions within the same power domain. When a power node (such as When it detects both supply and demand sides within its jurisdiction, it automatically convenes a local coordination meeting. All submissions The vehicle The encrypted data is uploaded to this power source, which is responsible for decrypting and sorting it in descending order, while also aggregating all available data. Composition of total supply Next, applicants' needs are met according to priority until resources are exhausted. This ultimately creates a matching list. It clearly indicates which recipient each unit of released power will be transferred to and its corresponding amount.

[0068] Step 7.4: Announce the allocation results and update the charging parameter instructions for all parties. power supply The generated Broadcast to all participants. For vehicles that successfully acquire incremental resources, immediately adjust their target power to the new level and send updated voltage / current settings through a secure channel; for those who have committed to reducing load, confirm whether their actual output has decreased as scheduled, and if they have not fulfilled their obligation, record credit deduction information. If this vehicle is on the list, immediately increase charging intensity to accelerate the refueling process while ensuring battery safety.

[0069] Step 8: Perform adaptive disconnection upon completion of charging and accumulate experience. As the battery gradually charges, the vehicle needs to accurately identify the termination point, promptly disconnect the connection, and release the interface for others to use. The disconnection action is not simply based on reaching 100% SOC, but rather on a comprehensive assessment of multiple signals, including voltage response hysteresis and current decay rate, to determine whether the battery has entered the final stage of saturation. After completion, the vehicle proactively disseminates feedback on the service quality to the surrounding area and updates the local decision-making knowledge base to accumulate experience for the next charging session.

[0070] Step 8.1: Monitor the changing trends of electrical parameters at the end of charging to identify the saturation inflection point. when Once the value exceeds 0.92, this vehicle strengthens its control over the input current. Rate of change monitoring. Every Calculate the moving average slope once per second: ; in The window size is 4. If within three consecutive periods... ( A small positive value (e.g., 0.05 A / min), indicating that the current is almost no longer decreasing, suggests that the battery can no longer effectively absorb more energy and is entering the final stage of float charging. This is supplemented by voltage ripple detection—if the high-frequency fluctuation amplitude at the output is... The significant increase also suggests that the internal chemical reactions are tending to stagnate.

[0071] Step 8.2: After confirming that the termination conditions are met, send a disconnect request to the power supply. If both signals are satisfied, the vehicle determines that the charging process has reached its natural end and generates a disconnect command. Send to the power source via an encrypted channel The instruction includes the total electricity consumption for this transaction. Average efficiency throughout the process (Derived from the ratio of input energy to the increase in battery energy storage), and the maximum instantaneous deviation during operation. After receiving the power supply, the output voltage is gradually reduced to zero, then the relay connection is physically disconnected, and finally an acknowledgment message is sent back. This completes the service loop.

[0072] Step 8.3: Generate structured quality of service feedback and broadcast it to neighboring nodes. To enrich the group's understanding, this vehicle has been compiled into a simplified experience report based on the entire journey. The fields include: power supply ID, total time consumed, whether voltage regulation was performed, whether there was a communication interruption, and overall satisfaction rating. The score is derived from a weighted average of three factors: ; Each of these measures voltage stability, timeliness, and connection reliability, respectively. The encrypted report is simultaneously sent to nearby vehicles and power sources, allowing them to update their respective maintenance service files.

[0073] Step 8.4: Compress and archive the complete interaction log to a local knowledge base for subsequent decision-making. Finally, this vehicle integrates the entire event flow from the initiation of the request to the complete disconnection—including original parameters, intermediate negotiation records, voltage adjustment trajectories, and details of adjacent interactions—into a single complete log entry. This entry is then linked to previous historical records using a hash chain structure, forming an immutable time-series database. This database will serve as a crucial reference source for future matching selection, voltage prediction, and risk warning mechanisms, enabling the vehicle to achieve experience-driven autonomous evolution through repeated charging processes.

[0074] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. A dynamic voltage regulation charging method for electric bicycles based on distributed control, characterized in that, include: Collect the current battery status and charging intention intensity of electric bicycles, calculate the request weight based on the battery status and charging intention intensity, determine the set of nearby vehicles within the effective communication coverage radius based on the request weight, and generate and spread the initial request message; Identify infrastructure nodes with power supply capabilities within the broadcast range, generate a power service quality score by combining historical usage feedback from nearby vehicles, calculate a matching tendency value based on the request weight and the power service quality score, send connection invitations to power sources with high matching tendency values, and establish a secure communication channel. The optimal battery acceptance voltage and real-time load data of surrounding power sources are obtained through a secure communication channel. The initial suggested voltage is dynamically corrected based on the real-time load data to form a negotiated voltage. Based on the negotiated voltage setting, a voltage ramp-up curve is set, and the actual input electrical parameters are collected in each time period. The deviation index is calculated based on the actual input electrical parameters to verify the connection stability. After the connection is stable, the real-time power consumption of nearby charging vehicles is collected periodically. Based on the real-time power consumption, the short-term load peak is predicted. When the predicted load peak approaches the safety threshold, a power reduction initiative is initiated. It receives power transfer notices from surrounding vehicles, assesses its own charging urgency, organizes anonymous bidding within the same power domain to generate a matching scheme, monitors the changing trend of electrical parameters at the end of charging to identify the saturation inflection point, and sends a disconnection request to the power source based on the saturation inflection point and generates service quality feedback.

2. The method for dynamic voltage regulation charging of electric bicycles based on distributed control according to claim 1, characterized in that, The generation and dissemination of the initial request message includes: Activate the short-range communication unit to transmit a detection signal at a fixed power and continuously listen for response; Based on the determination that the signal strength is higher than the threshold, nearby vehicles are identified, and the direction angle and estimated distance of each member relative to the vehicle are recorded. Construct a structured request message based on the unique identifier, charge status value, service level, and request weight; When multi-hop forwarding is enabled, duplicate transmissions are avoided based on the unique identifier of the request message, and random delays are set to balance the channel load.

3. The method for dynamic voltage regulation charging of electric bicycles based on distributed control according to claim 1, characterized in that, The generated power service quality score includes: Extract the power supply device's maximum output power, supported voltage range, and current load information; The collected historical usage feedback from nearby vehicles is processed by weighted averaging, with the weights inversely proportional to the distance between the reporting vehicle and the current vehicle. A comprehensive score is constructed by integrating basic capability score, operational reliability score, and historical reputation score. A recommended access order list is generated based on the comprehensive score in descending order, and a distance penalty term is introduced to optimize the sorting by combining the Euclidean distance from the current location to each power node.

4. The method for dynamic voltage regulation charging of electric bicycles based on distributed control according to claim 1, characterized in that, The establishment of a secure communication channel includes: Verify the validity of the digital signature returned by the power supply device; Based on the verified public key of the power supply device, encrypt the temporary public key generated for this vehicle and then send it back; A shared session key is derived using the elliptic curve Diffie-Hellman protocol and the public keys exchanged between the two parties; The application-derived shared session key is used to encrypt and verify the integrity of all subsequent communication content, protecting voltage negotiation and current regulation commands.

5. The method for dynamic voltage regulation charging of electric bicycles based on distributed control according to claim 1, characterized in that, The dynamic correction of the initial suggested voltage includes: The base voltage is compensated and adjusted according to the ambient temperature to form a recommended voltage starting point; Request the total instantaneous power of all charging points under the same branch and the average growth rate over the past five minutes; The adjustment offset is calculated based on the deviation ratio between the predicted load and the safety threshold, and the offset increases as the overload ratio increases. Verify that the corrected voltage is within the power supply's allowable range and the battery's safety limits, and use the verified voltage as the negotiated voltage.

6. The method for dynamic voltage regulation charging of electric bicycles based on distributed control according to claim 1, characterized in that, The verification of connection stability includes: Record voltage and current sampling values ​​at a frequency of not less than 10Hz within each time period; The absolute error between the average voltage value and the target voltage value is calculated based on the sampled values. The system assesses whether the average current value is within the theoretical range estimated based on the battery's internal resistance. When the absolute error exceeds a preset threshold or the average current value exceeds the theoretical range, an interruption protection mechanism is triggered to terminate the connection.

7. The method for dynamic voltage regulation charging of electric bicycles based on distributed control according to claim 1, characterized in that, The predicted future short-term load peak includes: Regularly collect historical sequence data of total branch power; A trend line is fitted based on historical sequence data to obtain the current load growth rate; The system uses an exponentially weighted moving average method to process historical data and predict the load level for the next five minutes. When the predicted load level reaches 95% of the safety threshold, the maximum power margin that can be transferred is calculated, and a power release announcement is generated.

8. The method for dynamic voltage regulation charging of electric bicycles based on distributed control according to claim 1, characterized in that, The anonymous bidding within the same power domain of the organization includes: The total supply is formed by summing up all available power transfer quotas within the same power domain. The system receives encrypted uploads of competitive scores from each vehicle. The competitive score is determined by the proportion of missing state of charge and the service level. The allocation of transfer quotas will be determined in descending order of competition scores until the total supply is exhausted. Broadcast the pairing list to all participants and update the charging parameters of vehicles that have successfully obtained incremental resources.

9. The method for dynamic voltage regulation charging of electric bicycles based on distributed control according to claim 1, characterized in that, The identified saturation inflection point includes: Once the state of charge exceeds the 0.92 threshold, monitoring of input current changes begins. Calculate the slope of the moving average of the input current and determine whether the current decay rate is below the critical value within three consecutive cycles. The output voltage ripple fluctuation amplitude is detected synchronously. When the voltage ripple increases significantly, it is considered that the internal chemical reaction tends to stagnate. When the current decay rate is lower than the critical value and the voltage ripple increases significantly, the saturation inflection point is confirmed.

10. A distributed control-based dynamic voltage regulation charging system for electric bicycles, used to implement the method as described in any one of claims 1-9, characterized in that, include: The request weight calculation module is used to collect the current battery status and charging intention intensity of electric bicycles, and calculate the request weight based on the battery status and charging intention intensity. The request broadcast module is used to determine the set of neighboring vehicles within the effective communication coverage radius based on the request weight, and to generate and spread the initial request message. The power assessment module is used to identify infrastructure nodes with power supply capabilities within the broadcast range and generate a power service quality score by combining historical usage feedback from nearby vehicles. The secure connection module is used to calculate the matching tendency value based on the request weight and the power service quality score, send connection invitations to power supplies with high matching tendency values, and establish a secure communication channel. The voltage negotiation module is used to obtain the optimal battery acceptance voltage and real-time load data of the surrounding power source through a secure communication channel, and dynamically correct the initial suggested voltage based on the real-time load data to form the negotiated voltage. The soft-start control module is used to set the voltage ramp-up curve based on the negotiated voltage, collect the actual input electrical parameters in each time period, and calculate the deviation index based on the actual input electrical parameters to verify the connection stability. The load balancing module is used to periodically collect the real-time power consumption of nearby charging vehicles after the connection is stable, predict the future short-term load peak based on the real-time power consumption, and initiate a power reduction initiative when the predicted load peak approaches the safety threshold. The resource allocation module is used to receive power transfer notices from surrounding vehicles, assess its own charging urgency, and organize anonymous bidding within the same power domain to generate a matching solution. The charging termination module is used to monitor the changing trend of electrical parameters at the end of the charging process, identify the saturation inflection point, send a disconnection request to the power supply based on the saturation inflection point, and generate service quality feedback.

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